The AEMBAC Project: Final Report - Nando Peretti Foundation

5 th Framework Contract Ref: QLRT-1999-31666 

Definition of a common European analytical 

framework for the development of local agrienvironmental 

programmes for biodiversity 

and landscape conservation 

AEMBAC 

The AEMBAC Project: 

Final Report 

April 2004 

Riccardo Simoncini 

(Annex 1 to this report has been written by Barbara Neumann; 

English revised by Simon Milward)

Table of contents 

PROJECT FINAL SUMMARY.............................................................................................................. 4 

1. INTRODUCTION ............................................................................................................................. 8 

2. MATERIALS AND METHODS................................................................................................... 12 

3. RESULTS.......................................................................................................................................... 17 

3.1 STEP 1 - IDENTIFICATION AND DESCRIPTION OF STUDY AREAS............................. 17 

3.2 STEP 2 - IDENTIFICATION AND ANALYSIS OF ENVIRONMENTAL FUNCTIONS .. 23 

3.2.1 Identification of environmental functions to be studied within the area and 

description of the most important attributes and characteristics (critical 

aspects) for their performance..................................................................................................23 

3.2.2 Identification and description of indicators.............................................................................26 

3.2.3 Measurement of actual values of indicators (data from literature or from 

field measurements when feasible) and interpretation of results ..........................................34 

3.2.4 - Identification of EMR values and description of the methodology used to 

analyse data and of the rationale behind the definition of EMR for each 

single state indicator selected....................................................................................................39 

3.2.5 Assessment and analysis of impacts: Gaps between EMR and actual values on 

state indicators ...........................................................................................................................43 

3.3 STEP 3 - DESCRIPTION OF LOCAL AGRICULTURAL SYSTEMS AND 

IDENTIFICATION OF THE MOST IMPORTANT PRESSURES AND DRIVING 

FORCES ON ENVIRONMENTAL FUNCTIONS..................................................................... 48 

3.3.1 Agricultural system: Qualitative and quantitative description of 

environmental characteristics...................................................................................................50 

3.3.2 Agricultural system: qualitative and quantitative description of economic 

characteristics.............................................................................................................................63 

3.1.3 Agricultural system: Qualitative and quantitative description of social 

characteristics.............................................................................................................................72 

3.3.4 Identification of most relevant pressures exerted on environmental functions 

by local agricultural system ......................................................................................................73 

3.3.5 Analysis of aspects acting as driving forces (environmental, economic and 

social) for the pressures identified............................................................................................76 

3.4 STEP 4 - ASSESSMENT OF ECOLOGICAL SUSTAINABILITY OF LOCAL 

AGRICULTURAL PRESSURES AND DEVELOPMENT OF RECOMMENDATIONS ON 

HOW TO LESSENING/ELIMINATING NEGATIVE IMPACTS AND ENHANCING 

POSITIVE ONES.............................................................................................................................. 81 

3.4.1 Identification of the part of the gap between EMR and actual value of state 

indicators directly imputable to agricultural pressures .........................................................84 

3.4.2 Assessment and linking of degrees of sustainability to agricultural pressures 

by looking at the impacts exerted .............................................................................................86 

3.4.2.1 Qualitative ranking system in reference to sustainability of local 

agricultural pressures...............................................................................................................87 

3.4.3 Recommendations on how to lessen/eliminate negative impacts and enhance 

positive ones................................................................................................................................90 

3.4.3.1 Feasibility analysis of the most important constraints and 

opportunities for implementation of recommendations .........................................................93 

3.4.4 Analysis of relations between degrees of sustainability and different 

hypothetical intensities of pressures of local agricultural systems. .......................................95 

3.4.5 Identification of the multifunctional character of the local agricultural 

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systems in reference to the performance of more than one environmental 

function .......................................................................................................................................96 

3.5 STEP 5 – ECONOMIC VALUATION OF NEGATIVE/POSITIVE IMPACTS AND 

IDENTIFICATION OF EXTERNALITIES.............................................................................. 100 

3.5.1 Translation of results of environmental functions analysis into economic 

information. ..............................................................................................................................100 

3.5.2 Identification of externalities...................................................................................................107 

3.6 STEP 6 – STUDYING LOCAL SUSTAINABLE AGRI-ENVIRONMENTAL POLICY 

TARGETS AND MEASURES...................................................................................................... 109 

3.6.1 Analysis of existing agri-environmental measures and comparison with 

recommendations developed ...................................................................................................109 

3.6.2 Analysis of aspects likely to be influenced by agri-envrionmental policy ............................111 

3.6.3 Analysis of aspects related to design and implementation of agrienvironmental 

measures..........................................................................................................112 

3.6.4 Studying locally sustainable agri-environmental policy targets and their 

definition ...................................................................................................................................113 

3.6.5 Studying locally suitable agri-environmental measures to reach policy 

targets........................................................................................................................................116 

3.6.6 Direct involvement of local farmers and administrators in the final definition 

of agri-environmental targets and measures .........................................................................121 

3.6.7 Identification of farms agri-environmental accounting systems...........................................126 

3.7 STEP 7 – STUDYING AGRI-ENVIRONMENTAL MEASURES IMPLEMENTATION: 

DEFINITION OF MONITORING, EVALUATION PROCEDURES AND CONTRACTS; 

ANALYSIS OF ADMINISTRATIVE AND TRANSACTION COSTS AND OVERALL 

ECONOMIC AND FINANCIAL ASPECTS ............................................................................. 130 

3.7.1 Definition of monitoring procedures......................................................................................130 

3.7.1.1 Monitoring on achievements of agri-environmental objectives...............................131 

3.7.1.2 Monitoring on agri-environmental measures functioning .......................................134 

3.7.2 Evaluation procedures ..............................................................................................................135 

3.7.2.1 Effectiveness .................................................................................................................136 

3.7.2.2 Efficiency ......................................................................................................................137 

3.7.3 Studying procedures for drawing up contracts for the supply of 

environmental goods and services by farmers ......................................................................138 

3.7.4 Analysis of administrative and transaction costs. ..................................................................142 

3.7.5 Analysis of overall economic and financial aspects for the local 

implementation of agri-environmental measures. ................................................................146 

4. DISCUSSION .................................................................................................................................... 150 

5. CONCLUSIONS ................................................................................................................................ 154 

6. EXPLOITATION AND DISSEMINATION OF RESULTS...................................................... 155 

7. POLICY RELATED BENEFITS.................................................................................................... 156 

8. LITERATURE ................................................................................................................................... 157 

3

Section 1: PROJECT IDENTIFICATION 

Information to be provided for project identification 

Project Final Summary 

4 

NOT CONFIDENTIAL 

Title of the project 

Definition of a common European analytical framework for the development of local agri-environmental 

programmes 

Acronym of the project 

AEMBAC 

Type of contract 

Additional cost action 

Total project cost (in euro) 

€ 2,260,370 

Contract number Duration (in months) EU contribution (in euro) 

QLRT-1999-31666 36 Months € 1,996,594 

Commencement date 

1 March 2001 

PROJECT COORDINATOR 

Name 

Riccardo Simoncini 

Telephone 

++39 055 437 4553 

Title 

Doctor 

Telefax 

++39 055 437 4905 

Period covered by the final report 

1 March 2001 – 29 February 2004 

Key words (5 maximum - Please include specific keywords that best describe the project.). 

Agri-environmental measures, agri-ecosystems, ecological thresholds, biodiversity, landscape 

World wide web address (the project’s www address ) www.aembac.org 

Address 

IUCN Regional Office for 

Europe, Contractor, Blvd Louis 

Schmidt 64, 1040 Brussels, 

Belgium 

E-mail address 

riccardo.simoncini@libero.it

List of participants 

Participant 1: IUCN Regional Office for Europe, Contractor, Blvd Louis Schmidt 64, 1040 Brussels, Belgium 

E-Mail: Europe@iucn.org; Tel.: ++32 2 732 82 99; Fax: ++32 2 732 94 99 

Name of principal researcher: Dr. Riccardo Simoncini. 

Other researchers: Dr. Barbara Neumann, Visi Garcia, Andrzej Nowakowski, Simon Milward, Dr. Andrew Terry, 

Participant 2. SAW, Contractor, Sächsische Akademie der Wissenschaften (Saxon Academy of Sciences), Neustädter 

Markt 19 (Blockhaus), 01097 Dresden, Germany 

E-Mail: olaf.bastian@mailbox.tu-dresden.de; Tel.: ++49 351 8141 6806; Fax: ++49 351 8141 6820 

Name of principal researcher: Prof. Karl Mannsfeld 

Other Researchers: Dr. Olaf Bastian, Michael Lütz, Dr. Matthias Röder, Dr. Ralf-Uwe Syrbe, Sub-contractors researchers: 

IfLS – the Institute for Rural Development Research at the University of Frankfurt, Dr. Karlheinz Knickel; Institute for 

Geography, Department of Landscape Ecology of the University of Technology, Christiana Unger 

Participant 3: WU-NL, Contractor, Wageningen University, Department of Environmental Sciences, Environmental 

Systems Analysis Group, Ritzema Bosweg 32, 6703 AZ Wageningen, The Netherlands 

E-Mail: dolf.degroot@wur.nl; Tel.: ++31 317 482 247; Fax: ++31 317 484839 

Name of principal researcher: Dr Rudolf de Groot 

Other researchers: Drs. Lars Hein, Prof. dr. Ekko van Ierland, Ir Erik Ansink, Ir Gerko Wessels 

Participant 4: FiBL, Contractor, Forschungsinstitut für biologischen Landbau (FiBL), Ackerstrasse, 5070 Frick, 

Switzerland 

E-Mail: Bettina.landau@fibl.ch; Tel.: ++41 62 865 7276; Fax: ++41 62 865 7273 

Name of principal researcher: Dr. Bettina Landau 

Other researchers: Gabriela Uehlinger, Christian Schlatter, Dr. Mathias Stolze, Heidrun Moschitz, Christian Rust, Lukas 

Pfiffner, Siegfried Hartnagel, Johannes Brunner, 

Sub-contractor’s Researchers: Agroscope FAL Reckenholz - Swiss Federal Research Station for Agroecology and 

Agriculture: Thomas Walter, Dr. Beatrice Schüpbach Erich Szerencsits; Agrofutura: Dr. Daniel Schaffner, Joseph Schmidlin, 

Manfred Lüthy 

Participant 5: DSE, Contractor, University of Florence, Department of Economic Sciences, Via delle Pandette 9, Firenze, 

Italy 

E-Mail: pacciani@cce.unifi.it; Tel.: ++39 055 437 4608; Fax: ++39 055 437 4905 

Name of principal researcher: Prof. Alessandro Pacciani 

Other researchers: Dr. Giovanni Belletti, Dr. Claudia Corti (University of Florence, Dep. animal genetic and biology), Dr. 

Marco Lebboroni, Dr. Andrea Marescotti, Dr. Silvia Scaramuzzi, Andrea Innocenti, Dr. Sandro Angiolini, Francesco Felici, 

Francesco Milani, Tania Gualdo, Raffaella Serchi, Erika Savelli. Sub-contractors Researchers: Ministry of Agriculture and 

Forestry policy, Experimental Institute for Soil Study and Conservation: Dr. Paolo Bazzoffi and Dr. Rosario Napoli; Istituto 

Nazionale di Economia Agraria: Dr. Lucia Tudini; Istituto Regionale per la Programmazione Economica della Toscana: Dr. 

Roberto Pagni; Accademia di Scienze Forestali: Dr. Paolo Degli Antoni; Associazione Italiana Agricoltura Biologica: Dr. 

Sandro Angiolini; Agenzia Regionale per lo Sviluppo ed Innovazione dell’Agricoltura: Dr Anna Luisa Freschi 

Participant 6: ENVIST, Contractor, Environmental Protection Institute of the Estonian Agricultural University, Akadeemia 

4, 51003 Tartu, Estonia 

E-Mail: tiit@envinst.ee; Tel.: ++372 7 427 433; Fax: ++372 7 427 432 

Name of principal researcher: Dr Kalev Sepp 

Other researchers: Prof. Mari Ivask, MSc. Annely Kuu, MSc. Marika Truu, Age Merila, MSc. Olavi Hiiemäe, Piret Palm, 

Margit Heinlaan, Tiit Lepasaar, Elviira Villa; Sub-contractor researchers: Centre for Ecological Engineering (CEET): MSc 

Merit Mikk, Argo Peepson 

Participant 7: UD-CEMP, Contractor, Debrecen University, (Hungary) The UD Team, Egytem ter 1, 4032 Debrecen, 

Hungary 

E-Mail: karacsonyiz@tigris.klte.hu; Tel.: ++36 52 512 921; Fax: ++36 52 512 928 

Name of principal researcher: Dr Zoltán Karácsonyi 

Other researchers: Tünde Szabo, Dr. Laszlo Stündl 

Subcontractor: Expert-Europe Consultants, Debrecen 

Participant 8: SLU, Contractor, Department of Economics, Swedish University of Agricultural Sciences, Johan Brauners 

v.3, S-750 07 Uppsala, Sweden 

E-Mail: Ingrid.Ragnarsdotter@adm.slu.se; Tel.: ++46 18 671 437; Fax: ++46 18 673 556 

Name of principal researcher: Ass. Prof. Knut Per Hasund 

Other researchers: Josefin Kofoed, Jennie Åström, Jennie Sahlsten, Fredrik Nilsson, Paula Quintana, Anders Glimskär, Roger 

Svensson. 

Sub-contractors researchers - NaturGIS AB: Tommy Löfgren; Naturcentrum AB: Svante Hultengren; Department of Physical 

Geography and Quarternary Geology, Stockholm University: Helle Skånes 

5

Section 2: Project Summary Report NOT CONFIDENTIAL 

(2 pages maximum.. Use short sentences. Be factual. Avoid technical terms as much as possible ) 

Objectives: 

The overall objective of the AEMBAC project was to define a common European analytical framework on which 

to develop local agri-environmental programmes. 

Results: 

The AEMBAC project has defined a common European analytical framework for the development of local agrienvironmental 

programmes for biodiversity and landscape conservation. The framework developed has been 

tested in 15 studies areas in 7 different European Countries. 

This result has been achieved by carrying out the project in three main phases: 

Phase 1: Definition of a methodology to assess the impacts exerted by agricultural pressures on the local 

environment: 

Phase 2: Definition of a methodology to develop Agri-environmental measures at local level 

Phase 3: Definition of a methodology to implement the Agri-environmental measures developed 

Phase 1 has identified the performance of environmental functions (e.g. related to biodiversity and landscape 

conservation) in different local agricultural systems, in the 15 study areas of 7 countries participating in the 

project. 

This has involved analysing the capacity of agri-ecosystems to perform selected environmental functions (i.e. 

biodiversity and landscape conservation, soil erosion and water run off related functions) through the use of a 

driving forces-pressures-state-impacts-responses model (DPSIR). The most important ecological aspects for the 

performance of environmental functions have been identified by state indicators, measuring, for instance, species 

diversity and composition, landscape features, soil fertility and water quality. For each state indicator identified, 

the respective Environmental Minimum Requirement (EMR) value to be matched in order to achieve the 

Environmental function performance was assessed. By looking at the gaps between actual values of state 

indicators and their corresponding EMR, positive or negative impacts on the performance of the environmental 

functions were identified. Ecological, economic and social aspects of agricultural systems have been then analysed 

and most important pressures on the environment and relative driving forces identified (e.g. pesticide and fertiliser 

application, land use and cultivation practices, etc). 

Phase 2 has built on the outcomes of the first phase. Starting from the analysis and identification of causality 

relationships between detected impacts on environmental functions performances and locally most relevant 

agricultural pressures, the research has focussed on developing an operational tool, capable of building a bridge 

between science and policy. Possible recommendations on adjusting agricultural pressures in order to overcome 

negative impacts and enhancing positive ones have been studied and ranked in Tiers of sustainability on respect of 

environmental function performances. The agri-environmental impacts resulting from the analysis carried out in 

Phase 1 have been translated into economic terms and externalities have been identified. Also the envisaged costs 

on the eventual implementation of proposed recommendations have been assessed. This information, coupled with 

studying the most relevant local socio-economic aspects, enabled the identification of agri-environmental policy 

targets tailored to local conditions, and the development of suitable agri-environmental policy instruments to 

achieve the targets. These policy instruments have included regulatory and/or market based tools that can be used 

for both the supply of environmental goods and services by farmers and the abandonment of unsustainable 

agricultural practices. 

Whereas it was appropriate, depending on the local ecological and socio-economic aspects, detailed agrienvironmental 

measures based on a quasi-market approach have been developed and compared with already 

existing programmes in the study areas. The understanding of the agri-environmental measures proposed by 

stakeholders, namely local farmers and administrators, and the feasibility of eventual implementation, have also 

been assessed as well as the procedures for reporting (by farmers) the correct implementation of the Agri- 

Environmental Measures (AEMs). A study on the impact of EU enlargement on biodiversity and landscape 

conservation within the agricultural sector has been carried out in the countries concerned (Estonia and Hungary), 

but it has not been included in this report concerning the analytical framework to develop local agri-environmental 

measures (see ENVIST and UD-CEMP reports). 

6

Phase 3 has been built on the first two phases. In this phase the procedures and indicators for monitoring the 

effectiveness and efficiency of agri-environmental measures developed have been identified. 

An analysis of administrative and transaction costs (for administrators and farmers) has also been carried out in 

this phase. Finally, the overall economic and financial aspects of the eventual implementation of the agrienvironmental 

measures proposed have been considered. 

In defining the common European analytical framework, the work carried out has allowed to identify scientific 

topics where further research will have to be carried out in order to enhance the scientific basis of the results 

achieved. The most important topics are the following: 

• Integration of different scales of analysis (field, farm, agri-ecosystem, region) and of socio-economic data with 

environmental data (e.g. ecological and administrative boundaries, FADN); 

• Validation of EMR and of dose-effect relationships between pressures and impacts by field research (e.g. 

Ecosystems functioning and resilience); and 

• Integration of ecological thresholds in economic evaluations and valuation of environmental benefits (e.g. 

consequences of irreversible ecological situations). 

The framework and the tools provided by AEMBAC can contribute to the development of a coherent, 

scientifically sound and transparent European agri-environmental policy taking into account the specific 

differences at the local level. The results obtained from the testing of the analytical framework defined in 15 study 

areas in 7 countries, show that the analytical framework for the development of local agri-environmental 

programmes is very promising in its foreseeable practical implementation and that it can be applied to very 

different ecological, economic, social, etc. situations. 

Benefits and Beneficiaries: 

The AEMBAC methodology is based on the idea of a knowledge driven Agro-environmental policy and 

Sustainable Rural Development and will contribute to the integration of scientific results into policy 

development both at local and European levels. 

The results of the project at the local level can contribute to: 

•The selection of scientifically based suitable indicators to analyse and measure the supply of environmental goods 

and services by agriculture; 

•Clear distinction between ecological sustainability in agriculture (i.e. respect of EMR) and realistically achievable 

results for the short term considering socio-economic aspects (i.e. agri-environmental policy targets); 

•More precise ecological, economic and social information to make trade-offs between different rural development 

objectives (e.g. scientific based definition of “good farming practices” at local level, clearer definition of risks and 

uncertainties with regard to unsustainable agricultural practices); 

•A more effective monitoring of impacts on the environment and consequently a better evaluation of AEM 

effectiveness and efficiency; and 

•Devolution to local farmers and administrators of the fine-tuning of policy measures in local agriculture, thereby 

creating an "evaluation culture”. 

The AEMBAC project at European level can contribute to: 

•The development of dynamic programmes for agricultural sustainability and conservation of European 

biodiversity and landscapes; 

•The enhancement of transparency and a wider application of the subsidiary principle in managing agrienvironment 

programmes; 

•The increase of environmental awareness amongst EU citizens; 

•The diversification of rural economies by enhancing the provision of environmental goods and services; 

•A smooth transition from compensation payments coupled to production to a more socially acceptable agrienvironmental 

payments for supply of environmental goods and services; and 

•Provision of scientific support to the concept of multifunctionality in agriculture (e.g. in relevant international 

fora such as WTO) by measuring the real supply of environmental goods and services. 

The results coming out from the AEMBAC project will clearly be of use to EU institutions, Member States, 

Regional and local administrations, Universities, Farmers’ organisations, Environmental organisations, Rural 

Development Planners, etc. 

7

1. Introduction 

The overall objective of the AEMBAC project was to define a common European analytical framework on 

which to develop local agri-environmental programmes. 

The project has achieved this overall objective and has defined a scientific methodology based on the 

concept of multifunctionality and of an ecosystem approach, to "internalise" positive and/or negative 

environmental externalities resulting from agricultural practices. This has been developed by adopting a 

comprehensive and interdisciplinary approach capable of identifying the value of the multiple environmental 

goods and services supplied by agriculture in Europe. 

From an ecological and socio-economic point of view, European agriculture is very diverse. In order to 

identify a common framework to develop agri-environmental measures, this diversity had to be taken into 

account. A representation of such diversity has been achieved by carrying out the proposed project in 15 

study areas in the 7 different countries participating in the project. 

The principal aim of the project was not to find common solutions to achieve sustainable agriculture across 

Europe, but to identify a common tool for the identification, development and evaluation of locally 

appropriate agri-environmental measures for biodiversity and landscape conservation. 

The choice of concentrating on the issues of biodiversity and landscape was due to the following reasons: 

Loss of biodiversity and its importance for agriculture. 

Biodiversity (at all levels: genes, species and ecosystems) is the basis of life on earth. Globally, the rate of 

loss of biodiversity has been estimated as being “at least 4 orders-of-magnitude greater than the typical rates 

seen in the fossil record” (Nowicky, 1999; Saether and Solhaung, European Commission, 1998a). Without 

biodiversity both natural environmental processes and human activities (such as food production) would be 

impossible. 

In fact biodiversity is a prerequisite of agricultural production: according to FAO (FAO, Netherlands 

Government, “Cultivating our future”, 2000) “…the main productive elements of agriculture and the genetic 

diversity within crops and livestock allows continued improvement and adaptation to changing needs 

through evolution and deliberate breeding.”. McNeely and Sherr (IUCN-Future Harvest, 2001) highlight the 

importance of biodiversity for soil fertility and quality, regulation of pest population, pollination, water 

quality and regulation of water run-off. 

The European Commission has adopted the Community biodiversity strategy (COM(98) 42 final) on 4 

February 1998. The strategy provides the framework for developing Community policies and instruments in 

order to comply with the CBD (which was signed by the EU at the United Nations Conference on 

Environment and Development in Rio de Janeiro in 1992, and ratified on 21 December 1993). Agriculture is 

one of the policy areas within the Community biodiversity strategy. 

From a more nature conservation policy perspective, a number of directives have been set up in order to 

conserve biodiversity, such as Directive 79/409/EEC on the conservation of wild birds (Birds Directive, 

1979), Directive 92/43/EEC on the conservation of natural habitats and wild fauna and flora (the Habitats 

Directive, 1992) and financial instruments such as LIFE-NATURE which started in 1984. 

The implementation of these Directives and instruments is showing some progress in some areas, but the 

pressures on ecosystems such as wetlands (according to the European Commission, 1996, agricultural 

intensification has reduced wetland areas by 60%) and dry grasslands, is still high (EEA, 1999). 

It is important to point out that under the heading of Natura 2000 and following the Birds Directive and the 

Habitats Directive, it has been proposed to build a network of European areas where socio-economic 

activities must be in accordance with the conservation of high natural values. 

8

Primary sector impacts on biodiversity 

European agriculture covers more than 50% of land use (Commission Européenne, 1997). The consequences 

of not adequately paying consideration in agricultural and rural development policies to the pressures exerted 

by cultivation practices on the environment (e.g. the encouragement given by the CAP on intensive 

production methods), have resulted in significant adverse impacts on biodiversity (EU, 1998). One of the 

most important objectives for the CAP reform stated by EU Commission in Agenda 2000 (1997) was the 

integration of environmental objectives and the empowerment of farmers' roles as managers and conservators 

of natural resources and landscapes. 

The need to integrate Biodiversity and landscape conservation objectives in the CAP has been recently 

confirmed by the reform proposed in June 2003 and by the European Conference on Rural Development held 

in Salzburg, 12-14 November 2003. 

Other international organisations such as OECD (2001), FAO (2000) and IUCN (1999), have also pointed 

out the importance of the agricultural sector’s relationship with biodiversity. FAO has a programme of 

classification on agrobiodiversity, OECD on agro-biodiversity indicators (among a wider programme on 

agro-environmental indicators), and IUCN has recently started to develop a policy on agriculture and 

biodiversity. 

The main negative impacts on biodiversity exerted by agriculture are those related to conversion of natural 

ecosystems and biotopes, reduction in number of species and varieties through homogenisation of 

production, introduction of alien species, effects of pesticides on non-targeted species, soil and water 

pollution (EEA, 1995; European Commission, Biodiversity action plan for agriculture, 2000). Among the 

positive impacts are the maintenance of traditional landscape and knowledge, conservation of local 

agrobiodiversity, and proper monitoring and management of the land. 

The character of the European landscape 

The Pan-European Biological and Landscape Diversity Strategy, promoted by UNEP and the Council of 

Europe, and endorsed by 55 European countries at the Ministerial Conference held in Sofia in 1995, 

highlights conservation of landscapes as one of its thematic actions. 

Article 1 of the European Landscape Convention gives the following definition of the term “landscape”: an 

area, as perceived by people, whose character is the result of the action and interaction of natural and/or 

human factors. 

It is the relationship between natural and human elements which makes the analysis of environmental 

functions related to the landscape strategic, when analysing interactions between agricultural activities and 

the environment. 

This is particularly true for Europe, where farmers have for centuries shaped the rural landscape. The 

existing interactions between anthropological and natural factors in shaping the landscape are widely 

recognised in scientific disciplines such as that of landscape ecology (see Box 3 below). 

Box 1: Landscape - Different definitions (Bastian, 2001) 

“Regarding the position, development and future of landscape ecology, we should remember the existing – rather 

numerous – definitions of the term ‘landscape ecology’ and its two roots ‘landscape’ and ‘ecology’. First, the scientific 

term ‘landscape’ was shaped by geographers, essentially by the German geographer and scholar Alexander von 

Humboldt 200 years ago (‘the total character of a region’). 

In 1850, Rosenkranz defined landscapes as hierarchically organized local systems of all kingdoms of nature. Neef 

(1967) characterized landscape as a part of the earth’s surface with a uniform structure and functional pattern. Both 

appearance and components (geofactors: relief, soil, climate, water balance, flora, fauna, humans and their creations in 

the landscape) including their spatial position are concerned. Landscape is, however, not only the sum of single 

geofactors, but an integration of the geographical complex (or geosystem). Thus, landscape is from different spheres: 

9

inorganic spheres, biosphere and sociosphere. According to Naveh (1987): ‘landscapes dealt with in their totality as 

physical, ecological and geographical entities, integrating all natural and human (‘caused’) patterns and processes...’ or 

Forman and Godron (1986) defined ‘landscape as a heterogeneous land area composed of a cluster of interacting 

ecosystems that is repeated in similar form throughout’. Leser (1997) regards the landscape ecosystem as a spatial 

pattern of abiotic, biotic and anthropogenic components which form a functional entity and serve as an environment for 

humans. 

Early definitions (19 th and beginning 20 th century) from Central and Eastern Europe (where the geographical and the 

biological roots of landscape ecology lie) reflect a holistic landscape conception. Later, influenced by the rising 

analytically working natural sciences, the ‘core of an all-embracing thinking was failing to be appreciated’ (Lehmann, 

1986). 

Still today, we also can observe repeated tendencies of reduction and specification. Landscapes consist of ‘structural 

components, or landscape elements, (which) are patches of several origins, corridors of four types, and a matrix“ 

(Forman, 1981) or ‘The (ideal) landscape is a primarily aesthetic phenomenon, closer to the eyes than to the mind, more 

related to the heart, the soul, the moods than to the intellect’ (Hard, 1970). We also find the rejection of the landscape 

paradigm, if King (1999) asks: ‘Is there in fact a landscape level’, or if Widacki (1994) wants to turn away from 

geocomplexes because we could fall back now on ‘satellite images as well as the resulting possibilities of integration 

and transformation of data read into computer with the aid of GIS’. 

Generally we can realize, however, that in view of the environmental problems coming to the fore, landscape is 

regarded more and more as a complex, highly-integrated system.” (Bastian, 2001) 

Other important results have been achieved as by-products of the AEMBAC project, for instance, in 

reference to the main elements for the evaluation of agri-environmental programmes 1 , the proposed project 

has achieved: 

• The identification of general and specific agri-environmental objectives at local level; 

• Collection of baseline data and establishment of systems to monitor impact; 

• Identification of elements to be monitored and evaluated: environmental, agricultural, socio-economic; 

• Selection of suitable indicators and creation of a data base; and 

• Assessment of relation to other policies, including competition with other land use schemes. 

The AEMBAC project has provided scientifically based information related to detailed environmental 

objectives, such as Environmental Minimum Requirements (from now on referred to as EMR), which help 

determining agri-environmental policy targets and measures. 

Following this approach a clear distinction has been made between ecological sustainability in agriculture 

and realistically achievable results in the short term (i.e. agri-environmental policy targets) at the local level. 

The framework and the tools provided by AEMBAC will help to build a European agri-environmental policy 

with specific differences targeted at the local level. At local level the adoption of the methodology developed 

is expected to enhance: 

• A more effective monitoring of agri-environmental effectiveness compared to current practices which 

usually focus more on the correct implementation of agri-environmental undertaking practices than on 

environmental benefits achieved; 

• The development of dynamic programmes for the transition phase towards sustainability; 

• The promotion of environmental awareness amongst EU citizens; 

• A clearer definition of risks and uncertainties with regard to unsustainable agricultural practices; 

• A trade-off between different objectives with more precise information; and 

• The devolution at local level (farmers and administrators) of the fine-tuning of policy measures in local 

agriculture which will make stakeholders more responsible, thereby creating an “evaluation culture”, 

fundamental for the development of an environmental ethic. 

The framework and indicators proposed will directly contribute to European policies concerning: 

• The growing demand for food quality and environmental conservation by EU citizens. This will require 

1 Listed by the Commission in the STAR Working Document VI/3872/97 

10

an increase in the supply of these goods and services; 

• The enhancement of transparency and promotion of a wider application of the subsidiarity principle in 

managing agri-environment programmes; 

• The diversification of rural economy by enhancing the multifunctional character of European agriculture; 

• The problem of EU CAP budget constraints. The framework proposed will offer a smooth shift from a 

highly criticised system of compensation towards a more acceptable system of agri-environmental 

payments; and 

• The envisaged requirement of a progressive and substantial reduction in support and protection in 

agricultural world markets e.g. subsidies. Only subsidies that do not distort trade will still be allowed, 

such as those related to decoupled agri-environmental measures, pre-retirement subsidies and structural 

payments for rural development (e.g. the so-called green box). 

The proposed methodology could also prove useful in evaluating and promoting the sustainability of other 

sectors such as forestry, fisheries, tourism and management of Protected Areas. 

Throughout the project, the methodology developed has been tested in 15 case studies in the 7 countries 

participating in the project. The objectives of the AEMBAC project have been addressed by considering 

three interdependent project phases: 

• Phase 1: Definition of a methodology to assess the impacts exerted by agricultural pressures on the local 

environment 

• Phase 2: Definition of a methodology to develop Agri-environmental measures at local level 

• Phase 3: Definition of a methodology to implement the Agri-environmental measures developed 

Fig. 1 gives a schematic representation of the three phases and relative steps of the project 

Phase I 

Phase II 

Phase III 

Step 2 - Identification and analysis of 

environmental functions 

Fig. 1: AEMBAC methodology flow diagram 

Step 1 - Identification and description 

of study areas 

11 

Step 3 - Description of local agricultural systems and 

identification of the most important pressures and driving 

forces on environmental functions 

Step 4 - Assessment of ecological sustainability of local agricultural pressures and 

development of recommendations on how to lessening/eliminating negative impacts 

and enhancing positive ones 

Step 5 – Economic valuation of 

neative/positive impacts and 

identification of externalities 

Step 6 – Studying local 

sustainable agri-environmental 

policy targets and measures 

Step 7 – Studying agri-environmental measures implementation: Definition of monitoring, evaluation 

procedures and contracts; Analysis of administrative and transaction costs and overall economic and 

financial aspect

2. Materials and methods 

The overall objective of the AEMBAC project was to define a common European analytical framework for 

the development of local agri-environmental programmes for biodiversity and landscape conservation. 

To achieve the definition of a European analytical framework for the development of agri-environmental 

programmes, there was the need to identify a common and clear scientific rationale to take into account the 

diversity of ecological, social and economic aspects amongst and within European countries and the inherent 

complexity of biodiversity, rural landscapes and agricultural systems. 

Diversity. From the ecological and socio-economic points of view, European agriculture is very diverse. 

Diversity is probably the most identifying character and richness of Europe together with the capacity and 

willingness of European citizens to be unified under the respect of such diversity. 

Diversity amongst and within European Countries should be taken into account and respected while defining 

a common framework for the development of agri-environmental schemes. Failure to do so will mean to 

define something which will not be “Europeanly” sustainable. 

In AEMBAC a representation of such diversity was achieved by carrying out the proposed project in at least 

two areas per each of the seven different countries involved. From the results of the analysis carried out in 

the seven country studies, a common European framework has been identified. 

The principal aim of the framework proposed in this project was therefore, not to find common solutions to 

achieve sustainable agriculture across Europe, but to identify a common tool for the identification, 

development and evaluation of locally appropriate agri-environmental measures. 

Complexity is in the topics to be analysed. Biodiversity and landscape conservation are very difficult topics 

to analyse because of their inherent comprehensive and interdisciplinary characters. Just looking at two 

definitions, one for biodiversity and one for landscape, is sufficient to give an idea of this complexity: 

Biodiversity has been defined by art. 2 of the Convention on Biological Diversity as follows: “Biological 

diversity means the variability among living organisms from all sources including, inter alia, terrestrial, 

marine and other aquatic ecosystems and the ecological complexes of which they are part; this includes 

diversity within species, between species and of ecosystems”. 

Landscape has been defined by art. 1 of the European Landscape Convention: “An area, as perceived by 

people, whose character is the result of the action and interaction of natural and/or human factors”. 

Also it is important to point out that, while progress in knowledge and information on biodiversity and 

landscape has been considerable during the last century, many aspects of processes and components 

interacting in natural and agricultural ecosystems still need further investigation and understanding by 

natural and landscape sciences. 

To make things even more complex, AEMBAC also had to deal with economic and social issues, such as the 

economic valuation of biodiversity and rural development. 

Another issue to be taken into account when developing an analytical framework for the building up of agrienvironmental 

schemes locally tailored for the supply of multiple environmental goods and services and the 

reduction of negative impacts exerted by agriculture, was the practical implementation of the scientific 

results to be done by decision-makers, local farmers and administrators. 

In order to deal with such diversity and complexity some decisions on the approach to be adopted had to be 

taken from the very beginning. 

12

In fact to address effectively the topic of biodiversity and landscape conservation in different countries 

through the agricultural use of land there is a need for an approach that is: 

• Interdisciplinary and comprehensive (i.e. holistic): it has to be capable of reflecting the complexity of the 

topic studied; 

• Manageable: it has to be capable of synthesing the object of analysis while at the same time still 

retaining its complexity; 

• Realistic: suitable to facilitate the integration of analysis results in the development and implementation 

of agri-environmental programmes; and 

• Comparable between different countries: it has to be able to represent different ecological, economic, 

and social realities within the same analytical framework. 

Regarding the comprehensive and interdisciplinary character, it was decided to concentrate the analysis on the 

performance of environmental functions by (semi-)natural and agricultural ecosystems. 

Environmental functions in AEMBAC have been defined as “the capacity of natural processes and 

components to provide goods and services that satisfy human needs, directly or indirectly” (De Groot, 1992). 

The environmental functions approach synthesises much ecological information while at the same time 

retaining the complexity of biodiversity, landscape and agriculture systems. 

Studying environmental functions means to investigate natural processes and components through an 

ecosystem approach (comprehensive) and to link natural and social sciences (interdisciplinary) to analyse 

the satisfaction of human needs. This approach, while looking at the performance of environmental 

functions, is capable of providing information on the environmental goods and services supplied. This fact, 

which already points out the utilitarian and anthropocentric character of the benefits which can be derived 

from biodiversity and landscape conservation, facilitates integration between natural and social sciences. The 

consideration of this aspect becomes important when the ecological results of analysis in phase 1 have been 

translated into economic values for the development of agri-environmental measures in phase 2. 

To make the environmental functions approach manageable what is needed is a definition of the scale of 

analysis and the thresholds against which to measure the performance of environmental functioning. 

Having defined the environmental functioning as the result of the interaction between ecosystems processes 

and components, the scale of analysis to be addressed in order to identify environmental functions and 

capable of reflecting both the ecological and agricultural systems is the local level, and in particular the agroecosystems/landscape 

level including cultivated fields and semi-natural habitats. 

Beside the above it is a well-accepted fact that evaluation of conservation of biodiversity and landscape tends 

to be site specific, covering complex systems of biotic, abiotic and aesthetic components within the 

ecological dimension, which rarely can be found in similar conditions and relationships elsewhere. 

On this point, the Commission of the European Communities(2000), while addressing indicators for the 

integration of environmental concerns into the CAP, states that “… if these indicators are to be meaningful, 

they must give a sufficiently accurate picture of the underlying processes and relationships that link human 

activities with the environment. This is particularly the case for agriculture where the relationship is highly 

complex and where farming itself involves a range of biophysical and site specific processes”. 

This view is supported also by A. Moxey, M. Whitby and P. Lowe (1998) cited in the EU DGVI 

Commission Working Document VI/7655/98 (p. 33). Adding considerations of social and economic 

characters to the picture only enhances the specificity of each evaluation. 

For what regards thresholds, there is wide recognition, both scientific and political, of the necessity of 

establishing baselines (temporal, counterfactual and benchmarking), against which to measure: 

• the state of health of an ecosystem; 

• the sustainability of the intensity of pressures exerted on this; and 

13

• the effectiveness and efficiency of policy interventions. 

For the definition of baselines, it is important to point out that the concept of sustainability adopted in 

AEMBAC is one of so-called “strong sustainability”. This means that natural and man-made capitals are 

considered substitutable only up to a certain point. In other words a certain minimum quality and quantity of 

ecological processes and components have to be present so as to allow the performance of the environmental 

functions selected. This is the benchmark necessary to evaluate the ecological sustainability of the local 

agricultural system. In other words, if environmental goods and services have to be supplied to satisfy human 

needs directly and indirectly, some natural resources need to be maintained in order to allow nature to 

provide these. 

This approach to identify baselines is also in line with: 

• Article 6(1) of the ‘Habitats’ Directive 92/43/CEE, where it is explicitly stated that the necessary 

conservation management measures have to correspond: ‘to the ecological requirements of the natural 

habitat types of Annex I and the species in Annex II present on the sites’; 

• STAR documents VI/12004/00 and VI/43517/02, where reference is made to compare effectiveness of 

rural development programmes against baselines: Temporal, Counterfactual situation, and 

Benchmarking (against Norm or best practice); and 

Regulation (EC) No 1257/1999 (on Rural Development), Article 2, where there is explicit reference to: 

“the preservation and promotion of a high nature value and a sustainable agriculture respecting 

environmental requirements”. 

By looking at the state of (semi-)natural and agricultural ecosystems processes and components, which are 

crucial for the performance of the environmental functions, the approach consists of detecting their conditions, 

after pressures from agriculture have been taken into account, and assessing, against thresholds, if these are 

sufficient to allow a satisfactory performance for delivery of environmental goods and services. 

By recognition of the fact that without a certain level of environmental components, structures and processes 

both ecological and agricultural systems will experience a decrease in their performances, this project 

introduces a new scientific approach to look at thresholds. 

Thresholds are then defined by those Environmental Minimum Requirements (EMR) of agro-ecosystems 

components, structures, and processes which are necessary to allow for the performance of the selected 

environmental functions. 

Regarding the integration of project results into the agri-environmental policy development process, the 

environmental function approach points out the provision of environmental goods and services in a utilitarian 

and anthropocentric way, and offers the opportunity to develop an analytical framework which can be easily 

understood by policy-makers, farmers and the general public. This fact, together with the analysis of the 

social and economic aspects of agri-environmental measures, makes the practical implementation of project 

results more realistic. 

In order to have comparability amongst different countries and regions, common guidelines to carry out 

each Step of the methodology were developed by the scientific co-ordinator and sent to Partners whose 

comments were integrated into the guidelines. After this process, guidelines were produced which were to be 

followed in carrying out steps tasks. 

To achieve the definition of the analytical framework to develop AEMs, the project was divided into three 

phases as follows: 

Phase 1 has identified the performance of different environmental functions in different agro-ecosystems. 

The Driving forces, Pressures, State, Impacts, Responses (DPSIR) approach, developed by international 

organisations such as OECD and EEA, has been adopted to analyse the impacts exerted by local agricultural 

systems on the performance of selected environmental functions. 

14

Environmental functions have been described and analysed by a set of locally relevant state indicators 

(environmental profile) describing ecological structures, processes and components at landscape/agroecosystem 

level. For instance the habitat function has been described by state indicators such as ecosystems 

extension, ecosystems diversity, abundance and richness of key species, etc. 

For each state indicator identified, the respective Environmental Minimum Requirement (EMR) value to be 

matched in order to achieve the Environmental function performance was assessed. By looking at the gaps 

between actual values of state indicators and their corresponding EMR, positive or negative impacts on the 

performance of the environmental functions were identified. 

Local agricultural pressures have been identified by using agri-environmental indicators proposed by 

international organisations such as EU, OECD, ECNC, etc. and adapting these at farm level. 

Four broad classes have been used in AEMBAC: 

• Nutrients management indicators; 

• Pest control management indicators; 

• Land and soil management indicators; and 

• Water and irrigation management indicators. 

Driving forces have been identified both at local/regional (e.g. local economies of scope, cultural identity, 

environmental endownement, etc.) and national/European level (e.g. markets and vertical integration 

processes, CAP, social policy, etc.) 

The overall objectives of Phase 2 were the identification and development of agri-environmental 

programmes locally tailored to the most relevant impacts exerted by agriculture, in order to foster the supply 

of environmental goods and services by farmers (and to discourage unsustainable agricultural practices). 

Starting from the identification and analysis of causality relationships between detected impacts on 

environmental functions performances and locally most relevant agricultural practices, the research has 

focused on developing an operational tool, capable of building up a bridge between science and policy. The 

assessment of sustainability of local agricultural pressures in reference to environmental function 

performances has been carried out by developing a ranking system associating positive/negative tiers 

respectively to positive/negative impacts. Recommendations on locally tailored best agricultural practices to 

eliminate/lessen negative impacts and enhance positive ones have been developed. 

After studying the most important socio-economic aspects to be considered in order to assess the “socioeconomic 

carrying capacity” of the study areas, research teams carried out economic valuations of the 

envisaged costs (and where feasible, also the benefits) of proposed recommendations to scaling-up tiers. The 

research then focused on the identification of externalities, along the rationale that economic values of the 

environmental impacts are not always reflected in current agro-economic market performances and/or in 

government interventions. 

As the above analysis showed that the economic values of environmental impacts were not yet internalised, it 

was necessary to study which approach would be the most suitable to internalise the economic value of 

externalities through agri-environmental policy on a local level. The ranked agronomic recommendations, 

the economic valuation and the socio-economic information constituted the basis for the identification of 

feasible agri-environmental policy targets and the corresponding policy instruments (e.g. market or 

command and control) needed to achieve them. 

Qualitative and quantitative comparisons between agri-environmental measures developed using the 

methodology defined and those already existing in study areas have been carried out. The impact of EU 

enlargement on biodiversity and landscape conservation within the agricultural sector has been considered in 

the countries concerned (e.g. see Hungarian and Estonian Reports). 

The agri-environmental measures defined by using the methodology developed in AEMBAC for the specific 

areas studied have been presented to local stakeholders. Interviews and discussion on the implementation 

15

feasibility of the AEMs developed for the local situation has been carried out with the involvement of these 

stakeholders, namely local farmers and administrators. A definition of agri-environmental reporting 

procedures (for farmers) on the implementation of AEMs has also been carried out in this phase. 

Phase 3 has built on the first two phases. A definition of monitoring the effectiveness of agri-environmental 

measures to be used in case of implementation has also been carried out in this phase. Procedures to issue 

agri-environmental contracts between farmers and public administrations have been defined and 

administrative and transaction costs have been assessed. 

The overall economic and financial aspects of the eventual local implementation of the agri-environmental 

measures have also been considered. 

Finally, it is important to point out that a data base on indicators used and a co-ordination of the production 

of GIS maps was also achieved while carrying out the AEMBAC project (cp Annex 1 for more detail). 

16

3. Results 

3.1 Step 1 - Identification and description of study areas 

The objective of this Step was to identify and describe areas in which to test the methodology to develop 

agri-environmental measures for biodiversity and landscape conservation. 

The choice of the scale of analysis needs to take into consideration the adoption of the approach of the 

environmental function analysis to define the analytical framework to develop AEMs. 

Having defined environmental functioning as the result of the interaction between ecosystem structures, 

processes and components, the scale at which analysis shall be carried out in order to identify environmental 

functions and to reflect both the ecological and agricultural systems is the agri-ecosystem/landscape level. In 

fact environmental functions need a minimum critical area to become measurable. 

As far as measurement of the impacts of human activities is concerned, the agri-ecosystem/landscape 

intended also, as “habitat of people” (European Commission, 1998), represents a critical level of analysis. In 

Europe agricultural practices have shaped natural and semi-natural areas for centuries into cultural 

landscapes. It therefore becomes strategic to assess agricultural impacts over environmental functions 

considering the aggregate effects of farming within the same landscape. This approach facilitates a further 

in-depth analysis at the farm level, which is the critical unit for the practical implementation of the agrienvironmental 

measures. 

Beside the above, it is a well-accepted fact that evaluation of conservation of biodiversity and landscape 

tends to be site-specific, covering complex systems of biotic, abiotic and aesthetic components within the 

ecological dimension, which rarely can be found in similar conditions and relationships elsewhere. 

Once defined the scale of analysis at the agri-ecosystem level, (consisting of rural landscape, natural and 

seminatural ecosystems, farms, and fields levels), it is important to underline that there is no fixed extension 

to be analysed in order to develop agri-environmental programmes, but on the contrary this depends on the 

ecological and agricultural systems studied. 

In AEMBAC, the local level was identified in approximate dimensions of study areas ranging from 5,000 to 

100,000ha. This wide range is due to different ecological situations present in different areas and has to be 

considered only as indicative. In fact, for certain environmental aspects the area to be interested by the 

development of agri-environmental programmes could be far greater than the upper level of the range 

adopted in AEMBAC, so creating economies of scale in the developing and eventually administering of agrienvironmental 

schemes. 

It is worth noting that the non-territorial coincidence of the ecological dimension with the socio-economic 

one and with administrative boundaries, is the norm rather than the exception. In other words the 

ecosystem/landscape level of analysis results in a non-coincident contextualised juxtaposition of the 

ecological, socio-economic, institutional and administrative dimensions of agriculture. This fact could create 

problems of significance of socio-economic data gathered within administrative boundaries, when these have 

to be used to develop agri-environmental measures which are studied following ecological boundaries. 

The influences on natural and agricultural systems from upper levels of the spatial hierarchical approach 

adopted, i.e. regional, national, global levels (e.g. WTO agreements, Global Warming) were acknowledged 

in AEMBAC but not analysed (see Fig. 2.1 below). 

17

World 

Country 

Fig. 2 Spatial hierarchical scales: some examples of different spatial relationships (in red circles levels 

analysed in AEMBAC) 

In order to facilitate the selection of study areas, some general criteria were given, while taking care not to 

restrict each Partner country’s freedom of choice, so that the selection would reflect the diversity of the 

European ecological, social and economic realities. 

These criteria are: 

Commodities and Non- 

Commodities: e.g. C02 

emission, biodiversity 

Commodities and Non- 

Commodities: e.g. 

biodiversity, landscape 

Economic, social and 

ecological structures 

Landscape/ 

Ecosystem 

Environmental 

goods and 

services 

Cultural 

Products 

identity 

Region Farm 

Field 

Markets & Economic 

infrastructures, 

investments, etc. 

Environmental, social 

and macro-economic 

policy, CAP, etc. 

Investment and purchases, 

Global environmental 

priorities, WTO 

agreements, etc. 

1. Importance and measurable extension of biodiversity and landscape aspects and/or severity of 

environmental problems in the area; 

2. Environmental and Agricultural aspects relevant at country level so as to address problems which 

may also be of interest to other areas of the country; 

3. Pedagogic properties of the area for testing the methodology the project will develop; and 

4. Availability of existing data. 

18 

Rural development 

and agrienvironmental 

policy 

Goods and 

services 

Processing and 

Market facilities 

Managemen 

t decisions 

Labour, 

machines and 

processed 

inputs

Tab. 1 - AEMBAC - Application of selection criteria to the choice of proposed pilot areas in Estonia 

Selection criteria Kihelkonna Community 

Palamuse Community 

(Saare County) 

(Jõgeva County) 

Size Total area – 24,595ha; 

Total area– 21,607ha; 

total agricultural land – 4,042ha; total agricultural land – 10,286ha; 

agricultural land in current use – 1,724ha agricultural land in current use – 9,349ha 

Contrasting natural Situated in lower Estonia* on Silurian Situated in higher Estonia 

factors 

limestones 

Maritime western climate 

2 on Devonian 

sandstone 

More continental eastern climate 

Contrasting 

An area of extensive agricultural An area of intensive agricultural production 

agricultural activity production on poor, drought-prone soils with relatively fertile soils 

and 

Encompasses valuable (high biodiversity) Unique (drumlin area) heritage landscape 

biodiversity/landscap 

e 

semi-natural habitats 

value 

Project 

Kihelkonna Community 

Palamuse Community 

administration factors (Saare County) 

(Jõgeva County) 

Co-operative local Local government, Viidumäe Nature Local government, County government 

actors present Protection Area, West-Estonian 

Biosphere Reserve 

Availability of As above + 

As above + 

secondary data Local environmental adviser 

Estonian Agricultural University 

sources 

specialists from the protected areas 

Centre for Ecological Engineering 

Centre for Ecological Engineering 

Local political In both areas the community government is very interested in having their community as a 

support/approval pilot area and they recognise the need for agri-environment measures 

Once the areas (at least two per country) had been identified, a general description of the most relevant 

ecological, economic and administrative-social characteristics was needed in order to give an initial picture 

of the local situation. This description serves the purpose of introducing the basic aspects which have to be 

analysed and considered in the following steps. At this level of analysis, economic and social information 

(such as per capita income or population density) is likely to respect more administrative boundaries than 

those of selected agro-ecosystems. It was then suggested to point out the different scale regarding this type of 

information. In fact ecological aspects of the areas were to be analysed more in depth in the following step 2, 

while economic and social issues related to the agricultural system had to be analysed in step 3. 

The information required to draw the ecological profile of the study area was a territorial description of the 

morphology, geology, hydrology, ecology, climate, land use, and natural, semi-natural and agricultural 

ecosystems present in the area. Many of these data were acquired and analysed using GIS and other related 

digital data processing techniques (cp Annex 1.2). This information was to be used as background for the 

analysis in the following Steps. 

Box 2 - AEMBAC project: Ecological aspects in Oberes Fricktal case study, Switzerland (extract) 

Localisation and extent: The study area Oberes Fricktal is situated in the north of Switzerland, in the department 

(“Kanton”) Aargau. It includes both Jura landscape and parts of the river Rhine plain. In the north, the river Rhine 

forms a natural border on a length of 12 km. In the east it is the mountain of Besseberg, in the west the Kaistenberg that 

are confining the study area. The altitudes range between 300 m a.s. (Rhein) and 722 m a.s. (Schinberg near Ittenthal). 

The extension of the study area is 6.550 ha. 

Administrative Borders: There are 11 municipalities in the study area: Hottwil, Etzgen, Gansingen, Ittenthal, Kaisten, 

Laufenburg, Mettau, Oberhofen, Schwaderloch, Sulz, Will. The administrative borders of these municipalities do not 

coincide with the limits of the study area. 

Geomorphology: The region is formed by the typical Jura mountains with smooth hills. The topography is of wide 

diversity. Different types of minerals and sediments built up the soils: Shelly limestone, “Gipskeuper”, opalinus tone. 

2 Estonia is divided into higher and lower Estonia. Lower Estonia has been more influenced by glacial lakes and by the 

sea, is more marshy, more densely wooded and flatter than higher Estonia, which has been untouched by flooding from 

glacial lakes and the sea. 

19

On the plateau along the Rhine river there is morainic scree and in the river valley there is river crushed stone. 

Hydrology: Less than 1% of the surface is water. The water shed of the study region Oberes Fricktal covers 6.570 ha. 

Several creeks in the study area flow into the river Rhine which evacuates the water of this area. Most creeks have 

water all the year because of relatively high precipitation. 

Climate: In the Rhine plain the average temperature last year was at 9° C, the middle temperature in July around 18 – 

19° C. The vegetation period lasted in the lower parts of the valleys 210 – 230 days, ca. 180 days in higher locations. 

There are between 1000 and 1150 mm precipitation per year, the average rainfall in July was 80 mm. On 130 days per 

year, the daily precipitation is higher than 1mm per day. The region has less than 50 days of fog and there is low risk of 

hail. 

Land use: 

Tab. 2: Land use of the study area Oberes Fricktal (2000) 

Type of surface Area (ha) Area Share (%) 

Total (all the municipalities of the study area) 6.569 100,0 

Forests 2.844 43,3 

Agricultural land (arable crops, grassland) 2.923 44,5 

Settlements 460 7,0 

Source: Statistisches Jahrbuch des Kanton Aargau – 2000. Statistisches Amt des Kanton Aargau. Effingerhof AG, 

Druck und Verlag, Brugg (Schweiz). 363 pp. 

Agro-ecosystems: 45% of the landscape is used as agricultural land. Although in Switzerland agriculture is mostly of 

high input and high energy, almost all farms are producing under the label of integrated production which allows only a 

restricted and controlled use of synthetic fertilisers and pesticides. 

Arable fields: Almost 40 % of the agricultural land is used for arable crops, mainly cereals. There is limited rape 

cultivation and very few potatoes, sugar beets or vegetables, especially in the flatter areas of the Rhine plane. 

Commonly cultivated are corn and wheat. The area covered by agricultural crops is currently decreasing in the Aargau 

Canton. 

Grassland (meadows and pastures): Fodder cultivation dominates the region. 60% of the agricultural land is made up 

of various types of pastures and meadows. Due to traditional cultivation practices, Mesobromion and Arrenatherion 

(meadow types with high biodiversity) were once widespread types of extensively used grassland. Today they are 

endangered due to intensification and abandonment of patches. Pastures are usually on rather steep slopes and used in 

an extensive way. 

Other agro-ecosystems: The fields or grasslands are often bordered by high stem fruit tree orchards, in particular 

cherries and plums. These high stem orchards are the rests of traditional extensively used fruit plantations, which were 

dominating the landscape in former times (end of the 19 th and first half of the 20 th century). Vineyards sometimes cover 

the slopes of the Rhine plane. Usually they cover the Southern slopes. There are many hedges which connect the 

different ecosystems of the landscape. 

Non-agricultural ecosystems: 

Forests: The rounded hilltops are covered with large and well connected forests. The forests represent an important part 

of the landscape, since they cover 43% of it. It mainly consists of Carpinion and Quercion pubescentis like forest types 

with Molinio pinetum areas on very steep and dry slopes. 

Waters: Rivers and creeks occupy less then 1% of the area. Besides the river Rhine there are only some creeks as the 

Galtersbach, Sulzerbach and Etzgerbach. A considerable part of the flowing surface waters – in particular small brooks 

– are now flowing underground. 

Settlements: 7% of the landscape is covered by settlements. The 9.000 inhabitants are live in heaped and concentrated 

small villages in 11 municipalities. It is expected that the settlement area will grow in the coming decades. 

Others (incl. natural and semi-natural ecosystems): 7% of the surface of the study region is covered by nature 

reserves. More than 650 plant species found, reflect the variety of the habitats. The plain of the Rhine with its crushedstone 

soils is an important migration corridor and site for the spawning amphibians. 

Future targets: 

The most important changes in the last 50 to 100 years occurred in extensively used meadows with a reduction of 99%. 

Since 1951 also 75% of the high stem fruit orchards were destroyed. Together with hedges, structurally rich forest 

borders, heaps of stones and bushes they were offering precious habitats for insects, birds and flowers that vanished at 

many places. 

The main aim in the region is to assure the maintenance of extensively used meadows. By integrating them with high 

stem fruit orchards, hedges, vineyards and creeks into the existing landscape elements, the structural diversity can be 

20

intensified. In the plane of the Rhine, new habitats have to be created and connected: extensively used meadows, 

fallows, ruderal spaces in gravel-pits... 

Analysis of local social, cultural, economic and institutional features. 

The objective of studying the local social structure, cultural identity, rural economic activities, institutional 

framework, legislation and relations between agriculture and other sectors, was that of understanding the 

socio-economic environment where farmers and their families live and work. 

Topics proposed to be analysed and commented upon were: 

Substrate for social development (e.g. analysis of educational and basic sanitation rates, unemployment 

rate, population density, population age and growth, poverty rate) 

Social identity/ethics/laws/values (e.g. historic, spiritual, religious, cultural and artistic information and 

value systems, institutional systems) 

Satisfaction of human material needs (e.g. food sufficiency, shelter, health services, etc.) 

Opportunities for satisfaction of human non-material and recreation needs (e.g. landscape attractiveness, 

leisure activities, etc.) 

Substrate for economic development (e.g. infrastructures for agriculture, tourism, fisheries, housing, 

transport, access to credit, etc.) 

Existing socio-economic sectors, local GDP, incomes and investments (e.g. per capita income, 

employment, etc.) 

Equitable sharing of economics benefits (e.g. income distribution) 

The importance of considering socio-economic factors in the building up of agri-environmental measures lies 

in at least three facts: 

Firstly they can act as driving forces for the agricultural pressures identified as exerting impacts on the 

environmental function performance. Therefore their analysis allows those forces to be identified which are 

responsible for the pressures causing the impacts (see section 3.3.5 below). 

Secondly when developing agri-environmental measures, it is important to be aware of the possible effects 

that these, as any other policy, can have on socio-economics variables such as income distribution, per capita 

income, employment, etc. These aspects had to be considered in Step 6 where the most suitable approach 

(e.g. market based or command and control) was proposed for the development of agri-environmental policy, 

given the local socio-economic and institutional situation. 

Thirdly some socio-economic aspects such as social values and institutional functioning could have a role in 

designing the agri-environmental measures. For instance, different environmental awareness held by the 

local community can influence the content and kind of agri-environmental measures proposed, or the 

institutional structures and functioning can have an impact on the transaction costs incurred in their 

implementation. 

Considering the above and suggestions from the task force, the following scheme was proposed for 

identification, description and analysis of socio-economic factors: 

• Provide a list of the most important socio-economic aspects to be analysed for the case study area. This 

had to include relevant aspects listed above plus any others which are considered crucial for the local 

situation. 

• For each selected aspect explain its importance and the indicators that measure it. The use of indicators 

already standardised at the European level would obviously facilitate comparisons between countries 

(such as the Farm Accountancy Data Network (FADN) which has been used in Step 3). 

• Provide the actual measurement of the aspect analysed and historic trends if these were available. 

• Provide reference to the source of information and data. 

21

Box 3 – AEMBAC project: Socio-economic data in Egyek-Pusztakócs study area -Hungary (extract), 

Data and information from different sources: 1 - Mayor’s Office of Egyek, 2 - County Directorates of Hungarian Central 

Statistical Office, 3 - Regional Statistical Yearbook 2002, 4 - Micro-Regions of Hungary – North-Plain, 2002, 5 - National 

Health Insurance Office 

Tab. 3 Summary of social, cultural, economic and institutional features 

Socio-Economic 

aspect 

Indicator 

Egyek- 

Pusztakócs Pilot 

Area 

Balmazú 

jváros 

Microregion 

POPULATION 

22 

North- 

Plain 

Region 

Population Persons 6045 30548 1559073 10174853 

Area of 

settlement 

Population 

density 

Sex distribution 

Ageing index 

Natural growth 

rate 

km 2 104.8 731 17729 93029 

population per 1 km 2 58 42 88 109 

old-age population as a 

percentage of child 

population 

difference between birth 

rate and death rate - per 

1000 inhabitants 

Rate of 

population living under 

inhabitants 

the subsistence level in 

living under the 

the % of total population 

subsistence level 

Number of 

primary school 

students 

Education of 

Informatics 

Education of 

foreign 

languages 

Male: 49% 

Female: 51% 

- 

M: 47,9% 

F: 52,1% 

Hungary Importance 

M: 47,5% 

F: 52,5% 

79,7 - 74,8 93,5 

-4.9 -1.2 -1,7 -3,4 

19.8 - - - 

EDUCATION 

Persons 520 - - - 

available or not + - - - 

available or not + - - - 

Rate of students in the percentage of 

finishing students beginning 

secondar. school secondary school 

Population of 

working age 

Rate of 

employed in the 

agricult. sector 

Rate of 

employed in the 

industrial sector 

Rate of 

employed of the 

service sector 

Rate of 

employed of 

local 

government 

Unemployment 

rate 

economically active and 

inactive population as a 

percentage of total 

population 

number employed in 

agriculture as a 

percentage of employed 

number employed in 

industry as a percentage 

of employed 

number of employed in 

service sector as 

percentage of employed 

number of employed in 

local government as % 

of those employed in 

service sector) 

unemployed persons as % 

of economically active 

population aged 15-74 

Houses connected to public water conduit 

network as a percentage of dwellings 

Households consuming piped gas as a 

percentage of dwelling stock 

90 - - - 

EMPLOYMENT 

74.8 - 73.9 75.4 

88.7 15.1 - 6.2 

4.6 40.5 - 34.2 

6.7 44.4 - 59.6 

27 - - - 

22.5 11.3 7.8 5.7 

INFRASTRUCTURE 

99 93.2 91.6 92 

60 66.9 65.1 71.3 

aspect representing local driving 

force with direct impact on pressures 



aspect with indirect impact on 

pressures 

important aspect but not determinant 

relating to pressures 


pressures 


pressures 


pressures 










pressures 




pressures 

aspect meaning local driving force 

with direct impact on pressures 









Source 

of 

informat 

ion 

1 

1 

1 

1 

1; 3; 4 

1; 3; 4 

1 

1 

1 

1 

1 

1; 2; 4 

1; 2; 3; 4 

1; 2; 3; 4 

1; 2; 3; 4 

1; 2; 3; 4 

1; 2; 3; 4 

1; 3 

1; 3

Telephone main lines per 1000 inhabitants 232 245 258 323 

Total paved roads as a percentage of all 

roads 

Households connected to public sewerage 

as a percentage of dwellings 

Inhabitants per General Practitioner and 

family pediatrist 

Accessibility of 

consultation by 

specialists 

distance from Egyek – 

km 

30 - 99.1 98.9 

30 27.8 35.3 53.5 

SANITATION 

3022 1697 1612 1516 

62 (Debrecen or 

Balmazújváros) 

- - - 

Dental service inhabitants per dentist 3023 - - 2100 

Pharmacy inhabitants per pharmacy 6045 5091 5029 5085 

ECONOMIC FEATURES 

GDP per capita €/persons 650 - 3236 5152 

Net income per 

capita 

Age of 

settlement 

Religious 

distribution 

Library 

Civil 

organisations 

€/persons 740 1509 1837 2025 

23 








pressures 


pressures 


pressures 


pressures 


pressures 


pressures 

HISTORIC-RELIGIOUS-CULTURAL INFORMATION 

Years ~700 - - - 



religion of more than 

90% of religious popul. 

stock per 1000 

inhabitants 

Roman Catholic - - - 

4963 - 2941 4551 

number of organisations 8 - - - 

Recreational possibilities for inhabitants 

Rural tourism 

farmhouse accomodation 

- number of bed-places 

per 1000 inhabitants 

LEISURE ACTIVITIES 

angling, hunting, 

riding, River 

Tisza 

- - - 

16 51 23 31 




pressures 







3.2 Step 2 - Identification and analysis of environmental functions 

Once study areas had been identified and a first overview of their main ecological, social and economic 

aspects had been given, the objectives of Step 2 were to identify and analyse the environmental functions 

that are performed by natural and agricultural ecosystems in those areas. 

3.2.1 Identification of environmental functions to be studied within the area and description of the 

most important attributes and characteristics (critical aspects) for their performance 

As already stated above, environmental functions in AEMBAC have been defined as “the capacity of natural 

processes and components to provide goods and services that satisfy human needs, directly or indirectly” 

(De Groot, 1992). 

Many different types of environmental functions performed by natural, semi-natural and man-made 

ecosystems can be identified. Stig Wandén and Peter Schaber (1998) identify functions which have 

information values (aesthetic, educational, scientific, orientation, signal), functions which have ethical values 

(e.g. right to existence for all living creatures), functions which have production values (e.g. production of 

food, fibre, fruits) and functions which have life support values (e.g. carbon fixation by green plants, 

protection of the soil against erosion, the maintenance of soil structure and fertility by a healthy soil flora and 

fauna, biological control of crops and fruits by insects). 

The Saxon Academy of Sciences (SAW) have elaborated such an approach since the 60s and 70s (see also 

references in SAW report to Neef, 1966, 1967 and 1969, Haase, 1978, and Mannsfeld, 1979, 1998). Rudolf 

1; 3 

1; 3 

1; 3 

1; 5 

1 

1; 5 

1; 2; 5 

1; 4 

1; 3; 4 

1 

1 

1; 3 

1 

1 

1; 3

de Groot and others (2002), provide a useful list of environmental functions from which Table 4 below has 

been drawn. 

Tab. 4 Environmental functions, ecosystems’ critical aspects and performances (delivering of 

environmental goods and services) Adapted from Costanza et al, (1997), de Groot (1992), de Groot et al, (2002). 

FUNCTIONS ECOSYSTEM PROCESSES & GOODS AND SERVICES 

(examples) 

COMPONENTS (examples) (examples) 

Regulation Functions Maintenance of essential ecological processes and life support systems 

1 Gas regulation Role of ecosystems in biogeochemical 

cycles (e.g. CO2/ 

• 

• 

UVb-protection by O3 (preventing disease) 

Maintenance of (good) air quality 

O2 balance, ozone layer, etc.) • Influence on climate (see also function 2.) 

2 Climate regulation Influence of land cover and biol. • Maintenance of a favorable climate (temp., 

mediated processes (e.g. DMS- • precipitation, etc) for, for example, human 

production) on climate 

• habitation, health, cultivation 

3 Disturbance 

Influence of ecosystem structure • Storm protection (e.g. by coral reefs) 

prevention 

on dampening env. disturbances • Flood prevention (e.g. by wetlands and forests) 

4 Water regulation Role of land cover in regulating • Drainage and natural irrigation 

runoff & river discharge • Medium for transport 

5 Water supply 

Filtering, retention and storage • Provision of water for consumptive use (e.g. 

of fresh water (e.g. in aquifers) drinking, irrigation and industrial use) 

6 Soil retention Role of vegetation root matrix • Maintenance of arable land 

and soil biota in soil retention • Prevention of damage from erosion/siltation 

7 Soil formation Weathering of rock, • Maintenance of productivity on arable land 

accumulation of organic matter • Maintenance of natural productive soils 

8 Nutrient regulation Role of biota in storage and re- • Maintenance of healthy soils and productive 

cyling of nutrients (eg.N,P&S) ecosystems 

9 Waste treatment Role of vegetation & biota in • Pollution control/detoxification 

removal or breakdown of xenic • Filtering of dust particles 

nutrients and compounds • Abatement of noise pollution 

10 Pollination Role of biota in movement of • Pollination of wild plant species 

floral gametes 

• Pollination of crops 

11 Biological control Population control through • Control of pests and diseases 

trophic-dynamic relations • Reduction of herbivory (crop damage) 

Habitat Functions Providing habitat (suitable living space) for wild plant and animal species 

12 Refugium function Suitable living space for wild • Maintenance of biological & genetic diversity 

plants and animals 

(and thus the basis for most other functions) 

13 Nursery Function Suitable reproduction habitat • Maintenance of commercially harvested species 

Production Functions Provision of natural resources 

14 Food Conversion of solar energy into • Hunting, gathering of fish, game, fruits, etc. 

edible plants and animals • Small-scale subsistence farming & aquaculture 

15 Raw materials Conversion of solar energy into • Building & Manufacturing (e.g. lumber, skins) 

biomass for human construction • Fuel and energy (e.g. fuel wood, organic matter) 

and other uses 

• Fodder and fertilizer (e.g. krill, leaves, litter). 

16 Genetic resources Genetic material and evolution • Improve crop resistance to pathogens & pests, 

in wild plants and animals • Other applications (e.g. health care) 

17 Medicinal resources Variety in (bio)chemical sub- • Drugs and pharmaceuticals 

stances in, and other medicinal • Chemical models & tools 

uses of, natural biota 

• Test- and essay organisms 

18 Ornamental resources Variety of biota in natural • Resources for fashion, handicraft, jewelry, pets, 

ecosystems with (potential) worship, decoration & souvenirs (e.g. furs, feathers, 

ornamental use 

ivory, orchids, butterflies, aquarium fish, shells, etc.) 

Information Functions Providing opportunities for cognitive development 

19 Aesthetic information Attractive landscape features • Enjoyment of scenery (scenic roads, housing , etc.) 

20 Recreation Variety in landscapes with • Travel to natural ecosystems for eco-tourism, outdoor 

(potential) recreational uses 

sports, etc. 

21 Cultural & artistic Variety in natural features with • Use of nature as motive in books, film, painting, 

information 

cultural and artistic value 

folklore, national symbols, architect., advertising, etc 

22 Spiritual and historic Variety in natural features with • Use of nature for religious or historic purposes (i.e. 

information 

spiritual and historic value 

heritage value of natural ecosystems and features) 

23 Science & Education Variety in nature with scientific • Use of natural systems for school excursions, etc. 

and educational value 

• Use of nature for scientific research 

24

The environmental functioning approach can be seen as the most meaningful synthetic and holistic approach 

to study the biotic and abiotic components and ecological processes existing within the ecosystem complex. 

In fact, in the Information Paper “Sustainable Use within an Ecosystem Approach” prepared by the IUCN 

Sustainable Use Initiative for the 5th meeting of the Subsidiary Body for Scientific, Technical and 

Technological Advice to the Convention on Biological Diversity, held in Montréal, Canada on the 31 

January–4 February 2000, “ecosystem” is defined as “A complex of plant, animal and micro-organism 

communities and their non-living environment interacting as a functional unit”. 

Joanna Treweek (2001) refers to the approach of Noss (1990) of viewing biodiversity “in terms of 

composition, structure and function for different levels of biological organisation,[which] … mix purely 

biological definitions (genes, species, populations, communities) with ecological concepts that also take 

account of relationships between biotic and abiotic factors (habitats, ecosystems and landscapes).”. 

According to her, this approach runs the risk of being interpreted as too wide, trying to include everything, 

but instead it has the merit of pointing out that it is also unavoidable to consider, while analysing 

biodiversity, the complex interactions between components and processes of the ecosystem, if impacts of 

human activities have to be identified and assessed through “...the responses of ecosystems to external 

development pressures” (Treweek, 2001). 

Fig. 3 Ecosystem complex and human activities 

Ecosystems abiotic and 

biotic components 

Human activities 

Ecosystems functioning 

Ecosystems ecological processes, 

structure, organisation 

In order to allow for the performance of environmental functions by (semi-)natural and agricultural 

ecosystems, certain ecological conditions have to be present. These ecological conditions are critical 

ecological processes, abiotic and biotic components of ecosystems and their inter-relationships. Identifying 

these critical ecological aspects is a possible way to describe what are the most important attributes and 

characteristics necessary for the performance of environmental functions (i.e provision of environmental 

goods and services) in a specific ecosystem. 

Because of resources and time constraints, in AEMBAC only some of what are believed to be the most 

important characteristics and attributes necessary for selected environmental functions performance have 

been analysed. Moreover, it is important to stress that existing scientific knowledge on ecosystem 

functioning is far from complete, so a possible significant lack of information can impair the possibility of 

achieving precise results on some ecological issues, or can orient the choice on the aspects which can be 

analysed. 

However, even a partial analysis of these aspects can offer much more detailed and reliable scientific 

information to the process of developing agri-environmental measures than what is currently done (e.g. 

25

considering the impacts of pesticide use on biodiversity by the quantity sold or used). 

The approach proposed also has the merit of reorganising the scientific information available in a structured 

form, suitable to give some indication on the environmental functions performance and also to point out 

where there is a lack of information and scientific knowledge to draw out more significant conclusions. This 

last fact can be very useful in showing where future research is needed, so increasing the effectiveness of 

research funding. 

In AEMBAC, two environmental functions, one related to biodiversity and one related to landscape (such as 

habitat functions and information functions respectively as in Table 4 above), were analysed by all partners. 

Other functions, such as maintenance of soil fertility and soil erosion control, water quality and groundwater 

recharge, etc., were studied by partners on a voluntary basis (see final reports from UNIFI-DSE, SAW, and 

UD-CEMP). 

3.2.2 Identification and description of indicators 

The identification of the most crucial aspects for environmental performance in the previous section (see 

Table 4 above) was just a starting point for a further detailed description of environmental functions. 

In fact it is possible to describe environmental functions more analytically by using indicators of the 

qualitative and quantitative state of those crucial aspects, attributes and relationships among these, which are 

necessary for allowing the supply of environmental goods and services. Within the AEMBAC project these 

were referred to as state indicators. 

In AEMBAC, the complexity of environmental functions performance has been studied through: 

• Indicators measuring some of the most important aspects and attributes of environmental functions; 

• Acknowledgement of the direct relationships between these indicators while leaving out of the analysis 

the secondary aspects (feedback effects from relationships); 

• Making the best of existing information and knowledge because of time and resources constraints to 

carrying out exhaustive field research; and 

• Identification of plausible relationships between state and function performance capacity, not definition 

of the performance level. 

The criteria for indicator selection were adapted from Robert Prescott-Allen, (1998), and are as follows: 

“Characteristics of a high quality indicator are that it is: 

Relevant – It relates to a specific objective; 

Representative – It covers the most important aspects of the issue concerned; 

Accurate – It correctly reflects how far the objective is met and the state of the issue; 

Measurable; 

Feasible – It depends on data that are readily available or obtainable at reasonable costs; 

Analytically sound – It is well founded and uses standardised measurement whenever possible to permit 

comparison; 

Sensitive – It shows trends over time; and 

Responsive – It reflects changes in condition and differences between places” 

In selecting indicators it was also considered desirable to bear in mind subsequent requirements for the 

development of agri-environmental measures and monitoring procedures in phases 2 and 3 of the project: 

Clear, transparent and standardised methodology for indicators selection, data gathering, processing; 

Availability of financial, human, and technical resources for indicators monitoring; 

Political acceptability at the appropriate level (local, regional, national, international); and 

Participation of, and support from, the public in the development process of indicators. 

(Adapted from Gallopìn, 1997) 

26

Given the difficulties in selecting indicators which fulfil all the above criteria, it was suggested to make two 

lists: 

1. One selecting indicators to represent the most significant and crucial attributes for the environmental 

functions to be performed considering the most meaningful indicators from a scientific point of view; 

this being the theoretical/scientific list. 

2. The other including all the indicators realistically feasible to carry out the analysis in the study area (i.e. 

considering time, human and financial resources constraints in AEMBAC). This being the 

practical/manageable list. 

In selecting indicators it is important to adopt a hierarchical approach linking the indicators to their 

respective level of analysis, such as field/farm and ecosystem/landscape. 

This is a very important point because some indicators can have relevance at specific scales of analysis, 

while others can be used at different spatial levels. For instance the indicator diversity of the scenery has 

significance at the level of landscape whereas the indicator length of field boundaries is meaningful both at 

the level of field and of agro-ecosystem. 

Coming to the relationships between indicators it is important to point out that the project adopted the 

general DPSIR (Drivers-Pressures-State-Impact-Responses) framework to promote the development of agrienvironmental 

programmes. This is a framework proposed by international organisations such as OECD and 

EEA to integrate the complex information concerning the environment into the decision-making process. 

The establishment of such a framework is for developing and integrating indicators to measure the state of 

the environment, the driving forces (e.g. human socio-economic activities) which exert pressures over 

natural resources, the impacts on the environment resulting from pressures and finally the societal responses 

to the changes in the state of the environment. While the DPSIR framework itself could probably be 

improved, it was useful to adopt common tools of analysis at the international level in order to facilitate 

communication and comparisons. 

In AEMBAC only the main relationships between state indicators contributing to performance, such as for 

instance that between the number of species and ecosystem size in reference to the performance of habitat 

function, have been considered. These kinds of relationships were named horizontal relationships 3 , because 

they exist between aspects measured by state indicators (i.e. relationship between the same DPSIR category 

of indicators). 

Other relationships consisting of causality assumptions to be addressed by associating the values of 

indicators measuring the pressure of the local agricultural systems (to be identified in step 3, see below) to 

certain impacts on environmental functions measured by the values of state indicators, such as the 

relationship between the use of pesticide (pressure indicator) on species richness (state indicator), were 

named vertical relationships (i.e. relationship between a different DPSIR category of indicators) and were 

addressed in Step 4 below. 

Both these types of relationships probably have interesting secondary effects but these couldn’t be addressed 

in AEMBAC, only pointed out. 

An important aspect that has been taken into account was the value judgement that can be expressed when 

dealing with indicators. Sometimes this is built into the indicator itself (e.g. presence/absence of certain 

species) resulting in a more objective measurement. In other cases the value judgement is expressed directly 

in the measuring or observation process by researchers (e.g. aesthetic value of a landscape), so giving room 

for more subjective assessments. Clearly the increase in scientific knowledge in analysed aspects will reduce 

the subjectivity of the relative judgements. 

Another fundamental aspect when addressing sustainability issues was the reference to the time frame. The 

3 This kind of horizontal relationship can also exist among pressure indicators measuring the most relevant pressures 

exerted by local agricultural systems on the performance of environmental functions to be addressed in step 3 (e.g. crop 

rotations can have relationships with the management of fertilisers and at the same time on landscape management). 

27

assessment of sustainability has to be considered in a time dynamic dimension. Data on past and present 

ecological conditions and future trends are of obvious value when analysing sustainability allowing for 

changes to be assessed over time. In AEMBAC for some ecological analysis of the environmental functions 

performance, only current data and information were available given that these aspects were being studied 

for the first time in the study area. Past analyses were taken into consideration, whenever these data were 

available, to evaluate future trends (e.g. historical landscape development). 

Following the above considerations on criteria for indicator selection, hierarchical approach, identification of 

relationships and aggregation amongst indicators, value judgements, and time dimension, the methodology 

explained below has been recommended to identify indicators and to define their Environmental Minimum 

Requirement (EMR) values which are addressed in section 3.2.4 below: 

1 - Scale of analysis: entire study area 

Identification of different ecosystems (natural/semi-natural, agricultural/man-made) which are present in the 

study area (from step 2 above). Assessment of land cover and land use at different times for the area, e.g. 

potential natural vegetation, before the industrial revolution (1750–1800), before World War I (1900), just 

after World War II, the present time, others (see Box 4 below). 

Box 4 – AEMBAC project: Historical evolution in % land use Maremma study area, Italy (for 

references in the box, see AEMBAC final report, University of Florence, Department of Economics Sciences). 

In order to study the refugium function, it can be useful to look back at the types and extents of ecosystems in the past. 

The histogram depicted below, based on existing and affordable literature and theme mapping, shows the evolution of 

different ecosystems during the last 170 years that we have briefly introduced before. For this area enough information 

is available for this purpose. 

Different periods show us different land use patterns, according to different demographic, economic, and technical 

trends affecting agriculture. In the year 1830, 7% of the territory was natural wetland and 79% was covered with seminatural 

ecosystems, extensively used for seasonal activities. In the winter, charcoal makers inhabited the coppice on the 

hills and shepherds took advantage of the same coppice and of semi-natural grassland on the plain, partly flooded for 

short periods of the year, for feeding their nomadic livestock. The resident population was very small and agriculture 

was scarce and extensive. The main conversion of semi-natural ecosystem to agriculture was due to the reclamation 

policy adopted by the Absburgs Lorene, who were the sovereigns of the land until 1859 and simply the owners of the 

largest farm after that date, up to 1914. 

Mechanised ploughing was introduced in the late 19 th century which creates uninterrupted, square, bare, large fields, 

somehow reintroducing the classical centuriatio. In those regular fields, wheat was the most important culture in a 

traditional four-year rotation pattern. The land was used as meadow for the other three years. Intensive agriculture was 

confined to specialised permanent crops. In the plain included in the buffer zone, land reclamation was even more 

radical and proper wetland, such as the Alberese lagoon, previously covered with natural vegetation, was definitively 

dried out. 

The agriculture system changed greatly after the Absburgs were banned. A sort of share agriculture, similar to the 

traditional system dominant elsewhere in Tuscany, was introduced. It required a significant immigration of farmers 

from northeastern Italy. Unlike the rest of Italy, land reclamation here didn’t reach its peak until after World War II, 

when agriculture became intensive, also due to the introduction of modern methods of irrigation, and perennial 

meadows became rare. 

The current situation is characterised by a blend of extensification (set-aside of agricultural land within and around the 

park area has been strongly subsidised) and specialisation trends within the same territories. In this perspective the 

amount of woodland must be theoretically added to the percentage of land under extensive use. It is worth remarking 

that the Maremma Park has had an increasing influence on farmers’ choices of crop since the middle of the 1990s. 

28

Fig. 4 Historical evolution in % land use in the Maremma study area 

2 - Scale of analysis: whole area/ecosystems 

Definition of the most appropriate mix of ecosystem diversity and their extent which, on Best Professional 

Judgement (BPJ), (i.e. based on the most appropriate existing scientific evidence), are believed to provide the 

best circumstances for the performance of the environmental function studied (e.g. biodiversity-related 

functions, landscape-related functions, soil erosion control, maintenance of water quality and water recharge 

processes, etc.). This has served to assess the first EMR at the study area level for the indicators Typology of 

ecosystems and extension of ecosystems (see section 3.2.4 below). 

3 - Scale of analysis: ecosystem/landscape 

Once the extent (quantity) of each ecosystem has been defined, it is important to concentrate the analysis on 

the quality of each ecosystem selected. For instance, if we want to assess the quality of a wetland for the 

performance of habitat function, we could analyse the presence/absence of a key species which is known to 

be present only if the general conditions in the wetland (e.g. water quality, presence of other species, etc.) are 

optimal. The same holds true for the analysis of certain types of agro-ecosystems (e.g. presence of (semi- 

)natural habitats such as meadows, shrubland, marshland, hedgerows, ponds, lakes, etc. or animal species 

such as birds in the fields, insects, earthworms, etc.). Proceeding in this way facilitates the selection of 

indicators which are site-specific relevant, and the consequent assessment of their relative EMR. So 

following the example, in the wetland the presence of a minimum number of key species could be considered 

the EMR for the performance of the habitat function in that ecosystem. 

The result is the selection of one or more quality indicators for each ecosystem and the following assessment 

of EMR for each indicator in section 3.2.4. It is also important to consider that in principle, the EMR for 

each indicator had to be assessed considering the overall quality result at the level of study area. This meant 

that EMR values for quality indicators for each ecosystem present in the area had to be defined in such a way 

that the overall result of quality for the whole area will be that of performing biodiversity related functions or 

landscape related functions, etc. (for instance as it is supposed should be in the ecosystem mix selected), as 

illustrated in Figure 5 below. 

Fig. 5 Study area quality as a result of the quality of each ecosystem present and their interactions 

(N.B. interrelationships between different ecosystems should be taken into account as much as possible): 

Forests 

100% 

90% 

80% 

70% 

60% 

50% 

40% 

30% 

20% 

10% 

0% 

Historical evolution in % land use Maremma study area 

1830 1901 1953 2001 

Grasslands 

Study Area quality 

Wetlands 

29 

Urban/industrial/infrastructure 

Intensive agriculture 

Extensive agriculture 

(semi)Natural grass/shrubland 

Forest 

Unexploited wetland 

Agro-ecosystems 

Others

4 – Scale of analysis: Farm/field 

Following this spatial hierarchical approach downward the farm/field level was analysed to identify the 

indicators which were to be used in the developing of agri-environmental targets and measures. So looking at 

the results for agro-ecosystems, it was possible to define the type of indicators and their EMR values, to 

assess the most significant aspects for the performance of environmental functions at this scale of analysis. 

For instance it could emerge from the analysis that to have a certain quality of agro-ecosystem which 

contributes to biodiversity conservation at the study area level (e.g. habitat function for insects and birds), 

hedgerows have to be present at field margins in the farms. The EMR would then be calculated as the length 

and width of hedgerows needed to eliminate/mitigate on-farm negative impacts on agrobiodiversity (or when 

referring to off-farm impacts such as conserving biodiversity in nearby natural ecosystems with the creation 

of vegetation corridors of certain width). Another example can be that of maintaining a certain rate of soil 

erosion (EMR) in the fields so that sedimentation in the river in the valley below (off-farm impacts) is 

sustainable for the maintenance of the quality of that ecosystem. 

Fig. 6 Agro-ecosystem quality as a result of the state of seminatural habitats, farms and fields quality 

Semi-natural 

Habitats 

Farm 1 

Farm 2 

Agro-ecosystems 

quality 

Once the indicators were selected it was important to identify some of their important attributes to record 

information so as to allow comparison on their use amongst different national projects. This was done easily 

by filling in the following identification form for each single indicator selected to describe an environmental 

function: 

Table 5 - Indicator Identification Form 

Indicator n° Description 

Definition 

Scale (i.e. field/farm, ecosystem/landscape, whole study 

Farm 3 

Level of analysis for the indicator and unit of 

area) and unit of measurement 

measurement used 

Purpose What the indicator is used for 

Relevance to the analysis of the environmental 

How relevant is the indicator for the analysis of the 

function…. (i.e. measuring crucial aspects of 

selected environmental function 

performance) 

Limitations of the indicator What are the limits in terms of significance of 

measurements carried out? 

Alternatives Are there any other possible indicators to measure the 

same aspects? 

DPSIR category (e.g. state indicator or pressure indicator) 

Linkages (relationships) to other state or pressures Possible correlation with other indicators? 

indicators 

Measurement methodologies What are the methodologies to be applied to calculate the 

value of the indicator? 

Data needed to compile the indicator, What data are needed to measure the indicator? 

Data availability and sources (including time series) What is the availability and sources of data? 

International Conventions and agreements in which it is Is the indicator already in use in the international arena? 

addressed 

Source: Adapted from United Nations www.un.org/esa/sustdev/indisd/ 

Table 6 below shows examples of indicators selected by the Estonian partner using the indicator 

identification form above. 

30 

Farm 4 

Farm n

Table 6 AEMBAC project: Some examples of biodiversity indicators selected to analyse the refugium function in Estonian case studies 

Definition Scale and unit Purpose Relevance to the 

analysis of 

environmental 

Abundance and 

species 

composition of 

plants in fields 

and field edges 

Number and 

diversity of 

carabids 

(Carabidae) in 

fields and field 

edges 

Number and 

diversity of soil 

earthworm 

(Lumbricidae) 

communities 

Functional 

structure and 

hydrolytical 

activity of soil 

micro-organisms 

Presence of 

indicator species 

in agricultural 

landscape (birds, 

bumble-bees) 

Field/farm: 

number of species 

Field/farm: 

number of 

species, number 

of carabids and 

occurring species 

(other groups of 

noxious insects) 

in fields and field 

edges, calculate 

the Shannon 

index 

Field, farm: 

number and 

species of 

earthworms, 

calculate the 

Shannon index 

Field/farm: 

number and 

activity of the 

micro-organisms 

of the soil and 

functional 

diversity of 

microbial 

community 

Entire area: 

list of species, 

number, number 

and diversity of 

indicator species 

in agricultural 

landscape 

Quantitative 

and 

qualitative 

assessment 

of 

biodiversity 

Quantitative 

and 

qualitative 

assessment 

of 

biodiversity 

Quantitative 

and 

qualitative 

assessment 

of 

biodiversity 

Qualitative 

assessment 

of 

biodiversity 

Qualitative 

assessment 

of 

biodiversity 

function 

DPSIR 

Category 

Connection 

with other 

indicators 

31 

Methodology Necessary data Data 

availability 

and 

Very high State In field edge (0.5–1.5m outwards from cultivated 

field), which doesn’t directly border (it means without 

at least 1–1.5 wide strip) with field (under the annual 

culture), the plant species are identified in three 

quadrates (1m²). The quadrates are marked. Three 

quadrates are also marked out in the middle of the 

field. Mean average number of quadrates per field is 

10–12. 

In total, data from 10 farms are collected. 

All existing species and the coverage of 5 dominant 

species are identified (June–July) 

Very high State Collection of data (April–September/October) is 

carried out in the same field as monitoring of botany. 

To each field edge, 2–3 pitfall traps (trap with roof, 

and 20% salt solution, kept in soil for 1 week) are 

located 5m in from field edges. 2–3 traps are also 

located 1m out from field edges. 

3 traps are placed in the middle of the field. 

In total, about 25 traps per field. 

Carabids are identified down to individual species 

level, other insects to group level. 

Very high State State of soil Collection of data is carried out (September–October) 

in the same field as monitoring of botany and insects. 

At each monitoring point, earthworms are collected 

from 10 identical soil blocks measuring 50x50x40cm 

(Meyer; Satchell, 1967); distance between digs is 3m. 

The number and species of earthworms are identified. 

High State State of soil Collection of data is carried out (September–October) 

in the same field as monitoring of botany, insects and 

earthworms. 

From each monitoring point, soil samples are 

collected (using a soil auger with 2cm diameter, up to 

a depth of 15cm). 10 samples are mixed to produce an 

average sample. The number and activity of soil 

microbiota (Schnürer and Rosswall, 1985) and the 

functional diversity of the microbial community 

(using microplates) is determined. 

Very high State /…/ on the ground of database the composition and 

number of species is determined (monitoring data of 

rare plant species, monitoring data of rare and 

threatened plant communities etc). 

List of existing 

plant species and 

the number of 

species on 1m² 

experimental 

plots in field and 

field edges. 

Bibliographic 

data, accurate 

inventories 

Bibliographic 


inventories 

Bibliographic 


inventories 

Bibliographic 


inventories 

sources 

Special 

field 

studies 

Special 

field 

studies 

Special 

field 

studies 

Special 

field 

studies 

Special 

inventories 

International 

Conventions, 

agreements 

The Bern 

Convention, 

Convention on 

Biological 

Diversity, 

Habitats 

Directive 


Convention 


Convention, 

Habitats 

Directive 


Convention, 

Habitats 

Directive

Description of composite indicators and of the methodology to aggregate indicators 

Following the above, in AEMBAC the tool for describing an environmental function was a set of state 

indicators. It is worth noting that a set of indicators and a set of assumed relations among them constitute a 

“model” of the original system (Gallopìn, 1997). 

A number of indicators presented simultaneously to give a picture of environmental conditions (but not 

aggregated) were defined in AEMBAC as an “Environmental profile”. An environmental profile is a vector 

indicator (including non-numerical indicators). Conversely a single number generated by aggregation from 

two or more values is a scalar indicator. 

Choosing to represent an environmental function through a set of indicators means to “prefer data in their 

most complete form possible (environmental profile) but ... to accept the resulting complexity, while the other 

viewpoint (scalar indicators) prefers data in as simple a form as possible…, but is willing to accept distortion 

introduced in the simplification process” (Ott, 1978). 

In AEMBAC, both types, environmental profiles (set of vector indicators) and/or composite indicators 

(aggregation of different variables through a model resulting in a scalar value such as the Universal Soil Loss 

Equation (USLE)), have been used to describe important ecological aspects identifying the performance of 

the environmental function studied. 

Box 5 gives an example, drawn out by the SAW final report, of a set of indicators constituting an 

environmental profile of the biotope value (cp map 1 and map 2). 

Box 5 - Aembac project: Complex biotope values 

(for references in the box, see AEMBAC project, SAW, final Report) 

Complex biotope values characterise the performance of an area’s biotope to provide suitable living conditions for wild 

plants and animals, and their communities (biocoenoses). Such complex biotope values include various analytical 

indicators, and they can be calculated by different methodological approaches, e.g. by decision trees, combination 

matrices (e.g. Bastian, 1998; Bastian and Schreiber, 1999). 

The most usual criteria or indicators are: 

• degree of naturalness of vegetation; 

• regenerative capacity, age, duration of development; 

• diversity; 

• spatial criteria (biotope size, isolation, connectivity); 

• representativeness; and 

• rare, endangered. 

All of these indicators characterise very special aspects of animated nature, some of them are, however, marked by 

serious scientific-methodological problems and not undisputed. 

It is worth noting that the environmental profile can also include composite indicators as is the case with the 

index of naturalness in the example above. See Box 6 below for some examples of composite indicators 

drawn from the Italian and German final reports (for references in the box, see the respective national final 

report). 

32

Map 1: Biosphere reserve “Upper Lusatian Heath and Pond Landscape” – land use 

Map 2: Biotope values in the study area biosphere reserve “Upper Lusatian Heath and Pond 

Landscape” 

33

Box 6: AEMBAC project: Examples of composite indicators 

Natural Capital Index (Paolo degli Antoni, 2002, from UNIFI-DSE final report) 

In (semi-)natural ecosystems the Natural Capital Index is a composite synthetic indicator, calculated for the sum of 

(semi-)natural ecosystems as Ecosystem quantity x Ecosystem quality. Both ecosystem quantity and ecosystem quality 

are expressed as a % on a baseline. The value 100 for quantity is the total surface of (semi-)natural ecosystems in the 

pilot area in 1830, that is, immediately before industrialisation. Ecosystem quality has been esteemed as a number on a 

0–100 baseline, according to the best professional judgement. Theoretical value 0 indicates the total absence of the 

typical characters of the considered ecosystems, theoretical value 100 indicates the maximum quality which is 

attainable in the inhabited pilot area (historic time). 

Naturalness/Artificiality Index (Paolo degli Antoni, 2002, from UNIFI-DSE final Report) 

In terms of landscape, the synthetic Index Naturalness/Artificiality (after Dugrand et al., 1974) measures the natural 

value of the blend of ecosystems, grouped in eight classes as follows: 

Tab.7 Naturalness/Artificiality Index 

Naturalness Artificiality Meaning of the degrees 

Degree 8 Degree 0 Primeval ecosystems with no human presence 

Degree 7 Degree 1 Climax vegetation with no transformations, nor wood cutting, nor grazing 

Degree 6 Degree 2 (Para)climax vegetation with wood cutting and/or grazing 

Degree 5 Degree 3 Degraded area due to fires, excessive grazing or wood cutting 

Degree 4 Degree 4 Areas where human culture has introduced exotic species and/or managed the soil 

Degree 3 Degree 5 Non-irrigated cropland 

Degree 2 Degree 6 Irrigated cropland 

Degree 1 Degree 7 Greenhouses, gardens, sport grounds, extensive building 

Degree 0 Degree 8 Urbanised/industrial areas, quarries, waste deposits 

The artificiality index is calculated as follows: (1 x % surface + 2 x % surface + 3 x % surface +4 x % surface +5 x % 

surface + 6 x % surface + 7 x % surface + 8 x % surface)/8. 

Naturalness is calculated as 100 - artificiality index. 

As one can see, naturalness degree 5 is the limit of self-regeneration. In that class ecosystems are borderline cases 

between natural and man-made. Ecosystems included in naturalness degrees 6, 7 and 8 are (semi-)natural and selfregenerating; 

those classed naturalness degrees 0, 1, 2, 3 and 4 are man-made. Existing forests are mostly included in 

naturalness degree 6, partly in degree 5; conifer plantations are classed degree 4; intensive agriculture is classed degree 

3; urbanised and infrastructured areas are classed degree 0. 

Heterogeneity (Olaf Bastian et al., 2002, from SAW Final Report) 

There are a lot of indices to describe and characterise the biotope pattern and heterogeneity. The data needed can be 

obtained from CIR-photographs (in digitised form). Main (generalised) biotope types (CORINE-classes) were used. 

Such indices have the following advantages: they are manageable and comparable. But there are also disadvantages: the 

ecological meaning of the heterogeneity is not clear. Diversity is not a measure for stability. 

Shannon’s Evenness Index (Olaf Bastian et al., 2002, from SAW Final Report) 

SHEI equals minus the sum, across all patch types (CORINE-classification), of the shareal abundance of each patch 

type multiplied by that share, divided by the logarithm of the number of patch types. 

− 

SHEI = 

m 

∑ 

i= 

1 

( P o ln P ) 

i 

ln m 

i 

3.2.3 Measurement of actual values of indicators (data from literature or from field measurements 

when feasible) and interpretation of results 

In order to have the opportunity also to compare the methodologies used in field research to gather data 

between countries, researchers were asked to describe these. This information, besides allowing scientists to 

acknowledge different methodologies and share their opinions about those used, also enabled them to assess 

the validity of the data gathered through field research methods. 

34

In cases where the data used were found in the scientific literature available, researchers were asked to 

indicate the methodology which was used for data gathering in the field by authors in the literature. 

Boxes 7 and 8 show examples drawn from the ENVIST and UNIFI-DSE AEMBAC final reports (for 

references in the box, see the respective final report). 

Box 7 - AEMBAC Project: Gathering data on Earthworms and soil microbial community in Estonia 

Agricultural activities have significant influence on soil organisms. The diversity of soil invertebrates in the soils of 

fields in ecologically and conventionally managed farms was studied. 

Earthworms were collected according to the internationally recognised methodology from soil blocks measuring 

50x50x40cm (Satchell, 1967). Earthworm samples were collected in September or October (on 19 September – from 

three fields in the Saare community; on 20 September – from three fields and on 21 September from four fields in the 

Palamuse community; on 26 and 27 September – from the Kihelkonna and Lümanda Communities (repeat samples 

were taken on 16 October)). 

September–October is the time of maximum density, greatest activity and lowest variability of individuals (Nordström 

and Rundgren, 1973). Three digs were made in each field. Soil from the digs was placed on plastic sheets and sorted by 

hand. All individual specimens were washed, kept in the refrigerator for 48 hours, counted and identified as to species. 

During this time their intestinal tract emptied and it was possible to distinguish the characteristics. The number of 

earthworms (Lumbricidae) was calculated as a mean of track per 1m². 

To study the response of earthworm species to environmental factors, a linear ordination method, Redundancy Analysis 

(RDA) (ter Braak and Prentice, 1988) was used. This technique is a multivariate form of regression analysis, in which 

the species data are modelled as a function of environmental data. The most important factors explaining the ordination 

can be extracted, i.e. those with the highest values of correlation coefficients. The programmes used for data analysis 

and graphical display were CANOCO 3.1 (ter Braak, 1986) and CanoDraw 3.0 (Smilauer, 1992). 

Soil samples were collected as composite samples. In all soil composite samples, the moisture content (in muffle oven 

at 105 ºC), organic matter content (in muffle oven at 360 ºC), nitrogen concentration (by the Kjeldahl method) and 

soluble phosphorus concentration (by lacate method) were determined. Source: (Mari Ivask, Kalev Sepp et al., 2002). 

Box 8 – AEMBAC project: Collecting data for Animal species biodiversity related state indicators in 

Italian case studies 

Concerning AEMBAC, most data have to be derived from specific zoological works in restricted areas (if published or 

available by local agencies). Recently, publications of distribution map for most species of vertebrates (Atlas method) 

has provided available information. Nevertheless, this kind of data suffers from both lack of sufficient precision in 

geographical position and absence of information on habitat typology. This is only useful at the higher spatial scale of 

AEMBAC project (whole study area level). The other problem is that information is a qualitative one. Nevertheless, an 

analysis of this kind can provide general information on medium-time variation in community composition. At this 

point of the work, references have been used using the following main sources: Atlante provvisorio degli anfibi e rettili 

italiani: The spatial unit is 10x10 km UTM, where data from 1980 up to 1996 were merged. Atlante Uccelli Nidificanti 

e Svernanti in Toscana: The spatial unit is 100 square km, where data referring to 1982-1992 were merged. 

Moreover, data coming from field works and/or occasional surveys in years 1990-2000 were used as references (C. 

Corti and M. Lebboroni, pers. obs.). 

Field data. Collecting data ad-hoc is a 

necessary step in order both to check 

reliability of bibliographic information 

and to analyse local situations to be 

specifically evaluated. Data have been 

collected during a series of surveys in 

both study areas. Surveys have been 

made in two ways: at ecosystem level 

(i.e. wood, mixed farmland); and at farm 

level. 

35 

Data collection at ecosystem level: 

These data were collected from 

April2001 to October 2001. Quantitative 

data for birds were collected using BBS 

methodology (Robbins & Van Vezzel, 

1967; see Fig. 7).

Quantitative data for reptiles and butterflies were collected using line transects in about the same stations sampled for 

birds. 

Data collection at farm level 

Precise data collection at farm level have been obtained in spring and early summer 2002 in sunny or moderately cloudy 

days, avoiding in summer the midday hot hours. No data were collected during rainy and particularly windy days. 

Because data were collected along transects walked at regular speeds, duration of survey was generally related to the 

farm area. These surveys have been carried out taking into account the different crops and habitats within the farm 

including, where present, ecotones. 

Example of data analysis of actual values of indicator “Density of lacertidis” 

We detailed the methodology of data collection on reptiles, because of the scanty specific literature available, if 

compared with that available for birds. Density of lacertids was obtained by line transects of different length along a 

sample of ecotones present inside farm boundaries. Density was relativized to 100 m. Transects were conducted in 

spring and early summer, in favourable temperature conditions (cp map 3: actual no. of reptile species). 

Fig. 8: An example of actual values of density 

of the different searched species of lacertids 

n. ind / 100 m 

2,5 

2 

1,5 

1 

0,5 

0 

Density of lacertids 

Podarcis muralis Podarcis sicula Lacerta bilineata 

Birds Species occurrence in natural and agricultural ecosystems 

For each study area each breeding species 

of birds and reptiles has been assigned to 

one of the following five groups: 

N - Species occurring only in natural 

habitat 

Na - Species occurring mainly in natural 

habitat but occurring also in agricultural 

ones 

na - Species occurring more o less equally 

in natural and agricultural habitats 

nA- Species occurring mainly in 

agricultural habitat but occurring also in 

natural ones 

A- Species occurring only in agricultural 

habitats 

Note that the same species can be assigned 

to different categories in the two study 

areas, also on the basis of different habitat 

selection. Percentages of presence were 

based were possible on fieldwork, 

otherwise on BPJ. 

crops 

ecotones 

relative abundance in 

agricultural habitats 

relative abundance in 

agricultural habitats 

100 

90 

80 

70 

60 

50 

40 

30 

20 

10 

0 

100 

90 

80 

70 

60 

50 

40 

30 

20 

10 

0 

36 

A 

Fig. 9: The situation assessed in Chianti farms 

of Podarcis sicula, (species linked to open landscape) 

n.ind. / 100 m 

overlappin 

4 

3,5 

3 

2,5 

2 

1,5 

1 

0,5 

0 

Density of Podarcis sicula in different crops 

nA 

g overlappin 

vineyard (bare 

ground) 

ABACO for assessment 

of species 

category 

g 

na 

vineyard (with grass) oliveyard 

overlappin 

Na 

0 10 20 30 40 50 60 70 80 90 100 

relative abundance in natural habitats 

Phoenicurus 

phoenicurus 

Jynx 

torquilla 

Parus 

major 

g 

overlappin 

0 10 20 30 40 50 60 70 80 90 100 

relative abundance in natural habitats 

g 

N 

Examples from field 

data on birds 

Aegithalos 

caudatus Phylloscopus 

collybita

Once indicators and the methodology for gathering relevant data were identified, it was possible to proceed 

to the measurement of their actual values at the relevant scale of reference. These measurements were done 

by direct surveys in the field or by using existing data in the scientific literature (including maps and aerial 

photographs). The actual values measured by single indicators were then to be commented against the past 

measured values or by Best Professional Judgements. 

Map 3: Actual number of reptile species in the Chianti Area, Italy 

37

Box 9 - AEMBAC project: Examples of measurement of just some of the indicators used for the 

Moritzburg small-hill landscape study area – Germany 

(for references in the box, see SAW Final Report) 

The Moritzburg small-hill landscape is characterised by a small-scale pattern of small hills and low ridges with exposed 

rocks and flat hollows. The bedrock is dominated by monzonits, but granodiorite, sandy and holocene substrates also 

occur. The basic geomorphological pattern causes a high diversity of soil, water and climatic conditions which is 

responsible for the present vegetation cover and land use. Effective agricultural production is hampered by the complex 

natural conditions. Forests and woods are concentrated on the crests of the rocky and stony hills, arable fields on slopes 

and grassland in moist hollows. Land improvement (especially drainage) has been tried in order to diminish this natural 

heterogeneity but with little success. Drainage facilities fell into disrepair after a few years, and the thin soil cover on 

the hills is an insuperable obstacle to ploughing. The result is a richly structured rural landscape with notably high 

biodiversity and interesting scenery. The area is particularly rich in species which are adapted to less intensive 

agriculture, e.g. rare arable weeds, plants of field margins, edges and small coppices, birds breeding in hedges, woods, 

grassland and arable fields; amphibians, reptiles and many insect species. 

Vegetation and flora 

Segetal flora 

Rather poor variants of the Aphano-Matricarietum are dominant. Interesting is the Scleranthus annuus-subassociation, 

indicating poor and acid soils. Characteristic species are Scleranthus annuus, Spergula arvensis, Arnerosis minima and 

Trifolium arvense (Bastian, 1986; 1991). The results of the analysis of the floristical maps of Saxony are shown in the 

table below. 749 vascular plant species were established, 122 (16.3%) are endangered (Red list Saxony). This is the 

highest share of endangered plants among all Saxon AEMBAC study areas, (apart from the biosphere reserve “Upper 

Lusatian Heath and Pond Landscape” which has the same percentage). However, the biosphere reserve is almost eight 

times larger than the Moritzburg study area and is of extraordinary importance for nature conservation. This situation is 

a result of the various heterogeneous natural conditions, and the different levels of intensity of agricultural activity 

(mostly moderate to low). The share of endangered grassland species (19.3%!) is by far the highest among all Saxon 

AEMBAC study areas. Regarding occurrence of arable weeds, the Moritzburg area occupies second place (8.8% after 

the biosphere reserve which has 18.1%). 

Grassland flora 

These vary depending on the site and type of management. The spectrum of grassland communities includes moist and 

wet meadows, dry meadows with a lot of xerothermophilic species. Due to intensive agriculture, grassland communities 

rich in species have become rare. There are still remnants of Polygono-Cirsietum oleracei, Holcetum lanati and 

Molinietum (e.g. with Iris sibirica). Relics of rather original grassland communities still occur in the immediate vicinity 

of settlements, at edges of dry and rough meadows, slopes and tracksides (Bastian, 1986). 

The table 8 below represents an overview of the number of plant species in the study area. 

Tab. 8 Number of plant species in the Moritzburg small-hill landscape 

Total 

Including:: 

arable field species 

Including: 

grassland species 

Species Red list Species Red list Species Red list 

0 1 2 3 R 0 1 2 3 0 1 2 3 

Total number of species 749 4 11 43 62 2 137 2 0 4 5 57 8 3 

No decrease 598 0 4 21 29 2 118 2 3 48 4 1 

in % 80 86 84 

Decrease 151 4 7 22 33 0 19 2 2 2 9 2 4 2 

in % 20 14 16 

Extinct since 1949 59 2 1 1 1 

Extinct since 1989 40 2 1 1 1 

Key: Red list: 0 = extinct or missing; 1 = critically endangered: 2 = endangered; 3 = slightly endangered; R = rare, 

decreasing 

Fauna 

Insects 

During the investigation of insects in a part of the study area, an above average diversity was established, thanks to the 

existence of many small habitats (Lorenz and Scholz, 1997): 

Beetles (Coleoptera) (in total): 1,355 species established (25% of all beetle species in Eastern Germany) 

including e.g.: 

Carabidae: 158 species (32% of all in Eastern Germany) 

38

Coccinellidae: 47 species (67% of all in Eastern Germany) 

Curculionidae: 204 species (26% of all in Eastern Germany) 

Digger wasps (Sphecidae): 109 species (53% of all in Eastern Germany) 

Plant wasps (Symphyta): 225 species (35% of all in Eastern Germany) 

Bumble bees (Bombinae): 12 species (41% of all in Eastern Germany) 

Hoverflies (Syrphidae): 120 species (33% of all in Eastern Germany) 

Grasshoppers (Saltatoria): 21 species (34% of all in Eastern Germany) 

The partial study area Bärnsdorf-Volkersdorf small hill landscape is a refuge for many endangered insect species of 

supraregional importance. 37 beetle, 2 plant wasp, 19 butterfly and 7 moth, about 100 wild bee and one grasshopper 

species were established which belong to the category “especially protected” after the German Species Conservation 

Regulation. 144 Red list (Germany) species (Blab et al., 1984) were found. Especially remarkable is the discovery of 

three plant wasp species belonging to the category 0 (extinct) for the Red list of Western Germany (Blab et al., 1984). 

The table below shows the number of threatened insect species in the Red list of Saxony. 

Tab. 9 Number of threatened insect species in the Red List of Saxony 

Saxony Red List category 

Insects 0 1 2 3 4 

Extinct or Almost Heavily Endangered Potentially 

missing extinct endangered 

endangered 

Carabidae 

- - 

4 12 3 

Scarabaeidae 

- - 

1 2 2 

Cerambycidae 

- - 

3 3 2 

Syrphidae 

- 1 7 5 6 

Symphyta 

- 10 18 18 12 

Sphecidae 

- 6 12 21 8 

Saltatoria 

Source: Lorenz and Scholz, 1997. 

- - 

1 5 - 

A detailed field analysis of birds, grasshoppers, and some groups of beetles has been also carried out. 

39 

R 

Rare, 

decreasing 

3.2.4 - Identification of EMR values and description of the methodology used to analyse data and of 

the rationale behind the definition of EMR for each single state indicator selected 

There is wide recognition, both scientific and political, of the necessity of establishing baselines (temporal, 

counterfactual, benchmarking), against which to measure: 

the state of health of an ecosystem; 

the sustainability of the intensity of pressures exerted on this; and 

the effectiveness and efficiency of policy interventions. 

By recognition of the fact that without a certain level of environmental components, structures and processes 

both ecological and agricultural systems will experience a decrease in their performances, this project has 

introduced a new scientific approach to look at thresholds. 

Thresholds in AEMBAC were defined by those Environmental Minimum Requirements of agro-ecosystem 

components, structures, and processes which are necessary to allow for the performance of the selected 

environmental functions. 

The definition of EMR is in line with: 

Article 6(1) of the ‘Habitats’ Directive 92/43/CEE, where it is explicitly stated that the necessary 

conservation management measures have to correspond: ‘to the ecological requirements of the natural 

habitat types of Annex I and the species in Annex II present on the sites’. 

STAR documents VI/12004/00 and VI/43517/02, where reference is made to compare effectiveness of 

rural development programmes against baselines: Temporal, Counterfactual situation, and 

14 

- 

1 

10 

6 

- 

6

Benchmarking (against Norm or best practice). 

Regulation (EC) No 1257/1999 (on Rural Development), Article 2, where there is explicit reference to: 

“the preservation and promotion of a high nature value and a sustainable agriculture respecting 

environmental requirements”. 

The concept of “Basic Environmental Requirements” as stated in the Communication of the Commission 

of the European Communities, Directions towards sustainable agriculture, COM (1999) 22 final, in 

reference to Regulation (EC) No 1259/1999 (common rules for direct support schemes), Article 2: 

“Member States take the appropriate measures in view of the situation of agricultural surfaces used or in 

view of the productions concerned and which correspond to the potential effects of these activities on the 

environment. This may allow the Member State to link the granting of aid to compliance with basic 

environmental requirements relating to biodiversity.” 

In AEMBAC, as said, the basic environmental requirements for state indicators selected were called 

Environmental Minimum Requirements (EMR). Following the above and having described environmental 

function performance by a set of state indicators, baselines had to be assessed for each selected indicator in 

each study area. 

Environmental Minimum Requirements values of indicators representing critical thresholds for the 

performance environmental functions are those values (or range of values, or qualitative aspects) that 

constitute a benchmark, a red line below which the performance of the environmental function is 

jeopardised. 

The object of reference in determining the value of EMR has to be the presence/absence of the performance 

of the environmental function. The crucial question that has to be asked is: what are the minimum values of 

the indicators measuring the most critical aspects of the environmental function in the study area, which if 

not matched, the performance of the environmental function could be seriously put at risk in the study area? 

Fig. 10: Example of possible relationships between environmental function performance and the value 

of a state indicator. 

In order to assess agricultural impacts, the following methods to identify reference values of state indicators 

were suggested for (semi)-natural and agricultural areas respectively (please note that the reference level 

adopted in AEMBAC corresponds to option three for agricultural area): 

40

(Semi)-Natural areas 

First best: the actual or closest possible value to the (semi-)natural situation at study area level, if this 

information is available (e.g potential natural land cover) – this would indicate the positive/negative off-farm 

impacts of agricultural activities (amongst others pressures) on the performance of environmental functions. 

Second best: The actual value of state indicators in similar (semi-)natural habitats in Protected Areas. 

Agricultural areas 

First best: the value of the same state indicators in similar agro-ecosystems that have been abandoned for 

10, 20, 25, etc. years (depending on the agri-ecosystem type and potential natural vegetation). In fact in some 

cases it may happen that biodiversity is richer in agri-ecosystems than in abandoned ecosystem (e.g. richer 

plant species in semi-natural pastures than in abandoned fields). 

Fig. 11 Assessment of impacts on biodiversity by agricultural activities (Adapted from AEMBAC 

project Sweden Final Report) (Please notice that this example can be applied under special 

circumstances only, e.g. in Sweden for the comparison of semi-natural grassland and arable fields!) 

Second best: the value of the state indicator in similar agri-ecosystems that perform the environmental 

function resulting in measurable (and sufficient) supply of environmental goods and services. 

Third best: the value of state indicators determined by Best Professional Judgement, which would be 

expected to ensure the environmental function would be performed adequately. 

The Best Professional Judgement (BPJ i.e. based on scientific evidence available) is the factor determining 

the value of EMR (standard for the study area). This means that the researcher, on the basis of her/his 

knowledge and experience, for each state indicator has to identify an EMR value that ensures a positive 

contribution of the critical ecological aspect analysed to the environmental function performance. Needless 

to say the EMR value can be revised and refined according to the verified correctness of the BPJ assessment 

(for instance by field research). 

Examples of EMRs can be: what is believed to be the minimum extent of a habitat and the number of key 

species present in it for the habitat to fulfil a refugium function; or what is the minimum level of BOD in 

41

surface water to ensure maintenance of biological and genetic diversity in water bodies (using a particular 

species as bio-indicator for instance); or what is believed to be the minimum vegetation cover needed on hill 

slopes for soil erosion to be controlled; or what is believed to be the minimum requirement of diversity in the 

scenery for it to have aesthetic value (locally!), etc. 

As stated above, to look at what are the values of selected state indicators in natural ecosystems performing 

the function of interest, when this is feasible, could be useful in developing the BPJ for certain indicators, as 

well as looking at past or particular agro-ecosystems (e.g. in 1920s, organic agriculture, and abandoned field) 

where the performance of the environmental function was/is performed successfully. 

An important aspect to be taken into consideration when determining EMR values is that these have to be 

defined as much as possible scientifically and not politically!!! 

In this phase, one of the objectives was to scientifically analyse the environmental function performance 

through the use of state indicators measuring ecological characteristics and their respective EMR in the study 

areas. Another thing was to define policy targets for agri-environmental programmes, which had to be dealt 

with in Phase 2 after social and economic aspects have also been considered. This meant that policy targets 

defined for instance in existing environmental regulations (such as that of 50mg/litre of nitrogen in water, 

EU Nitrate Directive 98/83/EC, or 1.4 Livestock Unit per hectare) could not be taken as references to 

determine EMR, because they are the results more of a political, social and economic compromise with 

ecological objectives than of scientific analysis. 

The recent example of the agreement on the Kyoto protocol on reduction of greenhouse gas emissions, where 

the policy target was set at the level of 5–8% reduction of 1990s levels, when the scientific community was 

indicating as necessary a reduction of 60%, explains well what a difference in values can exist between the 

scientific and political assessment of a phenomenon. 

Box 10 - AEMBAC project: EMR values for plant biodiversity indicators: some examples extracted 

from the Maremma study area, Italy (for references in the box see UNIFI-DSE final report) 

Number of key plant species 

Certain key species, apart from rare and threatened ones, were chosen for their sensitivity to land use changes. 

As key species, some orchids, which live in open spaces, are very good indicators of agro-environment. They tolerate 

pesticides rather well and can survive in fertilised grasslands. They are however very sensitive to tillage or cultivation. 

They disappear after just one tillage, and take a minimum of five years (e.g. Orchis morio) to appear again. In fact they 

are herbs with perennial roots and live in symbiosis with a fungus. Therefore, the mechanical and microbiological 

disturbance involved in soil management (i.e. tillage or overgrazing due to wild boar overpopulation) destroys them. 

Considering the high mobility of orchid pollen and seeds, cells of 1km 2 are suitable as surface units for the 

measurement. Considering the huge geological heterogeneity that makes some sub areas much more suitable than 

others, a value of at least one key orchid species per km 2 , in mere terms of presence/absence seems a reasonable EMR. 

Number of phytogeographically rare species 

Different lists of phytogeographically rare species were compiled. The main list includes species that cannot be found 

elsewhere, going towards one or more cardinal directions. Evidence of this can be found on special atlases, such as 

Atlas Florae Europae. Calluna vulgaris, for instance, is at its European southeastern limit. A second list includes 

species with different features, such as fragmented populations, and small local semi-natural habitats. Conservation of 

all the species listed as phytogeographically rare is the EMR; no loss is acceptable. 

Number of endemic plant species 

Endemic plant species have a small area. Both their survival and the opportunity for future evolution much depend on 

the conservation of their whole area and, as a consequence, no loss is acceptable. So in the Maremma park the EMR is 

11 (all the endemic species). 

Local loss of plant species 

Two centuries of overexploitation of forests have seriously reduced the number of plant species present in the pilot area. 

In the woodland, frequent coppicing selected the less needy species against the most specialised ones. Some herbaceous 

42

“internal” species have recently reconquered the coppice, which had been abandoned for over 30–40 years. This is due 

to competition for light and topsoil improvement; but the most precious trees have become locally extinct or are 

seriously threatened, or even extinct. It is very difficult to distinguish between the two conditions because an accurate 

(and not feasible!) investigation is needed to make sure that no individual of a certain species presently lives within the 

pilot area. When some available records refer to sites close to the chosen border, everyone should be suspicious and 

verify that single individuals can still be found within the pilot area, before assessing the definitive extinction. Moreover 

the genes of some species also survive within hybrids so they cannot be considered definitively extinct. The problem 

can be solved by putting threatened and extinct species into one group. EMR is 0 (no loss). 

Population dynamics of key species 

A value of 172 individuals per population is commonly accepted as the EMR to ensure a positive dynamic. At any rate, 

conversion of semi-natural ecosystems to agriculture influences the phenomenon, making the distance between 

populations longer (fragmentation is an important risk of extinction). 

Ecosystem quantity 

As for the previous indicator, fragmentation of plant populations is an important threat to extinction. Concerning 

postcultural ecotones, there is direct evidence that 5% of the territory is the minimum acceptable in order to avoid 

extreme fragmentation of the habitat. 5% cannot be concentrated in a small, insulated sub-zone. Effective corridors are 

needed and their width has to be larger than 20m in order to maintain all the "internal" species. In fact, a hedgerow may 

be an effective corridor for very common shrubs such as Prunus spinosa, but not for species that need sunny, 

undisturbed herbaceous spots surrounded by thorny shrubs that protect those herbs from being grazed. The value 66,6% 

(2/3) of total surface covered by (semi-)natural ecosystems ensures they are the territorial matrix. But this value need 

not be rigidly respected because the natural environment, if well connected with suitable corridors and not fragmented, 

performs its functions with lower (50%) values as well. 

Biotopes and habitats 

The Maremma Park is one of the few coastal areas in Tuscany safe from tourist and industrial exploitation. The most 

precious habitats are strictly connected with the sea, being salt marshes and matorral on cliffs. Parts of the natural 

ecosystems of the plain were converted to extensive pastures many centuries ago and are still in use for the same 

traditional purpose. 

EMR for the indicator “threatened habitats” is = 0, meaning that those precious habitats should not be threatened. 

3.2.5 Assessment and analysis of impacts: Gaps between EMR and actual values on state indicators 

Having defined the value of EMR for each state indicator used at the study area level, it was possible to 

produce a list indicating the selected set of state indicators constituting the environmental profile for each 

environmental function analysed and their respective EMR and actual (measured) values as in the example 

below (Table 10). 

Tab. 10 - Examples of EMR and actual values of some state indicators by natural ecosystem and agroecosystem 

in the two Estonian study areas, Palamuse (P) and Kilkonna (K) 

Indicator EMR values Actual values 

Gap between EMR 

(Measured or data from 

bibliographic/field research) 

values and actual 

values 

Abundance and species Four herb species per 1m 

composition of plants in 

fields and field edges 

2 

0…12 plant species in field Varied field by field. In 

in the middle of the field edge 

some fields less than 

EMR. 

Number and diversity of Four individuals per trap 9.37 (1.33…55.63), species Generally above EMR. 

carabids (Carabidae) in as the mean average of all 5…12 

fields and field edges determined biotopes of one 

field (edges + middle). 

3 carabid species per one 

determined biotope 

Number and diversity of 

earthworm 

P – 82 individuals and two 

species per 1m 

(Lumbricidae) 

communities 

2 of ground 

K – 65 individuals and two 

species per 1m 2 P – average 96 individuals 

(22…224 individuals) per 1m 

of ground 

2 ; 

Generally above EMR. 

In some fields less than 

1…6 species 

EMR. 

K –average 104 individuals 

43

Functional structure and 

hydrolytical activity of 

soil micro-organisms 

Presence of protected 

species (communities) in 

agricultural landscape 

Presence of indicator 

species in agricultural 

landscape 

P – hydrolytical activity 

0.618 OD/g 

K – hydrolytical activity 

0.751 OD/g 

P − average 

K − high 

P − 6 

K − 10 

(0…614 individuals) per 1 m 2 ; 

0…6 species 

P – hydrolytical activity 0.622 

(0.375…1.022) 

K – hydrolytical activity 0.756 

(0.446…1.128) 

The analysis of data concerning 

functional structure is not 

finished yet 

P − average 

K − high 

P − 8 

K − 12 

44 


In some fields less than 

EMR. 

“0”, stable. 


The above table, when filled in, clearly showed for each state indicator the gaps between its EMR values and 

the actual values which constitute the impact. This information had to be interpreted in order to assess: 

the actual performance of environmental function by natural and agricultural ecosystems in the study 

area; and 

if the effective pressures causing the impacts were imputable to those exerted by agriculture or other 

socio-economic activities. 

If historic data were available for a state indicator, it was possible also to assess the positive/negative trends 

with reference to the EMR. This is important because for instance it pointed out a long-term perspective in 

the evaluation of the opportunity to build agro-environmental measures for those key environmental 

indicators which despite their actual positive values compared to EMR, show a downward trend. 

In interpreting the potential for performance of environmental functions, it was important to consider all the 

points mentioned above on the complexity of giving a complete and exhaustive description of all the 

ecological aspects and the relationships amongst them. It was also important that researchers put forward 

some hypothesis on the reasons why eventual gaps have been measured between EMR and actual values. 

This meant to envisage the pressures (coming from the agricultural and/or from other sectors) which were 

believed to be responsible for such gaps (i.e. environmental impacts). The causality relationships between 

assessed impacts and pressures have been further defined in Step 4 after most relevant local agricultural 

pressures have been identified in Step 3. 

Box 11: Gap between EMR and Actual Values of some state indicators in the Chianti case study, Italy 

(UNIFI-DSE final report) 

In this section, on the bases of the preliminary work carried out to have the general picture of the diversity of the chosen 

groups, we measured the actual values of the definitive state indicators selected. Note that these values have been 

assessed (by both standard surveys in farms and BPJ) as average values to be expected to be found on farms in the agroecosystem 

studied by a standard survey (see Methodology in chapter 4.1. Animal species biodiversity-related state 

indicators). Note also that the EMR value reported have to be intended as values that should be obtained from standard 

survey in farms, carried out by professional biologists. The definition of the EMR is based on BPJ. 

Nevertheless, EMR values could be theoretically higher: on the other hand, we think that it would be unrealistic to give 

values that cannot be assessed in short time by field surveys. 

To give an example: the number of breeding bird species / km 2 (indicator n.1) as revealed by more intensive surveys on 

farms, can reach values of 35-40 species / km 2 ; but these values require a series of surveys along the breeding season in 

order to detect both all resident species (nesting and singing early) and long-distance migrants (nesting and singing 

later). Moreover, rare species could be also occasionally recorded. So, the value of 30 species (EMR) is chosen by BPJ 

as the value that can be recorded in standard field surveys (although probably more species are present in the area).

Tab 11. Definitive state indicators at farm level. 

Actual values EMR GAP 

1. Total number of breeding birds species / km 2 25 30 -5 

2. Number of "forest interior" breeding birds species / km 2 3 6 -3 

3. Density of "hedge" breeding bird species / 10 ha 10 15 -5 

4. Density of "key" breeding bird species / km 2 2 5 -3 

5. Number of reptile species / km 2 3 6 -3 

6. Number of reptile species / ha 1 3 -2 

7. Density of lacertids / 100 m 3 6 -3 

8. Number of butterflies species / ha 5 8 -3 

Actual values were computed as average values obtained by field surveys in farms and in the whole area, integrated by 

BPJ (see chapter 4). 

Total number of breeding bird species/ km 2 

The number of breeding bird species on a certain area is generally given by habitat diversity and complexity. In 

agricultural habitats, landscape features such as hedges, uncultivated plots, shrubland (and also buildings) can increase 

breeding bird richness. Particularly in the Mediterranean region, the long-term diversified land use and the periodic 

human presence increases bird richness and abundance (Farina 1997), but this is not true when the diversified land use 

shifts on large extension of monocultural crops.Although some plots (km 2 ) provide breeding habitats for 30 or more 

species, so without gap, the average value for the whole area is below the EMR because of the presence of large 

extension of the same crops (e.g. vineyards), where no hedges and even no herbaceous layer are present. Moreover, 

anthropic pressure on riparian strips and running waters does not allow the presence of some others species. 

Number of ‘forest interior’ breeding bird species / km 2 

This indicator measures the degree of fragmentation of woods in agricultural landscape. The gap is due to the presence 

of patches of wood that are, on average, not large enough to provide habitats for the whole assemblage of forest interior 

birds species. 

Density of ‘hedge’ breeding bird species / km 2 

Although hedges are present in the study area, only in a few cases these habitats are well structured with trees and 

bushes. Large extensions of olive- and vineyards are lacking of hedges. Other cases are ‘hedges’ of riparian vegetation, 

that are limited in the study area. 

Density of ‘key’ breeding bird species / km 2 

Key breeding species, as defined above, are present at low density in the study area. This could be due to the lack of 

food availability (at least large insects) and probably also for the lack of nesting sites (e.g. holes in old trees). 

Number of reptiles species / km 2 (mixed landscape) 

The gap increases when the area is dominated by extended crops (e.g. vineyards) without hedges, stone walls, riparian 

vegetation, and uncultivated field margins. Moreover, it would be also important that the above mentioned land setting 

features were connected with (semi-) natural habitats. 

Number of reptile species / 1 ha 

The gap is mainly due to intensive cultivated large areas (vineyards), that are on average larger than 1 ha. Speaking of 

crops, we have to distinguish between the field and its edges. The crops itself are not a suitable habitat, because they do 

not provide the refugium function. Old olive-yards are better in providing refugium function, at least for lizards. On the 

other hand crop edges can support some species when at least these are vegetated. 

Density of lacertids / 100 m 

The absence of ecotones (e.g. vegetated field margins, stone walls) drastically reduces or even do not allow the presence 

of lizards. The gap also increases when ecotones are not interconnected. 

Number of butterflies species / 1 ha 

The gap increases in monocoltural crops (including vineyards) and generally when ecotones with herbaceous and 

shrubby vegetation are removed. On the other hand, flowers in small patches of uncultivated land, and also in weeds 

around buildings, can attract butterflies of the selected families. 

45

In assessing the potential for performance of environmental functions, state indicators could be left separated 

as environmental profiles or they could be aggregated into composite indicators. 

Environmental profiles required: 

formulating criteria for assessing the potentiality for performance of the environmental functions looking 

at the values of single indicators (e.g. the majority of indicators are respecting EMR values, or those 

which are believed to be the most important), and interpreting the results considering implicitly the 

possible influences of the value of one indicator on the overall performance of the environmental 

function analysed. 

Composite indicators required: 

making quantitative assumptions regarding the horizontal relationships between indicators; and 

developing a model, an equation to link indicators (e.g. Universal Soil Loss Equation (USLE) for soil 

erosion control). 

The analysis of the gaps (between EMR and actual values of indicators) which measure the impacts exerted 

by agricultural practices and/or other socio-economic activities on environmental function performance, had 

to be carried out in detail. The outcome from this analysis was the identification of the most important 

negative impacts which need to be lessened and positive impacts which can be enhanced and that are 

imputable mainly to the agricultural activities. In the case of impacts not imputable to agriculture, these have 

not been analysed but simply indicated. 

Production of spatial maps (GIS) 

A Geographical Information System map was suggested to show the gaps between the actual values of key 

indicators of environmental function performance, and their EMR. (see also annex 1) 

Explanation of the approach used had to be included. This map will serve to facilitate immediate georeferential 

visualisation of the environmental performance in the area. Future GIS works may build upon this 

and include maps showing the economic values of the performance. 

46

Fig. 13 Example of GIS analysis for the Soil Erosion Control function in the Chianti Area, Italy. (P. 

Bazzoffi, R. Napoli). 

(A) EMR for soil erosion (tolerable soil erosion); (B) Actual soil erosion risk (by RUSLE model); (C) Gap 

analysis (B minus A), (D) Scenario analysis of soil erosion risk, by simulating the application of the agrienvironmental 

measure “grass soil cover” to tier +1 (75% soil covered by grass) in Vineyards. 

47

3.3 Step 3 - Description of local agricultural systems and identification of the 

most important pressures and driving forces on environmental functions 

The objective of step3 was the analysis of the local agricultural systems in order to identify the most 

significant pressures and the underlying driving forces which exert positive/negative impacts over the 

environmental functions studied. 

The description of the agro-environmental characteristics, production, organisation and management of the 

agricultural systems at the study area level (or sub-area when this was necessary and feasible), had to be 

displayed following the format of the AEMBAC agro-environmental questionnaire distributed at the second 

AEMBAC meeting (and attached in annex 2). Topics and issues peculiar to specific local agricultural 

systems of the area studied, were added and analysed enlarging the following guidelines framework, while 

agricultural topics not relevant for the area studied, were left blank (e.g. information on irrigation where no 

irrigation is carried out). 

After an overview of the local agricultural system, the analysis concentrated on the description of the average 

farm which is the centre of management decisions (production, agricultural practices, use of inputs, etc.) and 

also of the implementation of agri-environmental policy. This analysis was carried out beginning with agrienvironmental 

information and proceeding with a more agricultural economic and social perspective. To 

have as accurate a picture of the local agricultural system as possible, farms were clustered in three size 

categories representing the average small, medium and large farms in the study area: 

Example: 

0–5ha: small farm 

6–50ha: medium farm 

more than 50ha: large farm 

The extent and location of the farms played an important part in the analysis given that the eventual impacts 

exerted by agricultural activities on environmental functions have to be identified also from a spatial point of 

view. 

The time dimension was considered and indicated in the description where historic data was available (in 

fact some data were gathered for the first time), and in calculating the average data to be included in the 

tables (i.e. average of the past three years). 

The analyses of the environmental, economic and social dimensions of agricultural activities for the average 

farm are described in section 3.3.1, 3.3.2 and 3.3.3 respectively. It is worth noting that the socio-economic 

information, such as the balance sheet item on income and costs, have been of use in subsequent steps (5 and 

6) when the monetary evaluation of direct costs of providing environmental goods and services and of 

opportunity costs related, for instance to the reduced production output, had to be analysed. In section 3.3.4 

from the results of this analysis, the most meaningful pressures exerted by the local agricultural systems on 

the environmental function performances were identified. Environmental, economic and social driving forces 

underlying the identified pressures were described and analysed in section 3.3.5. 

Also it is pointed out that the scope of gathering some information by the use of the AEMBAC questionnaire 

at farm level, on environmental aspects which have been already analysed by experts in step 2, such as those 

related to soil, water and biodiversity, was that of investigating the farmers’ awareness of the relevant topics. 

So, for instance, asking farmers: What is the rate of soil erosion? or How many wild animals are present on 

the farms? served the purpose of building agro-environmental measures on environmental problems and 

topics which are already recognised and understood by those people who will have to implement them. 

Needless to say that where a particular environmental problem or opportunity is discovered by the experts 

but not acknowledged by farmers, the need for the dissemination of information on that issue should be 

arranged and discussed between experts, rural extension services, local administrators and farmers. 

48

Finally, it is important to point out that the analysis of agricultural systems done in this section has been the 

basis for developing agri-environmental measures and relative agri-environmental accounting system for 

local farms in Step 6 (see below). 

Description of the methodology used and the source of information 

Sources of information for the description of local agricultural systems were existing scientific literature, 

agricultural census, statistics (e.g. communes and province/county level) and the information gathered in the 

field through the use of the AEMBAC agri-environmental questionnaire distributed at the Park of Maremma 

meeting (see Annex 2). The purpose of the agri-environmental questionnaire was to overcome the problem 

of the, sometimes awkward, juxtaposition between existing statistical data (usually gathered following 

administrative boundaries) and the boundaries of the study areas, which usually do not coincide. 

Owing to AEMBAC’s economic and time constraints, it was suggested to gathered the information and data 

(qualitative and quantitative analysis) by this AEMBAC survey only on a selected sample of farms, to 

describe the local agricultural system. 

Being aware of the constraints of using a meaningful statistical sample, it was proposed to select a small 

number of farms which could be considered critical or representative cases for the local agricultural system 

(critical case sampling method). 

In fact, it was reasonable to assume that farms which: 

are located in the same area (i.e. operate on the same ecological and socio-economic substrate); 

adopt the same cultivation practices; and 

have the same organisation and structural features (including size) 

would exert similar pressures on the local environment. 

In the analysis of the agricultural system, data which were already available at aggregate level (i.e. number 

of farms in the area, production output at the commune level within the area, average Utilised Agricultural 

Area (UAA) for cultivation in the land registry and land use maps, etc.) could be used for the extrapolation 

process from what has been surveyed at farm level to the whole study area. So for example: 

the total production of a specific crop could be derived by looking at the average yield per hectare in 

the sample farms with the same size and cultivation practices (intensive, extensive, organic, etc.) and 

multiplied by the number of hectares which are cultivated with the same crop as derived from land 

use and/or land registry maps; and 

the total income of small farms in the study area could be derived from the average income of small 

farms of the sample multiplied by the number of small farms in the area. 

Consequently, to study the agricultural system, it was important to use appropriate classifications to identify 

agricultural activities, such as farm Economic Size Unit (ESU), production specialisation, tenure forms, etc. 

For this purpose, referring to the document Definitions of variables used in FADN standard results was 

strongly recommended (downloadable at the EU FADN web page: 

http://europe.eu.int/comm/agriculture/rica/index_en.cfm) 

Also it could have been the case, for some areas, that specific ecological and agricultural features would have 

been better addressed at a lower/sub-area level. In fact, selection of study areas was done looking more at the 

performance of environmental functions than at particular agricultural systems. Therefore different 

agricultural activities could be carried out within a relatively homogeneous environment. In these cases it 

was suggested to carry out the analysis at the level of sub-areas for each agricultural system identified. 

49

3.3.1 Agricultural system: Qualitative and quantitative description of environmental characteristics 

The analysis in this section started from the contents of Step 1 and expanded upon these, with a detailed 

qualitative description of prevalent agricultural activities, crop and cultivation methods, land management, 

biodiversity management, irrigation and water management, and production output of agriculture (and 

forestry products if appropriate) at the study area level. 

For each study area (and sub-area, where appropriate) the description was supported by quantitative 

estimates of data relative to agricultural/rural activities with particular care with regard to land use; prevalent 

cultivation; extent of each type of cultivation (ha); production (q./ha); use of inputs; degree of mechanisation 

(kW/ha); etc. as is shown below. 

Agricultural land use 

The description of the local agricultural systems in AEMBAC started from that of agricultural land use. 

Agricultural use, together with climate, geomorphology and soil quality, has shaped the landscape in the 

European countryside. The history of land use is of great importance in understanding biodiversity and 

landscape evolution and also that of the socio-economic aspects, which are to be interpreted as the causes 

and the results of agricultural changes in the areas investigated by AEMBAC. 

Having analysed historical land use and land cover in Step 1 and Step 2 for natural and semi-natural 

ecosystems, in this section the actual land use of agri-ecosystems had to be investigated in detail. Different 

land uses exert different pressures on the environment, depending on local ecological aspects. Information on 

the different uses and their extent, was therefore very useful for identifying impacts exerted by local 

agricultural systems on the performance of environmental functions analysed in the study areas. 

To have a homogeneous classification of land use categories AEMBAC has adopted the Corine Land Cover 

Inventory. Unfortunately the minimum mapping unit of Corine (25ha), ideally presenting a square of 5x5mm 

on a map of scale 1:100000 (European Commission, 1999a), is not detailed enough for some of the topics 

addressed by AEMBAC (e.g. agricultural parcels within a farm area). Consequently it was decided that 

Partners could use more detailed information and classification starting from Corine level 3. The Saxon 

Academy of Sciences, for instance, while adopting the Corine-classification as legend, has based the studies 

on land cover and biotope maps at the scale of 1:10000 (ColorInfrared-Images), which are very detailed and 

provide a suitable source of information. 

According to the European Environmental Agency, European Topic Centre on Land Cover (Corine Land 

Cover Technical Guide, 1997, web site: http://etc.satellus.se/ ) categories of land cover include: 

Non-irrigated arable land: Cereals, legumes, fodder crops, root crops and fallow land. Includes 

flowers and tree (nurseries cultivation and vegetables, whether open field or under plastic or glass 

(includes market gardening). Includes aromatic, medicinal and culinary plants. Does not include 

permanent pasture. 

Permanently irrigated land: Crops irrigated permanently or periodically, using a permanent 

infrastructure (irrigation channels, drainage network). Most of these crops could not be cultivated 

without an artificial water supply. Does not include sporadically irrigated land. 

Rice fields: Land prepared for rice cultivation. Flat surfaces with irrigation channels. Surfaces 

periodically flooded. 

Vineyards: Areas planted with vines. 

Fruit trees and berry plantations: Parcels planted with fruit trees or shrubs: single or mixed fruit 

species, fruit trees associated with permanently grassed surfaces. Includes chestnut and walnut 

groves. 

Olive groves: Areas planted with olive trees, including mixed occurrence of olive trees and vines on 

the same parcel. 

Pastures: Dense grass cover, of floral composition, dominated by graminaceae, not under a rotation 

system. Mainly for grazing, but the folder may be harvested mechanically. Includes areas with 

50

hedges (bocage). 

Annual crops associated with permanent crops: Non-permanent crops (arable land or pasture) 

associated with permanent crops on the same parcel. 

Complex cultivation patterns: Juxtaposition of small parcels of diverse annual crops, pasture and/or 

permanent crops. 

Land principally occupied by agriculture, with significant areas of natural vegetation: Areas 

principally occupied by agriculture, interspersed with significant natural areas. 

Agro-forestry areas: Areas principally occupied by annual crops or grazing land under the wooded 

cover of forestry species. 

Box 12 – AEMBAC project: Land use in the Jahna river basin, Germany 

The Jahna study area is located in central Saxony, in a hilly loess region. The headwater region of the Jahna River 

(Central Saxon Loess Hill Country) is characterized by a loess cover reaching a thickness of several meters. In the 

northern part, the Jahna River crosses the Northern Saxon Plateau and Hills. Aeolic sediments (sandy loesses rich in 

silts) are dominant. The altitudes extend from 90m above sea level near the mouth to more than 280m. A distinctive 

relief step (terrace) of 30–50m (the so-called loess border terrace) divides the study area into two parts. 

The test area belongs to the region of moderate dry, slightly continental interior climate of the lower hill country and 

lowlands. The average annual temperature is between 8 and 9°C. The annual mean precipitation is 550–600mm 

(decreasing from 650–700mm in the headwater region to less than 550mm at the river mouth). It is typical for the loess 

plateaux that they are exposed to winds coming mostly from the west. 

More than 80% of the test area is covered with arable crops. Winter cereals dominate, followed by maize, root crops, 

rape and peas. The share in other land use types is very low (see table below). Within the Jahna basin, valuable 

ecosystems cover only 20% of the area. This is much lower than the Saxon average. These natural or semi-natural 

ecosystems are concentrated in the floodplains. Among these ecosystems, forests and woods with a high degree of 

naturalness dominate, e.g. oak-hornbeam forests, riverine and swamp forests. Fruit orchards are typical near the 

settlements and fruit-tree rows along roads and paths, willows along rivulets. Further valuable ecosystems are natural 

parts of rivulets, ponds, and very few remnants of mesophilic and moist grassland as well as rough meadows, and rocks. 

This intensively used agricultural area of the fertile loess region is typically poorly equipped with landscape structural 

elements, which leads to low biodiversity and serious problems with soil erosion and accumulation due to high-erosive 

loess soils and large field sizes. 

Tab. 12 - Land use in the Jahna basin 

CORINE classification 

No. Land use 

51 

Area (ha) 

0 Without determination 0.00 

1.1.1 Town building areas 100.26 

1.1.2 Village building areas 814.15 

1.2.1 Industrial and commercial area 295.75 

1.2.2 –1.2.3 Traffic area 316.34 

1.3 Deposit, disposal or excavation area 94.25 

1.4 Area for recreation and leisure activities 551.56 

2.1 – 2.2 Arable fields and special crops 19,769.97 

2.3.1 Meadows and pastures 1751.39 

3.1.1 Deciduous forests 276.29 

3.1.2 Coniferous forests 10.37 

3.1.3 Mixed forests 154.56 

3.2 Shrub and herb vegetation 191.57 

3.3 Open area with sparse vegetation 12.89 

4.1 Moist areas (swamps, bogs) 0.00 

5.1 Water 72.70 

Total 24,412.05 

Source: Olaf Bastian et al., 2002, Germany WP4 report.

Livestock 

Given the possible pressures on land such as ammonia effluents, overgrazing, soil erosion, etc. coming from 

rearing livestock, it was asked to specify the species, the number and the livestock unit per hectare in detail. 

Box 13 – AEMBAC project: Livestock in Kihelkonna and Lümanda case study, Estonia 

Compared to the case in 1998, the number of sheep/goats in the farms has increased and the number of cattle has 

decreased. 

The number of cows is relatively low compared to other communities; there are a lot of hobby farmers with 1-2 cows. 

There are 1500 sheep and 30 horses in total in the pilot area. Pig production is nearly hardly occurs in Kihelkonna and 

Lümanda. There are seven producers in the Kihelkonna and Lümanda Communities who have Estonian native horses 

and one producer who has cows of Estonian native cattle. 

Table 13 describes the average numbers of livestock density 3 (LU/ha), based on the data of 20 farms. 

Tab. 13 -Number of animals 4 and LU In Small (S) and Medium (M) Farm (2000/2001) 

Animal No of farms breeding Annual average Livestock Unit 

number per farm 

3 /Ha 

Milking cows S: 8 

S: 2.1 

S: 0.08 

M: 4 

M: 10.8 

M: 0.1 

Beef cow/ young S: 5 

S: 3.7 

S: 0.05 

cow 

M: 4 

M: 4.5 

M: 0.05 

Sheep/goat S: 11 

S: 12.3 

S: 0.09 

M: 2 

M: 13.5 

M: 0.02 

Poultry S: 10 

S: 14.1 

S: L 0.006 

M: 3 

M: 16.7 

M: - 

TOTAL S: 0.15 

M: 0.24 

Medium farms are more specialised in milk production and the average number of milking cows (10.8) is about 5 times 

higher than in small farms (2.1) (tab. 13). Medium farms are breeding more sheep, the average number of sheep in 

medium farms is 13.5 compared to 12.3 in small farms. Total average livestock density (calculated on total agricultural 

land) in medium farms is a little bit higher than in small farms. 

Chemical and organic inputs: Fertilisers and pesticides 

According to the EU report Agriculture, environment, rural development – Facts and Figures: “For the EU 

as a whole, the main source of nitrogen input to agricultural land is mineral fertiliser, with livestock manure 

a close second”. 

Over-use of fertilisers can have a big impact on the performance of environmental functions related to 

biodiversity conservation. Fertilisers, together with ammonia effluents from livestock, can be responsible for 

increasing the nitrate and phosphate concentration of nutrients in water and soils. The accumulation of 

nutrients pollutes the soils and can impact on the characteristics of semi-natural habitats, affecting the 

species living there. Leaching of fertilisers into water bodies gives rise to the eutrophication phenomenon. 

(EU Commission, 1999; European Environment Agency, 1998.) 

To get a clear idea of the use of chemical fertilisers in the study area, information on fertiliser use, such as 

hectares treated, type of fertilisers (e.g. manure, synthetic fertiliser, active ingredients N, P, K,) quantity used 

and type of treatment (seed, rows, fields) was assessed for each crop and average farm of each size category 

(small, medium and large). 

3 

1 LU equals: one 500 kg cattle or horse, two beef cows or young cows, six slaughter pigs, hundred chickens or four 

hundred broilers 

4 

Figure shows the number of animals from 20 farms sampling (15 small farms, 5 medium farms) 

52

To get a picture of organic fertiliser use, information on use of vegetable residues and animal manure, such 

as on farm production, quantity used, processed, sold, disposed and stocked (including assessment of the 

unitary cost of final disposal for average small, medium and large farms and of sewage sludge) was also 

assessed. 

Box 14 – AEMBAC project: Fertiliser use in the Geldersey Valley, Netherlands 

(for references in the box, see WU-NL final report) 

Inorganic mineral inputs 

The problems arising from the over-application of inorganic fertilisers are discussed in WP4. In such crops as grass, 

which are not adversely affected by the application of high doses but give lower yields when doses are low, fertilisers 

are used generously (LNV, 1995). 

For the two dominant farm types in the case study area, dairy farms and pig farms, fertiliser use is given in the table 

below. Improved fertiliser recommendations and the replacement of fertilisers by manure have led to a significant 

reduction in fertiliser use over recent years. The table illustrates that, especially on grasslands used for dairy farming, 

significant doses of nitrate fertilisers are being applied. 

Tab. 14 - Fertiliser use in kg/ha utilised in agricultural area (the Netherlands) 

Average pig farm 

1990/91 1994/95 1999/00 

Nitrate 

(calculated in N) 

79 44 26 

Phosphate (in P2O5) 20 12 8 

Potassium (in K2O) 2 2 3 

Average dairy farm on sandy soil 

1990/91 1994/95 1999/00 

Nitrate (calculated in N) 253 230 200 

Phosphate (in P2O5) 30 26 24 

Potassium (in K2O ) 28 10 8 

Source: elaboration on Farm Accountancy Data Network – data (LEI). 

Note: Data is not available at the study area level. However, due to institutional and economic circumstances, farm size 

and farming practices are to a large extent homogeneous across the country. For this reason, regional or even at national 

data (if specific for e.g. soil conditions), may be considered representative. Possibilities for a dataset more specific to the 

region (note: larger than case study area!), on soil type etc., that might better fit the case study area are being considered. 

Organic mineral inputs 

The livestock sector in the case study area produces far more manure than is needed, which in turn leads to the overapplication 

of manure on crops. In the last decade the government manure policy has aimed at reducing the surplus of 

livestock manure. Manure production rights were introduced to restrict the production of livestock manure and animal 

feeds with low mineral contents were promoted (LNV, 1995). Moreover, the sale of high-quality manure and the 

redistribution of manure, moving the manure from areas of high stocking densities to areas of lower stocking densities – 

arable farming areas – was promoted. Manure reprocessing on a large scale has not come up to expectations in spite of a 

whole package of promotion measures. Manure reprocessing has turned out to be far more expensive than was initially 

thought due to high costs for the development of new technology, expensive treatment processes and the difficulty of 

finding outlets for the reprocessed products. 

The measures mentioned have proven to be insufficient to solve the manure surplus problem (although significant 

reductions have been achieved). Therefore policy now aims at total restructuring of the intensive livestock sector. For 

this purpose an act on the restructuring of the pig sector came into force at the end of 2000. The case study area is 

among the regions with the highest rates of ammonia emission and nitrate and phosphate production by agriculture in 

the Netherlands. Therefore, the Gelderse Vallei Southwest has been selected as one of the pilot areas for development 

and execution of a reconstruction program. 

53

Details on the nitrate, phosphate and potassium production and use in the case study area are given in the tables below. 

Production of organic minerals is higher than use of organic minerals, indicating that part of production is transported to 

other areas and to manure processing plants. 

Tab. 15 - Mineral Gelderse Vallei 

production per hectare of Southwest 

cultivated land 1999 

Production of Nitrate 

(kg N) 

432 

Production of Phosphate 

(kg P2O5) 

193 

Production of Potassium 

(kg K2O ) 

563 

Source: CBS-data for Woudenberg municipality 

(assumed to be representative for whole study area) 

Pesticides 

54 

Tab. 16 - Mineral use per Gelderse Vallei 

hectare of cultivated land Southwest 

1999 

Production of Nitrate 

(kg N) 

360 

Production of Phosphate 

(kg P2O5) 

141 

Production of Potassium 

(kg K2O ) 

496 

Source: CBS-data for Woudenberg municipality 

(assumed to be representative for whole study area) 

Pesticides have negative effects on human health and biodiversity. Pesticides (insecticides, herbicides and 

fungicides) are purposely made and used to kill insects, plant and fungi which can damage crop yields. 

Depending on the types, ways of application and quantities used, their toxic elements can contaminate water, 

soil, air and even food. 

According to the EU (1999b), monitoring of pesticide residues in water is difficult and costly and only a 

limited number of these have been monitored (e.g. atrazine, simazine and bentazone). It is therefore strategic 

to gather more information on their actual qualitative and quantitative use in the fields, than what is actually 

is done, namely measuring pesticide use by the quantities sold. 

The information requested on pesticide use by crop focussed on hectares treated, type of pesticide and active 

ingredients, quantity and type of treatment (seed, rows, fields). 

Box 15 – AEMBAC project: Pesticide use in the Vetlanda study area, Sweden 

(for references in the box, see SLU final report) 

Herbicides stand for the main part of biocide use in Swedish agriculture, when it comes about treated area as well as 

quantities of active substance (see table below). Thanks to a – in this respect – favourable climate, but also serious and 

durable efforts by the authorities and the farmers, the use is relatively low in European terms and has been cut back in 

quantities and even more in negative effects. 

The use of biocides in the Vetlanda study area and its region is considerably lower than the national average. It is 

mainly explained by the high proportion of leys – where hardly any biocides are used. A colder climate reduces the 

need for insecticides further. 

Herbicides and pesticides still have negative effects on terrestrial biodiversity 4 , thus reducing the positive externalities 

of agriculture. Besides the direct toxic effects affecting the soil fauna, insects, plant populations, etc., the fauna may 

also be indirectly impoverished by the flora getting poorer, giving less feeding chances. It is forbidden to spray pastures 

and meadows, and also anything outside the cultivated field, but it is still voluntary to leave spray-free zones along the 

field edges to save the biodiversity of the edge zones. 

4 

The possible, negative externalities on human health and biodiversity of limnic and marine ecosystems are outside the Swedish 

AEMBAC study.

Tab. 17 - Use of pesticides in arable crops by treated area (TA) in percent of arable land, and active substance 

(AS). Kg/ha and metric tonnes. 1998 

Pesticide County of Jönköping Production area Götalands skogsbygder 

Total crop area (ha) 92 400 482 500 

Treated area % 16 24 

Herbicides 

Fungicides 

Insecticides 

Total 

AS on TA kg/ha 0,61 0,50 

AS on TA tonnes 9,1 57,9 

Treated area % - 3 

AS on TA kg/ha - 0,82 








Source: SCB, 2000a. 

Land Management 

Land management is an important agricultural activity usually carried out to prevent physical, chemical and 

biological deterioration. According to the European Environmental Agency, in Europe (including the 

European part of the CIS) over 7% of the total land area (64 million ha) has been degraded by bad land 

management and in Southern Europe land degradation is believed to threaten over 60% of land (The Dobris 

assessment, 1995). 

The report Agriculture, environment, rural development – Facts and figures (European Commission, 1999b) 

identifies certain farming practices which are held responsible for land degradation and others which instead 

contribute to land conservation. Amongst the former are to be included practices such as deforestation, 

intensive grazing, ploughing up grasslands and clearing hedgerows, amongst the latter traditional farming 

such as erosion control measures, integration of organic matter, crop rotation, maintenance of crop residues 

in the fields, etc. 

Therefore the analysis concentrated on main agronomic practices of land management such as: maintenance 

of straw/litter on the fields (ha), cover crops (ha), traditional crop rotations (specify the type for 1 st , 2 nd , 3 rd , 

etc. years) (ha), other rotations (ha), green manuring (ha), maintenance of hedgerows at field boundaries (m), 

set aside/fallowing (ha), time of mowing (date), and any other practices existing in study areas. 

Box 16 – AEMBAC project: Main agronomic practices in the Fricktal study area, Switzerland 

(for references in the box, see FiBL report) 

Tab. 18 - Main agronomic practices Small Medium Large 

Maintenance of straw/litter on the fields (ha) 0 ha 0 ha 0 ha 

Cover crops (ha) n.a. n.a. n.a. 

Traditional crop rotations (specify the type for 1 st , 2 nd , 

3 rd , etc. years) (ha) 

There are no traditional but typical crop rotations: 

1. temp. fodder 

2. temp. fodder 

3. maize for silage 

4. winter wheat 

5. winter barley (alternatively: rape, sun flowers) 

6. maize for silage 

7. winter wheat 

8. winter barley 

cover crop after winter barley 

55

Other rotations (ha) n.a. n.a. n.a. 

Green manuring (ha) temporary meadows 1.2 77.5 233 

Maintenance of hedgerows with hemline (ha) 

Maintenance of hedgerows without hemline (ha) 

0.01 

0.23 

Set aside/fallowing (ha) See 1.1.1 see 1.1.1 See 1.1.1 

Time of mowing (date) mid May mid May mid May 

Source: Swiss federal statistical office, structure survey statistic 2000, interviews with advisers. 

For those study areas where forestry activities carried out at farm level were important, it was requested to 

highlight information on forest extension and use such as coppice (ha), high forest (ha), conversion from 

coppice to high forest (ha), recent reafforestation (ha), abandoned woodland (ha), etc. 

Tillage 

In the process of tilling or cultivating the land, the topsoil is inverted and mixed by means of a plough, disc 

or simply a hoe. The way in which soil is tilled can have a significant impact on the retention of soil, 

nutrients and water. These problems usually occur during the period between sowing and the growth of 

sufficient vegetative cover to prevent soil erosion by water or wind. In order to avoid these problems, 

conservation tillage, where the soil surface is disturbed as little as possible, can be adopted. (Jules N. Pretty, 

1995). Information analysed regarding the depth of tillage (e.g. Deep > 60cm, Medium 30–60cm, Minimum 

60 cm - - 50 43 - 

Medium 30-60 cm - 25 - - 47 

Minimum < 30 cm 100 75 50 57 53 

Zero-tillage - - - - - 

Total 100 100 100 100 100 

Source: elaboration on AEMBAC questionnaire

From the survey, we have noticed that the presence of man-made land settings (hard landscape features and structures) 

is quite different between medium and large conventional farms. Open fields are more prevalent in large farms, while 

up-down ditching arrangements, being the most used method of cultivation both for medium and large farms, are more 

widespread in medium farms. Up-down ditching and contour ditching arrangements are only present in large farms, 

while terraces are prevalent in medium farms. 

Tab. 20 - Existence of man-made land settings (% of UAA) 

Man-made settings Conventional farm Organic farm 

Medium Large Total Small Medium Large Total 

Open fields 12 28 19% 40 23 77 

Up-down ditching 66 58 63% - 48 - 

Contour ditching and similar - 8 4% 60 29 23 

Walls of terracettes 12 6 6% - - - 

Total 100 100 100% 100% 100% 100% 

Source: elaboration on AEMBAC questionnaire 

Consequently: 

On large conventional farms, in general we have noticed that there are mainly up-down ditching (58%) and open fields 

(28%), while contour ditching and walls of terracettes are marginal (respectively 8% and 6%). This probably derives 

from the progressive acquisition of small holdings leading to the formation of large farms, and low wine prices 

especially up to the 1980s. In fact, for a long time while wine prices were low (when high labour costs reduced 

profitability), large farms cut down on land amelioration, limiting their activities to the maintenance of the existing 

structures; they have only in recent years started new land amelioration especially up-down ditching, leaving the 

remaining areas to the original settings; 

On medium conventional farms, in general we have witnessed an adaptation capacity to the economic adversity of 

market, using family labour for the maintenance and progressive renewal of land settings. As a consequence, medium 

farms have slowed the substitution of old settings with up-down ditching, leaving old terraces where this was not 

possible; 

On organic farms, the situation is quite different. In fact open fields and contour ditching are the prevalent land settings, 

independent of farm size. It is reasonable to believe that organic farmers have maintained and/or changed the existing 

land settings, preferring these to up-down ditching. 

Regarding the state of stone walls, it appears that they are better maintained in vine cultivation than in olive groves due 

to the difference in care regimes. (Fonseca, Guiducci, 2000). Nevertheless, new olive plantations on terraces are usually 

in better condition than the stone walls of plantations after the frost in the middle of the 1980s. Consequently, although 

there are strong moves towards transforming share-farming land settings with new up-down ditching vineyards due to 

the massive investment of some large farms, we note that in the last few years there is also a slight trend towards the 

maintenance of existing stone walls by some farmers due to the increase in crop gross margin. 

In general, stone walls are usually in a state of abandonment and carelessness (Fonseca, Guiducci, 2000): the state of 

conservation and maintenance of hydraulic-agrarian settlements depends directly on crop state on terraces, both for 

olives and wine, while cultural interventions are not always likely to be adequate for settlement conservation 5 . The main 

obstacle to the maintenance of stone walls is low labour force availability and high labour costs. 

Water Resources 

Water is fundamental to natural and agricultural ecosystems, and its scarcity or over-abundance can create 

problems for agricultural production. Humans have always tried to control water to enhance agricultural 

production. Where there is an excess of water, drainage is carried out in order to lower the groundwater 

table, or to convert wetlands into arable fields. Where water is scarce, irrigation schemes are built and 

maintained to allow water to flow into the fields. 

Needless to say, both drainage and irrigation can have serious environmental impacts on biodiversity and on 

5 The maintenance of hydraulic-agrarian settlements also depends on family traditions of land management, which is 

handed on from father to son. Consequently it is reasonable to believe that this kind of work is usually carried on by 

small–medium farms, rather than large farms which are market-oriented. 

57

natural and semi-natural ecosystems, some of which, according to the European Commission (1999b), are as 

follows: 

• lower groundwater and river flow levels as a direct result of water abstractions; 

• the disappearance of wetlands, oxygen deficits in rivers leading to the possible extinction of species of 

flora or fauna or the gradual salinisation of ground water in coastal areas; 

• natural ecosystem conversion through the construction of dams and the diversion of water-courses for 

irrigation purposes; and 

• increased nitrate and pesticide leaching, and the pollution of ground water and rivers. 

The proportion of irrigated land is about 5% of Europe (EEA, 1995). According to the European 

Commission (1999b) in the European Union of 15 Member States, the irrigable area rose from 6.5 million 

hectares in 1961 to 11.6 million hectares in 1996, trends varying considerably from one Member State to 

another: climate (the average water consumption per hectare is higher in Mediterranean countries because of 

low precipitation and high temperatures), soil characteristics, cultivation practices, crop types, the state of 

infrastructure and irrigation methods, are all factors influencing the water demand. 

The analysis of: availability and supply of water resources; water-uses; irrigation; and drainage schemes was 

necessary to give a clear picture of possible environmental pressures coming from water use by the 

agricultural system in the study areas: 

Water availability within the holdings for agriculture and tourism activities for the average farm of each 

size category (small, medium and large farm). 

Trends in the levels of the groundwater table in the past 5 years (Increasing, Stable, Decreasing, 

Unknown) and possible causes. 

Usual on-farm water supply (quantity in cubic meters) for the average farm in each category (ponds, 

well, watercourses and streams, water reservoirs, other). 

Usual off-farm water supply for the average farm in each category (municipal water supply, co-operative 

system, tank truck system, marsh drainage, other). 

Water uses (quantity) and supply systems, (irrigated ha, submersion, rain, sprinkler, drop, other methods) 

per crops cultivation and other agricultural activities (e.g. livestock, product processing, agree-tourism, 

etc.) for the average farm in each size category. 

Description of any maintenance and checking of the irrigation system carried out. 

Description of any drainage, diversion or extraction works carried out in the area. 

Box 18 - AEMBAC project: Water management in the Geldersey Valley study area, Netherlands 

(for references in the box, see WU-NL report) 

Intensification of agricultural activities in the Netherlands has contributed to the lowering of groundwater levels 

through: (i) the intensified drainage of agricultural areas in order to raise production, (ii) increased agricultural 

groundwater extraction for sprinkling purposes and (iii) the enhanced evapotranspiration of crops, as a result of 

increased crop yields (Hellegers, 2001). The topic of agricultural groundwater extraction is dealt with in more detail 

below. Lowering of groundwater levels for agricultural purposes is an important contributor to the desiccation problem. 

Agricultural groundwater extraction. Agricultural extractions contribute heavily to the desiccation problem, since 

these are shallow extractions (2–3m below the soil surface). Details of agricultural groundwater extraction (LEI, 2000) 

in the Netherlands are given in the tables below. These data are not available at the study area level. However, it is 

assumed that they are also valid for the case study area. 

Tab. 21 - Average groundwater extraction per farm 

type in the Netherlands 

Average per farm (1.000m 3 ) 

Grazing cattle farm 5.2 

Factory farm 3.6 

Source: elaboration on LEI-data in LEI (2000). 

58

Tab. 22 - Average agricultural water usage by application (m 3 /farm) in the Netherlands 

Sprinkling Drinking water Cleaning Cleaning TOTAL 

for cattle machinery farm 

buildings 

Grazing 

livestock farm 

7,447 (73.9%) 2,499 (24.8%) 48 (0.5%) 78 (0.8%) 10,072 

Factory farm 5,817 (67.1%) 2,617 (30.2%) 55 (0.6%) 185 (2.1%) 8,674 


Tab. 23 - Agricultural water usage by source (percentage) in the Netherlands 

Ground water Surface water Tap water Rain water 

Sprinkling 63.3% 36.6% 0.0% 0.0% 

Cattle drinking 43.4% 

water 

11.9% 44.7% 0.1% 

Cleaning 

machinery 

41.2% 0.7% 58.1% 0.1% 

Cleaning farm 47.5% 

buildings 

1.2% 50.9% 0.5% 


Tab. 24 - Average sprinkling with ground 

water for selected crops (mm/ha) 

Grass 42 

Maize 39 


Soil Resources 

Soil is made by mineral and organic particles and is formed by the physical and chemical alteration of the 

parent rock and from the biological and biochemical transformation of organic residue. 

Soil is characterised by the presence of organic and mineral components deeply influenced by climate. Soil 

dynamically interacts with atmosphere, lithosphere, hydrosphere and biosphere and is responsible for several 

ecological and socio-economic functions of vital interest (Blum, 1990; 1998). Among these functions, the 

most important are: the biomass production function, the biological filter and substance transformation 

action, the CO2 sink action, the biological habitat and genetic reserve function, the conservation of 

paleontological and archeological patrimony, etc. (Bazzoffi, 2001; European Commission, 1999; European 

Environmental Agency, 1995). 

Because of its functions and its very slow formation rate (100–400 years/cm of topsoil), according to the 

European Commission (1999b) “soil must be considered as a non-renewable resource and must be 

preserved”. 

Among the soil qualities which are important for agriculture, soil fertility, texture, organic matter content, are 

the most frequently cited. It is therefore strategic to gather the relevant information for the study area, to 

verify both the suitability and maintenance of local soil quality for agricultural production and their 

acknowledgement by farmers. Information on soil texture (% of clay, sand, silt) for the average farm in each 

category and on Soil fertility and organic matter content at the level of agro-ecosystem (% of total UAA) was 

to be analysed. 

Soil is affected by physical, chemical and biological degradation. Agricultural activities contribute to these 

negative impacts. The most significant forms of physical degradation of the soil due to agriculture are 

decreased fertility, erosion, desertification, water-logging and compaction. 

Therefore the analysis concentrated on information relating mainly to the state of soils in the local agro- 

59

ecosystems and to possible pressures coming from local agricultural activities. 

The information relating to pressures which may be responsible for chemical damage exerted by agricultural 

practices, such as leaching, acidification, salinisation, contamination by micro-pollutants such as pesticides, 

heavy metals and fertilisers, leading mainly to poisoned soil and eutrophication of water courses were 

gathered already while analysing livestock, use of chemical inputs, and water above. Also for biological 

damage to soil, such as impacts on soil biodiversity and humus, information on the pressures responsible 

could be derived from information on livestock, on use of chemical inputs, and on land management already 

analysed above. 

The analysis concentrated also on soil fertility trends (increasing, stable, decreasing, unknown) in the last 

five years, on the main reasons for an eventual decrease in soil fertility (e.g. crop selection, lack of rotation, 

monoculture, soil erosion, other) for the average farm of each size category (small, medium and large farm). 

Soil erosion is a major socio-economic and environmental problem throughout Europe and it reduces the 

productivity of the land and degrades the performance and the effectiveness of the ecosystems (European 

Commission 1999b). Soil erosion is present almost everywhere in Europe on sloping land, but particularly in 

the Mediterranean countries, Central and Eastern Europe, Ireland and Iceland (EEA, 1995; 1998). 

Soil erosion and salinisation are factors which increase the risk of desertification in the most vulnerable 

areas, particularly in the Mediterranean region. Among the factors causing soil erosion are steep slopes, 

climate, soil conditions and agricultural practices. Therefore, in those study areas where soil erosion was a 

problem, the analysis had to focus on the quantity of UAA on slope (level ground - 0-3%, moderate hills- 4- 

15%, steep slope –16-20%) for the average farm in each category, the average soil depth at the level of agriecosystem 

(% of total surface), the main reasons for soil erosion (land morphology, cultivation methods, 

poor maintenance of land settings, other) on the average farm for each size category. 

Besides erosion, other forms of physical soil degradation are soil compaction and salinisation. Soil 

compaction is caused by the use of heavy machinery and results in the loss of organic matter and soil 

structure. According to the EEA (1995) this is the most widespread physical degradation in Europe involving 

around 90% of those areas affected by physical degradation of soils. Here the analysis had to concentrate on 

the use of heavy machinery related to soil compaction phenomena (number of tractors, overall tractor power 

HP, number of powered cultivators HP, number of other engine-driven machinery, etc.) 

Salinisation of soils is the result of using saline water for irrigation and creates problems of alkalinisation and 

damage to soil structure. According to the EEA (1995), it is more intense in Mediterranean and eastern 

European countries. For the above reasons, it was important to include information on the existence, 

intensity and causes of both soil compaction and salinisation in the description of local agricultural systems. 

Box 19 - AEMBAC project: Soil resources in Palamuse study area, Estonia 

The analysis of soil resources is based on the data from ten farms (four small farms and six medium farms). 

The bedrock in the Palamuse area is composed of Lower Silurian limestone (in the north-western part) and Lower 

Devonian sandstone (in the south-eastern part of the community). The thickness of quaternary sediments (mainly 

moraine) is 30–40m on the drumlins and 10–20m between them. The predominant sediment types are moraine and 

fluvioglacial deposits (sand and gravel), but also clay, peat and lake chalk etc. is found. 

The soils are rather fertile. The dominant soil-texture classes are silt, sandy clay and others. The soil is not very stony. 

Tab. 25 - Soil Texture (%) Small Medium 

Silt 25 50 

Sandy clay 25 17 

Clay - - 

Sand - - 

Other 50 33 

60

The dominant soil-texture classes on the small farms are silt (25%) and sandy clay (25%); in 50% of farms, there are 

other classes, mainly mixed silt/sand and sandy clay/sand. On the medium farms, silt dominates (50%) and other classes 

(33%) are mainly silt/sand and silt/sandy clay. 

Content of organic matter (%) 

The average content of organic matter is 3.1% on small farms, which is a little bit higher than on medium farms (2.8%). 

The overall average 2.9%. 

Soil fertility trends in the last five years 

According to the results of the questionnaire, soil fertility has increased in 50% of the small farms in the last five years, 

compared to 20% of medium farms (see below). In 80% of the medium farms, soil fertility is stable and in 20% of 

farms it has increased. 

In the last five years very few farmers have adopted crop rotation. It was (and is still) very common to grow grain in 

monoculture, which is the main reason for the loss of soil fertility. 

Tab. 26 - Soil fertility trends (% of farms) 

Trend Small Medium 

Increasing 50 20 

Stable 25 80 

Decreasing 25 - 

Soil erosion and erosion reasons 

The main problems originate from the intensive agriculture of the Soviet period. Considering that the Palamuse pilot 

area is a classical drumlin area, with characteristic features such as series of drumlins ranging from the north-west to the 

south-east with long, narrow lakes and wetlands between them, inadequate agricultural practices have caused severe soil 

erosion problems. 

Wind erosion is caused by changing original mosaic landscapes (loss of landscape elements and field margins) and 

establishing large fields. Inappropriate soil tillage (considering the landscape relief), insufficient use of winter cover 

crops and use of very heavy machinery, which causes soil compaction, are the main reasons for water erosion. 

In the Palamuse pilot area, soil erosion is still a serious problem in many cases, although the overall situation has 

improved. 

Soil compaction 

As mentioned above, the intensive agriculture of the Soviet period caused many severe problems, including soil 

compaction – the result of using very heavy machinery. Soil compaction problems are mentioned in 30% of the 

questioned farms. Compared to the situation five years ago, soil condition has improved in 45% of the farms surveyed. 

Biodiversity resources 

Biodiversity has a dual relationship with agriculture. At one and the same time, it is influencing agricultural 

production and is influenced by agricultural practices. 

Many of the aspects related to this relationship need to be considered. Amongst the on-farm and off-farm 

impacts exerted by agricultural practices are the following (EEA, 1995; European Commission, 2000): 

Positive impacts: 

• maintenance of semi-natural habitats and traditional landscape; 

• fire control; 

• conservation of breeds and varieties of local agro-biodiversity; and 

• regulation of water run-off. 

Negative impacts: 

• conversion of natural ecosystems and habitats, for instance by the elimination of wetlands and 

hedgerows (see land use, soil and water sections); 

• reduction in number of species and varieties used and simplification and homogenisation of ecosystems 

61

y monocultural and intensive agriculture; 

• introduction of alien species; 

• impacts on the quality of soil (acidification) and water (eutrophication) by excessive use and consequent 

leaching of chemical fertilisers (see chemical inputs, soil sections); 

• killing of non-target animal and plant species by pesticides (see chemical inputs section); 

• the overgrazing and pollution consequences of excessive livestock intensity (see land use section); and 

• removing breeding habitat for wild species by early mowing. 

Data and information required to identify the pressures causing the above impacts have already been 

addressed in earlier sections, while the quantitative and qualitative state of natural and semi-natural 

ecosystems, biotopes and wildlife have been studied in step 2 when biodiversity-related functions have been 

analysed. 

In this section the attention was more on the (genetic) in-situ conservation of local varieties and breeds and 

their use, and on the farmers’ knowledge of local biodiversity. The former type of information can help 

assess what use agriculture is making of local agrobiodiversity at the gene level, the latter type will be of use 

when control and monitoring measures have to be built into agro-environmental measures in collaboration 

with farmers and local administrations (Step 6). 

The identification of local animal breeds and plant varieties and their uses for farmers (e.g. for flowers, 

aromatic herbs, medicinal plants, fruits, vegetables, cereals, etc.) and the assessment of farmers’ knowledge 

of (semi-natural) habitats and wild animal species that can be found within their farm boundaries (e.g. foxes, 

roe-deer, birds, wolves, etc.), were therefore the topics analysed in this section. 

Box 20 – AEMBAC project: Biodiversity in farms in the Maremma case study, Italy 

The presence of different ecosystems is almost completely absent in conventional farms, this being limited to modest 

pastures and to hedges on boundaries only in the largest farms. The situation in organic farms is certainly more varied 

and more consistent in terms of surface. Particularly in large organic farms, wooded areas represent around 30% of the 

total area. In medium-sized farms, we surveyed the presence of woods, hedgerows and semi-natural areas which 

account for about the 20% of the total farm area. 

Amongst farms interwieved only a large one has recently reconverted a limited area (3,7 ha) to woodland. The planted 

species are pine wood, ilex, cork-tree, ash-tree and flowering ash. 

In fams surveyed, the diversity and quantity of plant species is very limited. Only cypressus, aromatic plants and pine 

tree are present in more than one farm. However, the presence of particular plant species in largest farms and organic 

ones is worth noting. These species are completely absent in small and medium conventional farms which are oriented 

towards a more intensive agriculture. 

Courtyard animals (rabbit, turkey cock, chicken, hen, goose, pig, horse, peageon, etc.) are present in all the interwieved 

farms. The total number is however very limited. These animals are used for family self-comsuption and only a small 

part is sold on the local market. 

Animal biodiversity is quite interesting given that within farm boundaries there are many wild animals and it is 

possibile to get sight of migratory birds. The presence of wild animals is not linked to farm size or to conventional or 

organic farms. Farmers have a good awareness of animal species present in their farms. 

Tab. 27 - Wild animal species detected within the farms boundaries (% of farms) 

Wild boars 88,9 

Foxes 88,9 

Roe-deer 77,8 

Hares 88,9 

Pheasants 100,0 

Sedentary birds 88,9 

Migrant birds 88,9 

Lizards 100,0 

62

Snails 100,0 

Frogs 88,9 

Mice 100,0 

Hedgehogs 100,0 

Porcupines 88,9 

Badgers 44,4 

Tortoises 22,2 

Fallow deer 22,2 

Beech-martens 11,1 

Weasels 11,1 

Among permanent birds, the more common are: buzzard, seagull and duck-hawk; among migrant birds: heron, little 

heron, cormorant, lapwing and plover. 

3.3.2 Agricultural system: qualitative and quantitative description of economic characteristics 

In this section the local agricultural systems have been studied from an economic perspective. The analysis 

started from the description of the farm structure and management which influences the performance of the 

primary sector. 

Description of farm structure of the area 

The structure of the local agricultural system refers to the number of farms, total farm area, average utilised 

agricultural area (UAA), tenurial forms, average economic size unit, type of farming, vertical and horizontal 

integration and marketing of agricultural products. 

The information to be obtained (for small, medium and large farms 6 ) from the analysis of data relative to the 

above aspects of agriculture was as follows: 

Number of farms: this is useful for determining the degree of competition for the same natural 

resources and the parcellisation or spatial distribution of the agricultural activities present within the 

study area; 

Total farm area: defines the total territorial extent of the farms and serves to identify the type and 

proportion of agricultural holdings in the study area; 

UAA: defines the extent of the area actually under agricultural production, compared to the overall 

area of the farms. It is relevant to the analysis of environmental impacts; 

Tenurial forms: indicates the ownerships and types of agreement/contract existing to use the land. 

Land tenure is an important factor influencing the management of farms and the sustainability of 

agricultural activity. It is in general believed that the more defined the land-use rights are, the more 

users will take into account the long-term impacts of their actions (also in case of community 

ownerships); 

Economic Size Unit 7 : refers to the economic size of farms expressed in European size unit 

categories (Reg. 85/377/EEC). This information describes the economic magnitude of the farming 

activities by a European standard gross margin. One ESU is 1200 ECU of standard gross margin. 

Eight ESU is believed to be the minimum size for a full-time holding (Paul Brassley, 1997) 

Type of farming: refers to the kinds of agricultural activities carried out within the farms; 

Degree of vertical and/or horizontal integration: Vertical integration occurs when two or more 

firms operating at different levels in the production, processing and marketing chains, join together 

under single ownership or through contracts specifying collaborative relationships. Horizontal 

6 In the context of AEMBAC: 0–5ha - small farm; 6–50ha - medium farm; more than 50ha - large farm 

7 For exact definition of each item please see the document of the EU Community committee for the farm accountancy data network 

(RI/CC 882 rev. 6.1 text Definition of variable in EU- FADN standard result.doc) in the web 

site:http://europe.eu.int/comm/agriculture/rica/index_en.cfm 

63

integration refers to the combination of firms operating at the same stage of the production, 

processing and marketing processes. In agriculture this occurs when a number of small producers 

join to sell their products together in order to achieve stronger contractual power in commercial 

transactions. 

Box 21 - AEMBAC project: Details on farm structures in Oberes Fricktal study area, Switzerland 

(for references in the box, see FiBL report) 

Tab. 28 - General information on farm structure at the study area level 

Small Farms Medium Farms Large Farms 

Number of Farms*** 47 80 66 

Number of Farms**** 61 87 64 

TOTAL FARM AREA*** 160 996 1’844 

Average Utilised Agricultural Area (UAA)*** 2.3 11.3 29.9 

Tenurial forms:**** 

Private ownership 

 

Public ownership 

Open access 

 

Rented 

0.8 5.6 16.3 

n.a. n.a. n.a. 

n.a. n.a. n.a. 

1.8 5.9 12.5 

Average Economic size unit (ESU)**** 6‘493 

5.4 ESU 

TYPE OF FARMING (TF) 

*** Reference: Swiss federal statistical office, structure survey statistic 2000 

**** Reference: Swiss federal statistical office, mechanical survey statistic 1996 

64 

34'430 

28.7 ESU 

87'820 

73 ESU 

34% of the farms in the Oberes Fricktal area are large farms which cultivate 61% of the total UAA in the study area. 

41% are medium farms, cultivating 33% of the total UAA, and 24% are small farms. Compared to other regions in 

Switzerland, in the Oberes Fricktal area, there are a relatively high proportion of small farms. 55% of the cultivated area 

of large farms is owned by the farm whereas small farms only own 35% of their cultivated land. Due to the high 

proportion of tenured land, small farms have a higher risk of land losses as a consequence of tenure termination. 

The proportion of main-occupation farms amounts to 63% (122 farms) which cultivate 86% of the UAA. 

Degree of horizontal and vertical integration 

Identification of the presence of meso-economic organisation in the study area, such as co-operatives, 

associations of producers, consortiums, upstream and downstream enterprises (number of organisations, 

members, date of foundation). Complementary activities. Extension services. 

Access to market and integration 

Information on most important geographical markets, distribution channels, marketing activities in general 

for farm and for co-operatives (including contribution and remuneration of products) for the local 

agricultural production was analysed. This information is useful to determine the costs of transportation of 

products to the market, the type of clients and the contractual power of farmers. 

Box 22 – AEMBAC project: Access to market and integration in the Selaön study area, Sweden 

(for references in the box, see SLU report) 

Especially for some more remote districts in Sweden, the long distances and poor services for production are significant 

threats to cultivation or husbandry, and consequently also to the preservation of landscape amenities. High fees for 

collecting the milk or for visits by veterinary services may, for example, reduce profitability significantly. Below some 

size and distance limits, no service is available at all. 

The dairy as well as the slaughter markets in Sweden are characterised by a very few enterprises having almost regional 

monopolies. Although these are farmer co-operatives, a single farmer has in practice little choice and has to accept 

given prices and delivery conditions.

As regards slaughterhouses, the Selaön study area is situated in an area that is covered by the Swedish slaughter 

enterprise Scan Foods. The closest slaughterhouse is located in Linköping, approximately 200km away. They do not 

apply any extra fee depending on distance to the farm or animal quantity. If the number of animals is too low for some 

farms in the same area they try to combine the delivery days. The only restriction applied is that there can be a 

maximum of 8 hours’ drive from the farm to the slaughterhouse (animal welfare reasons). There are also fees applied 

for the collection of pigs and sheep. For any number of pigs, Scan Foods charges 13,5 Euro 8 for each collection and for 

less than six sheep they charge 16,2 Euro (Scan Foods, 2001). 

As regards dairy plants, Selaön is situated in the area covered by the dairy enterprise Arla Foods. 90% of the milk 

produced in Selaön is delivered the dairy plant in Stockholm, approximately 100km away. About 10% goes to the dairy 

plant in Norrköping, 150km away. Arla has a general rule that they can cancel a supplier that produces less than 100 

litres on each occasion, which is every second day. Farms can be periodically cancelled as suppliers to the plant if 

production goes below 100 litres on five consecutive collection opportunities. This can periodically affect those farms 

with many milk cows but a synchronised milking period for all the cows and, more often, farms with around 10 milk 

cows or less. Arla also applies an administrative fee, the same for all farms for each collection, of 3,5 Euros. This fee is 

in general more likely to have strongest effects on those with a lower delivery than 1 700 litres of milk per collection 

occasion. However, in the Selaön area there is only one dairy supplier and the farm’s production is big enough not to 

suffer from any cancellation (Edvindsson, 2001). 

Ecological production 

The idea of the organisation KRAV is to contribute to sustainable development through a market label that farmers can 

get if they comply with specific criteria for ecological production. The label involves production without chemical 

fertilisers and biocides, where animals are well treated, and where no genetically modified crops are allowed. 

The total area of certain KRAV approved crops is 2 440ha. Oats are the most common crop and count for 33% of the 

total area. Potatoes, on the other hand, constitutes only 0.2% of the total area for certain KRAV approved crops in the 

county of Södermanland. 

Production 

All data referring to agricultural production are gathered together in this section, starting from crops and 

livestock production output and costs, and processing output and continuing with agro-environmental goods 

and services. 

Raw productions were analysed by looking at physical yields per crop or livestock (including livestock 

products such as eggs, milk, wool, etc.), quantity of product sold and of product unprocessed, and identifying 

the monetary values of output, selling price and grant and subsidies obtained per crops or livestock. 

Information on the main marketing channels used was also analysed. 

Costs, output and gross margin of cultivation (seeds purchase, fertilasers purchase, crop protection, rented 

machinery and equipment, other specific costs, home-produced seeds and dung used, labour, total specific 

costs, total output, and gross margin) and those of rearing animals (feedstuff purchased, fodder, strawlitter 

purchased, other costs, home produced feedstuff, fodder and straw litter used, labour costs, total output 

(meat), total output, gross margin) were analysed in detail for crops and livestock respectively. 

The physical quantities and monetary values of product processing outputs and costs were calculated for the 

three farm categories. Information on marketing channels for raw and processed products was also analysed. 

The information resulting from the analysis of the above data was to be used to calculate the average 

economic results for the average farm of the three categories (see below farm income statement). The 

economic information on outputs and costs relating to crops and livestock production have also been of use 

when the comparison with the economic value of environmental goods and services production was done in 

AEMBAC phase 2, and for the calculation of the economics of agri-environmental measures to be proposed. 

8 Calculated with the average exchange rate for 2001 

65

Box 23 - AEMBAC project: Crop production in the Chianti study area, Italy 

(for references in the box, see UNIFI-DSE report) 

The gross margin per hectare has only been calculated for olive and vine crops. Other crops are not considered in our 

analysis because of their low importance in the local economy and the absence of historical data in FADN. 

For olive and wine cultivation, we have disaggregated the results distinguishing between medium and large farms (see 

table below). 

The first analysis of the results from the period 1997–2000 showed up an interesting fact, namely a great difference in 

gross margin between wine and olive crops: the former has a gross margin about 8,37 times greater than the latter. 

For both, the gross margin is greater in medium farms than in large ones (95% for olives and 138% for wine, 

respectively). This is due to a difference in crop yield and a different cost structure: in fact medium farms usually have 

plantations in better condition and in full production, while large farms have built new plantations especially in recent 

years according to the favourable trend in wine market prices. 

It is important to note that the selling price of wine and olives is calculated according to the local price paid by the 

cooperative industry of transformation. We retain that the gross margin is quite different in those large farms which are 

market-oriented. In fact it is likely that they are able to attribute a greater value to raw materials by processing them on 

their own. 

Tab. 29 - Average gross margin for conventional farms for principal crops of the area in the period 1997–2000 

(€/ha) Labour costs excluded 

CROP OLIVE VINE 

Average 

medium 

Average 

large 

66 

Total 

average 

Average 

medium 

Average 

large 

Total 

average 

A)Total production 2.024,47 1.070,19 1.398,08 21.748,76 9.910,28 11.970,41 

Seed purchase costs (replanting) 4,63 0,00 1,58 16,12 44,56 42,84 

Fertilisers purchase costs 54,75 35,72 42,20 78,06 123,12 124,68 

Crop protection costs 20,35 5,26 10,39 255,73 381,33 388,79 

Rented machinery and equipment costs 8,99 0,00 3,06 7,05 134,88 121,83 

Other specific costs 2,69 39,65 27,07 157,91 326,19 321,12 

Home grown seed used 0,00 0,00 0,00 0,00 0,00 0,00 

Home grown dung used 0,00 0,00 0,00 0,00 0,00 0,00 

B)Total current costs 91,42 80,63 84,30 514,87 1.010,08 999,26 

Gross margin (A-B) 1.933,05 989,56 1.310,57 21.233,89 8.900,20 10.971,15 

Grant and subsidies 515,11 452,84 474,02 412,76 1.016,61 911,53 

Source: elaboration on local FADN 

Of the other crops, the only economic data available is for irises which are cultivated for the production of bulbs for the 

perfume industry. The profitability of the crop is quite low and so it carries on through family tradition rather than 

economic convenience 9 . Although this crop represents a good family income integration in some small farms in the 

area, not one of them specialises in its cultivation. The bulbs are usually gathered by a cooperative (external to the study 

area), which sells them to industry. 

Livestock Production 

Box 24 - AEMBAC project: Dairy farming in Gelderse Vallei Southwest, Netherlands 

Dairy prices were under pressure in the second half of 1998 and 1999; however, in 2000 the dairy market recovered 

(LEI, 2001). Due to an increase in world market prices – which was mainly the result of the strong US dollar, export 

subsidies and intervention – stocks in the EU were reduced. Mainly as a consequence of higher milk prices, the average 

family farm income for dairy farms increased slightly between 1999/2000 and 2000/01. The higher production costs and 

9 From WP4 Italy elaboration on FADN, we have determined that the gross margin for this crop is around 6.500 €/ha. 

The cultivation labour intensive, which drastically reduces its profitability. So it is progressively substituted by more 

profitable crops, grapes in particular.

the BSE crisis somewhat counterbalanced the positive results at the end of 2000. The effects of the Foot and Mouth 

Disease crisis on income are not yet clear. 

Milk is the main grassland-based livestock farming product in the case study area. Some key figures on outputs and 

costs of milk production are given in the table below. 

Tab. 30 - Specification of gross margin per dairy cow (1999/00) for an 

average dairy farm on sandy soil in the Netherlands 

(costs and outputs in EURO) 

Milk yield per dairy cow (1999/00, kg) 7,625 

Factory price per 100kg (1999/00, EURO) 33.36 

Output milk 2,505 

Output and change in volume dairy cattle 322 

Other output 64 

TOTAL OUTPUT 2,886 

FEED COSTS 

Concentrates 340 

Milk products 32 

Roughage (inc. stock changes) 50 

Total feed costs 422 

OUTPUT MINUS FEED COSTS 2,464 

Veterinary costs, breeding costs, etc. 177 

Other specific costs 113 

GROSS MARGIN 2,169 

Costs milk quota 399 

Source: LEI, Farm Accountancy Data Network 

Note: Data included in this table is not available at the case study area level. However, due institutional and economic circumstances, 

farm size and farming practices are to a large extent homogeneous across the country. For this reason, regional or even national level 

data (if specified for e.g. soil conditions) may be considered representative. Possibilities for a dataset more specific to the region 

(note: larger than case study area!) for soil type etc., better fitting the case study area, are being considered. 

Environmental goods and services production 

It was suggested to gather data on the production of environmental goods and services by the average farm in 

each size category in order to assess both the their supply and the quantity of production and labour spent on 

them. This information, when available, was used to assess the labour costs of environmental goods and 

services produced. Information on subsidies obtained for this agro-environmental activity is also relevant to 

the analysis on the economics of agro-environmental measures. Environmental goods and services 

considered here were those related to biodiversity conservation (such as ecosystems managed, number of 

indigenous species managed, number of wild and cultivated/reared local varieties/breeds), maintenance of 

landscape traditional features, and works done for mitigation of soil erosion and water run-off. 

Labour 

Data analysed were on labour spent on each agricultural activities carried out in the study area such as agroenvironmental 

practices, agro-tourism, production of crops and rearing of livestocks, etc. This information 

was used to calculate labour inputs into agricultural productions, and relative costs. 

67

Box 25 – AEMBAC project: Labour in Oberas Fricktal, Switzerland 

Tab. 31 – Labour in Farms 

Unpaid labour (family) Valley area 

Dairy farms 

Mixed farms 

Total hours 3,510 3,483 

Annual average hours for agro-environmental practices: n.a. n.a. 

Annual average hours for tourism n.a. n.a. 

Annual average hours for crops n.a. n.a. 

Annual average hours for livestock n.a. n.a. 

Annual Work Units (AWU) 1.3 1.29 

Social security costs 

Total Paid Labour 

1,410 1,436 

Total regular hours 1,026 1,134 

Annual average hours for agro-environmental practices: n.a. n.a. 

Annual average hours for tourism not relevant n.a. 

Annual average hours for crops not available not available 

Annual average hours for livestock not available not available 


Wages and social security costs 10,315 SFr. 

10,921 Fr. 

7,014 E 

7,426 E 

Total casual and seasonal: hours 1,026 1,134 


Wages and social security costs 10'315 Fr. 

10'921 Fr. 

70014 E 

7'426 E 

Labour use: 

In 1996, a total of 616 persons working on farms were registered in Oberes Fricktal, corresponding to 385 AWU in total 

(0,13 AWU/ha UAA). 77% of AWU are working on main-occupation farms, 23% on part-time farms. 

Main-occupation farms: 2,4 AWU/farm, 0,11 AWU/ha 

Part-time farms: 1,0 AWU/farm, 0,22 AWU/ha. 

Small farms: 1,3 AWU/ha 

Medium farms: 0,17 AWU/ha 

Large farms 0,09 AWU/ha. 

Statement of assets and liabilities for the average farm each category 

The balance sheet serves to provide an indication of the farm’s financial situation at a given point in time. 

This information describes how the farm is performing and how it is managed. In fact the measure of 

liquidity assesses the capacity of the farm to match its financial obligations. This solvency state indicates the 

degree of financial sustainability of the farm management which has important implications for the viability 

and expected profitability of the business. 

The information on financial status is also useful for the definition of agri-environmental measures when the 

value resulting from the implementation of environmental land improvements, which have the character of 

being fixed assets, has been calculated and accounted for. 

In AEMBAC it was suggested to use the balance sheet proposed in the document of the EU Committee for 

the Farm Accountancy Data Network (FADN) (RI/CC 882 rev. 6.1 text Definition of variable in EU- FADN 

standard result.doc). The reason for this choice was that it is recommendable to use existing information and 

categories of items which are already harmonised at a European Union level. 

For an exact definition of each item please see the document of the EU Community committee for the farm 

accountancy data network (RI/CC 882 rev. 6.1 text Definition of variable in EU- FADN standard result.doc) 

in the web site:http://europe.eu.int/comm/agriculture/rica/index_en.cfm ) 

68

Please note that land improvements (such as environmental ones) in AEMBAC were included in the category 

Land, permanent crops and quotas. 

The subsidies on assets were to be included in each asset item. The amount of subsidies on assets has been 

identified as an item of net worth. Details on subsidies are given below. 

Box 26 – AEMBAC project: Statement of assets and liabilities in Gelderse Vallei Southwest, 

Netherlands 

For the two dominant farm types in the case study area, dairy and pig farms, the statement of assets and liabilities is 

given. The solvency ratio for pig farmers is lower than that of dairy farmers. 

Tab. 32 – Statement of assets and liabilities 

ASSETS (1999/00, in Euro) Average 

dairy farm 

69 

Average 

pig farm 

Intangible fixed assets (e.g. quota) 103,961 39,933 

Land (inc. investments) 527,973 180,378 

Farm buildings 148,432 281,616 

Machinery and equipment 65,48 84,902 

Breeding live stock 55,225 59,037 

Other fixed farm assets 0 227 

Farmhouse 72,605 90,484 

Other fixed assets private 21,827 39,887 

Total fixed assets 891,542 736,531 

Investment in agr. cooperatives 14,476 2,042 

Long-term loans 590 6,988 

Total financial fixed assets 15,066 9,03 

Non-breeding live stock 6,943 77,415 

Other stocks 17,471 5,945 

Accounts receivable for products delivered 17,153 9,666 

Other account receivable 1,815 227 

Stocks and shares 11,571 14,521 

Saving accounts with banks 26,773 9,802 

Current accounts with banks 5,808 8,123 

Cash 454 272 

Total liquid resources 33,035 18,242 

Total current assets 87,943 125,969 

Total of balance sheet 1,098,557 911,463 

LIABILITIES (1999/00, in Euro) 

Net worth 823,656 475,108 

Loans by banks (incl insurance companies) 234,831 387,211 

Loans by the state 3,903 4,629 

Loans by farmers’ relatives 26,909 17,879 

Loans by other private persons 908 7,487 

Total long-term loans 266,505 417,206 

Current accounts with banks 2,768 2,95 

Accounts payable 4,992 15,292 

Other short-term liabilities 635 908 

Total short-term liabilities 8,395 19,195 

Total liabilities 274,9 436,4 

Total of balance sheet 1,098,557 911,463 

Solvency ratio 75 52

Source: LEI, Farm Accountancy Data Network. 

Average dairy farm figures are for average dairy farms on sandy soils in the Netherlands. Average pig farm figures are 

for average pig farms in the Netherlands 

Note: Data included in this table is not available at the case study area level. However, due to institutional and 

economic circumstances, farm sizes and farming practices are to a large extent homogeneous across the country. For 

this reason, regional or even at national level data (if specified for e.g. soil conditions), may be considered 

representative. Possibilities for a dataset more specific to the region (note: larger than case study area!), on soil type 

etc., better fitting the case study area, are being considered. 

Farm income for the average farm each category at study area level 

The Profit and Loss Statement (Farm Income) gives a picture of the revenues and expenses of the farm over 

a given period, usually one year. From the difference between these, the calculation of the final profit or loss 

for the farm for the relevant period is made. The farm income is useful to determine the payoff for each 

single different farming activity and for their total (i.e. return on inputs: land, labour and capital). This 

information will be also of use in the tailoring of agri-environmental measures (e.g. definition of incentives 

proposed for supplying of environmental goods and services) to the local agricultural systems. 

The farm income proposed here, as for the balance sheet above, is drawn from that presented in the 

document of the EU Committee for the Farm Accountancy Data Network (FADN) (RI/CC 882 rev. 6.1 text 

Definition of variable in EU- FADN standard result.doc). The reason for this choice was that it is 

recommendable to use existing information and categories of items which are already harmonised at 

European Union level. 

For an exact definition of each item please see the documente of the EU Community committee for the farm 

accountancy data network (RI/CC 882 rev. 6.1 text Definition of variable in EU- FADN standard result.doc) 

in the web site:http://europe.eu.int/comm/agriculture/rica/index_en.cfm ) 

Box 27 – AEMBAC project: Economic account at area level and for farm size (€) in the Chianti study 

area, Italy 

The average farm account for the area was estimated by considering data gathered through the AEMBAC questionnaire, 

direct interviews and the total number of farms in the three categories present in the area as reported in WP4. 

The aggregated farm output increases according to size. The different output items vary within this aggregated output. 

The agritourism activities outputs, in particular, (the only activities complementary to the agriculture ones in the area) 

are inversely proportional to the farm size, from 17% of total output in small farms to 6,5% in large ones. The low 

presence of livestock activities and the absence of actual statistical data do not allow valuations of these at area level. 

The specific costs in term of total output are substantially similar in small and medium farms (round to 6,5% of total 

output), while large farms have current costs slightly higher in percentage (8,5%). According to the different incidence 

of agritourism activities related to farm size, it results that in the composition of current costs, for these activities, total 

specific costs are about 54% in small farms, and 18% in the large ones. 

In the large farms current costs for agricultural activitities are far higher than those of the small and medium farm. 

Following the different relative importance of current costs, gross farm income is around 93% of total output for small 

and medium farm while it is a little lower for large farms. 

The depreciation quota imputable to the annual current costs results has a high incidence in the small farms compared to 

that in the large ones. 

The annual quota of depreciation in small farms is represented mainly by plantation and machinery according to 

renewal process in the last years. Conversely, large farms hold consistent investments which are mostly depreciated. 

The labour costs are greater on large farms (12% of total output) whereas they are quite low on small farms (8%) 

because of the large use of family labour. 

In consequence of the different incidence of costs on total outputs due in particular to depreciation quotas, the large 

farms have a profitability of (taxes excluded) around 70% of total output, while this value is less for small ones (40%), 

although the latter present more favourable results in current management. 

70

Tab. 33 - Average farm account at area level for farm size (€) Average small Average medium Average large 

for the year 2000 

farm 

farm 

farm 

(€) (€) (€) 

a) Total output 24.625 76.014 441.621 

· Total output: crops and products 20.954 69.196 415.221 

· Total output: livestock product 0 0 0 

· Total tourism receipts 3.671 6.818 26.400 

· Total output: environmental goods and services --- --- --- 

b) Total cost 1.694 4.611 37.781 

b1) Total specific costs: 1.694 4.611 37.781 

· Specific crop costs 625 1.969 27.628 

· Specific livestock costs 0 0 0 

· Specific tourism costs 910 2.124 7.141 

· Specific environmental costs 158 518 3.012 

b2) Total farm overheads 

Balance current subsidies 

· Total subsidies (excl. invest.) 748 3.404 30.902 

· Total crop production support 748 3.404 30.902 

· Total livestock production support - - 

· Total structural support * * * 

· Total rural development support (reg. 1257/99) * * * 

Gross farm income 22.931 71.402 403.840 

Depreciation total 11.036 11.036 41.199 

· Plantation 4.645 4.645 22.122 

· Machinery 4.668 4.668 5.360 

· Buildings 1.723 1.723 13.718 

Farm net value added 11.895 60.366 362.641 

· Total external costs 2.013 6.587 54.537 

· Wages paid 2.010 6.581 54.517 

· Rent paid - - - 

· Interest paid 3 6 20 

Farm income 9.882 53.779 308.104 

Details on balance of government payments and taxes 

In order to define the entity of public contributions given to farms in general (compensation payments, 

subsidies to export, etc.) and that of payments for environmental amelioration of the land, the following 

information was analysed: 

Detailed description of any compensation payments (per hectare and headage) and subsidies to 

export received; 

Detailed description of any public contribution for soil conservation, maintenance of land settings, 

landscape conservation, etc.; 

Detailed description of any public contributions regarding biodiversity conservation (EEC 

reg.2078/92) and forest management (EEC.reg.2080/92); and 

Description of taxes in details. 

The above information will give a fairly accurate picture of public intervention on local agriculture and how 

much of it is allocated to environmental issues. Needless to say this will be considered in developing agrienvironmental 

measures (e.g. building on existing ones). 

71

Box 28 – AEMBAC project: Details on subsidies in Palamuse study area, Estonia 

Since 1998 the Estonian government has offered direct subsidies to farmers. The types of support that influence the 

agricultural sector are: direct support, capital support, interest subsidy, motor fuel excise subsidy, co-financing of land 

amelioration works, support to liming works, animal breeding, and support for using extension services. 

In 2001 the direct state subsidy for dairy cow breeding was 72.37 euros per cow (for native cattle 108.97 euros) and the 

grain subsidy was 25.64 euros per hectare. Organic farming support in pilot areas (different administration and 

requirements as nationally) was 40.38 euros (organic) and 53,85 euros (converted from Estonian currency); nationally 

14.73 euros for permanent and natural grassland; 44.19 for crops in arable rotation and 132.57 for vegetables and fruits. 

In 2001, the Pilot Agri-environmental Project started. Related to the project, the following measures are supported in 

the Palamuse pilot area: 

Environment-friendly management – obligatory for every applicant and offering baseline payment; 

Supplementary measures (available in any combination and providing additional payments for additional undertakings); 

Organic farming (different payment levels in-conversion, organic); 

Endangered breeds (Estonian Native Horse); 

Management of abandoned land; 

Creation of ponds and wetlands; and 

Planting of hedges. 

Tab. 34 - The structure of support (%) based on the data from ten farms (four small, six medium) 

FARM TYPE 

Agri- 

environment 

support 

Dairy cow 

subsidyt 

72 

Grain subsidy 

Advisory 

support 

Interest support 

No. of recipient farms 4 - 2 - - 

Small farms 96.7 - 3.3 - - 

No. of recipient farms 6 3 6 - 3 

Medium farms 65,8 5,7 27.2 - 1.3 

A significant part of the support received in 2001 in the farms surveyed, is made up of agri-environment support, 

especially in small farms (96.7% of all support in small farms and 65.8% in medium farms). There are remarkable 

differences between small and medium farms as regards other support received: while small farms received only grain 

subsidies (3,3% from all support) in addition to the agri-environment support, medium farms received grain subsidies 

(27,2%), dairy cow subsidies (5,7%) and interest support (1,3%) as well. 

Tab. 35 - Average amounts of support (EUR) per Farm 

FARM TYPE 

Agri- 

environment 

support 

Dairy cow 

subsidy 

Grain subsidy 

Advisory 

support 

Small farms 2 448.8 - 168.5 - - 

Medium farms 4 908.7 844.3 2 036.4 - 196.8 

Average TOTAL 3 924.7 844.3 1 569.4 - 196.8 

3.1.3 Agricultural system: Qualitative and quantitative description of social characteristics 

Interest support 

In this section starting from the historical profile of the area with particular reference to the agricultural 

history presented in Step 1, farmers were asked to give a brief description of the social characteristics of the 

rural population in the study area. Topics relating to education, employment, age, part time [time series if 

possible], cultural traditions were investigated in this section. 

Box 29 – AEMBAC project: Historical and social information on the Palamuse study area, Estonia 

Palamuse parish is one of the oldest parishes in Estonia. It was first mentioned in 1234 in Pope Gregorius IX’s letter. 

Earlier the Palamuse parish comprised also Maarja-Magdaleena parish, but in 1641 these two parishes were separated. 

At the end of the Swedish period Palamuse was a wealthy parish with 220 farms. The first written mention of the farms 

originates from 1584. The farms belonged to manors. 

During the Great Northern War (1700–1721) the population decreased by 50%. In 1785 Palamuse parish had 170 farms

with 2,200 inhabitants. In 1795 there were already 3,000 inhabitants, but it still took about twenty years to restore the 

economy and way of life of the parish after the damages of the war. 

Serfdom was finally abolished in North Estonia in 1816 and in South Estonia in 1819 but without any rights to land. This 

meant that every peasant got the right to buy land. Intensive renting and purchasing for perpetuity began, as the landlords felt 

there was a possibility to make money. Mainly land lots in marginal areas were distributed for instance in 1852, when four 

farms were bought from Luua manor. Active buying started in 1864 and by the end of 1880, the majority of farms had 

been bought out from the manor. There were 13 manors in Palamuse parish. The first two decades of the 20 th century 

changed little in the land-use structure in Estonia. The same processes of renting and buying for perpetuity of land from 

landlords continued up to 1918, when the Republic of Estonia was declared independent. The land reform proclaimed on 

February 17, 1919, was one of the first important acts of the independent state. All land belonging to the 1,149 estates of the 

Baltic-German landlords, was nationalised and later distributed to Estonian peasants. 

In the Palamuse parish the land of 10 manors was divided into 195 plots. 170 of them were given to the farmers by 

virtue of temporary lease as normal farms, one to the farmer by virtue of private agreement, 7 to industrial enterprises, 2 

to companies and municipal institutions, 14 to the employees and 1 was left for backlog-land. 

There were 280 farms in the Palamuse community. 208 farms were bought and 72 were leased. 

7543.4 ha (35.1% of the total land area) was fields and gardens, 4983.5 ha (23.2%) meadows, 2949.4 ha (13.7%) 

pastures, 3989.4 ha (18.6%) forests and 1999.7 ha (9.4%) was out of use. 

When at the second half of the 19 th century the communities were formed, Palamuse parish was divided into four 

communities: Kuremaa, Kudina, Kaarepere and Roela. In 1945, the Palamuse community was formed from Kuremaa 

community. In 1972 the area of Palamuse community was 247km² and it had approximately 2,900 inhabitants. 

In 1964 there were 25 villages in Palamuse. Three of them had less than 9 families, 10 had 10–19 families, 3 had 20–29, 

2 had 30–39, 5 had 40–49, 1 had 60–69 and 1 had more than 100 families. These villages were mostly agricultural 

villages. there were two collective farms in Palamuse, “Uus tee” in Kudina and “V. Kingisepa nimeline kolhoos” in 

Varbvere village. 

In 1991 Palamuse got local government status. 

Nowadays the area of the community is 216km² and the population consists of 2,650 people. The sex and age group 

structure is presented in the table below. The average population density is 12,3 inh/km². 

Tab .36 - Population of the Palamuse municipality by sex and age groups (01.01.00) 

Population 

Age groups 

01.01.00 0–14 15–24 25–39 40–54 55–64 65+ 

Palamuse M 1 302 263 246 284 251 132 126 

F 1 348 267 194 246 234 147 260 

TOTAL 2 650 530 440 530 485 279 386 

Most of the employees in the community work in Palamuse, less than 10% (9,4) of employees are working outside the 

municipality, compared to 12,6% in 1998. The number of employees has increased compared to 1998. 

Tab. 37 - Employees by actual place of residence in the Palamuse municipality (01.01.00) 

Total number of Working out of rural % 

employees 

municipality 

1998 1999 2000 1998 1999 2000 1998 1999 2000 

Palamuse 872 1 054 1 038 110 99 98 12.6 9.4 9.4 

3.3.4 Identification of most relevant pressures exerted on environmental functions by local agricultural 

system 

From the analysis of the local agricultural system above it has been possible to identify significant pressures 

that may have causal relationships with impacts on state indicators values measuring the level of 

performance of the environmental functions of interest (see Step 2 above). 

Amongst the many possible pressures exerted by agriculture on environmental functions a selection had to be 

made by looking at results of analysis of information gathered in the above sections. Four broad classes of 

pressure indicators were suggested herewith following. These are pressures related to: 

73

Table 38 - Pressure indicators 

Please note that the list below is general Descriptions 

and only indicative. Other pressures may 

have been used depending on the case 

study 

a) Nutrient management indicators 

a1) Farm gate nutrient balance Balance of N and P purchased in fertiliser and feed, plus fixation of atmospheric N by 

legumes minus amount of N and P in product sold from farm: Nitrogen surplus Kg/ha; 

Phosporus surplus kg/ha; Ammonia evaporation kg/ha; Nitrogen leaching kg/ha. 

a2) Adjusting application rates to crop needs Matching application rates to expected crop yields increases nutrient use efficiency - used 

in precision fertiliser systems. 

a3) Timing of nutrient applications Applications of N at time of maximum plant uptake 

a4) Crop rotations System of alternation of cultivation of crops 

a5) Placement of fertilisers Time and type of application of fertilisers such as on the fields, on vegetation rows or just 

near the seeds 

a6) Fertilisers used per hectare Amount of fertilisers used per hectare 

a7) Livestock density (LU/ha) Number of livestock unit per hectare 

b) Soil and land management indicators 

b1) Land use Utilisation of the territory for different purposes 

b2) Soil cover, mowing, hay cutting, grazing; N° of days that soil is covered, factored by the % of soil cover provided by vegetation and 

crop residues. Plant and crop residue cover protects soils from erosion, reduces runoff of 

nutrients and pesticides and provides habitat for biodiversity (OECD, 1998) 

b3) Land management Use of reduced and zero tillage and other best management practices. % of crop land 

cultivated using minimum and zero tillage practices, crop rotations, grassed waterways, 

contour strip cropping, etc. (OECD, 1998) 

b4) Landscape management Reflects the removal of fencerows, walls, hedges, wetlands and woodlands, as well as the 

fencing of riparian areas to protect them from damage by livestock. Areas of buffer strips 

and fenced land along ditches and watercourses can also be included (OECD, 1998) 

c) Irrigation and water management 

indicators 

c1) Water use efficiency Volume of agricultural produce per unit of irrigation, water volume consumed; Volume of 

agricultural produce per unit area of rain fed agriculture, water volume consumed (OECD, 

1998) 

c2) Irrigation delivery systems % of irrigation applied by flooding, high pressure rain guns, low pressure sprinklers and by 

drip-emitters. Indicate the probable water use efficiency, and risk of over-irrigation (OECD, 

1998) 

c3) Drainage/diversion/extraction processes Area drained, or the length of of drain pipe or surface drains installed, or outlet drains 

excavated. Proportion of total surface and groundwater resource diverted/extracted for all 

purposes; proportion of total surface and groundwater resource diverted/extracted for 

agricultural production; proportion of total annually renewable water resource used by 

agriculture. Are indicative of disturbance of fish and wildlife habitat, and of lowering of the 

water table (OECD, 1998) 

d) Pesticide use indicators 

d1) Pesticide use per ha Measured in the amount of active ingredients (kg/ha) and standard doses (kg/ha) (OECD, 

1998) 

d2) Use of integrated pest management (per Area of crops where integrated pest management is used (OECD, 1998) 

area and timing) 

d3) Use of alternative (non-chemical) pest Area of crops where pest control is achieved without use of chemicals (OECD, 1998) 

control methods 

d4) Timing of herbicide use % of use only when required by weed pressure, rather than pre-plant and pre-emergence 

which are used as insurance (OECD, 1998) 

d5) Timing of insecticide use % of insecticide use only after determining level of infestation (use only as required by 

insect infestation) (OECD, 1998) 

d6) Toxicity of pesticide used e.g. the total amount of LD50 doses applied per ha 

Main source: OECD Workshop on Agri-Environmental Indicators, York, UK, 1998, ECNC, Agri-environmental 

indicators, 2000. 

74

Box 30 – AEMBAC project: Identified pressures in the Geldersey Valley study area, Netherlands 

A summary and short explanation of pressure indicators for both functions is presented in the tables below. The 

recreational appeal of the area is partly determined by its ‘natural beauty’, including the plant and animal species to be 

spotted by tourists. In this respect all the pressures identified for the ‘habitat function’ are also relevant for the 

‘recreation function’. Due to data-availability problems, in this stage of the project, precise quantification of pressures 

has not yet been undertaken. 

Tab. 39 - Habitat function pressures 

Pressure 

Land use 

Unit of account Explanation 

Area agricultural land Percentage of total 

area 

Agricultural land increase is at the expense of forests and other 

natural elements. 

Average field size Hectares Many species depend on the border zones between different 

agricultural fields and fields and natural areas. (length of border zones 

is negatively affected by increase in average field size). 

Nutrient Management 

Net organic and inorganic 

kg per hectare High mineral input and ammonia emission levels have negatively 

input of N 

affected the vitality of the wetlands, canals and other natural elements 

Net organic and inorganic kg per hectare 

input of P 


input of K 

through eutrophication. 

Wet atmospheric 

deposition of NH4 

kg per hectare 

Dry atmospheric 


Land management 


Mowing period grassland First date of mowing / Mowing period is especially relevant for hatching field birds, which 

last date of mowing are heavily disturbed by mowing activities during the breeding 

Mowing intensity Number of cuts season. Both mowing intensity and grazing intensity are relevant for 

grassland 

during mowing the plant species richness of fields. Specific management of field 

period 

edges is of great importance, since on average, edges account for the 

Grassland grazing Number of grazing majority of total species richness of a field. 

intensity 

cows per hectare 

Total length of 2m wide 

uncultivated field edges 

Pesticide use 

Metres 

EPA-category-1 active kg per hectare of Pesticide use causes pollution of soil, groundwater and surface water, 

ingredient applied cultivated land which affect the habitat quality of the agro-ecosystem and adjacent 

EPA-category-2 active kg per hectare of nature areas. 

ingredients applied cultivated land 

EPA-category-3 active kg per hectare of 

ingredients applied 

Water management 

cultivated land 

Direct shallow m3 per hectare Intensification of agricultural activities has contributed to the 

groundwater 

lowering of groundwater levels, leading to desiccation of the agro- 

extraction by agriculture 

ecosystem, causing a decline in ‘moist and ‘wet’ species. 

Drainage Percentage of total 

cultivated 

drained 

land 

Groundwater level Decrease (in metres) 

decrease 

since 1900 

(cultivation improvement 

related) 

Note: since the pressure exerted by pesticide use in the case study area is relatively minor (see WP4 report), inclusion of 

75

the related indicators in the analyses of phase 2 and 3 of the AEMBAC project is still under consideration. 

Tab. 40 - Recreation function pressures 

Pressure 

Land use 

Unit of account Explanation 

Area agricultural land Percentage of total Agricultural land increase and increase in average field size poses a 

area 

threat to forests and other natural elements (large field sizes tend to 

Average field size 

Nutrient Management 

Hectares 

be correlated with less diverse and less structured landscapes). These 

elements are assumed to be highly valued by tourists. 

Net organic and inorganic kg per hectare High organic mineral application on fields causes nuisance of 

input of N 

manure-related odours, which might deter tourists. High mineral 

Net organic and inorganic kg per hectare input and ammonia emission levels might also negatively affect the 

input of P 


input of K 

quality of recreational waters. 

Wet atmospheric 



Dry atmospheric 




Grassland grazing Number of grazing The presence of grazing cattle on fields (captured by the pressure 

intensity 

Pesticide use 

cows per hectare indicator ‘number of cows per hectare of grassland’) is assumed to be 

a fundamental attribute of rural landscapes, as perceived by tourists. 

EPA-category-1 active kg per hectare of Through pollution of ground and surface waters, pesticide use can 

ingredient applied cultivated land have a negative impact on the quality of recreational waters. 





Note: since the pressure exerted by pesticide use in the case study area is relatively minor (see wp4 report), inclusion of 

the related indicators in the analyses of phase 2 and 3 of the AEMBAC project is still under consideration. 

3.3.5 Analysis of aspects acting as driving forces (environmental, economic and social) for the 

pressures identified 

This section identifies and analyses the main driving forces behind agricultural pressures on the environment 

identified in section 3.3.4 above. It is important to determine what are the relevant factors which drive the 

farmers’ decision-making process, such as environmental, economic and social conditions, and which of 

these result in impacts on the performance of environmental functions. These decision-making processes can 

result in changes in cultivation practices such as that from crop rotation to intensification and monocultural 

cultivation (specialisation effect), or in changes between agricultural activities and complementary ones 

(substitution effect), or in conversion of natural ecosystems into agricultural ones and vice versa, etc. 

Starting from the results of the analysis in the previous section on most important pressures driving forces 

such as the social structure, markets, institutional functioning, agricultural policy, etc., were identified in 

detail and their roles in promoting the pressures impacting on environmental function performance were 

described and analysed. 

Regarding this it was useful to distinguish between local and foreign driving forces. 

Local driving forces, are those which originate from local socio-economic realities, e.g. traditional 

76

knowledge or specific local economies of scope or local specialisation. These could be a great 

entrepreneurial spirit of farmers, good road infrastructure, nearby location to high nature value areas which 

allow to develop agritourism activities, etc. 

Foreign driving forces are those which originated and/or are imposed from upper scales such as national, 

international and world levels (e.g. National policy, CAP, WTO agreements, etc.). These could be CAP 

subsidies coupled to production and export subsidies, national fiscal policy favouring big farms, etc. 

The results of this analysis were important because they allowed the issues to be identified (and at what 

level) that have to be addressed through agri-environmental programmes, aiming to lessen pressures 

impacting negatively or enhance those impacting positively on environmental functions. 

Environmental driving forces 

This section enlarges the description of Step 1 concerning environmental features of the area studied. Hydrogeological, 

morphological, climate, general ecological site conditions which can be considered driving forces 

of the decision-making process, such as fires, changing climate, slope, soil quality, sun exposure, etc. were 

identified and described here. 

Box 31 – AEMBAC project. Environmental driving forces in the three German study areas 

Jahna river basin 

Restrictions on production methods, which go beyond good professional practice do not exist. Endeavours to protect 

parts of the study area (valleys covered with grassland between plateaus with arable land) as a “Landscape protection 

area” failed due to opposition from the farmer. 

Große Röder river basin 

Large parts of the Große Röder river basin are protected by several “Landscape protection areas” (e.g. Moritzburg 

small-hill landscape). But there are no restrictions for the farmers. 

The heterogeneity of soil conditions are responsible for a partly small-structured landscape (small plots which are often 

bordered by hedges). Moist and wet hollows favour a higher proportion of grassland than in the Jahna river basin. 

Biosphere reserve “Upper Lusatian Heath and Pond Landscape” 

In the biosphere reserve area, soil fertility is the lowest among the Saxon study areas chosen. There are marginal soils 

and the region is categorised as a potential area of land abandonment (DRL, 1997). 

Because of the different suitability of sites for plant production, proportions of livestock increase in Saxony from West 

to East (in general) (sandy soils, low precipitation, high differences between temperatures in summer and winter). 

Heterogeneity in soil conditions led to an heterogeneous land use mosaic and extensive use in history, which is in large 

parts preserved till today. Therefore, the whole region is protected as the biosphere reserve “Upper Lusatian Heath and 

Pond Landscape”. 

Economic driving forces 

To identify economic driving forces it was suggested, for each prevalent agricultural production, to analyse 

the resulting economic indicators in section 3.3.3 above. For instance it was suggested to look at gross 

production, current cost (e.g. detail of chemical inputs), and gross margin profit, because these, amongst 

others, can be very useful in determining the economic driving forces which have led to the present situation. 

For example it can be interesting to analyse shifts among cultivation according to changes in gross margin 

profits. 

Other factors analysed in order to identify economic driving forces were: 

Factors which lead to rural economy diversification at farm level, such as the substitution/synergies 

between strictly agricultural activity and other types of activity (e.g. economies of scope); 

The role and the influences of horizontal (e.g. economies of scale) and vertical integration processes in 

the local agricultural system, including the resulting contractual power of farmers and farm structure, and 

77

the role which farm associations can play in the agricultural changes at local level; 

The principal agricultural and environmental subsidies; and 

The evolution of market demand in general for typical local products, environmental and cultural 

amenities, at local, regional national and international level. 

The analysis of aspects acting as local driving forces concentrated on: 

• Identifying the socio-economic aspects considered acting as driving forces in reference to the 

agricultural pressures identified in Step 3; 

• Explaining in detail what are the relationships between the driving forces identified and the pressure 

exerted, and how the former could vary to cause a change in the latter. The explanation had to be 

supported by clear and science-based arguments; and 

• Envisaging what should be done to reduce driving forces related to negative impacts and enhance those 

related to positive impacts. 

Box 32 – AEMBAC project: Economic and technological driving forces in Selaön study area, Sweden 

A first, tentative analysis indicates that the economic driving forces are decisive, although not in sole power. High costs 

of labour, combined with low profitability in milk production, cattle and sheep husbandry appear as the major economic 

obstacles to the preservation of biodiversity and other landscape amenities. Among the many reasons for low 

profitability are high taxes, not just on farming but also, for example, high petrol taxes which harm those living in the 

country-side with long distances to any service. 

The economic forces behind the development of agriculture and landscape on Selaön are otherwise the same as in 

general throughout Sweden and Western Europe. Changing relative prices is an expression of these forces, but the 

price mechanisms are also a means by which these forces act. As prices of labour have increased relative to machinery, 

fertilisers and biocides, there has been a long and far-reaching substitution between these production factors. Between 

labour and land there are – on the contrary – various kinds of complementarity, implying that land has been substituted 

for chemicals when labour costs have increased. Prices of land have furthermore increased in the historic perspective 

relative chemicals, reducing the demand for cultivated or grazed land. High taxes on labour have reduced the work 

force, not only in traditional agriculture giving biodiversity and other values as joint products, but also for directed 

landscape management. Another, significant example is how the relative prices of imported concentrates became more 

competitive than locally produced feedstuff, reducing the demand for land further. Prices of agricultural commodities 

have decreased relative inputs and a basket of other consumption products, making the land use less profitable and 

leading to abandonment of vast areas. (Hasund 1986) 

Underlying the changes of supply and demand of agricultural land via changing relative prices are the universal forces 

of technical developments, changing preferences, increasing purchasing powers, population growth, changing resource 

accessibility, etc. The subject is too comprehensive to be analysed here, although it is of the utmost importance for the 

long-term development of the agricultural landscape and its qualities. If pointing to some examples, the importance of 

technical innovations like fertilisers, biocides, drainage, sowing machines etc. that have increased the hectare 

productivity cannot be underestimated, as they have reduced the total demand for land. Other technical developments 

that have improved the productivity of the used land in a wider sense include plant and animal breeding, veterinary 

science, or more efficient harvesting and storing techniques. Tractors have replaced about 600 000 horses in Sweden 

over the last century that needed hundreds of thousands of hectares of arable land and pastures to be reared. The 

inventions of the barbed or electric wires have, on the other hand, decreased the costs of using pastures in the animal 

production significantly. Without them, there would probably be hardly any pastures remaining in Scandinavia. The 

new, efficient techniques for producing poultry and pork give cheaper meat that drive out beef or mutton from the 

market, with manifest consequences for the pastures and their biodiversity. High income-elasticities for meat in general 

or growing preferences for riding just partially balance in the other direction. 

Economies of scale and the further development of the market economy have led to a far-reaching specialisation of 

farming – with profound consequences for the landscape. The access to markets for agricultural commodities, as well as 

the protection of the domestic market, was a determining factor for the development of Swedish agriculture from the 

opening of oat exports to Western Europe in the 19 th century to the import barriers between the 1930s until membership 

of the EU. (Pettersson 2001) 

78

Box 33 – AEMBAC project – Driving forces in Chianti study area, Italy 

(for references in the box see UNIFI-DSE report) 

The first observation is that the market power of Chianti wine has strongly influenced territorial development. 

The increase of the prices recorded in the last five years – 100 Kg. of wine in Chianti are usually sold at 157 € (RICA; 

2002) - has influenced prices and decisions of the producers such as: the general conversion of the olive cultivation into 

vineyards and the relevant increase in prices of agricultural land. 

Market Driving Forces 

Management of soil cover 

The introduction of the new P.O.C. (Protected Origin Controlled) "Olio Chianti Classico" (D. M. 4 December 2000) has 

indirectly influenced the “management of soil cover” with the covering the soil 10 on olive-producing land. Nowadays, 

soil grass cover is not a normal agricultural practice for vineyards but a lot of agronomic practices underline the 

usefulness of soil grass cover to improve the quality of wine (a smaller yield per plant improves the total production 

quality). Appropriate “management of soil cover” is very important as it can decrease soil erosion. 

Hedgerows conservation 

Market forces produce negative effects on “hedgerow conservation”. 

Hedgerow conservation improves the refugium function and the scenic diversity of the landscape. There are two 

different problems connected with improving hedgerow conservation: 

The plantation of hedgerows on field margins could produce problems in the use of mechanical tractors which could 

add time to farmers tasks; andThe total quantity of wine will be reduced by the set of hedgerows on the line of 

maximum slope.Land use conversion 

Lastly, referring to land use conversion we can assert that the market is a negative driving force and pushes towards the 

specialisation of vine cultivation (i.e. mono-culture), which gives a greater income than olives, woodland strips and 

pastureland. Other driving forces are determined from the disciplinary P.O.C. where the cultivars admitted 11 are 

indicated, limiting the possibility of using other varieties. However, in contrast with this fact, there is a growing demand 

for market products that use new varieties (Merlot, Cabernet, Sauvignoun…). 

Fig. 14 Example of land levelling before plantation 

Clearance of semi-natural vegetation by heavy 

machinery 

(P.Bazzoffi, ISSDS, 2003) 

Public intervention Driving Forces 

79 

Removal of Fertile topsoil (brown) from the top 

and replacement at the foot of the hill before 

vineyard plantation (P.Bazzoffi, ISSDS, 2003) 

Management of soil cover 

The management of soil cover was provided for in the measures of Reg.2078/92 through the practice of "green 

manure" 12 as well as grass soil cover but it has not received remarkable uptake. 

Hedgerows conservation 

The effect of the public sector on "hedgerow conservation" can be determined by local and non-local driving forces. In 

10 

The grass cover is helped by Art. 6 that obliges the oil "Chianti Classico" to be produced only with fresh olives, put with the best agronomic 

technique ( this means a olive-harvesting from the tree and not from the soil) and the indirect possibility of leave the grass soil cover. 

11 

Some examples of the variety of vines and olives: san giovese, canagliolo, trebbiano, malvasia (vines); pendolino, frantoio, leccino, muraiolo 

(olives). 

12 

For the green manure pratices we can use leguminose, composite, crucifere and graminacee.

the first case, we consider the Forest Law at regional level, while in the second case, we refer to the European 

regulation 2080/92. The Italian forest law considers forest 13 as "all the shrubs and the plants living on land abandoned 

for a period of 15 years", (Art.5 L.R. 39/2000). The direct consequence of this law is that it is impossible to modify the 

forests without authorisation. This has the effect that farmers coppice the strip margin vegetation in order to avoid any 

possible future impediment. The application of Reg. 2080/92 produces positive effects on hedgerow conservation but 

does not permit the development of semi-natural habitat. 

At a provincial level the regulations have been adopted 34 times from 1994 to 2001 (267,98ha were under 

implementation) for the improvement of the woodlands and the windbreak function of hedges. Unluckily in the new 

Reg. 1257/99 for the Measure 8.1 "Afforestation of agricultural lands", Greve is not considered a priority municipality 

(BURT 2001). In the last three years several companies working in the study area applied for measures of the European 

Regulation on wood forestry 2080/92, and preferred to give back the grants they received in order to substitute the 

woodland with vineyards (interview with an employee of the public provincial administration). 

Land use conversion 

The tendency to convert olive groves and forests into vineyards, shown in the Wp4, is in part reduced by the 

Reg.1493/1999 and by the trend of the last decade. From 1982 to 1990 in the municipality of Greve, the land covered 

by vineyards decreased by 13%, while the relative surface area covered by of the olive production increased by 18% 

(Dini, 1997 Pg. 169). In any case the field visits in 2002 demonstrated that the situation is not under control and in a 

few years vineyards could be planted anywhere. 

The vine sector does not receive a general subsidy for the production of vine but only an eventual subsidy after the 

adoption of the Reg. 2078/92 (INEA, 2002). We consider, finally, that the tendency to use certain types of cultivar 

comes from the principles of Good Farming Practice in the Rural Development Plan, where the use of transgenic 

cultivars for wine and olive sectors is forbidden (BURT, 2001). 

Social driving forces 

Social driving forces underlying pressures on the local agricultural system were identified analysing the 

social, historical and cultural components of local milieu, such as cultural heritage and/or traditional 

knowledge which influence the cultivation practices, tenurial forms, environmental awareness of farmers, 

land abandonment, etc. 

Box 34 – AEMBAC project: Land policy and land reform as social driving forces in Palamuse study 

area, Estonia 

Land policy 

National land policy is a part of social policy. Land policy forms the basis for all economic sectors, which are directly 

tied to the land: agriculture, forestry and construction. The economic aspects of land policy can be regulated mainly via 

land prices and land taxes. Land policy is primarily land-use policy with which, on the basis of the country’s historical 

background, the social, legal and economic relationships in the country are regulated. 

Today’s land policy is characterised by the allocation of land ownership – returning of land to the former owners, 

privatisation through sale, but also nationalisation and municipalisation of land. 

National land policy has an important role in the resolution of environmental protection issues. This happens via the 

respective legal acts, which safeguard and regulate land as real-estate. Land policy should consider mainly the 

following environmental aspects: soil conditions, landscape mosaic, groundwater quality, surface water conditions, the 

condition of livestock farms, hazardous waste. From now on we should take the aims of biological and landscape 

diversity conservation into account. The condition of land that is no longer used for agricultural production must be 

evaluated from an environmental protection point of view and the possibilities for its use in the new production 

environment should be considered. 

Land reform 

The Land Reform Act defines the principles applicable to the reorganisation of land ownership (land reform), the rights 

and obligations of land users, and it establishes the basis for other legislation regulating land ownership. The basic 

principle of the Estonian land reform is that anyone who was a landowner before June 16 th , 1940, or who is an heir of 

such a person, has the right to demand return, substitution or compensation for land that was unlawfully alienated. Thus, 

those who did not wish to receive the land, would be compensated, and those whose land was no longer available 

13 For the L.R. N. 39 / 2000 a wood is every area with an extension of at least 2000 square meters and a width of more than 20 meters, covered by 

spontaneous or artificially implanted trees, in every stagre of growth, with a density bigger than 500 plants per hectare. Woods are also chestnuts and 

cork forest. 

80

ecause of, e.g., urban development or the construction of Soviet military bases would be permitted to receive 

alternative land. The land that is nationalised and the land that can be given either for money or free of charge to private 

legal persons, public legal persons or to municipalities is defined within the land reform. 

The main objective of the land reform is to establish the owner of the territory of Estonia. The planned stages to achieve 

this objective were: definition of land retained in state and municipal ownership, return and compensation for 

expropriated land (this initially included replacement of land, while in reality mostly compensation and privatisation 

were applied), and privatisation of land for which no restitution claims were submitted. 

About 66% of the territory of the Palamuse Pilot area is currently entered in the state land registry. 

A slow and incomplete privatisation process and inadequate rural policy have been the main reasons for arable land 

abandonment. This creates several environmental problems – decrease in biodiversity and aesthetic value of the 

landscape, distribution of weed seeds and danger of fire. 

3.4 Step 4 - Assessment of ecological sustainability of local agricultural pressures 

and development of recommendations on how to lessening/eliminating negative 

impacts and enhancing positive ones 

3.4.1 Definition of the causal relationships with pressure indicators of the local agricultural 

system 

In Step 2, Environmental Minimum Requirement (EMR) values of state indicators, describing relevant 

ecological aspects contributing to the performance of the environmental functions, were identified at local 

level. Comparisons between EMRs and actual values of state indicators have elicited a positive/negative gap 

in reference to the EMR. In Step 4 researchers had to identify causal relationships between the measured 

gaps and agricultural pressures studied in Step 3. 

Following conclusions from step 2 on gap analysis between EMR and actual values of state indicators, and 

those from Step 3 on identified most relevant local agricultural pressures, a matrix on state, pressures, 

impacts (see Fig. 15 below) was constructed, to show at a glance what the causal relationships between state 

and pressures indicators and the resulting impacts are. The measured gaps were ranked by qualitative order 

of magnitude of positive/negative impacts (using colour coding: green = low impact, yellow = medium 

impact, red = high impact and +/- signs for positive and negative impacts respectively). 

For each environmental function analysed, the matrix represents in the vertical column the state indicators 

used to describe it (environmental profile) and in the horizontal axis the pressure indicators of the local 

agricultural system which are responsible for detected impacts (through gap analysis). 

From the analysis of the causal relationships (vertical) between state and pressure indicators and the 

identified relevant impacts, the following results and conclusions were achieved: 

Detailed explanation and conclusions on why agricultural pressures are impacting on the value of state 

indicators through the causal relationships identified; and 

Detailed indications on what actions are most needed to lessen negative impacts relative to agricultural 

pressures to achieve sustainability for the performance of the environmental function selected, or what 

actions are suggested to increase positive impacts. In cases where good information on dose-effects 

relationships between pressures and impacts were available, it was possible to understand what would be 

the effects of reducing the intensity of pressure of the agricultural system on the relevant impacts, so as to 

achieve or enhance environmental performance more effectively. 

81

Fig.15 Habitat Function 

(Biodiversity conservation): 

Evaluation of performance by Natural 

Ecosystem and Agro-Ecosystem at 

local level. Example of positive 

impacts exerted by land use, soil 

cover maintenance and negative 

impacts exerted by use of pesticide 

(Semi)Natural Ecosystem (NE) state 

indicators 

(data from bibliographic/field research) 

Plant genetic and species 

di In situ itPlant 

Genetic 

RNumber of 

Number i of rare 

Number i of endemic 

Number i of varieties for each plant 

Threatened i and extinct 

Species i population 

dAnimal i genetic and species 

di Breed it 

Breed b drichness 

Threatened and extinct 

bNumber d of 

Number i of rare 

Number i of endemic 

Threatened i and extinct 

Species i population 

dEcosystems i and habitats 

di Ecosystem it quantity as % of the area 

Ecosystem it 

Natural lit Capital Index 

(NCI) Biotopes/Habitats variability and 

hThreatened t ithabitat 

tSpecies abundance, richness in 

h 

Faunistic 

bit t 

activity in 

h bit t 

. Agro-Ecosystem (AE) pressure 

indicators(data from questionnaire 

bibliographic/field d 

h) 

a) Nutrient management 

a1) Farm gate nutrient 

b l 

a2) Adjusting application rates to crop 

d 

a3) Timing of nutrient 

li i 

a4) Crop 

i 

a5) Placement of 

f 

a6) Fertilisers used per 

h t 

a7) Livestock density 

(LU/h ) 

Box 35 – AEMBAC project: Analysis of the causal relationships between main agricultural pressures 

and state indicators describing the aesthetic quality of the landscape, Chianti study area, Italy 

On the basis of the analysis carried out in Step 2 and Step 3 in the Greve study area, the following causal relationships 

between agricultural pressures and measured impacts on the environmental functions have been identified as the most 

probable given the local ecological and agricultural context. 

Land use conversion (pressures) 

Land use conversion is the most important pressure detected: in fact it has very strong negative impacts on boundaries 

water/land and linear and punctual features. Boundaries and water land is impacted because riparian ecosystems are 

seriously below their EMRs due to agriculture and urbanisation. 

Linear and punctual features are impacted because agriculture is practised in riparian environment. 

Land management (pressures) 

Boundaries and water land is impacted by logging and coppice cutting and habitat fragmentation because of repeated 

82 

b) soil and land 

b1) Land use 

b2) soil cover, mowing, hay cutting, 

i 

b3) Land management 

b4) Landscape 

(WP5) 4. Hypothetical Impacts 

no impact significant 

low high 

c) Irrigation and water 

t 

c1) Water use 

ffi i 

c2) Irrigation delivery systems 

c3) Drainage/diversion/extraction 

d) Pesticide use 

d1) Pesticide use per 

h 

- 

- 

- 

- 

d2) Use of integrated pest 

t 

d3) Use of alternative pest control 

h d 

d4) Timing of herbicide 

d5) Timing of insecticide use 

d6) Toxicity of pesticide 

d

coppice cutting. Strips of uncultivated land within farms are very marginal in extension. This fragmentation of linear 

boundaries is negative for the aesthetic appreciation of landscape. 

Naturalness of forests is degraded by logging and coppice. 

Linear and punctual features are impacted because of cutting of riparian vegetation. 

Season compliance is not fully respected because of the diffusion of summer crops (e.g. maize and sunflower), 

encouraged by the CAP. Without contribution from EU to summer crops, farmers surely would be much interested in 

forcing natural seasonal cycle. Seasonal compliance is also affected by crop diversity in a controversial way. Traditional 

cultivation such as of olives and vines respect the seasonal compliance, while the summer crops encouraged by the CAP 

have a negative impact as said above. 

Landscape management (pressures) 

Diversity of scenery is impacted because incoherent suburbs and infrastructures have been introduced in a 

heterogeneous agriculture landscape. Heterogeneity is increased so loosing the previous matrix and does obtaining a 

worse quality. 

Harmonisation of the landscape is impacted because landscape in the main ridge, traditionally occupied by pastures 

and heaths, nowadays is conquered again by woodlands or artificially afforested, thus loosing its qualities of open 

space. 

Boundaries and water land is impacted because of riparian woodland, which is the most precious habitat, is seriously 

threatened by the present landscape management. 

Protected areas are impacted because in Chianti only the highest part of the main ridge is classed as site of interest for 

the Community. At any rate, it is not yet actually protected. 

Fig. 16 Landscape-related function: 

evaluation of performance by natural 

ecosystem and agro-ecosystem at a local 

level (Chianti study area, Italy) 

Pressure indicators (data from 

questionnaire and 


83 


Logging and coppicing 

Shrub cutting 

Soil cover 


(Semi-)natural ecosystems (NE) state 

indicators 

Diversity of the scenery (no. of classes) - - +/- - 

Harmonisation of the landscape - - + - 

Openness versus closedness + matrix 

fragmentation +/- + 

Biotopes and habitat types 

Land cover diversity (Shannon index) 

Boundaries: water/land - - - - 

Naturalness - - - 

Linear and point features - - - 

Protected areas - 

Number of protected species 

Season compliance +/- - _ +/- - 

High impact 

Significant impact 

Low impact 

No impact 

Crop diversity 

Uncultivated field margins 

Hedge conservation 

Habitat fragmentation 

Presence of land settings 

Landscape management

Following this approach, an analysis was carried out to assess if the causes, responsible for each gap 

identified, could be completely imputable to agricultural pressures or if some part of the measured gap was 

also due to pressures exerted by other socio-economic sectors (see section 3.4.1.1 below). The assessment of 

the relative importance of agricultural impacts on the measured gap between EMR and the actual value of 

state indicators was necessary, in the light of developing agri-environmental measures around those 

positive/negative impacts exerted mainly by agricultural pressures. 

3.4.1.1 Identification of the part of the gap between EMR and actual value of state indicators directly 

imputable to agricultural pressures 

The assessment of what is the part of the gap between EMR and the actual value of state indicators measured 

in Step 2, which could be directly attributed to agricultural pressures, serves a double purpose. 

Firstly it indicates whether the gap between EMR and actual value of a state indicator can be totally 

imputable to agricultural impacts. If this is not the case (i.e. the total % of impacts which can be attributed to 

agriculture would not cover the 100% of the gap), other pressures coming from other socio-economic 

activities or other causes could also be partially responsible for the measured gap. 

Secondly this assessment serves to give a better picture of the relative importance of different agricultural 

pressures impacting simultaneously on the same state indicator. It may be the case that more than one 

agricultural pressure is responsible for the gap measured in Step 2 on a single state indicator (e.g. removal of 

hedgerows and pesticide use on key animal species). This information has been useful later on to assign 

priorities to ease or remove different pressures through agri-environmental measures. 

This analysis required making a more precise assessment of how much of the gap (difference between EMR 

and actual value of state indicator) was thought to be attributed to the agricultural pressures identified, for 

each state indicator. In other words, it had to be assessed how much of the gap measured in Step 2 can be 

explained by agricultural pressures identified in Step 3 and correlated to the gap in Step 4, section 3.4.1 

above. 

Carrying out this analysis in quantitative terms requires very good knowledge and information on the doseeffect 

relationships between pressures and resulting impacts on the value of state indicators. At present this 

knowledge and information is limited for some of the aspects analysed. However, for some other state 

indicators it was possible to estimate a rough percentage value of the gap directly attributable to agricultural 

pressures, as it can be the case, for instance, for the percentage of encroachment of (semi-) natural habitats 

by agricultural and other land uses. 

Therefore to analyse how much of the gaps identified and measured in Step 2 could be directly attributed to 

agriculture, the following was proposed: 

• For those gaps where the scientific knowledge, information and data were available, to envisage the 

relative importance of agricultural impacts, in percentages of the measured gap, using Best Professional 

Judgement (BPJ). 

• Otherwise, using BPJ to indicate qualitatively for each single state indicator whether the gap could be 

totally attributed only to agricultural pressures (specifying what these were), or whether other socioeconomics 

pressures could be responsible for the gap, and explaining why. 

In fig 17, an example of the analysis in % terms is shown for the refugium function. The analysis starts by 

looking at the gap between the EMR and the actual value studied for each state indicator in Step 2 (left 

column). Each measured gap had to be analysed through the causal relationships with pressures exerted by 

the local agricultural system (identified in Step 3 and correlated to the gap in section 3.4.1 above), in order to 

assess for how much of it, in percentage terms, agricultural pressures are responsible. 

84

Measured gaps between EMR 

and actual values of state 

indicators 

Fig. 17 Refugium Function: Example of hypothetical relative importance 

of agricultural impacts in % terms 

Refugium Function: Example 

on hypothetical relative 

importance of agricultural 

impacts in % terms 

(WP4) 3. Agro-Ecosystem 

(AE) pressure indicators (data 

from questionnaire and 


a1) Farm gate nutrient balance 

a6) Fertilisers used per hectare 

b) soil and land management 

b1) Management of hedgerows 

or seminatural habitats 

b2) Management of soil cover, 

mowing, grazing 

Box 36 – AEMBAC project: Area of biotope types valuable for biodiversity in Greifensee, Switzerland 

Tab. 41 - Gap between actual values and EMR for the indicator “Area of biotope types valuable for biodiversity” 

in the study area Greifensee and the estimated level of responsibility of agriculture. 

Area Land Cover (ha) Responsibility (%) 

Land Cover Measured 

∆ 

value 

EMR agriculture others 

Surface standing water & waterside vegetation 1158 -2 1160 90 10 

Low input pastures and meadows 957 -171 1128 90 10 

Wetland 408 -93 501 90 10 

High stem orchards (extensive) 286 -15 301 80 20 

Small wood lots and hedgerows 163 -39 202 90 10 

Groups of trees 86 -6 92 90 10 

Surface standing water & waterside vegetation 

46 

within Greifensee and Pfäffikersee 

-2 48 90 10 

Ecological compensation area on arable land 37 -103 140 100 0 

Total 90 10 

Many of the landscape elements were created by cultivating the land (extensively used meadows, high stem orchards). 

That is why agriculture was responsible for such a high diversity of species in cultivated land. The clearing of the open 

landscape (“Flurbereinigung”), land “improvements” and rationalisation measures led to the removal of exactly those 

high biodiversity landscape elements. Therefore agriculture has a high impact and influence on these valuable biotope 

types. This also corresponds with linear features, for example the removal of hedgerows or the channelling and taming 

of water bodies. 

85 

b3) Management of field size 

a7) Livestock density (LU/ha) 

b4) Landscape management 

c) Irrigation and water manage 

c1) Water use efficiency 




d1) Pesticide use per ha 

d6) Toxicity of pesticide used 

Total % of relative importance 

ofimpacts correlated to 

agricultural pressures 

Total % of relative importance 

ofimpacts correlated to other 

socio-economic pressures 

(WP3) 1. (Semi)Natural 

Ecosystem (NE) state 

indicators 


Plant genetic and species diversity Number are % of relative importance of impact on measured gap 

In situ Plant Genetic Resources: 

-7 Number of species -100 100% 0% 

-3 Number of varieties for each plant specie -100 100% 0% 

Animal genetic and species diversity 

-12 Number of species -30 -30 -30 90% 10% 

-3 Number of rare species -70 70% 30% 

-9 Number of endemic species -60 -30 90% 10% 

Ecosystems and habitats diversity 

-32 Ecosystem quantity as % of the area unit -60 -10 70% 30% 

qualitative Ecosystem quality -70 10 60% 40% 

-3 Biotopes/Habitats variability and heterogeneity -80 80% 20% 

Species abundance, richness in 

-4 habitats 

-70 

70% 30%

Box 37 – AEMBAC project: Quantitative assessment of % of impacts imputable to agricultural 

pressures in Northwest Overijssel, Netherlands 

Quantitative example: nutrient management. 

Although the estimates for the sustainability tiers have been made using BPJ, in line with the AEMBAC methodology, 

there is one case for which data availability is sufficient to allow for a quantitative analysis of the tiers of sustainability: 

the issue of nutrient management, in the form of inputs of nitrogen and phosphorus into the system. These indicators 

strongly relate to the overall state indicator of dissolved oxygen in surface water, the higher the nutrient loads, the lower 

the dissolved oxygen concentration. 

The main indicators for the nutrient status of the surface water are Total Nitrogen (TN) and Total Phosphorus (TP). The 

total input of these two nutrients in Northwest Overijssel is presented in Table 44. It appears that agriculture inside the 

study area is responsible for 35% of the input of TN, and 41% of the TP. However, also for the water entering the area 

from the agricultural area upstream of Northwest Overijssel, an important share of the nutrients is from agricultural 

sources. For the purpose of this study, it is assumed that this share is equal to the share inside the study area: 35, and 41 

percent for TN and TP, respectively. This means that agricultural input of nutrients equals: 16 + 0.35 times 20 = 23 

kgN/ha/yr (or 50%) for TN, and 0.95 + 0.41 times 1.1 = 1,40 (or 60%) of the TP input (including agriculture inside and 

outside the study area). 

Tab. 42 - Total nutrient input in Input of Total Nitrogen 

Input of Total Phosphorus 

Northwest Overijssel 

(kgN/ha/year) 

(kgP/ha/year) 

Residues waste water treatment plants 2 0.10 

Agriculture 16 0.95 

Input from outside the area 20 1.10 

Deposition 7 0.08 

Other 1 0.10 

Total 46 2.33 

Source: Grontmij, 1999 and Groot-Salland Water Board, 2000 

3.4.2 Assessment and linking of degrees of sustainability to agricultural pressures by looking at the 

impacts exerted 

In section 3.4.1.1, researchers indicated, in qualitative and/or quantitative terms (where there was sufficient 

scientific knowledge and data), the part of detected impacts which could be attributed directly to local 

agricultural pressures. 

In this section, by adopting a qualitative approach, they then linked different tiers of sustainability to local 

agricultural pressures by looking at the environmental impacts exerted. The proposed approach was used to 

rank the sustainability of the local agricultural pressures in reference to the most relevant impacts exerted on 

environmental functions performance. 

It is important to note that this analysis has been carried out for each environmental function by studying 

impacts on all relevant state indicators, but analysing these impacts separately. In reality, the critical aspects 

measured by state indicators describing the same environmental function are all inter-linked (e.g. number of 

species linked to biotope/habitat variability and heterogeneity; species abundance, richness in habitats to 

ecosystem extension, etc.). The ideal would have been to find out, for each environmental function, what 

were the main relationships linking the value of one state indicator to the value of another 14 so as to assess 

more precisely the level of the environmental performance analysed, after that the effects emerging from the 

totality of impacts would have been acknowledged and their relative importance taken into account. This 

would have allowed the degree of sustainability of a local agricultural system to be assessed considering the 

overall performance of the environmental function, not just the sustainability of agricultural pressures by 

measuring the exerted impacts on single state indicator values separately. 

Obviously where the relationships between state indicators were available or could be scientifically defined, 

they had to be analysed and the results taken into consideration when assessing the overall performance of 

14 the so called “horizontal relationships” between state indicators, see Step 2, section 3.2.2. 

86

the environmental function studied. Unfortunately lack of sufficient scientific knowledge existing on 

ecosystem functioning (and for some aspects also time and resource constraints in AEMBAC), have forced 

the analysis to be carried out only on separated ecological aspects (i.e. single state indicators) describing the 

environmental function analysed. 

Therefore, summing up the above, in this section 3.4.2, the linking of degrees of sustainability to local 

agricultural pressures was done in reference to the gaps defined in Step 2, for each state indicator which was 

directly imputable to agricultural pressures. However, this approach, while not producing a judgement on the 

sustainability of the total impacts (i.e. considered altogether and simultaneously) on the environmental 

function performance, had the advantage of indicating what were the most important impacts to be 

considered when developing agri-environmental measures for local agricultural systems. 

3.4.2.1 Qualitative ranking system in reference to sustainability of local agricultural pressures 

The focus of AEMBAC is on sustainability of local agricultural systems measured through the impacts 

exerted on the performance of selected environmental functions within study areas. 

The objective of ranking degrees of sustainability to local agricultural pressures (identified through the 

analysis of causal relationships of the environmental impacts exerted) is to provide a tool for selecting and 

defining agri-environmental policy targets to be reached through agri-environmental measures. 

In fact, after the ecological sustainability of the pressures of local agricultural systems was ranked into tiers 

in this section, and socio-economic aspects were studied and considered in Step 5 below, it was then possible 

to identify agri-environmental targets and to develop the appropriate agri-environmental measures to reach 

these in Step 6. 

The matrix linking the environmental profile (set of indicators) describing the environmental function 

analysed with the local agricultural pressures exerting impacts on the values of state indicators developed in 

section 3.4.1 above, indicated the envisaged causal relationships and what was the intensity of the impacts 

(low, medium, high) and its positive/negative characther. 

Section 3.4.1.1 indicates (in quantitative and/or qualitative terms) the part of the measured gap between 

EMR and the actual value of state indicators, which could be directly attributed to agriculture, by BPJ. In 

order to associate different tiers of sustainability to agricultural pressures, in this section researchers were 

asked to look at the impacts which had been identified and analysed, and link a degree of sustainability to the 

corresponding causal pressures of the local agricultural systems (see fig.18). 

The following qualitative ranking criteria were proposed to associate different tiers of sustainability to 

agricultural pressures: 

Tier +2 = Presence of only high positive impact (red) 

Tier +1 = Presence of only positive impacts (yellow) 

Tier 0 = respect of EMR= ecological sustainability of agricultural practice = no impacts or only low 

positive/negative impacts (green) exerted by agricultural practices 

Tier -1 = Presence of moderate negative impacts exerted by agricultural pressures (yellow) 

Tier -2 = Presence of high negative impact (red) 

87

Fig. 18 Refugium Function: Example of qualitative ranking of pressures resulting from causal 

relationships between performance of environmental function and impacts exerted by the agricultural 

system at a local level. 

Refugium function 

(WP4) 3. Agro-Ecosystem (AE) 

pressure indicators (data from 

questionnaire and 





As can be seen in the example in Fig 18, the ranking of pressures is done simply by looking at the qualitative 

intensity of the impacts exerted by agricultural pressures. When there was more than one impact exerted by 

the same pressure on different state indicators, due to the impossibility of aggregating the simultaneous 

effects of different impacts exerted by the same pressure on the performance of the environmental function 

studied (e.g. because of lack of sufficient scientific knowledge), it was proposed to associate a tier to the 

relevant pressure by considering the impacts grouped together (using BPJ and explaining the reasoning of the 

given valuation). See the following example referring to fig. 18 above: 

Management of hedgerows and/or semi-natural habitats exerts 4 negative significant impacts and 2 high 

negative impacts on state indicators (relative to plant and animal species and ecosystems) because there are 

very sporadic field margins with hedgerows and no semi-natural ecosystem is maintained. This pressure is 

ecologically very unsustainable. It therefore ranks: Tier –2 

Management of soil cover exerts a significant negative impact on the number of plant species/varieties, a 

high negative impact on the number of animal species, and a significant negative impact on the number of 

rare animal species. These impacts make this pressure very unsustainable ecologically because the soil is left 

without any cover for most of the year even in the uncultivated borders, which does not offer the opportunity 

88 

b1) Management of hedgerows or 

seminatural habitats 






(WP3) 1. (Semi)Natural Ecosystem 

and/or agroecosystem (NE) state 

indicators 


Plant genetic and species diversity 


Number of species - 

Number of varieties for each plant specie - 


Number of species - - - 

Number of rare species - 

Number of endemic species - 


Ecosystem quantity as % of the area unit - - 

Ecosystem quality - + 

Biotopes/Habitats variability and heterogeneity - 


habitats 

Ranking tiers of agricultural sustainability in 

reference to pressure indicators 

- 

S 0 0 NS -2 -2 0 -1 A NS -2 

c) Irrigation and water manageme 



c3) Drainage/diversion/extraction pr 


no impact significant impact 

low impact high impact 

S=Sustainable 

NS=Not Sustainable 

A=Absent 


d6) Toxicity of pesticide used

for animal and plant species to colonise the field borders: Tier –2. 

Management of livestock density exerts a slightly positive impact on ecosystem quality but not enough to 

encourage the establishment of permanent natural pastures. 

However, this pressure is sustainable: Tier 0 

Landscape management exerts a significant negative impact on the extension of diverse ecosystems, as 

traditional rotational systems have been replaced by a more intensive system. This unsustainable pressure 

therefore ranks: Tier –1 

Pesticide use exerts two high negative impacts. This pressure is very unsustainable because the 

indiscriminate use of pesticide is also killing valuable non-targeted species: Tier –2 

Obviously this qualitative ranking system of sustainability risks being subjective, depending on the 

availability of information and on the researcher who is making the assessment. However, despite this, the 

proposed qualitative assessment offers the opportunity to provide an overall starting point for a more 

analytical picture of what degree of sustainability can be associated to individual pressures of the local 

agricultural system. In synthesis the ranking system has to be interpreted as a policy tool, based on the best 

scientific knowledge available, to identify where action is most required locally through the building up of 

agri-environmental measures. 

Box 38 – AEMBAC project: Qualitative ranking system of pressures in Egyek-Pusztakócs Pilot Area, 

Hungary 

Explanation 

Figure 19 Qualitative ranking of impacts 

resulting from causal relationships 

between biodiversity function in agriecosystems 

and pressures exerted by 

agricultural system at local level 

rotations 

State indicators Crop 

Ind.No. Biodiversity - agri-ecosystems 

s3 Length of habitat boundaries 

s7 Number of agricultural habitat blocks 

s8 Presence of organic farming - + - - 

s9 Grazing in endemic grasslands - - 

s10 Adequate land use for characteristic species 

s11 Number of nesting bird species - - 

s12 Number of migrating bird species - 

s13 Number of protected bird species - 

s16 Number of cultivated plant species or varieties - - 

s17 Number farm animal breeds - 

s18 Number of local plant species or varieties - - 

s19 Number of local farm animal breeds - 

s20 Integrated pest management - - - 


-1 


0 -2 -1 -1 -2 

Sustainability NS S NS NS NS NS 

89 

p1 

Fertilizer application rates 

p2 

Timing of nutrient applications 

p3 

Livestock density (LU/ha) 

p4 

Land use intensity 

p5 

Pesticide use per ha 

p6 

Toxicity of pesticide used 

p7 

Gene preservation 

p8 

Water management 

p9

Crop rotations (P1): this pressure exerts low negative impacts on presence of organic farming and significant negative 

impacts on the number of cultivated plant species or varieties, number of local plant species or varieties and integrated 

pest management. Traditional (conventional) crop rotation using a small number of plant species is the main farming 

practice. Moreover some farmers insist on monocultures that are very unreasonable on this poor land. This lowbiodiversity, 

monoculture-like crop rotation excludes organic farming. The number of cultivated plant species or 

varieties is low – there are only a few species grown, so this range needs to be improved. The low number of local plant 

species/varieties present in the agri-ecosystem limits the effectiveness of integrated pest management, with this kind of 

crop rotation, chains of infection cannot be broken and the natural restriction of pests is impossible. 

It therefore ranks: Tier –1 

Fertiliser application rates (P2): this pressure exerts a low positive impact on presence of organic farming because the 

use of fertilizers is at low or medium level. The current state of this pressure is sustainable but can be improved as the 

emphasis on nitrogen fertilisers may cause change in soil pH-value. It therefore ranks: Tier 0 

Livestock density (LU/ha) (P4): this pressure is very unsustainable because there is a very low grazing density in the 

area so that pastures dependent on human impact (regular mowing, grazing etc.) have started to deteriorate. Aggressive 

plant species have started dominating, which reduces bio-diversity and aesthetic landscape value. It has a strong 

negative impact on grazing in endemic grasslands. It therefore ranks: Tier -2 

Pesticide use per ha (P6): this pressure is unsustainable. It has a low negative impact on presence of organic farming 

as pesticide use automatically excludes organic farming. Pesticide use has two other significant negative impacts; on the 

number of nesting bird species - this pressure disturbs nesting bird species both via food supply and by toxicological 

effects including accumulation from the food chain and mutation - and integrated pest management - this is 

underdeveloped as production is focused on reasonable yields with no regard to other considerations. Farmers apply 

dosages recommended in packaging but sometimes apply extra as a precaution. A more serious issue is that the 

equipment is not modern enough to assure precision application, and to avoid spillage and leakage (chemical waste). 

Therefore more chemicals therefore get onto a unit of arable land than intended. It therefore ranks: Tier -1 

Toxicity of pesticide used (P7): this pressure is unsustainable. Although farmers use a small quantity of pesticides, 

they use herbicides with active hormone ingredients or other ones with a long decomposition period and which can be 

transported in inland waters. Moreover some active ingredients used belong to the so-called “clear-field technology” so 

that they kill a wide spectrum of species/varieties totally. For insecticides we also find chemicals with wide-spectrum 

active ingredients, and there are also poisons with multi-annual effects. This pressure also exerts significant negative 

impacts on presence of organic farming (organic farming obviously excludes pesticide use), the number of nesting, 

migrating and protected bird species (toxicity causes decrease in biodiversity) and integrated pest management (there is 

no integrated pest management in this area). It therefore ranks: Tier -1 

Gene preservation (P8): this pressure is not sustainable. This pressure exerts significant negative impacts on grazing in 

endemic grasslands (currently there is no grazing or the level of grazing is low – occasionally with several animal 

types), on the number of cultivated and local plant species or varieties and exerts high negative impacts on the number 

of farm and local farm animal breeds. Grazing pressure, especially by farm animals (not endemic species) is too low, 

resulting in the loss of plant species adapted to grazing. One of the most important reasons for this negative impact is 

that the pesticides used are not selected to be gentle enough not to damage bio-diversity. The National Park regulations 

provide some protection as the 70% of the study area is protected, but on the remaining 30% situation is not regulated 

enough. It therefore ranks: Tier -2 

3.4.3 Recommendations on how to lessen/eliminate negative impacts and enhance positive ones 

After having analysed the pressures causing the identified environmental impacts, possible solutions were 

analysed. Recommendations on how to reduce negative impacts and enhance positive impacts exerted by 

agricultural pressures on environmental functions were proposed. Two main kinds of recommendations can 

be envisaged: 

1. Those intended to change existing agricultural practices; and 

2. Those intended to create new environmental practices. 

1) Recommendations to change existing agricultural practices 

This required further consideration of the pressures identified in Step 4 as responsible for the detected 

90

impacts. Here some cases presented as examples. Please note these are not necessarily complete or 

exhaustive and that recommendations have to be designed for local agri-environmental situations. 


In the case that nutrient management is responsible for impacts on the performance of environmental 

functions, solutions have to be recommended in order to solve the problem and achieve a sustainable nutrient 

balance, e.g. through the following operations: 

a1) Select the most appropriate fertilisers for the fields according to soil and crop requirements 

a2) Adjust application rates to crop requirements 

a3) Respect the timing of nutrient applications in order to avoid leaching 

a4) Make use of crop rotations to fertilise the soil 

a5) Identify the most appropriate technique for the placement of fertilisers 

a6) Reduce fertilisers used per hectare: e.g. X kg. of nitrogen per hectare in total in one year 

a7) Others 

b) Land use and land management 

In the case that land use and land management are responsible for impacts on the performance of 

environmental functions, solutions have to be recommended in order to solve the problem and achieve 

ecologically sustainable land use and management, e.g. through the following operations: 

b1) Change land use in order to protect and maintain all habitats, biotopes, trees, shrubs and landscape point 

and linear features 

b2) Reduce livestock density (LU/ha) to a level that ensure that grazing pressure is sustainable and respect 

grazing periods appropriate for maintaining biodiversity (LU=Livestock Unit) 

b3) Adopt practices for land management, e.g. soil cover, mowing, hay cutting, tillage which do not 

compromise the performance of environmental functions 

b4) Protect and maintain all landscape features such as stone walls, field boundaries, hedges, ditches, banks 

etc. 

b5) Others 


In the case that irrigation and water management are responsible for impacts on the performance of 

environmental functions, solutions have to be recommended in order to solve the problem and achieve 

ecologically sustainable management, e.g. through the following operations: 

c1) Avoid all waste of water in order to increase efficient water usage 

c2) Promote sustainable irrigation delivery systems and their correct maintenance 

c3) Avoid drainage/diversion/extraction processes if this can damage habitats 

c4) Others 


In the case that pesticide use is responsible for impacts on the performance of environmental functions, 

solutions have to be recommended in order to solve the problem and achieve ecologically sustainable use, 

e.g. through the following operations: 

d1) Reduce or eliminate pesticide use on a per ha basis 

d2) Promote use of integrated pest management 

d3) Promote use of alternative pest control 

d4) Adopt the appropriate timing of herbicide use in order to avoid collateral damages to biodiversity 

d5) Adopt the appropriate timing of insecticide use in order to avoid collateral damages to biodiversity 

d6) Reduce the toxicity of pesticide used 

d7) Others 

91

2) Recommendations to create new environmental practices 

In some cases, a fundamental shift of land use away from agriculture-oriented activities to environmentoriented 

activities, including cessation of agricultural activity, could be recommended. Here follow some 

possible cases presented as examples. Please note that these are not necessarily complete or exhaustive and 

that recommendations have to be designed for local agri-environmental situations. 

- Creation or re-establishment of natural habitats 

- Monitoring of biodiversity 

- Starting eco-tourism activities 

- Starting ecosystem management 

- Cessation of agricultural activity 

Following the above two points, researchers were asked: 

• To provide recommendations for each detected impact, on how to eliminate or lessen negative impacts 

and enhance positive ones, providing appropriate agricultural practices and detailed explanations; and 

• Where specific environmental practices are recommended, including the cessation of agricultural 

activity, to provide a detailed description and explanations. 

Box 39 – AEMBAC project: Recommendations for the Selaö study area, Sweden 

In the Selaö study area it is most urgent to increase the area of maintained semi-natural pastures. Enhancing the 

environmental qualities of pastures and field elements are certainly also important measures. Concerning the more 

specific measures, it is difficult to pick out any single most important proposal. Increasing the number of grazing heads 

is crucial, but depends itself on many practical measures to reduce costs and increase profitability. Concrete measures 

that appear to have a considerable potential that could relatively easily be realised in the study area include: 

- grazing preferentially on semi-natural permanent grasslands/pasture rather than arable leys; 

- clearing invading brushwood; 

- restoration of wetland pastures; and 

- forest edge development. 

Grazing preferentially on semi-natural permanent grasslands/pasture rather than arable leys 

Not just high-yielding milk-cows, but also heifers, beef cattle, sheep and horses are grazing leys on arable land instead 

of cultivated or semi-natural pastures. This is partly caused by subsidies (this is an example of a policy failure) to 

convert cultivated fields into leys, with the aim of reducing the surplus of cereal production. In areas like Selaön, which 

have a deficit of grazers or browsers, there is a big potential for transferring cattle from arable fields to help maintain 

the semi-natural pastures. The biological, cultural and social benefits to society would be considerable. 

Clearing of invading brushwood 

Bushes and trees that invade the pastures can have positive impacts on some species, but damage the biodiversity, 

cultural and social qualities of the grasslands if allowed to advance too far (see the wp3 report). Grazing and browsing 

animals normally inhibit the establishment and proliferation of such woody scrub species, especially under a high 

grazing intensity. Sheep and some cattle breeds are better than other grazers in this respect. This control by grazing still 

needs to be supplemented by manual clearing at varying intervals, depending on the site conditions. The interval 

between the clearings is determined by soil conditions, the presence of surrounding trees, etc. 

The clearing can be carried out with hand tools or tractor machinery. Any cutting entails additional work, like the 

removal of branches. This is a major measure if the agricultural landscape services are to be preserved in the long run. 

As reported from the wp3 surveys of the study area, there are several pastures covering many hectares where the 

clearing has been neglected. 

Expanding the acreage of permanent pastures 

Almost all land that was not tilled served as combined open forest, mowed grasslands or permanent pastures for long 

periods in Selaön’s past. The recommended land use optimal for this ecologically rich landscape is the maintainance (or 

re-conversion into) permanent pastures, with or without some trees depending the site conditions. However, only a very 

small fraction of these are maintained as cultivated or semi-natural pastures: 93 ha in total. A further 16 ha are maintained 

as grazed forest, according to GIS and survey data. 

To reconvert more land into permanent pastures would be a major measure for promoting biodiversity and the sociocultural 

landscape services demanded in the area. Expanding the acreage of permanent pastures is an overall measure, a 

product of a set of other measures. Land restoration, increasing the number of grazing animals in the area, or grazing 

92

every second year are among the more specific measures that can be applied to succeed with the expansion. 

Forest edge development 

The permanent edges between open, agricultural land and forest are important to the biodiversity, the landscape 

scenery, etc. (see wp3-report). Selaön is moderately rich in forest edges, but they vary drastically in quality. Many are 

poor in biodiversity and landscape respects. There is a big difference between a closed wall of spruces and a stratified 

zone of grass and herbs mixed with bushes, low, flowering trees and large deciduous or conifer trees. The grass 

vegetation along the forest edges are remnants of mowed or grazed land in the past. 

Developing the forest edges for the sake of biodiversity and landscape may have an initial restoration phase and 

continuing maintenance phases. It involves selective thinning bushes and trees, and in extra ambitious cases also 

planting trees. The edge could be cleared for tracks where rambling is requested. There is little motivation for this in 

Selaön. Where feasible, the fences could be moved 10, 20 or 30 m into the forest from the field or grassland boundary 

to make grazing of the edge zone possible and preserve their openness. 

Once recommendations on how to change agricultural practices so as to lessen the negative impacts 

identified and enhancing positive ones were analysed, an agronomic feasibility analysis of the most 

important constraints and opportunities for their implementation had to be carried out (e.g. is there the 

agronomic knowledge and capacity to change agricultural practices according to the recommendations? How 

feasible is it for farmers to adopt the recommended agricultural practice? What are the foreseeable 

constraints and opportunities for their adoption from an agronomic perspective?). 

Please note that this part constituted an important basis for building up local agri-environmental programmes 

in Step 6, together with the socio-economic constraints and opportunities that have been analysed in the 

following Step 5. 

3.4.3.1 Feasibility analysis of the most important constraints and opportunities for implementation of 

recommendations 

In this section an agronomic analysis was carried out on the feasibility of the proposed recommendations on 

how to lessen the negative impacts identified and enhance positive ones. Researchers were asked to analyse 

the feasibility of the recommendations proposed in the context of the local agricultural system, pointing out 

which were more appropriate ones considering current agricultural practices and socio-economic 

characteristics and driving forces (studied in Step 3). 

Examples(not exhaustive) on the information to be analysed: 

• Agronomic knowledge of the practices recommended 

• Availability of the necessary know-how and capability of implementation 

• Effects on production yields, mechanisation and labour 

• Required adjustment of current agricultural practices 

Box 40 – AEMBAC project: feasibility analysis of recommendations proposed for Landscape related 

environmental functions, Chianti study area, Italy 

Feasibility analysis (area level) 

Farmers are not interested in permanently reducing their UAA (Utilised Agricultural Area) or converting short-term coppice to high 

forest; clear evidence of this is provided by the scarce interest in subsidised afforestation measures (Reg. 2080/92). The forestry 

measures of Rural Development Plan (Reg. EC 1257/99) even were less successful and almost no-one asked for contributions in the 

pilot areas. 

From the farmers’ point of view, this behaviour is perfectly understandable, because those measures produce their definitive effects 

in terms of landscape and income too many years after they have subscribed them, usually after the death of the farmer. 

In other countries (e.g. UK, Norway) experimental farms work effectively in public-owned land following special conservation 

projects. A small percent of UAA managed in this way in selected high priority areas could produce similar results as a higher 

percent of private land managed according to schemes accepted by private owners, randomly scattered in the territory. 

A command and control system could perhaps work in selected areas, but the establishment of protected areas is (currently, at least) 

not a priority for local authorities. In this case, funding should be given only to farms submitting accurate projects of conservation of 

cultural or natural heritage, i.e. aiming to reach Tier +2. Of course, only farms not far from tier +2 will be interested. In this way, a 

process of self-selection of farmers in terms of location and landscape quality is expected, and protection of high priority areas could 

become a spontaneous phenomenon. 

93

Nevertheless, some projects appear reasonably feasible, such as diversifying the forest management system, because the resulting 

improved woodland would be self-regenerating and would not need more maintenance work compared to current management 

methods. Experimental farms with the task of conserving cultural landscape and open spaces are terribly expensive, because they 

need continuous attention to fight against both the historic-economic and the natural trends. It is as expensive as restoring urban 

cultural heritage, and this is reasonably feasible only if and where new social functions develop, such as eco-tourism. 

Some farmers are already voluntarily involved in restoration programs of archaic features and public funds have already been 

given for this purpose. 

Feasibility analysis of the implementation of changes in agricultural practices (agro-ecosystem level) 

We must remember that a distinction between micro (farm) and macro (socio-economic) level will be taken into account, whenever 

possible, when assessing the actual feasibility of the proposed changes in current agricultural practices. 

Avoiding agricultural land use in relevant ecotones, such as riparian strip and shrub strips along existing woodland and property 

boundaries, will greatly help to sustain habitats where most wild species live and grow. This change will be difficult to achieve 

because it will require influencing farmers’ behaviour, but it is also true that operating in such patches is often difficult, and that setaside 

rules already impose restrictions on the amount of cultivable land within the farm. 

Moreover, in strategic water catchment areas, this kind of measure is already under careful scrutiny by the competent Water 

Authorities, so its implementation might become mandatory, even without economic compensation. 

Introducing updated and more sensitive guidelines for reafforestation patterns will benefit a relevant portion of landowners who do 

not intend to develop intensive farming practices, and should prevent the creation of forest “monocultures”, often introduced via the 

implementation of EEC regulation 2080/92, which in Tuscany basically favoured three species (poplar, chestnut and walnut). The 

underlying principle should be to join wood production with other relevant land uses (eg. honey production, light and extensive 

recreation uses, mushroom cultivation, etc), aiming at multipurpose reafforestation patterns that can be fairly accepted by farmers. 

The respect of traditional management structures (features such as terraces, earthworks, stonewalls, etc.) remaining in the 

countryside would represent a key change in current agricultural systems. The main problem is that, contrary to most other state 

indicators, this one has a high level of irreversibility. In addition, most traditional terraces have been destroyed in order to enlarge 

field sizes. Although it is true that farmers could well rebuild those structures, a series of problems affect the feasibility of such 

operations: 

First, walls were usually destroyed to plant new vineyards or olive plantations that are supposed to stand there for at least 30 years. 

Secondly, there is a serious shortage of craftsmen able to properly rebuild such structures (although relevant technical documentation 

is available for the Province of Florence). Thirdly, we may not possess the relevant documentation to locate the walls where they 

were previously standing. 

A potential solution might be to favour their conservation in farms offering quality (e.g. environmentally friendly) accommodation, 

to further sustain income diversification. 

Diversification of existing farm production lines implies searching for niche-markets to be exploited at the prevailing advantage of 

small and medium size farmers. This process should be based on local species/varieties and on the recovery of traditional land 

arrangements and processing techniques suitable for such varieties. The feasibility degree appears fairly good, given the special 

momentum gained by quality food all over the world. 

Proper maintenance of traditional drainage structures carries with it respect for traditional land management structures and manmade 

works, together with an increased awareness of soil/water relationships that is fundamental for conserving soil resources in the 

long term. The feasibility is average, mainly hampered in small farms by the time/money available, but several solutions can be 

worked out at reasonable costs, given that professional advice will be provided to farmers. This issue must be dealt with by strongly 

linking the respect of traditional land management structures (including stonewalls) with soil conservation and appropriate 

drainage (e.g. ditch maintainance). These all tend to be affected by the maximisation of field size. 

The voluntary introduction of new, higher quality environmentally friendly standards for farm-tourism is a process already 

experienced in some parts of Europe and the world (partly related to eco-tourism development). Considering the enormous success of 

this sector in Tuscany (nearly 2700 farms), some entrepreneurs are beginning to realise that it is vital to distinguish themselves from 

the crowd, and are willing to move further in such a positive direction. 

The introduction of restraints to the maximum field size regarding new olive and vineyards plantations (and every other arboriculture 

use) has the advantage of impacting positively on various landscape indicators. Its feasibility base lies in the principle that the Chianti 

area (as many other famous landscapes) sells its image together with its produce. Consequently, most farmers should accept the 

principle that to compensate the added value of a beautiful and well-managed countryside some restrictions are needed on farms 

seeking to utilise economies of scale. We chose the case of plantations because it is nowadays the most important cause for concern 

affecting landscape changes (e.g. land levelling), but in the future the same reasoning might apply to every farm field. 

Another issue concerning this suggested change is the possibility of enforcing a mandatory requirement regarding specialised rowcrops, 

that should have at least a 30% angle to maximum slope gradient, to prevent soil erosion and harmful water run-off. 

94

3.4.4 Analysis of relations between degrees of sustainability and different hypothetical intensities of 

pressures of local agricultural systems. 

Following on from the analysis above, once each relevant pressure had been linked to the corresponding tier, 

and recommendations were proposed about what agricultural practices should be adopted in order to 

eliminate or lessen negative impacts and enhance positive ones, it was important to envisage which different 

intensities of the same pressure would have corresponded to impacts ranking different tiers in the system 

proposed in section 3.4.2.1 above. The definition of relationships between degrees of sustainability and 

different intensities of pressures using tiers, was the basis for the economic calculation of undertaking cost 

and opportunity costs to be carried out in Step 5 and the definition of agro-environmental policy targets in 

Step 6. 

So for instance, if the actual pressure “maintenance of hedgerows or semi-natural habitats” had been ranked 

as Tier –2 (i.e. very bad maintenance) through the analysis of the exerted impacts, then also what 

hypothetical intensities of the same pressure “maintenance of hedgerows or semi-natural habitats” would 

have ranked Tier –1, Tier +1 and Tier +2 had to be envisaged, as well as the value of the pressure ranking 

Tier 0 = respecting of EMR = no gap or only low impacts. 

It is important to point out that the above correlation was intended only as indicative, given the presently 

limited scientific knowledge and the difficulty of assessing the effects of a change of a pressure exerting on 

more than one impact simultaneously. In fact, pointing out hypothetical correlations on dose-effects 

relationships constitutes the first step of assessing their scientific validity, to be tested by empirical field 

research. 

Following the example in fig.18 in section 3.4.2.1 and possible recommendations studied in section 3.4.3, 

researchers envisaged, by looking at the impacts exerted, what different intensity of the pressure would have 

ranked in different tiers, as in the following example: 

Actual situation: Maintenance of hedgerows and/or semi-natural habitats exerts 4 negative significant 

impacts and 2 high negative impacts on state indicators relevant to plant and animal species and ecosystems 

because there are very sporadic field margins with hedgerows and no semi-natural system is maintained. 

This pressure is ecologically very unsustainable. It therefore ranks: Tier –2 

Envisaged correlations between different tiers and intensity of the pressure “maintenance of hedgerows 

or semi-natural habitats” at the study area level: 

Tier +2 = Presence of only high positive impacts (red) = e.g. 20% of existing UAA reconverted to (semi- 

) natural habitat. This is expected to have very positive effects on plants, animals and ecosystems. 

Tier +1 = Presence of only significant positive impact (yellow) = e.g. 5% of existing UAA reconverted 

to (semi-)natural habitat. This is expected to have positive effects on plants, animals and ecosystems. 

Tier 0 = respect of EMR = no impacts or only low positive/negative impacts exerted by agricultural 

practices = e.g. field margins with hedgerows 3 meters wide for at least 30 % of the total length of field 

margins in the area. This is expected to have sustainable impacts on plants, animals and ecosystems. 

Tier -1 = Presence of significant negative impact exerted by agricultural pressures (yellow) = e.g. field 

margins with hedgerows 3 meters wide for at least 10 % of the total length of field margins in the area. This 

is expected to lessen negative impacts on plants, animals and ecosystems. 

Tier –2 = Presence of high negative impact (red) = e.g. very sporadic field margins with hedgerows = 

actual situation. 

95

Box 41 - AEMBAC project: Ranking different intensities of pressures for Kihelkonna study area 

Estonia 

Two environmental functions related to biodiversity and landscape conservation, were analysed in 2 study areas - 

Palamuse and Kihelkonna. The analysis of qualitative and quantitative relative importance of agricultural impacts in 

causing the gap measured between EMR and the actual value of state indicators was carried out. The most relevant 

agricultural pressures in both communities were the abandonment of agricultural land, livestock density, crop rotation, 

land use intensification, nutrient management and land improvement. Abandonment of traditional methods and 

changing to large-scale production has significantly decreased the area of semi-natural habitats during the last decades, 

which causes the decrease in biodiversity (as abandonment of arable management leads to the replacement of diverse 

wildlife with more common and widespread species) and aesthetic value of the landscape, distribution of weed seeds, 

fire risk, overgrowth of bushes over large areas, etc. 

The sustainability of local agricultural pressures causing the impacts detected was identified using a qualitative ranking 

system. For each relevant pressure the recommendations for enhancing positive and minimising negative impact were 

given and the analysis of relations between degrees of sustainability and intensity of pressures of local agricultural 

systems were determined. For instance the recommendations for the land abandonment (Tier –1) were as follows: 

- ploughing, sowing, establishing drainage systems, using pesticides and fertilisers and the artificial changing of species 

composition is prohibited; 

- wooded meadows must be mowed from 1 July at least once a year, the hay must be collected and removed, the share 

of the land covered by the crowns of bushes must be kept low (0.2–0.5), after mowing the grazing pressure has to be 

lower than 0.5 LU/ha; 

- the grazing pressure on alvars should be 0.2−1.0 LU/ha and on wooded pastures 0.3−1.0 LU/ha, the share of the land 

covered by crowns of bushes must be kept respectively at least 0.2 and at 0–0.4 respectively; and 

the grazing pressure on coastal meadows should be 0.4−1.3 LU/ha, at least half of the grazed area has to be short as a 

sward as a result of grazing (Appendix to the State Herald, 2002, 67, 1061). 

The analysis was carried out on the relations between degrees of sustainability of different envisaged intensities of the 

pressures identified as exerting the actual impacts, for each relevant pressure. An example of the correlation between 

different tiers and abandonment in Kihelkonna pilot area was as follows: 

Tier –1 = the area of managed semi-natural habitats is 345 hectares (actual situation) 

Tier 0 = the area of managed semi-natural habitats is 1,200 hectares 

Tier +1 = the area of managed semi-natural habitats is 1,676 hectares (meaning all semi-natural habitats with medium 

or high value are managed) 

Tier +2 = the area of managed semi-natural habitats is more than 1,676 hectares. 

3.4.5 Identification of the multifunctional character of the local agricultural systems in reference to the 

performance of more than one environmental function 

In the context of AEMBAC, the term “multifunctional” was used to indicate the performance of more than 

one environmental function. 

As seen in Step 2, each environmental function requires that certain levels (EMR) of critical environmental 

aspects/qualities (abiotic, biotic, and aesthetic) of natural resources, measured by state indicators, are 

satisfied. To address more than one environmental function to be performed by the agro-ecosystem, a first 

analysis was done to check what pressures the local agricultural system is exerting on the critical 

environmental aspects (abiotic, biotic, and aesthetic) needed to perform more than one function. 

This latter aspect is fundamental in assessing the sustainability of the local agricultural system in relation to 

multifunctionality (i.e. performance of more than one environmental function). 

In fact the agricultural use of the natural environment can be defined as competing or complementary in 

utilising those critical environmental resources (biotic, abiotic, aesthetic, etc.) which also allow the 

performance of environmental functions. In this sense the production of food could be regarded as an 

96

environmental function. 

In AEMBAC, competing agricultural practices are those agricultural pressures exerting negative impacts 

that are excluding or reducing the possibilities for environmental function(s) (other than food production) to 

occur. A classic example of this kind of relationship is that of intensive agricultural production that is 

impairing the possibility of habitat or recreation function taking place. 

In the case of agricultural practices competing with the performance of more than one environmental 

function, some values of “critical state indicators” can be affected simultaneously for both functions by 

agricultural pressures. From the analysis above on the causal relationships between impacts and pressures, it 

can result that reducing a certain agricultural pressure can simultaneously have beneficial effects for the 

performance of more than one environmental function, so adding value (because of expected production of 

more environmental goods and services) to the development of agri-environmental measures. 

The term complementary agricultural practices, in AEMBAC, addresses those agricultural pressures 

exerting in positive or neutral impacts for the performance of environmental functions. Also this kind of 

agricultural use can be analysed in relation to having beneficial effects on the performance of more than one 

environmental function (as it should result from the analysis of state indicators). If this is the case there will 

be an added value (resulting in increasing the sustainability of the multifunctional character of the local 

agricultural systems) in designing and implementing incentives through agri-environmental measures in 

order to enhance the adoption by farmers of practices beneficial to multifunctionality. 

Finally it is worth noting that some agricultural practices can conflict with some environmental functions 

while complementing others. An example can again be the case of an agricultural landscape which has 

shaped the natural one with beneficial effects for human recreation but negative impacts for wild species. 

The figure below shows an example of possible pressures of the local agricultural system that impact on 

more than one function. 

Fig.20 Example of pressures exerting 

impacts on more than one environmental 

functions 

Environmental Functions 

Biodiversity related function 

Landscape related function 

Soil erosion control 

Water run-off control 

Agro-Ecosystem (AE) pressure indicators 

(data from questionnaire and bibliographic/field 

research) 



a2) Adjusting application rates to crop needs 

a3) Timing of nutrient applications 

a4) Crop rotations 

97 

a5) Placement of fertilizers 




b1) Land use 

b2) soil cover, mowing, hay cutting, grazing 

(WP4) 4. Hypothetical Impacts 

b3) Land management 


no impact significative 

low high 




c3) Drainage/diversion/extraction processes 



d2) Use of integrated pest management 

d3) Use of alternative pest control methods 

d4) Timing of herbicide use 

d5) Timing of insecticide use 


In the matrix above, the pressures from land use, soil cover, mowing, hay cutting, and land management 

impact on more than one function (related to biodiversity and landscape, and soil erosion and water run-off 

control), while pressures such as livestock density and pesticide use impact on one function only (soil 

erosion control and biodiversity-related function respectively). 

Box 42 – AEMBAC project: Analysis of agricultural pressures impacting simultaneously on more than 

on environmental functon in the Chianti case study, Italy 

The agricultural system in the Chianti study area simultaneous impacts the performance of more than one function. 

From the analysis carried out the pressures of, land use conversion, logging and coppice cutting, crop diversity, habitat 

fragmentation and presence of land settlings, appear to be particularly important. In fact: 

Land use conversion impacts on: 

1. The refugium function (biodiversity): because patterns of land use in the last period of fifty years showed a swift 

by share farming system to specialised agriculture which has carried to a conversion of wide areas abandoned after 

the share farming decay. The reconversion is prevalent on low hilly areas, while the high hilly areas and mountains 

are not affected by this process. The impact is negative on the refugium function, because the specialisation towards 

monocultures causes a decreasing of species number (animal and plant); 

2. The Landscape related functions: because patterns of land use in the last period of fifty years showed a swift by 

share farming system to a specialised agriculture which has lead to a re-conversion to agriculture of wide areas 

abandoned after the share farming decay. It has negative impacts on landscape related function, particularly on 

diversity of the scenery, because the increasing of cultivated areas often erodes woodland of recent formation 

(ecotone) causing heavy repercussions on the landscape. Moreover the recent trend of creating wide and 

uninterrupted vine or olive plantations break the landscape harmony because the characteristic Chianti landscape is 

that of alternation between olive-yards, vine-yards and woods. 

3. The Soil erosion and water run-off control: because the increasing of cultivated lands to the detriment of natural/ 

semi-natural areas can favour the run-off speed of rain water even more if it is not associated with good agricultural 

practice and correct land management. The main risks are an increasing of potential erosion and a decreasing of 

slope stability (landslide). 

Logging and coppice cutting impacts on: 

1. The refugium function (biodiversity): because the wood management practised can affect biodiversity of birds, 

reducing the number of species linked to mature woods. 

2. The Landscape related functions: because two centuries of repeated coppice cutting simplified the previous forest 

mosaic made with different elements, such as oak high forest. 

3. The Soil erosion and water run-off control: because forestry activities are carried out by non-specialised workers 

with consequences for erosion control. 

Habitat fragmentation impacts on: 

1. The refugium function (biodiversity): because increasing farm dimension causes different pressures according to 

farm size and management (family farm/ capitalistic farm). It has a negative impact on Refugium function, because 

the farm size increasing damages shrub and wood areas, causing a negative pressure on ecotone. 

2. The Landscape related functions: because the increasing farm size leads to the destruction of ecotone. 

3. The Soil erosion and water run-off control: because the elimination of edges and shrubs in order to enlarge vine 

yards extension has impact on the soil erosion control. 

Presence of land settings impacts mainly on: 

1. The Soil erosion and water run-off control: because the maintenance of new and old land settings is substantially 

absent. In fact we do not survey landscape management in the farms. In the past landscape management concerning 

stone walls, terraces and agrarian hydraulic works was part of the local farmers traditional culture. Nowadays the 

maintenance of stone walls is not considered by commercial farms because the returning benefits are in the long 

term. Obviously the risk of soil erosion is increasing. The bad condition state of maintenance of land settling favors 

the possibility of indiscriminate increasing the speed of run-off, both on surface and depth. 

Crop Diversity impacts on: 

1. The refugium function (biodiversity): because it is scarcely present due to increasing olive and vine specialisation 

in some particular species. It has a negative impact on Refugium function, because the presence of scarce cultural 

diversification offers rare occasions to refugium of different animal species. Besides, the cultural specialisation leads 

to a reduction of local varieties in advantage of standardised varieties fixed by disciplinary; The risk is prevalent in 

plant diversity, because new plantations (vine in particular) are composed by standard species according to DOCG 

Chianti Disciplinary, to the detriment of local variety species which are progressively disappearing. 

2. The Landscape related functions: because the increasing size of homogeneous cultivation (i.e. vineyards) of 

landscape units (substantially uniform in their exasperate likeness) can make the complex vision for observer worse. 

Nevertheless the landscape remains agreeable in those areas which are not transformed by new specialised 

98

plantations. 

3. The Soil erosion and water run-off control: the specialisation of vineyard cultivation has negative impacts on soil 

conservation because the cultural specialisation is sometimes accomplished by land settings wich are not compatible 

to land morphology. In fact new plantations are usually established mainly according to exposure and soil 

composition, rather than the slope of the hillside. This fact can favour the potential risk of soil erosion phenomena 

especially if plantations are arranged by up-down ditching: however we retain that also in new up-down ditching 

plantations the soil conservation is strictly linked to agriculture practices 

Shrub cutting impacts on: 

1. The refugium function (biodiversity): Because in shrubland this destroys an exclusive habitat for some species of 

birds and reptiles 

2. The Landscape related functions: Because avoiding their overgrowth, shrub cutting in semi-natural 

shrub/grassland keeps the succession in states that are appreciated as landscape features for their peculiar season 

compliance and openness. 

Fig. 21 – Multifunctionality: evaluation 

of performance by Natural Ecosystem 

and Agro-Ecosystem at local level 

(Upper basin of Greve River) 

Pressure indicators 

99 

Land use 


Soil cover 

Logging and coppice cutting 

Shrub cutting 

Crop diversity 

Uncultivated field margins 

Hedge conservation 

Habitat fragmentation 

Presence of land settings 


Biodiversity Refugium function - - - - - - - * 

Landscape related functions - - + - - - 

Soil erosion control - - - - - - - - 

Summarising the above, while in Step 2 the relevant state indicators have been analysed for each 

environmental function, here state indicators were analysed simultaneously for more than one function, 

pointing out those which were indicating crucial aspects commonly affected by the same pressure(s). 

In fact it may also be the case that some of the key environmental aspects which are crucial for the 

performance of one function would also be crucial for the performance of another. This can be the case for 

instance of the indicator extent of ecosystems for the performance of refugium function and recreative 

function even if it may also be the case that for the value of respective EMR to be matched in order to allow 

for performance there would be differences (see Box 43 below). 

Box 43 - Common state indicators for multifunctional performances and relationships with EMR 

Having first identified the critical environmental aspects common to the performance of more than one environmental 

function, the next step is to analyse what are the values of EMR for the state indicators (describing the common critical 

environmental aspects) that are allowing the simultaneous performance of the environmental functions selected. This 

will come out just confronting results on EMR values for the common state indicators used to describe simultaneously 

different environmental functions. 

Two cases can result from this analysis: 

1. The same EMR value of a state indicator for performance of one environmental function that also satisfies the 

condition to allow the performance of another one; or 

2. A different EMR value of a state indicator to allow the performance of different environmental functions. In this 

case two further situations can be observed: 

2a. Stricter values of the EMR to perform one function than that needed to perform others: this can be the case for 

instance of the refugium function which may need a particular habitat to cover a greater area than that needed for the 

Rain fall water management 

Pesticide use

ecreation function (i.e. a stricter value of the EMR for the state indicator extension of ecosystem describing refugium 

function). 

2b. Conflicting values of the EMR for the same state indicator to perform different environmental functions: this can be 

the case, for instance, when for the refugium function it can be good to have a large extension of the same ecosystem to 

conserve species living there, while from an aesthetic point of view the diversity of the scenery is advocated, so in this 

case the EMR value of the indicator Patchiness is conflicting between refugium (often but not always low patchiness) 

and aesthetic function (often but not always high patchiness). 

It is worth noting that the values of some indicators (other than those in common) can have an influence on 

the values of other indicators describing a different environmental function. This should at least have been 

highlighted even if it couldn’t be analysed in case studies. 

3.5 Step 5 – Economic valuation of negative/positive impacts and identification 

of externalities 

3.5.1 Translation of results of environmental functions analysis into economic information. 

The information on positive/negative impacts resulting from the local agricultural system analysed in 

previous sections, has to be translated into economic information in order to build up agri-environment 

programmes. 

Adopting the perspective of looking at ecosystems functioning through the provision of environmental goods 

and services now offers the opportunity to concentrate on what has value for humankind. This approach which 

has already the character of being utilitarian and anthropocentric, facilitates the integration between natural and 

social sciences and also the understanding of the importance of environmental goods and services by non-natural 

scientists. 

To start the economic analysis, two considerations were made. The first concerned what was the objective of the 

economic valuation, the second how the economic valuation had to be carried out. 

In AEMBAC the objective of economic valuation was to indicate in economic terms what is the value of the 

increase/impairment, resulting from positive/negative impacts exerted by the local agricultural system, on the 

provision of environmental goods and services by environmental functions performance. 

More precisely, looking at each agricultural pressure ranked in Step 4, sections 3.4.2 and 3.4.3, the economic 

valuation had to be carried out to assess the benefits and costs to achieve upwards tiers associated to hypothetical 

impacts starting from the actual situation (i.e. real impacts). 

Once an indicative economic value had been assessed, it was then be possible to work out, for instance, what 

would be the costs to have farmers compensated for supplying environmental goods and services. 

Regarding how this economic valuation could be carried out, two possibilities were envisaged: 

1) The first approach was to calculate the “Total (partial) economic value 15 ” of agricultural positive/negative 

impacts on the environmental goods and services provided by the environmental functions, using the most 

suitable economic valuation techniques (see box 44 below) for the case study. This comprehensive approach is 

usually undertaken when there is a need to demonstrate the economic convenience of one use of natural 

resources compared to another through a cost-benefit analysis. This kind of economic evaluation is done for 

instance, when the economic value of environmental benefits of conserving a natural ecosystem have to be 

compared with the economic value of benefits of an alternative development plan. In this case the valuation of 

15 Total Economic Value is usually given by the aggregation of the following values: Use Values (Direct, Indirect and 

Option values) and Non-Use Values (Bequest and Existence values). (Pearce and Moran, 1994) 

100

environmental goods and services can be done, for instance, by measuring the willingness to pay to conserve the 

natural ecosystem and then this value is measured against the opportunity costs of giving up the benefits of the 

alternative plan, once the undertaking costs and savings have been accounted for, for both alternatives. 

This kind of economic valuation could be adopted in AEMBAC by calculating both the benefits and costs of 

the positive/negative impacts associated with the agricultural activities in terms of supply of environmental 

goods and services. This involves understanding in economic terms, what are the benefits of achieving EMR 

(i.e. by definition the minimum environmental requirements to allow performance of the environmental 

function), or what are the benefits of having a situation above EMR and comparing these benefits with their 

corresponding undertaking and opportunity costs. 

Box 44: Examples of environmental economic valuation techniques 

Are the environmental function performances protecting assets? The following valuation techniques can be used to assess 

the economic value of positive/negative impacts on the environmental goods and services provided by the environmental 

functions: 

• Cost of replacement 

• Rehabilitation costs 

• Value of lost production 

• Cost of relocation 

Is the value of the environmental functions performance reflected in the land value or some other composite price? The 

following valuation techniques can be used to assess the economic value of positive/negative impacts on the environmental 

goods and services provided by the environmental functions: 

• Hedonic pricing 

Do the environmental function performances support production or tourism? The following valuation techniques can be 

used to assess the economic value of positive/negative impacts on the environmental goods and services provided by the 

environmental functions: 

• Production function approach 

• Net factor income 

• Travel cost method 

Are there market prices for similar environmental function performances? The following valuation techniques can be used 

to assess the economic value of positive/negative impacts on the environmental goods and services provided by the 

environmental functions: 

• Substitute price 

• Indirect substitute price 

Is the environmental function performance not subjected to market transactions and are there also no close substitutes? The 

following valuation techniques can be used to assess the economic value of positive/negative impacts on the environmental 

goods and services provided by the environmental functions: 

• Contingent valuation 

(adapted from Rosemary F. James wetland valuation, Asian wetland bureau – Indonesia, 1991 

Moreover, if it could also be possible to estimate the marginal benefit (and the marginal cost) of having a 

further unit of the environmental good or service, this approach could have permitted to assess what would 

be the quantity of the environmental good or service that maximises the social utility. 

The intention of AEMBAC was not to discourage those who wish to try to look for such values, nor to start a 

theoretical debate on the validity of monetary evaluation techniques. However it must be pointed out that the 

present knowledge on ecological functioning does not allow to formulate such estimates on a solid scientific 

basis, not to mention the difficulties of considering the ethical aspects of associating an economic value, for 

instance, to the existence of living beings. 

2) A second, more pragmatic approach (albeit partial and less elegant from a theoretic point of view) adopted 

in AEMBAC to carry out the economic analysis of the positive/negative impacts resulting from agricultural 

pressures, was that of calculating only the undertakings and opportunity costs and relative savings of 

lessening impacts and of providing the environmental good and service (i.e. achieving upwards tiers starting 

from the actual situation). In fact the assessment of costs could be done in both the cases that the objective 

was to calculate the cost of filling in the negative gap between EMR and the actual value (negative impact), 

101

or to calculate the costs of filling in the positive gap between the actual value and EMR (positive impact). 

This second possibility was therefore to adopt “only” a partial economic valuation of what has to be done (or not 

to be done!) by farmers to allow for the supply of environmental goods and services, through the “cost 

assessment method”. In the case of AEMBAC, the willingness of European citizens to conserve biodiversity 

and landscape expressed through, for instance, the ratification of the Convention on Biodiversity by the EU, 

could be considered as a proxy for the demand of conserving biodiversity and landscape. Thus there would be no 

need to demonstrate the economic convenience of conserving biodiversity, but instead what the undertaking and 

opportunity costs would be of doing so, and who needs to be compensated in recognition of their provision of 

environmental goods and services. 

Following the two approaches to the economic valuation described above, researchers were asked to carry 

out two sub-sequential steps: 

Step one: Analysis of the supply of environmental goods and services by agricultural practices had to start 

from looking at the positive/negative (real and hypothetical) environmental impacts exerted by agricultural 

pressures on the performance of environmental functions. These impacts were ranked by qualitative tiers in 

section 3.4.4. The outcome of this step was a list of the ranked agricultural impacts (positive and/or negative 

that had to be evaluated in economic terms) as in the example in the following table 43: 

Tab. 43 - Tiers, impacts, recommendations and economic assessment 

Tiers Associated impacts Recommended necessary Option 1: Total/partial Option 2: 

agricultural practices 

Economic Value 

Costs Assessment 

Tier Presence of only high 10% of existing UAA reconverted to Assessment of environmental Assessment of 

+2 positive impacts (red) (semi-) natural habitat is expected to benefits and opportunity and opportunity and 

have very positive effects on plants, undertaking costs to achieve undertaking costs to 

animals and ecosystems 

the tier from actual situation achieve the tier from 

actual situation 

Tier Presence of only Field margins with hedgerows 3 Assessment of environmental Assessment of 

+1 significant positive meters wide for at least 50 % of the benefits and opportunity and opportunity and 

impact (yellow) total length of field margins in the undertaking costs to achieve undertaking costs to 

area, is expected to have sustainable the tier from actual situation achieve the tier from 

impacts on plants, animals and 

ecosystems 


Tier 0 respect of EMR = no Field margins with hedgerows 3 Assessment of environmental Assessment of 

impacts or only low meters wide for at least 30 % of the benefits and opportunity and opportunity and 

positive/negative total length of field margins in the undertaking costs to achieve undertaking costs to 

impacts exerted by area, is expected to have sustainable the tier from actual situation achieve the tier from 

agricultural practices impacts on plants, animals and 

ecosystems 


Tier Presence of significant Field margins with hedgerows of 3 Assessment of environmental Assessment of 

-1 negative impact exerted meter width for at least 10 % of the benefits and opportunity and opportunity and 

by agricultural pressures total length of field margins in the undertaking costs to achieve undertaking costs to 

(yellow) 

area, is expected to lessen negative the tier from actual situation achieve the tier from 

impacts on plants, animals and 

ecosystems 


Tier Presence of high very sporadic field margins with Assessment of environmental Assessment of 

–2 negative impact (red) hedgerows = actual situation costs and opportunity and opportunity and 

undertaking costs to do not undertaking costs of 

change actual situation not changing the actual 

situation 

Step two: this consisted of elaborating on the physical data, measuring the impacts of agricultural practices 

on the environment (derived from step 1), and translating environmental impacts into economic values 

(monetary) orders of magnitude. 

• In the case that for some objects to be evaluated there were economic valuation studies already existing, 

these had to be presented and described here (i.e. what had been valued, who was the valuing subject, 

year, etc). (see Box 45 below) 

102

Box 45 – Contingent Valuation Methods and Benefits transfers – AEMBAC project Switzerland, 

(for references in the box see the FiBl Report) 

For the Swiss study regions we choose the following mixed strategy in order to approach the valuation of the landscape. 

First, various European contingent valuation (CV) studies were analysed to get a rough idea of possible values for 

diverse environmental goods. The problem of value transfer was discussed and conclusions drawn for our special case. 

Tab. 44 - Results from different CV studies: 

Source Country Persons interviewed Topic in question Value collected 

a) 

Degenhardt, 

Hampicke et al., 

1998 

Kämmerer, 1994 

(cited in 

Geisendorf, 1998) 

Jung, 1994 (cited in 


DE Inhabitants of three rural 

areas 

Expenditures for definite 

measures to protect and 

develop grassland 

landscape 

DE Local population Agricultural use of fallow 

land 

DE Local population Aesthetics of agricultural 

landscapes 

Bullock et al., 1997 UK Inhabitants of Central 

Southern Uplands of 

Scotland 

Zimmer, 1994 DE Users of the landscape in 

the german districts 

“Emsland” and “Werra- 

Meißner-Kreis” 

Holm-Müller, 1991 

(cited in 


Cordes, 1994 (cited 

in Geisendorf, 

1998) 

Hampicke, 1991 

(cited in 


103 

14 – 33 

€/hh*year 

Oberes 

Fricktal 

€/ha b) 

Greifensee 

€/ha b) 

18 - 43 86 - 203 

25 €/hh*year 32 154 

29 €/hh*year 38 178 

Endangered species 52 €/hh*year 67 320 

Landscape change by 

grazing intensity 

DE Local population Preventing species going 

extinct 

DE Tourists Landscape conservation 

(inhabitants) 

German population Protection of endangered 

species 

60 €/hh*year 78 369 

Landscape 86 €/hh*year 111 529 

97 €/hh*year 126 596 

111 €/hh*year 144 682 

124 €/hh*year 161 762 

Drake, 1992 SE Swedish population Landscape 78 €/p*year 260 1309 

Correll et al., 1994 DE Rural and urban 

population of the German 

district “Lahn-Dill- 

Bergkreis” 

Roschewitz, 1998 CH Inhabitants of the region 

“Zürcher Weinland” 

Agricultural influenced 

landscape 

Value of cultural landscape 163 €/p*year or 

163 €/hh*year c) 

Jäggin, 1999 CH Day tourists Value of protection of 

endangered species 

Pruckner, 1994 AT Summer tourists (foreign 

and domestic) 

Landscape conservation 0,66 

€/visitor*day 

105 €/p*year 349 1762 

542 

or 211 c) 

2735 or 

1002 c) 

253 €/p*year 842 4246 

Not 

possible 

Not 

possible 

Notes: 

a) Exchange rates for the different currencies in which the values were originally collected date from the year the study 

was conducted. It is important to note that this extrapolation is just a rough calculation. Adaptations according to 

different levels of purchasing power in the different regions are not carried out. Also inflation rates are not taken into 

account so that the time factor is not considered.

) The values for Oberes Fricktal and Greifensee (column 6 and 7) are calculated as follows: the value from column 5 

(value collected) is multiplied by either the number of inhabitants or the number of households according to the 

aggregation level on which is was collected. It is then divided by the number of hectares of UAA in each region. 

It should be mentioned that other authors extrapolate their collected “willingness to pay” to the whole region by 

considering only the number of inhabitants older than 18 years (Roschewitz). This would, in our case, lead to figures 

about 25% less (corresponding to the share of under-aged inhabitants in both regions) for those figures which are given 

on a per person level (lines 11-14). 

Data used for calculations for “Oberes Fricktal”: 9008 inhabitants / 3505 households 

2707,5 ha UAA 

Data used for calculations for “Greifensee”: 125914 inhabitants / 46122 households 

7503,1 ha UAA 

c) For further calculation, Roscehwitz takes the collected values as per household figures. The “tax“ payment tool 

justifies this. In Switzerland it is mostly the household that is taxed, not the individual person. Consequently, giving a 

minimum level of “willingness to pay” of the population for conserving landscape she thus uses the lower figure for 

further calculations. (p = person) 

Conclusions for the Swiss situation 

The results of Roschewitz are rather high compared to other CV studies carried out in Europe (cf. Tab. 8.2.1). She 

explains these findings with two characteristics of the region: The high income level on the one hand, for nearly all 

Switzerland, including our study regions. On the other hand, the environmental good in question (cultural landscape) is 

rather scarce. Roschewitz further notes that her results are rather under- than overestimated and gives three reasons for 

this. First, the design of the question. As a payment tool she proposes a tax. This tool normally is a rather unattractive 

one and, thus, people questioned may be more conservative in their expressions of willingness to pay. She justifies her 

choice of this payment tool with its close relation to Swiss political reality. After public referendums this tool is often 

applied to realise a policy. Consequently, she interprets the values given as willingness of tax payment per household, 

not on per person level. Second, Roschewitzrecognised a high willingness to answer among the people questioned, 

which limits the danger of bias. Only 4% of them did not want to respond at all to the question of their “willingness to 

pay”. She estimates the credibility of the results as very high as no unrealistically high values were given. Third, the 

distribution of results is skewed and the median is lower than the mean value. Roschewitz uses the median value so that, 

again, the result is rather lower than higher. She concludes that due to her conservative assumptions her results show the 

minimum level of the value of cultural landscape of the region studied. 

• Then, if it was feasible to translate the environmental impacts attributable to agriculture into orders of 

magnitude of economic (monetary) values, using the most appropriate environmental economic 

valuation techniques (e.g. rehabilitation cost, hedonic pricing, travel costs, etc. see box 44 above) to 

assess the economic value (in orders of magnitude) of the benefits/costs of positive/negative impacts on 

environmental functions (e.g. habitat function, recreation function etc.), this would correspond to option 

1 in the table above; 

• If this was not possible the economic valuation could be carried out estimating “only” the undertaking 

and opportunity costs and relative savings of providing the environmental good or service (see box 46 

below) starting from the actual situation. This case would correspond to option 2 in the table above and 

has been the one adopted in the vast majority of case studies (see AEMBAC project National Final 

Reports). 

Box 46: Example of costs calculation 

In the option of calculating “only” the costs of supplying environmental goods and services, the following example was 

proposed: 

Suppose the result from the analysis carried out is that the absence of hedgerows at field margins is responsible for a 

high negative agricultural impact on the performance of the refugium function. Also from section 3.4.4 it is shown that 

the agro-environmental measure necessary to supply a suitable habitat for key species (i.e. to achieve tier +1) is planting 

3 meter wide hedgerows at field margins, for at least 50 % of the total length of field margins in the area, while to only 

reduce the negative impact to tier 0, it would be necessary to plant 3 meter wide hedgerows for at least 30% of the total 

104

length of field margins in the area. 

Then, in order to calculate the value in economic terms of the costs of achieving tier +1 or tier 0, the assessments of the 

undertakings and opportunity costs have to be carried out for both the targets tier +1 and tier 0. In terms of economic 

value these consist of reduced yield per ha, the cost of planting a variety of indigenous shrubs and managing hedgerows 

per meter. Undertaking savings such as reduced inputs used, have also to be accounted for and subtracted from the 

costs. 

The same procedures can also be applied in the case that the detected agricultural impact is positive (i.e. the situation is 

above the EMR), in order to assess the costs of the positive contribution of agriculture to the supply of environmental 

goods and services by agro-ecosystems. 

Here it has to be pointed out that the European Union is rightly stating that payments to farmers should be made only 

when there is a real provision of environmental goods and services taking as reference the respect of good farming 

practice. The Tiers ranking system identified in AEMBAC, while giving a baseline for provision of environmental 

goods and services (i.e. Tier 0 = respect of EMR) is also allowing a certain elasticity for assessing the level of good 

farming practices at different levels (e.g. Tier –1). This flexibility could be useful for instance when a traditional good 

farming practice believed to be ecologically sustainable, would not be so anymore, because of the climate change 

consequences. 

Box 47 – AEMBAC project: Cost assessment in the Chianti case study, Italy (for references in the box 

see UNIFI-DSE report) 

In order to evaluate the necessary costs for the application of the measure regarding hedgerow conservation in vineyards 

it is necessary to refer to three cost typologies: 

• Opportunity Cost (Value of lost production, Income foregone). To calculate the income foregone the total gross 

production of the single permanent crop (vine or olive) where the measure is applied has been used. The total gross 

production is an indicator, which refers to every product and which is based on the economic results obtained by 

the Farm Accounting Data Network (F.A.D.N.) on the 14 farms of the Chianti sample. The value of the gross 

production will be adjusted in our calculations considering the costs saved (see below). 

• Additional cost (Undertaking cost). These are the costs we connected to the environmental suggestions. Such costs 

are usually fixed during the period of the measure (5 or 10 years), but they can vary because of different operations 

as, for example, happens with hedgerows: cost of plantation for the first year, maintenance costs of hedgerows in 

the following years. 

• Cost saving. Production costs which are no longer necessary because the land use changed after a reduction of the 

UAA. 

Among the variable costs we will consider that of seasonal labour - € 1,453.32/ha (Franchini, 2002) together with the 

costs of pesticides and manures. The fixed costs amounting to a total value of € 2,326/ha, on the contrary, will not 

compose the cost saving as they are partially independent from UAA reductions. Data for the evaluation of costs linked 

to measures regard the three years average situation (1998, 1999, 2000), obtained by the Farm Accounting Data 

Network sample. 

Tab. 44 - VINES 

1998 1999 2000 

Average 

1998/2000 

Total Gross Production 

(€/ha) 

Grants and subsidies 

10681,36 9880,34 10038,89 10200,20 

(€/ha) 553,13 603,74 499,93 552,26 

Average fields size (ha) 15,22 15,22 15,22 15,22 

Specific costs (€/ha) 981,78 784,50 853,70 873,33 

Gross margin (€/ha) 9699,58 9095,84 9185,19 9326,87 

105 

Source: Elaboration of data from F.A.D.N. 2002 

Tab. 45 – OLIVES 

1997 1998 1999 Average 

Total production (€/ha) 1112.5 1493.1 1542.7 1383 

Grant and subside (€/ha) 565.0 631.6 636.3 611 

Average area (ha) 12.4 12.4 12.2 12 

Gross margin (€/ha) 978.7 1431.6 1488.4 1300 

Source: F.A.D.N. 2002 

Hedgerows Conservation cost assessment 

Definition: Hedgerows are linear boundaries with trees and/or bushes between fields, different from shrubs and needing 

artificial plantation and maintenance.

In Chianti, a desirable value for hedge density depends on which historical landscape is supposed to be worthy of 

protection. If we choose as a desirable model the archaic agriculture (still surviving in some places), hedgerows should 

be dense (as they were in the 15th century). If we choose as a model the landscape of the Hapsburg age, hedgerow 

density should be moderate and stone walls should be abundant. The present specialised agriculture keeps the previous 

medium value of hedgerow density and has a typical trend to maximise UAA but it also destroys stone walls. (Angiolini 

2003, personal comunication). The building up of hedgerows permits the division of properties and habitats for fauna. 

Fields can either be owned by a single owner or many. This recommendation is valid for all the land uses of Chianti. 

Starting from the total gross production of 10,200 €/ha in vineyards and of 1,398 €/ha in olives groves without 

hedgerows the income foregone on the basis of the length of the 3 meter wide hedgerows has been calculated. For 

planting hedgerows the additional cost is around 0.60 €/m 2 (PRS, Trento). For the hedgerows it was assumed that the 

cost per plant is 3€ and they were planted 2,5m from each other. The resulting value has been added to the additional 

costs of the first year. Starting from the second year it has been considered that the cost for the management of 

hedgerows is 0.40€/m2 (PRS, Trento). In olive groves the cost saving reaches very low levels due to the large use of 

family labour instead of temporary labour. 

The Regional Price List of Tuscany 1996 (including the increase of 10% of 2001) reconsiders the price of plantation of 

hedgerows with bushes and trees in a double line, whith local plants of 2-3 years old and 80 cm of height (Ref. 311) 

fixing it at around 5€ per meter. (Regional analytical and synthetic price list for the infrastructure improvement in 

agriculture and forestry. Decree of the Regional Council 29/10/1996, n.954) 

The following tables suppose the introduction of hedgerows in vineyards (Tab. 48) and olive groves (Tab. 49). The 

costs concern plantation for the first year and maintenance for the second year. 

Tab. 46 - Hedgerows conservation in vineyards 

Level Farm Level 

Vineyards 

Length of 

hedgerows 

Additional cost 

first years 

106 

Additional 

cost each 

following year 

Income 

foregone 

Cost saving 

Total cost first 

year 

Total cost 

following 

years 

Suggestion Creating or maintaining hedgerows meters € euro (€/ha) euro/ha (€/ha) (€/ha) 

Tier +2 

90 - 110 m/ha length of hedgerows 

100 

with 30% of trees 

197 108 306 70 433 344 

Tier +1 


80 


154 84 245 56 343 273 

Tier 0 60 - 80 m/ha length of hedgerows 60 103 60 184 42 245 202 

Tier -1 

Tier –2 


30 


38 24 92 21 109 95 

Hedgerows not forming a 

continuous feature (actual situation) 10 

Tab. 47 - Hedgerows conservation in olive groves 

Level Farm Level 

Length of 

hedgerows 

Additional cost 

first years 

Additional 

cost each 

following year 

Suggestion 

Olive 

Planting 

hedgerows 

or maintaining 

meters (€/ha) (€/ha) (€/ha) (€/ha) 

Tier +2 



100 197 108 39 13 223 134 

Tier +1 


80 


154 84 32 11 175 105 

Tier 0 60 - 80 m/ha length of hedgerows 60 103 60 24 8 119 76 

Tier -1 


30 


38 24 12 4 46 32 

Hedgerows not forming 

Tier –2 continuous 

situation) 

features (actual 10 

Income 

foregone 

Cost saving 

Total cost first 

year 

Total cost 

following years

3.5.2 Identification of externalities 

Externalities are defined by Pearce and Turner (1990) as: “An external cost [benefit] exists when the 

following two conditions prevail: 1) an activity by one agent causes a loss [gain] of welfare to another agent; 

2) the loss [gain] of welfare is uncompensated [unpaid]”. 

Externalities are often caused because of market failures. As far as markets are concerned, some important 

factors allowing them to operate efficiently can be distinguished: 

• Property rights; i.e. the ownership and the right to alienate or to use what is exchanged in markets must be 

clearly defined; 

• Business and contract law, able to deal with all the possible situations coming out of transactions, must be 

established; 

• Quality and safety standards as terms of reference for markets functioning are often necessary; 

• Perfect competition (i.e. large numbers of buyers and sellers) to avoid problems of monopoly; and 

• Adequate information, required in order to overcome problems such as asymmetric information, high 

transaction costs, risks and uncertainties. 

If one or more of the above factors are absent, the presence of externalities would be likely. The topics 

studied in the AEMBAC project are affected by the lack of some of these factors. 

In fact, biodiversity and landscape conservation are characterised by incomplete scientific knowledge on 

some ecological aspects. This corresponds to a lack of the factors regarding adequate information and 

quality and safety standards listed above, as two of the causes of not allowing markets to function properly. 

Incomplete information on positive/negative impacts exerted by agricultural pressures on the environment is 

often the reason why losses or gains of welfare are not accounted for. 

The goods and services related to environmental functions performance studied in AEMBAC have the 

character of public goods. The term public goods refers to those goods which have the characteristics of nonexclusivity 

and non-rivalry in consumption. Many environmental goods and services belong to this category. 

The supply of public goods, such as landscape management or conservation of biodiversity by farmers would 

not receive any compensation through free markets given the impossibility of excluding non-buyers from 

benefiting from them. In economic jargon this fact is referred to as “free-rider problem” (e.g. the landscape 

produced by farmers are enjoyed by passing travellers). In other words, benefits and costs resulting from 

supplying public goods cannot be exchanged exclusively through markets because the gain or loss of welfare 

is unpaid or uncompensated. This leads to a situation where the above factor of adequate business and 

contract law is lacking. 

The aforementioned factors certainly impair the ability of markets to signal the appropriate values of 

conserving biodiversity and landscapes to farmers, natural resources managers and the general public. 

This is not to say that government intervention is always a better option. Often, incomplete information is 

also the cause of government failures because environmental problems are not addressed and regulated or 

some negative effects of policy intervention are not taken into account (e.g. government-led perverse 

incentives). 

Despite the above problems, in some occasions externalities are, more or less consciously, somehow 

internalised. This could be the case for instance when the costs of maintaining the aesthetic qualities of the 

landscape are already internalised in the prices of staying in the agri-tourism houses managed by the same 

farmers who are taking care of the landscape; or when a subsidy is already given to farmers to not cultivate 

on field borders resulting in the positive impact on biodiversity eventually measured in previous sections 

(e.g. this could be the case of set aside adopted with a cross-compliance scope: reducing surplus and 

conserving biodiversity); or when the cost in terms of reduced yields of not using chemical pesticide is 

already internalised by a higher price of biological products (in this case eco-labelling allows for the 5 

107

factors of well functioning markets to be put in place by associating the selling of a public good to a 

commodity. The price may also reflects then the added value of using agricultural practices which are more 

friendly towards biodiversity conservation not just the quality of the product). 

Therefore, following the above, in AEMBAC there was a need to identify externalities through the 

assessment of the fact that economic values of the environmental impacts were or were not reflected in the 

market prices or in governmental interventions. 

If the analysis had shown that the economic value of environmental impacts had not yet been internalised, 

then it would have been necessary to study what approach would be the most suitable for the local situation 

to internalise the economic value of externalities through agri-environmental measures. 

Basically there are three main approaches to do so: market, quasi-market and command and control 

instruments. The most suitable instruments to internalise externalities depend on the ecological, economic, 

social, institutional, and ethical aspects of the local situation. 

Considering the above and suggestions from the task force, for the assessment of the externalities of the 

economic value of detected agricultural impacts, researchers were asked: 

• To assess, for each agricultural impact measured, if the economic value was or not not already 

internalised in the economics of the local agricultural economy (e.g. incomes, costs, prices, incentives, 

investments, etc.) or in policy interventions; and 

• To provide a list of externalities to be internalised through the development of agri-environmental 

measures. 

Box 48 – AEMBAC project: List of externalities –UD-CEMP report, Hungarian case studies 

Assessment of the status of externality of the economic value of detected agricultural impacts 

The list of externalities to be internalised through the development of agro-environmental measures is the following: 

Ex1 Impacts exerted on elements of environment 

The basic elements of environment are air, soil, and water which can be polluted by agricultural activities such as 

pesticides and fertilisers used, soil tilling and irrigation technologies, and equipment used for farming etc. To force or 

drive farmers to change technologies into protective ones entails sacrifices in economic terms in consideration of 

comprehensive features of the elements. 

Ex2 Impacts exerted on landscape 

In well-cultivated arable lands and grasslands, grazing animals are a valuable contribution to the scenic value of the 

landscape. This generates the “tidy countryside” feeling that is a social benefit and improve the attraction of the area 

which has positive impacts on businesses related to recreation and eco-tourism. 

Ex3 Gene preservation role 

Keeping and protecting local and endemic species and breeds are valuable contributions to the image and improve the 

attractiveness of the area. They also protect genetic information that cannot be protected in other ways or would cost so 

much that society and the economy could not afford to do so. 

Ex4 Maintenance of bio-diversity 

Maintaining diversity partly contributes to gene preservation but mainly secures the biological balance of an ecosystem. 

Accepting a certain level of weed infection on arable lands provides habitats and feed for many breeds of 

insects which has benefits for the whole food chain. We can protect animals, micro-organisms and plants which can be 

used as agents in biological plant protection, also as herbs or raw materials for medicine production when discovered 

through research. Most of them are not sufficiently well known. 

Ex5 Health protection 

If healthier foods are produced, the producer is often not not compensated enough in the price paid for them. 

Consumption of such foods contributes to a healthier society. That can help reduce costs of social security and save 

energy and costs of medicine production in consideration of the energy consumption and waste materials produced. 

Reduced chemical usage can prevent health problems for the labour force working with those chemicals e.g. cancer and 

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various allergies. 

Ex6 Energy consumption 

Energy saving results from reduced usage of oil, reduced quantity of pesticide and fertiliser use, which also save 

packaging materials and the costs of handling these dangerous waste. Reduced quantity of used chemicals help save the 

energy consumption of the production so that preserve the energy resources. 

Ex7 Impacts on employment 

Increasing environmentally friendly activities and work-processes of farming and related activities such as creation of 

routes for tourists, maintenance of canals etc., creating jobs. Job creation reduces unemployment rate and it creates 

positive spin-offs such as less unemployment benefit being necessary, reducing the burden on the economy (social 

network). Earning and working also have a positive effect on the mentality of rural people, as well as reducing the 

number of people using crime as a source of livelihood. 

3.6 Step 6 – Studying local sustainable agri-environmental policy targets and 

measures. 

3.6.1 Analysis of existing agri-environmental measures and comparison with recommendations 

developed 

Before defining the agri-environmental policy targets and measures, it was useful to compare the most 

important agri-environmental impacts and proposed recommendations identified in section 3.4.3 with already 

existing agri-environmental programmes in the study area, both qualitatively (i.e. checking if the 

environmental aspects addressed were the same in the existing programs and in proposed recommendations) 

and quantitatively (i.e. checking if the existing agri-environmental measures were aiming at the same 

physical, chemical or biological targets to be reached by the recommendations proposed in section 3.4.3). 

Conclusions on similarities and/or differences between the agri-environmental measures to be developed 

through the AEMBAC methodology and those already existing were drawn out in detail at this stage. 

It is worth noting that the already existing agri-environmental measures are supposed to have some effects on 

the local ecological and socio-economic situation studied. Researchers were asked to point out these effects 

here and consider these in the definition of the agri-environmental measures. (E.g. if the potential negative 

impacts coming from agricultural pressures were already partially lessened by the existing agrienvironmental 

measures, then this had to be accounted for accordingly in building the new one.) 

Box 49 – AEMBAC project: Comparison of recommendations with existing agri-environmental 

measures in Gelderse Valley Southwest Case study, Netherlands 

The recommended agri-environmental measures for the Gelderse Valley Southwest area focus on the three agricultural 

pressures that were identified as the most important: nutrient management, mowing and maintenance of field edges (see 

the WP7 report for a full description). 

Nutrient use. A series of measures can be identified to reduce the nutrient outflow of dairy farms. The precise choice of 

the optimal mix of measures will depend on the farm. Potential measures include: (i) reduction of manure levels; (ii) 

reduction of livestock density; (iii) change of animal feed; (iv) timing of manuring; and (v) use of field edges (Ministry 

of Agriculture, Fisheries, and Nature Conservation, 1995; CLM, 2001). Unfortunately, all these measures have a 

negative impact on agricultural productivity. 

• Reduction of manure levels. It depends on the local circumstances how large the reduction should be (in particular 

on the groundwater depth as well as the distance to waterways), but, assuming a linear relation between nutrient use 

and nutrient outflow 16 , an average reduction of nutrient use of 10 to 15% may be required; 

• Reduction of livestock density. This reduction would also lead to a reduction of nutrient outflow. It has been 

estimated that a reduction of milk production with 1000 kg/ha/year of milk would lead to a reduction of 5 to 10%; 

hence a reduction with around 2500 kg/ha/year of milk would be required. 

16 using BPJ 

109

• Change of animal feed; reducing the nitrogen (protein) content of the feed would also lead to reduced nitrogen 

output. A maximum reduction of 5% has been estimated by Mesu (1998). 

• Timing of manuring; spreading of manure in spring rather than autumn would increase denitrification and lead to 

less nitrogen output. However, this would, for many farmers, require the construction of larger storage basins; also 

it would not reduce the output of TP (Total Phosphorus), as phosphorous is not broken down. 

• Use of field edges. Excluding an area of around 1 meter from the ditches would in many cases allow for substantial 

reduction of eutrophication of surface water as it would reduce the direct flow of manure into ditches. However, its 

precise impact is hard to estimate. 

Mowing. That mowing dates have a profound impact on birdlife and butterflies is hardly disputed, and mowing dates 

are included in many current agri-environmental measures. However, there are not yet any scientific grounds for 

establishing a best practice regime. This makes the definition of ecological targets, in terms of packages of ‘optimal’ 

mowing dates next to impossible. However, some recommendations can be given based on current experiences (CLM, 

2000). 

It appears as if many of the agri-environmental measures related to mowing that are now being implemented do not lead 

to significant improvements in the survival of endangered species. The reason is that most measures focus on a late 

mowing obligation – for all farmers (!). This means that once the target date is passed, all farmers immediately go to 

their fields and mow the complete terrain. From one day to the next, many species cannot find any shelter, nor food. 

Even though many birds may have hatched after these dates (e.g. the 15 th of June is commonly used in Dutch agrienvironmental 

schemes), they die because of lack of food. In addition, many bird species require a mix of long and 

short grasses, which they used to find in old fashioned, small scale agriculture, but which is increasingly rare. 

Therefore, it is increasingly being recognised that the current measures are not effective. Much better would be a system 

where, in the course of end May, June and July, all fields would gradually, part by part be mowed. This would not 

necessarily bring enormous costs to the farmers, as some fields may be mowed earlier, however it would require a 

rethinking of the management of their fields 17 . 

In order to have a substantial impact on bird-life, it would be required that a substantial part of the fields, say 50%, 

would be mown according to this schedule. The costs relate to the somewhat reduced availability of grass in the springtime, 

and possibly to a decrease in quality of the grass harvested in July. 

Field edges including hedgerows. The use of field edges is part of several agri-environmental packages applied by 

farmers in the Netherlands (Ministry of Agriculture, Fisheries, and Nature Conservation, 1995).. Often they concern the 

promotion of more varied grass and plant species, and less frequent mowing regimes (CLM, 2000). This is beneficial 

for a variety of animals, in particular many bird and butterfly species. A particular case of field edges is the use of 

hedgerows. Hedgerows should not be established where there are important nesting areas for field birds, as they could 

lead to increased predation of eggs and young (because they attract foxes and rats). However, hedgerows can also fulfil 

an important corridor function for a variety of animals, including badgers, martens, some species of mice, etc. (Van 

Laar, 1980). This is most relevant as, under the development of the Ecological Main Structure, there should be corridors 

established between the forested areas west (Utrechtse Heuvelrug) and East (Veluwe forests) of the Gelderse Valley 

(SVGV, 2001). Thorough assessment of the required field edges is outside the scope of AEMBAC. It can, on a tentative 

and preliminary basis, be assumed that in total some 3000 ha of grassland (or around 10% of the total grassland area of 

the case study area) should have field edges (based on the IUCN norm of 10% of naturally managed areas per region). 

It is obvious that there is a whole range of agri-environmental measures currently being implemented in the Gelderse 

Vallei Southwest, resulting from EU, national, provincial and local policies, including laws, regulations and other 

initiatives. Nutrient management, mowing and field edge management are included in some of the SAN packages, and 

in addition the province of Utrecht is (generously) supporting the pruning of willows around the fields (which can be 

seen as a specific type of field edge). There are two major types of SAN packages, the ones focussed on meadows birds 

and the ones focussed on plants. In each type, there are different degrees of restrictions on land management – from 

relatively light packages (with low compensation) to much more stringent packages (with payments in the order of 1000 

euros/ha/year). Nutrient restrictions are higher in the plant packages, whereas the bird packages have more restrictions 

regarding mowing dates. Field edges is in a separate package. A major issue, however, is the effectiveness of the SAN 

packages – e.g. Kleijn et al (2001) found in an elaborate research effort that there was very little or no impact of most 

packages even after they had been implemented for 5 or more years. This is highly troublesome, and may be related to 

the fact that the requirements of the packages are not strict enough, or that the participation level (percentage of an area 

under a contract) is generally too low). In the course of AEMBAC, it could be examined if the concept of EMR could 

be used to help to explain the low effectiveness of these agri-environmental measures. 

17 a related measure that may be required is to sow the field with a mix of different grass species, in order to 

increase the variety of food for birds, as well as the timing at which the food is available. 

110

3.6.2 Analysis of aspects likely to be influenced by agri-envrionmental policy 

The information on the socio-economics of rural areas, gathered in step 1 above, was used in this and the 

following sections to build up the most appropriate agri-environmental measures according to the local 

situation, to analyse their suitability for enrolment by farmers, to assess the socio-economic feasibility of 

implementation and to identify what could be the transaction costs of local agri-environmental measures 

proposed. 

The analysis of aspects likely to be influenced by agri-environmental policy concentrated on: 

• Socio-economic aspects which were considered likely to be influenced by agri-environmental policy; 

• How the selected socio-economic aspects were likely to be influenced by agri-environmental policy; 

and 

• Socio-economic indirect or induced possible changes were desirable to be taken into account by agrienvironmental 

policy. 

Box 50 – AEMBAC project: Socio-economic aspects likely to be influenced by AE policy, Germany 

(for references in the box, see the SAW report) 

The major socio-economic aspects that are likely to be influenced by agri-environmental policy are: 

agricultural incomes; 

farm succession; 

viability of rural areas; 

image of region and potential for rural tourism; and 

reduced societal costs of environmental pollution and low food quality. 

Agricultural incomes 

The costs of agricultural production (input costs, costs of land management) as well as revenues (yield levels, product 

prices) are directly influenced by agri-environmental policy. It is a declared agricultural policy goal at the European and 

national level that agricultural incomes become comparable with incomes in other sectors of the economy (society) 

(BMVEL, 2002; European Commission, 1996, 1999). The internalisation of environmental costs (see below) has a 

direct effect on farm income levels and the competitive position of the farm in food markets. 

Farm succession 

Potential successors make their decision above all in terms of income potential, job satisfaction and the recognition of 

farmers and farming in society. Farm succession and the retention of young people in rural areas is generally considered 

vitally important for the future of rural areas (European Commission, 1996). 

Viability of rural areas 

Changes in type, scale and intensity of agricultural activity and land use have direct and indirect, multiplier and synergy 

effects on the rural economy. The viability of rural areas is a declared goal at the European and at the national level 

(BMVEL, 2002; European Commission, 1996; Künast, 2001). 

Image of region and potential for rural tourism 

Landscape amenity and biodiversity can be understood as economic potentials. Case studies indicate that substantial 

regional incomes can be based on these potentials (Knickel, 2001; Knickel, Renting & van der Ploeg, 2003). 

Reduced societal costs of environmental pollution and low food quality 

Agri-environmental policy directly or indirectly leads to a better internalisation of environmental costs into the 

economics of agricultural production. For example, relevant costs are the cost of water purification or health costs. This 

effect is in fact claimed by many representatives of the environmental lobby and it is supported by environmental and 

resource economics theory. Other assets can hardly be expressed in monetary cost terms but in society they clearly have 

a value. Examples are landscape amenity or biodiversity (Baldock & Lowe, 1996). More environmentally friendly and 

sustainable land use and food production can be linked with a higher quality of food products and better living 

conditions in rural areas (Knickel, 2001). Both will be reflected in public health and the costs of public health systems. 

Desirable indirect or induced socio-economic impacts 

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Based on the discussion of the major socio-economic aspects that are likely to be influenced by agri-environmental 

policy it is now asked whether some of these indirect or induced socio-economic impacts may indeed be desirable. The 

same five effects are examined again. 

Table 48 provides an overview of desirable indirect or induced socio-economic impacts. In the assessment it is assumed 

that agri-environmental policy measures are designed in the best possible way taking due account of farm, regional and 

societal level goals. 

The assessment given indicates that almost all indirect or induced socio-economic impacts are desirable. The only 

exception is the farm and regional level assessment of income effects. The main question here is whether additional 

costs and/or revenue foregone are indeed fully compensated. In agri-environmental incentive schemes according to Reg. 

(EC) 1257/99 member states are obliged to fully compensate additional costs and/or revenue foregone and, more than 

that, it is up to them to increase compensation by up to 20 % as an incentive element (European Council, 1999). The 

latter would lead to a positive income effect at farm and at regional level. Command and control policies, in contrast, 

would normally lead to a reduction in income that is undesirable from the farmers and - in some agricultural areas - also 

from the regional point of view. 

Table 48 - Overview of desirable indirect or induced socio-economic impacts 

Indirect or induced socio-economic impacts 

Desirability 

Farm Region Society 

Agricultural incomes ? ? ++ 

Farm succession ++ + 0 

Viability of rural areas + ++ ++ 

Image of region and potential for rural tourism + ++ ++ 

Reduced societal costs of environmental pollution and low food quality 

Source: Karheinz Knickel (subcontractor) 

+ ++ ++ 

3.6.3 Analysis of aspects related to design and implementation of agri-environmental measures 

The analysis of aspects related to design and implementation of agri-environmental measures focused on: 

• Identification of socio-economic and institutional aspects related to agri-environmental measures design 

and implementation; 

• Explaining how these could influence the formulation and effects of agri-environmental measures; and 

• Envisaging what were the aspects to be taken into account to maximise the effects of the agrienvironmental 

measures. 

Box 51 – AEMBAC project: Relevant socio-economic aspects in designing AEMs in “Oberes Fricktal” 

study area, Switzerland 

After the survey of socio-economic parameters in “Oberes Fricktal” and according to experts in charge of the agrienvironmental 

programme (AEP) “Natur2001” we can conclude that following aspects should be taken into account 

when introducing agri-environmental measures: 

• Quality of advisory service 

• Level of education 

• Income effect, financial design of measures 

• Working charge 

• Farm type/structure 

• Participation level of farmers 

In general, it can be stated that farmers in “Oberes Fricktal” act rather conservatively. That means that only little 

initiative is taken by them to change the situation of agriculture. As it has been shown in the past while implementing 

the AEP “Natur2001”, the advisory service plays an outstanding role in the successful implementation of new measures. 

The openness of farmers for new ideas or programmes corresponds with their level of education, which is already 

considerable among the younger generation. On the other hand, the extension service has to keep on working quite 

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intensively if more new ideas are to be introduced. 

For farmers, the best argument for signing up to the AEP is the expected effect on income. The attractive payments for 

the “Natur2001” programme did much for its acceptance. In the initial stage, the advisory service was also free of 

charge, which made it easier for farmers to introduce the programme on their farms. Only when this pioneer phase has 

succeeded and this success is well promoted in public, can one expect farmers to be willing to pay for additional 

extension services. 

For some farmers the reason for taking part in an AEP is to reduce their working charge or at least to have a better 

distribution of work throughout the year. This fact may also indicate why farmers in the studied region are not so 

interested in converting their farms to organic production. On the one hand, it would be attractive from an economic 

point of view, but, on the other hand, the working charge would increase instead of decrease. All in all, this makes 

organic production not too attractive compared with the opportunities offered by the AEP. 

Furthermore, the actual structure of the farm might or might not be favourable for taking part in an AEP. An already 

quite diverse farm can more easily decide to shift labour input from one activity to another or to dedicate one piece of 

land to the AEP. This does not automatically change the core activities of the farm. A highly specialised farm, however, 

attaches its available labour to only one or a few activities to which it is then bound. The question for such a farm is to 

focus on one activity and be as productive as possible. 

Another important point for successful development and implementation of the AEP is to actively involve the farmers. 

A good example could be recognised in the study region, where farmers set up an association for those taking part in the 

AEP. This association – again accompanied by some publicity – importantly fostered the acceptance of the agrienvironmental 

programme among colleagues. 

3.6.4 Studying locally sustainable agri-environmental policy targets and their definition 

In AEMBAC Phase 1 the Environmental Minimum Requirement (EMR) for the main ecological aspects 

believed to contribute to environmental function performance were identified and analysed. Once the socioeconomic 

aspects of the agricultural system were also studied, it was then possible to study what were the 

most feasible and environmentally effective policy targets to be reached. The analysis of setting the 

appropriate policy targets required the consideration of the local social and economic situation, studied in 

section 3.6.3 above. 

The tiers of sustainability (environmental goals) defined in Step 4, were the starting points for defining 

realistic and effective policy targets to be achieved through agri-environmental measures after socioeconomic 

aspects were considered. 

For example, by looking at each tier defined in Step 4, through the chosen ranking system, which had the 

scope to create an interface between science and policy building, and for which the relative undertaking and 

opportunity costs (and savings) were assessed in Step 5, an analysis of what policy targets were feasible for 

the local situation had to carried out. The following procedure was proposed: 

Task one: Identification of agri-environmental management practices 

The association between different tiers identified in section 4.4, and the relative agri-environmental 

management (undertakings) necessary to reach them identified in section 4.3 (i.e recommendations on how 

to lessen the negative impacts identified and enhance positive ones), had to be carried out as in the following 

example on the performance of the refugium function: 

Tier +2 = Presence of high positive impact (red) = 10% of existing UAA reconverted to (semi-)natural 

habitat 

Tier +1 = Presence of positive impact (yellow) = 5% of existing UAA reconverted to (semi-)natural 

habitat 

Tier 0 = respect of EMR= ecological sustainability of agricultural practice = no impacts or only low 

positive/negative impacts exerted by agricultural practices = field margins with hedgerows 3 meters wide 

for at least 30 % of the total length of field margins in the area 

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Tier -1 = Presence of negative impact exerted by agricultural pressures (yellow) = field margins with 

hedgerows 1 meter wide for at least 10 % of the total length of field margins in the area 

Tier -2 = Presence of high negative impact (red) = actual situation = very sporadic field margins with 

hedgerows 

For each agri-environmental measure a detailed explanation of the effects its adoption could have on 

reaching the associated tier had to be provided. 

Task two: Assessment of the agri-environmental management costs to reach the different policy targets 

(Tiers) 

This simply required inserting the results of the analysis carried out in Step 5, relative to the costs of the 

undertakings necessary to reach different tiers, and commenting on these. 

Please note that the opportunity costs, following the example above, of not cultivating the field margins, (i.e. 

reduced yields) together with the savings on relative production costs (i.e. less fertilisers or labour) had also 

to be considered later in section 3.6.5 below, on the definition of eventual payments to farmers by agrienvironmental 

measures. The analysis of the local agricultural system carried out in Step 2 was clearly of 

help for calculating undertaking and opportunity costs and relative savings. 

The outcome of the above analysis resulted, for each identified tier, in the relative necessary management 

undertakings costs/savings and opportunity costs. 

Task Three: Identification of the most appropriate policy target for the study area 

The choice of the policy target will always be a political decision. However, the approach proposed in task 

one of this section (on linking different degrees of sustainability to different agri-environmental 

managements) will help decision makers to define the policy targets with relevant information based on the 

available scientific knowledge. 

Moreover, the information identifying the undertakings and opportunity costs (task 2 above), assessed for 

each policy target (i.e. tiers in the ranking system), will further help to select objectives of the agrienvironmental 

policy after that the social and economic feasibilities of the proposed policy targets have also 

been analysed. 

Many socio-economic issues need to be taken into account in the selection of the policy targets, such as: 

farm economic and financial data (gross margin, fixed and current costs, farm income, etc.); environmental 

awareness of farmers; local institutional functioning; the financial resources available for agri-environmental 

policy; the commitment of the local and national government to achieving agricultural sustainability (e.g. 

ratification of the CBD, PEBLDS, etc.), and so on. 

The local economic, institutional and social features of agriculture studied in Step 2, Step 5 and section 3.6.3 

above, played an important role here, as well as the results of the analysis carried out in section 4.3.1 (i.e. 

agronomic feasibility of the most important constraints and opportunities for implementation of 

recommendations). In addition, some agricultural pressures were impacting on more than one environmental 

function studied (this was analysed in section 4.5), this creating the opportunity of obtaining a “value added” 

(i.e. the performance of more than just one environmental function) if these were addressed by agrienvironmental 

measures. The existence of already similar agri-environmental measures was a factor to be 

analysed in this selection of proposing policy target. 

The results of this section allowed suggestions to decision makers to be formulated on what were the most 

appropriate targets to be reached for the local situation, once the local agronomic and the main socioeconomics 

features were accounted for. 

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Box 52 – AEMBAC project: Definition of agri-environmental policy targets, Germany 

Agri-environmental management practices (or changes in land use) are identified on the basis of the shift in tiers needed 

to reach from the existing situation to a more sustainable situation. The relationships given are based above all on 

"Recommendations on how to lessen the negative impacts identified and enhance the positive ones". 

Based on the information given and on the results of the economic analysis, the costs of the undertakings necessary to 

reach the different tiers are given in Table 49. 

As has been explained in detail, the opportunity costs, for example of not cultivating field margins (i.e. the reduction in 

crop output and returns) together with the savings in production costs (i.e. less fertilizers or labour) has been taken into 

account where relevant. The consideration of this indirect costs and benefits is particularly important in the calculation 

of payments to farmers. 

Table 49- Changes in Agri-environmental management practices and the related costs in the three study areas 

Study area Changes Costs (€ / ha) 

Jahna Röder ULHPL* Jahna Röder ULHPL 

Landscape conservation 

-2 -1/0 -2 -1/0 Reduction in field sizes 59 59 - 

Habitat function 

-2 0 Valuable wet meadows - - 200 

-2 0 -2 0 Maintenance of new biotopes 156 a 156 a - 

0 +2 0 +2 " 90 90 - 

Soil function 

-1 0 Maintenance of fishponds - - 626 

-1 0 Increase in cropping diversity 0 a - - 

-2 0 -1 0 Soil conservation tillage 83 83 - 

(0 +1) 0 +1 Raising livestock density - 17 b - 

Water function 

-1/0 +1 -1 0 -1 0 Lowering agro-chemical use 114 114 80 

-2 0 -2/-1 -2 0 Establishment of buffer strips 92 56 36 

* ULHPL = study area of the biosphere reserve “Upper Lusatian Heath and Pond Landscape 

Source: Investigations of Karlheinz Knickel based on several Work Package reports, carried out by the SAW and subcontractors; a 

not including cost of establishment and opportunity cost of land; b savings in fertiliser cost slightly exceed reduction in crop returns; 

Identification of appropriate policy targets for the study area 

The choice of policy targets will be always a political decision. This section tries to pull together relevant information 

from previous analysis. This information can support decision-making and policy formulation at policy level. Based on 

previous analyses, the following aspects ought to be taken into account: 

Different degrees of sustainability could be linked to specific pressures related to agriculture and agricultural land 

use. For all the management practices dealt with in-depth and in economic terms, the relationships between 

pressures and impacts appear sufficiently strong to allow direct agri-environmental policy intervention. 

For the four environmental functions dealt with in the Saxony study areas and for specific ecological aspects and 

goals, relevant practices and necessary adjustments in management can be given. 

A reduction in field sizes and establishment of linear structures can very significantly improve landscape and 

habitat functions and also contribute to a reduction in soil erosion. The income losses and compensation payments 

necessary far outweigh regional-level benefits. 

Several changes proposed mainly address habitat functions: the maintenance of valuable wet meadows, the 

establishment and maintenance of new biotopes, and, specifically in the ULHPL study area, the maintenance and 

protection of fish ponds. Again, the income losses and compensation payments necessary far outweigh regional 

level benefits. 

For the changes that are proposed in respect of improving soil functions it must be asked where precisely good 

115

agricultural practice ends and where compensation payments are really justified. Examples of such management 

practices are an increase in cropping diversity (in the present situation cropping systems are extremely specialised 

resulting in additional fertiliser application and soil damage) and soil conservation tillage. The agronomic 

feasibility of these measures is very high. Income losses that could result from changes tend to be very small - 

mainly because the measures also lead to farm level cost savings and higher yields. 

Reintroducing livestock definitely is a measure that goes far beyond what can be achieved with agri-environmental 

programmes. It must also be asked whether there are no alternatives such as green manuring. The raising of 

livestock density could be an option in regions and on farms that still have livestock (cattle). A shift from slurry to 

straw-based husbandry systems requires investment support, i.e. the linkages between agri-environmental measures 

and other support measures are important. This corresponds well with the orientation of Reg. (EC) 1257/99. 

The last function that has been addressed is the water function. Here a lowering of the application of agri-chemicals 

and of nutrient surpluses has been proposed, plus the establishment of buffer strips along running waters and 

valuable biotopes (e.g. fish ponds in the ULHPL). At least some of the measures require more consideration in 

respect of the polluter pays principle. Some measures are already prescribed in relevant legislation. A consideration 

of the social and economic feasibility of the proposed policy targets again may mean that some compensation is 

appropriate, e.g. for buffer strips along running waters and valuable biotopes. 

The environmental awareness of farmers, the local institutional functioning, the financial resources available for 

agri-environmental policy and the commitment of the local and national government of achieving agricultural 

sustainability are other aspects that still ought to be examined in more depth. Please refer to wp4 and wp8 for 

further details about this. 

3.6.5 Studying locally suitable agri-environmental measures to reach policy targets. 

Once the most approriate agri-environmental policy targets for the local situation were identified, it was then 

possible to develop the agri-environmental measures to achieve them. 

Generally speaking it is possible to envisage the following 3 situations regarding the type of approach (i.e. 

policy instruments) used to achieve the agri-environmental targets set in section 3.6.4 above: 

Command and control: 

(e.g. laws and standards to be 

respected): the adoption of this 

approach could be necessary for 

instance when the ecological 

impact is so widespread and 

negative that the intervention has to 

be done through a law which 

guarantees that environmental 

impacts are eliminated or lessened. 

Fig. 22 Approaches to develop agri-environmental instruments 

Delivering of Agri-environmental goods 

and services 

Quasi-market: 

the adoption of this approach is the one 

used in Reg, (EC) 1257/1999. In 

AEMBAC the underlying philosophy 

for this approach is that the scaling up 

of positive tiers should allow the 

practical development of rewards for 

environmental friendly farming, while 

the scaling down (on reference to EMR 

or good farming practices) to negative 

tiers should allow to finally put in 

practice the polluter pays principle 

when translated in agri-environmental 

measures. 

Other important tools for implementation of agri-environmental measures are supportive measures such as 

training, extension services, research, etc. Agri-environmental education and training courses could often be 

the key to the success of implementing an agri-environmental measure. 

116 

Market: 

This type involves the exchange of agrienvironmental 

goods and services 

between Producers and Consumers 

through the market mechanisms (e.g. 

Organic product). 

Quality Standards or fiscal levies can 

also be used by governments to 

orientate the market.

In principle the approach used to build up agri-environmental measures, can be correlated to the exclusivity 

and rivalry in consumption characters (i.e. public/private good nature) of the agri-environmental goods or 

services to be delivered. OECD (2001) identifies 6 categories 18 of public goods. Below, only four categories 

linked to public/private characters of agri-environmental goods are taken into account: 

• Pure public goods: Are those goods which have the characteristics of non-excludability and nonrivalry 

in consumption such as biodiversity. These kinds of goods can be governed by government 

intervention only given the impossibility to exclude non-buyers benefiting from them. 

• Common goods: are those goods whose use can be governed by open access or common property 

regimes such as forest or pasture. 

• Club goods: are those goods whose use can be restricted to members of a club such as a private 

hunting reserve. 

• Private goods: these goods can be governed by the market mechanism (e.g. organic produce). 

So, depending on the public/private nature of the agri-environmental goods or services to be delivered, 

markets, quasi-markets, or government interventions may be more or less suitable for delivering 

goods/services. The private goods, for instance, may be produced and exchanged through the market but also 

by the government intervention, as it may be in the case of the public utility of the goods and services to be 

produced (e.g. medical care services). On the contrary, in the situation where the agri-environmental good or 

service has a pure public good character, this can only be delivered by the government intervention, thorugh 

regulations or quasi-market instruments because of the “free rider” problem (see also Section 3.5.2 above). 

It is worth noting that to internalise externalities through market mechanisms (i.e. to promote transactions 

between agents) one needs to consider the difficulties arising from the pervasive character of the sources of 

agricultural pollution, and the administrative costs of the great numbers of parties involved (administrative 

costs will be considered in section 3.7.4 below). To internalise externalities through government 

intervention, a well-defined framework of environmental public laws, regulations and environmental rights 

had to be put in place. 

After having identified the most suitable approach for delivering the specific agri-environmental good or 

service locally, in order to define what would be the most suitable agri-environmental measure for the local 

situation (e.g. depending on the targets to be reached, the management prescription to be adopted, the 

associated costs, farmers’ environmental awareness, etc.), researchers analysed the following issues: 

• Zonal or horizontal schemes 

Identification of the most suitable scheme, zonal (e.g. Environmental Sensitive Areas in the UK) or 

horizontal (e.g. conversion to organic farming scheme), to achieve the target. In general it can be said that 

zonal schemes are more effective in reaching a well-defined target in a circumscribed area, whereas 

horizontal schemes are more effective when applied in wider regions. 

• Time period of agri-environmental measures 

Analysis of the time period necessary for an agri-environmental measure to be implemented before obtaining 

some results and whether the agri-environmental measure has to be permanent or implemented only for a 

certain time span. E.g. in the case that the starting point is Tier –1 and to achieve Tier 0 is considered the 

only feasible target in a relatively short time (given the local socio-economics conditions), the time plan to 

reach Tier +1 (if this is the final objective) in the longer term has to be developed. 

• The minimum rate of enrollment by farmers necessary to achieve the environmental goal 

The minimum uptake rate by farmers of the prescribed management in order for the agri-environmental 

measure to be effective (i.e. to reach the target) had to be calculated. So, for instance, if the target to reach 

Tier 0 is field margins with hedgerows 3 meters wide for at least 30% of the total length of field margins in 

18 The categories are: Pure Public Goods, Local Pure Public Goods, Open Access Resources, Common Property 

Resources, Excludable and Non-Rival Goods, Club Goods. 

117

the area, then it will be necessary that at least enough farmers to represent a feasible 30% of the existing total 

field margins will adopt the agri-environmental measure. 

• Eligibility criteria for farmers 

Here (obviously depending on the target to be reached) the criteria for farmers to be eligible for enrollment 

had to be defined. So following the example in the point above, an eligibility criterion could be that only 

farmers who have X meters of feasible field margins on their farm are eligible (in order to avoid 

administration costs for smaller length), or that those with already a certain length of hedgerows have the 

priority for enrollment (in order to lessen costs of planting new hedgerows) and so on. 

• Payments to farmers 

The calculation of payments to enrolled farmers requires the consideration of: the expected loss of income; 

the additional costs incurred to comply with the necessary agri-environmental undertakings (starting the 

calculation from a baseline of Good Farming Practice which AEMBAC assumes to coincide with EMR); the 

savings on expenditure e.g. on reduced production operations, etc.; plus if appropriate, an incentive which as 

a rule should not exceed 20% of the loss of income forgone and the additional costs incurred (see Reg. (EC) 

1750/1999, art.18). 

This latest consideration covers a strategic aspect in defining agri-environmental measures. It is reasonable 

that farmers should be compensated for the environmental goods and services they provide 19 , considering the 

efforts undertaken or opportunity costs incurred in supplying them, and not just for the eventual mere 

ecological sustainability. In other words, if a particular environmental function is already maintained by 

current agricultural practices at Tier 0, farmers should not be compensated for the sustainability of their 

agricultural system in respect of that particular environmental function. If they cause this situation to 

deteriorate they should be held responsible (the polluter pays principle), if they enhance it they should be 

compensated for meeting an agri-environmental policy target (i.e. delivering environmental goods and 

services), as well as if they are already doing so in their farms (at tier +1 or tier +2). 

At the end of this process, policy targets to be achieved through agri-environmental programmes had to be 

defined clearly. Monitoring and evaluation procedures will be dealt with in section 3.7 below. 

Box 53 – AEMBAC project: Suggested agri-environmental measures. Oberes Fricktal, Switzerland 

Low input grassland 

a) Description of measure Extensively used meadows 

• Minimum botanical quality (to be defined) 

• No fertilisation 

• Very restricted application of herbicides (only single plant treatment allowed) 

• 1-3 cuts yearly; depending on the botanical quality and the site more cuts can be allowed (after consultation of 

an advisor) 

• No mowing before the 15 th of June (valleys) / 1 st of July (hilly regions) / 15 th of July (mountain regions) 

• Autumn grazing allowed, except on Mesobrometum meadows 

• Removal of the grass cut 

• Min. one cut per year is left on the soil for hay production (“Bodenheu”) 

• Leave grass piles and wood stacks as refugium for animals 

• Min. area of lot 5 ares 

• If the botanical quality is low, the sowing of special seed mixtures is required 

Requirements for the high quality scenario (Tier > 0): 

• Graded cut (for areas larger than 0.5 ha): the whole surface is divided in different plots, which are mown at 

different times (time gap of 2-3 weeks) 

• Use of mowing bars (recommendation: cutting height 8 cm) 

• No use of forage crimper 

• No silage allowed 

19 

As well as that they may be considered responsible for causing environmental damages, i.e. when they do 

not follow Good Farming Practices): 

118

• min. one cut per year is left on the soil for hay production (“Bodenheu”) 

• Meadows with high botanical biodiversity (corresponding to “Magerwiesen” and “Fromentalwiesen”) 

• Meadows within a biotope network, or lots with a high potential ecological value 

• Dry and sunny location 

• Soil poor in nutrients 

Tab. 50 - Aspect of measure Extensively used meadows 

Tool implemented Quasi-market 

Type of scheme Zonal with emphasis on the landscape types “Bergland”, “Hügelland Ost”, and 

“Hügelland West” (where more low input grassland is possible and is needed). In 

the rest of the region, conservation of the status quo. For more details, please refer 

to WP3-Refugium function. 

Time period At least 10 years. 

Eligibility criteria - Conservation of the existing field structure and small structured landscape: no 

enlargement of single lots, conservation of the mosaic of different crops, 

conservation of the areas of permanent and perennial crops 

- Conservation of existing livestock density: no further increment 

- Maintenance of the overall fertilisation intensity in the study area: no decrease in 

unfertilised area of the UAA, conserve the actual input per area of nitrogen and 

phosphate and conserve a well balanced nutrient balance on the farm 

Payments per ha per ha 946 € 

Target value for area involved 

total (EMR) 342 ha 

New (Difference to EMR) 75 ha 

Minimum number of farmers necessary At least 50% of the farmers in the landscape types “Bergland”, “Hügelland Ost”, 

and “Hügelland West” = ca. 65 farmers. Each farm increases the area of 

extensively used meadows by an average of 1.15 ha. 

Box 54 – AEMBAC project: Suggested the agri-environmental measures. Chianti Classico, Italy. 

Considering that the decrease of water runoff is strongly determined by the same factors affecting the decrease of soil 

erosion, the proposed agri-environmental measure “Soil cover” can reduce the harmful effects of both soil erosion and 

runoff. Under an agronomic point of view, the temporary grass soil cover from September to March is a well-known 

practice in the Chianti area, as a local farmer said in an interview. 

The recommendations proposed are re-formulated in the following table according to difference between actual soil 

erosion risk and EMRs for soil erosion and runoff coefficient. To determine the Tier for a field in the Chianti area it is 

possible to use the above mentioned excel-USLE spreadsheet calculator available at www.issds.it 

Tab. 51 - Tiers according to soil cover 

Tier +2 Establishment of sufficient percent of soil cover and set-up of proper field length to reduce soil erosion to 

less than 0.5 t/ha/year 

Tier+ 1 Establishment of sufficient percent of soil cover and set-up of proper field length to reduce soil erosion to 

0.5- 2 t/ha/year 

Tier 0 Establishment of sufficient percent of soil cover and set-up of proper field length to reduce soil erosion to 

2-4 t/ha/year 

Tier – 1 Establishment of sufficient percent of soil cover and set-up of proper field length to reduce soil erosion to 

4-10 t/ha/year 

Tier – 2 Insufficient percent of soil cover and proper field length that determine >10 t/ha/year of soil erosion 

119

Fig. 23 Visual examples of grass cover in vineyards (P. Bazzoffi, ISSDS, 2003). 

(Figures do not reflect the soil erosion value necessary to comply the Tier value, but only the most probable surface 

conditions when different Tiers are achieved). User should calculate soil erosion risk through the USLE calculator to 

determine the necessary percent grass cover, according to soil quality, slope and other site conditions. 

Tier –2: No cover, soil 

tilled and exposed to 

rain splash and runoff 

Tab. 52 - Measure on soil cover 

Description of the 

measure 

Tier –1 Tier 0: Natural 

sparse cover (Tier 0) 

with many exposed areas 

(Tier-1 on top-hill), 

runoff on wheel tracks. 

Tier +1: Cover crops 

on alternate rows 

120 

Tier +2: Grass cover 

on almost 100% of 

vineyard 

Tier 0: Commitment necessary in vineyards and olive groves 

Compulsory grass soil-cover for lands with more of 15% of slope and with a mix. Length of rows 

of m 150. 

Tier 1: Commitment necessary in vineyards and olive groves 

Artificial or Natural grass soil cover in vineyards and olive grove. Grass soil cover of rows 

connected to marginal areas (perimeter). In the artificial grass soil cover the suggested species are: 

Poa pratensis, Festuca Rubra, Festuca Ovina, Lolium Perenne, Acrostis Tenuis. The choice of the 

best mix is done according to soil texture of the land to be protected from soil erosion and 

excessive runoff. Prohibition of herbicide use in olive groves and vineyards 

Grass soil cover at field-margins and between the vine rows. Grass soil cover should not be 

mowed before 15 April (dates could be change considering the variety of season raining) 

Tool implemented Quasi-Market 

Type of scheme Horizontal scheme in vineyards and olive groves 

Time period Min. 6 years 

Priority Vineyards at up-down ditches (rittochino) 

Eligibility criteria Minimum surface of 1 ha of UAA. Slope more than 2,5 %. Agricultural managers, also associated, 

according to art. 2135 of the C.C. 

Payments per ha 150 € first year 100 € following years 

Area agreement Plus 10% of the payment 

The procedure proposed for the definition of agri-environmental measures, while providing a common 

framework throughout the whole European territory, allows also for local socio-economic conditions to be 

taken into account in the definition of policy targets. 

Socio-economic acceptability of the designed agro-environmental programmes by relevant stakeholders and 

institutional sustainability (functionality and administrative and transaction costs to be incurred in by local 

administrations) are analysed in sections 3.6.6 and section 3.7.4 respectively, following (as reference) the 

guidelines given by OECD on environmental policy evaluation criteria (OECD 1991, 2001) as shown in the 

example in box 55 below.

Box 55 - Environmental policy evaluation criteria (OECD 1991, 2001) and example on its application 

on a case study base 

Environmental policy evaluation criteria (OECD 1991, 2001) 

• Economic efficiency 

• Cost-effectiveness 

• Flexibility (characteristic of the development of AEMBAC methodology) 

• Enforceability 

• Transparency (characteristic of the development of AEMBAC methodology) 

• Equity/fairness 

• Policy compatibility 

• Political acceptability 

Example of application on a hypothetical case study basis 

1) The environmental impact is important in conserving biodiversity and the country has ratified the Convention on 

Biological Diversity (policy compatibility) 

2) There is the agronomic know-how and capacity of farmers to adopt the recommendations (cost-effectiveness, 

economic efficiency); 

3) There is a growing awareness by farmers of the environmental problem (policy acceptability) 

4) The cost of reaching tier 0/+1 is reasonable (and lower than the supposed economic benefits of doing so); (costeffectiveness, 

economic efficiency) 

5) There is a production surplus in the area and incentives for production are no longer justifiable under CAP reform 

and WTO rules (policy compatibility) 

6) In adopting the agri-environmental measure, no group is unfairly disadvantaged or favoured (equity) 

7) The agri-environmental measure has a flexible approach considering local farming traditions (flexibility) 

8) Monitoring can be done by remote control (enforceability) 

3.6.6 Direct involvement of local farmers and administrators in the final definition of agrienvironmental 

targets and measures 

In order to develop agri-environmental measures suitable to be implemented by farmers and effective in 

reaching their environmental objectives, the involvement of different stakeholders is necessary. Following 

the procedure set up in previous sections, this task had to be undertaken when the agri-environmental 

measures had already taken shape, but still were not finalised, so to present sufficiently detailed material to 

relevant stakeholders, who eventually will have to implement the agri-environmental measures so identified, 

and have the opportunity to consider also their views before final definition. 

Agri-environmental measures to be presented were those defined in section 3.6.5, taking into account the 

agronomic practices to be adopted, the minimum amount of enrolment by farmers to achieve the 

environmental goal at the area level, the eligibility criteria for farmers to enrol, the amount and type of 

payments eventually to be made, etc. 

The relevant stakeholders to be contacted were those who have a direct interest in the agri-environmental 

measures proposed, such as farmers, local administrators, environmental organisations, agro-industries, 

consumers associations, etc. The reason to involve these stakeholders was to have a first feedback in terms of 

understanding, acceptability, and feasibility, to finalise the measures proposed and to identify farms that 

would be available in the area for carrying out an eventual pilot project on agri-environmental measures 

implementation. 

Farmers are the most relevant stakeholders, being those who will have to implement agri-environmental 

measures and those who will be affected greatly by their adoption in terms of diversified incomes, 

production choices, rights of use of natural resources, way of living, culture, and know-how. Whereas in the 

study areas farmers were already contacted to be interviewed with the agri-environmental questionnaire (see 

Step 2 above), it was recommended to continue collaboration, presenting the identified agri-environmental 

121

measures to them and asking their opinion about these. A list of farmers interviewed had to be produced. 

Whereas this would have been difficult, it was advised to contact the representatives of local farmers 

associations and collaborate with them before finalising the agro-environmental measures proposed. 

The involvement of farmers and their associations focussed on the following topics: 

• Participation in the already existing agri-environmental measures, difficulties and /or opportunities 

experienced; 

• Awareness of the environmental positive/negative impacts detected and of the agricultural practices 

related to those impacts identified; 

• Awareness of the necessary changes to the agricultural practices recommended to overcome the 

negative impacts and/or enhancing the positive ones; 

• Assessment of the necessary agri-environmental knowledge and capacity to eventually implement 

and monitor the effectiveness of recommended measures; and 

• Agreement on the methods of assessment and identified amount of the undertaking and opportunity 

costs of adopting the recommended practices and eventual incentives. 

Box 56: Examples of some questions related to the participation by farmers in already existing and 

new agri-environmental measures 

1) How important has been the availability of existing agri-environmental measures in orienting farmers decisions on 

agricultural management? 1 (not important), 2 (slightly important), 3 (important), 4 (very important)? 

2) Regarding agri-environmental management decisions undertaken, how many of these would be maintained if the 

agri-environmental measures would be withdrawn? 1 (none), 2 (only some, indicating which), and 3 (all). 

3) What is the agri-environmental measure, amongst those already existing, which farmers believe to be the most useful 

for their farm? 

4) What environmental aspect do farmers believe should be addressed as a priority by new agri-environmental measures 

in their areas? 

5) What would be the minimum payments they would accept to adopt a measure addressing that environmental aspect? 

Local administrators are those who will run the proposed agri-environmental measures. They will deal with 

administrative aspects (e.g. issuing contracts to farmers) and transaction costs (e.g. making payments) to be 

dealt with in section 3.7.4, monitoring the implementation of the measures, evaluate their efficiency and 

effectiveness, etc. (see below sections 3.7.1 and 3.7.2). They usually also have important understanding that 

should be considered when developing new agri-environmental measures, having had prior experience with 

those already existing. 

The involvement of local administrators focussed on the following aspects: 

• Major difficulties/opportunities experienced in implementing the existing agri-environmental 

measures; 

• Awareness of the environmental positive/negative impacts detected and of the agricultural practices 

related to those impacts identified, and of synergies or differences with eventual existing agrienvironmental 

measures; 

• Awareness of the necessary changes to the agricultural practices recommended to overcome the 

negative impacts and/or enhancing the positive ones, and eventual aspects to be taken into account in 

their implementation; 

• Assessment of the necessary agri-environmental knowledge and capacity to monitor the 

effectiveness of recommended measures and envisaged difficulties in implementing these; and 

• Agreement on the methods of assessment and identified amount of the undertaking and opportunity 

costs of adopting the recommended practices and eventual incentives. 

Environmental, hunting and fishing organisations and protected areas authorities usually have a good 

understanding of the most important ecological aspects of an area. They can be a useful source of 

information on the most urgent environmental aspects to be addressed by the new measures and on the 

122

effectiveness of the existing ones, suggesting also practical methods to monitor impacts. 

Consumers associations’ interests such as those related to the quality and safety of the agricultural produce 

(i.e. healthy food) and of the landscape, can offer new societal demands and ideas (such as sustainable 

production labelling) that could be useful to consider when developing agri-environmental measures. 

The points of view of agro-industries, retailers and agri-tourism agencies, being those stakeholders closer to 

the final users of the agri-environmental production chains, also can confirm a certain trend in consumer 

demand for food quality and leisure activities, and therefore being of help in finalising proposed agrienvironmental 

measures. 

The final outcome of this process was the integration of stakeholders points of view in the final definition of 

agri-environmental measures at the farm level. A list of selected farms where to conduct pilot projects had to 

be produced in consideration of an eventual implementation of the AEMs developed. 

Box 57 - AEMBAC Project: Direct involvement of actors, identification of farms for pilot projects in 

the Hungarian case studies 

The appropriateness and adequateness of the present (currently running) AEP, and the proposed AEP measures was 

tested. The panel were the actors directly or indirectly involved in the implementation of the programme: mainly by 

farmers operating in the pilot areas. In order to check the opinion of administration (e.g. Chamber of Agriculture, local 

agricultural adviser) and authorities (national parks, etc.) – i.e. those who will implement the programme – the 

questionnaires were also filled by the representatives of these bodies. 

Results of the questionnaire 

26 of the 40 participants filled in the questionnaire. The panel of the questionnaire cultivate/manage more than 23.200 

hectares (in and around the pilot areas), of which 6.500 are already in the existing AEP programme. According to the 

administrative officers, there is intention to increase the AEP area with additional 5.800 hectares. This means, that the 

rate of land in AEP will be increased from 25 to 53% in the near future (Figure 24). 

Incr. 

25,1% 

Present 

28,2% 

Out of 

AEP 

45,7% 

Total area: 23.265 ha 

Fig. 24 Farming area covered by those who filled in the questionnaire 

The farmers were also asked whether they would increase the area currently under AEP. They provided positive 

answers, some of them would even buy/rent land to increase the current area (100%), as it is shown Figure 25. 

(questionnaire No 2, 3 and 4.) 

123

120 

100 

80 

60 

40 

20 

0 

1 2 3 4 5 6 7 8 9 10 11 12 

Rate (%) of land in AEP Planned increase (%) 

Fig. 25 Rate of managed land currently in AEP and the planned increase 

(selected questionnaires) 

300 

250 

200 

150 

100 

50 

0 

It has been concluded, that most of the interviewed farmers (87%) were applying for an AEP programme (organic, 

ESA, grassland or wetland scheme), and the vast majority (92%) were successful. This means that an AEP in its present 

form is already known and considered by the local farmers, however their opinion on the implementation, control and 

financial management is less than satisfying. Figure 26. presents the cumulative scores (level of satisfaction) in 

percentage. According to this, significant measures are needed to improve the financial management and the 

implementation of the programme. 

100% 

80% 

60% 

40% 

20% 

0% 

33,3 

62,5 

13,6 

Implementation Control Financial mgmt. 

Fig. 26 Opinion on the existing agri-environmental measures 

Stakeholders have also been asked to give proposals for improvement. The reply by groups is summarised as follows: 

• Farmers – authorities are to keep deadlines, improve information flow, and increase sums 

• Administration – improved control, informatics (data processing) and information flow 

• Authorities – co-operation between control authorities, improved control, keeping deadlines, institutional 

development 

In the second phase the AEP measure proposed by the AEMBAC project was tested. 

The farmers’ replies regarding the proposed measures in shown in Figure 27. 

The opinions were asked in three categories: (1) applicability of the proposed measure (on the operation area), (2) 

appropriateness for the elements to meet the proposed measure, and (3) adequateness of the sums to meet the measure. 

As one can conclude by the cumulative results (level of appropriateness) the proposed measures are well applicable in 

(and around) the pilot areas (score 71-89%). This is relatively high, considering that the farmers are rather from 

specialised field of activity (e.g. arable or grassland, etc.). The elements of each measure are considered to be 

appropriate (score 89-100%). As regards the financial aspects of the measures: the adequateness of the proposed sums 

vary (score 38-89%). 

124

% 

100 

80 

60 

40 

20 

0 

1. Crop rotation 

93 93 

78 77 79 77 

71 

64 

38 

2. Nutrient man. 

3. Farm animals 

89 

4. Land-use 

100 100 

69 

77 

5. Plant protection 

55 

6. Gene preserv. 

90 89 89 

82 

67 

71 

125 

7. Water man. 

Applicability Appropriateness of elements Adequateness of sum(s) 

Fig. 27 Questionnaire results (proposed measures) 

The financial aspects for the measures are under reconstruction though, in one hand the NAEP figures are higher than 

that of the previous years, and, in the other hand the proposed (AEMBAC) measures can be combined so, that the 

finances of the measures can be added. 

In Figure 28. the opinion of farmers and administrators is shown. Among the proposed measures the appropriateness 

(score) for 1. Crop rotation and 2. Nutrient management and 4. Land-use is higher among farmers than administrators. 

The 3. Farm animal, 6.Gene preservation and 7. Water management is similar, and only 5. Plant protection is lower in 

case of farmers. The differences are in most of the cases not significant. The reason for the farmers giving higher scores 

are the fact that usually they do not consider labour costs at realistic level (often they do not calculate their own labour 

cost at all), and their estimation for the evaluation is rather based on their practical experiences, instead of economic 

calculations. On the contrary, the administrators include the issues of implementation and e.g. the incentives into their 

opinion, resulting in lower scores for some of the proposed measures. 

% 

100 

80 

60 

40 

20 

0 


100 100 100 

100 100 100 100 100 100 100 

93 

90 

93 

89 88 

90 89 89 

63 

78 77 

64 63 

79 

75 77 

71 

80 

75 

69 

77 

67 

82 

67 

80 

75 

71 

55 

50 

20 

38 



4. Land-use 

33 



7. Water man. 

Applicability (auth.) Appropriateness (auth.) Adeq. of sum(s) (auth.) 

Applicability (farmers) Appropriateness (farmers) Adeq. of sum(s) (farmers) 

Fig. 28 Questionnaire results (proposed measures) – authorities and farmers 

Finally the applicability of the proposed measures in regional context was asked. The panel – actually managing 23.200 

hectares, and having information about a much larger area – approved the programme as shown in Figure 29. Most of 

the proposed measures are on a good level (69-84%). Only those with no or limited history in the region (Gene 

preservation and Water management) scored lower (50 and 63%), but this is due to the limited experiences regarding 

them and the latter doesn’t concern the total area. However the idea is not unknown, and considered to be applicable, 

the farmers are moderately optimistic on the implementation. In this case pilot scale implementation is to be considered 

to convince farmers on the applicability of the measure.

% 

100 

80 

60 

40 

20 

0 


76 75 



69 

4. Land-use 

77 


84 


50 

7. Water man. 

Fig. 29 Applicability of the current measure on the farmland 

3.6.7 Identification of farms agri-environmental accounting systems. 

Once the agri-environmental measures were finally defined, taking into account the stakeholders points of 

view, it was important to identify the most relevant aspects to be considered for their effective 

implementation and monitoring. 

A first step in this direction was the definition of the data that have to be recorded at farm level for testifying 

and reporting to the local authorities the correct implementation of the agri-environmental measures and their 

effectiveness. 

From the analysis carried out in Step 3, it has emerged that usually data relative to agri-environmental 

aspects, such as, for instance, the time spent on maintenance of land settings or hedgerows, is not reported on 

accounting books by farmers. The lack of data of this kind can seriously impair the possibility to assess, both 

at local and regional level, the real costs relative to agri-environmental measures implementation. 

Moreover, the involvement of farmers in recording data on the most important environmental aspects, such 

as the number of species seen or the soil erosion levels witnessed on-farm, allows the growing of their 

environmental awareness, the appreciation of progresses in the environmental situation on their farm 

(evaluation culture), and the understanding of the utility of implementing the agri-environmental measures. 

Keeping agri-environmental accounting also helps comparisons with field data recorded by experts of local 

administrations so contributing, for instance, to the monitoring and evaluation activities 20 . 

In building up an agri-environmental accounting system for local farms it is important to keep the paper 

work at the minimum so to not burden further that which already must be done. To do so it was strongly 

recommended to focus only on the most important data, necessary to be reported by farmers, on the correct 

implementation of the local agri-environmental measures and on their effectiveness. 

Three broad classes of data were used: those related to the environment, the agricultural practices and the 

socio-economic aspects. The analysis carried out in Step 2 (e.g. state indicators describing the performance 

of the environmental function at farm level and their relative EMR values) helped to define those state 

20 On this point see also the e-conference on bio-monitoring ''Auditing the ark - science based monitoring of biodiversity'', 5-20 

September 2002, organised by The European Platform for Biodiversity Research Strategy (EPBRS), the Danish Biodiversity 

Platform and the BioPlatform Thematic Network, whose proceedings are available at the web address: 

www.gencat.es/mediamb/bioplatform 

63 

126

indicators which could be reported by farmers and those which require the intervention of specialised 

personnel. Also indicators used in Step 3 were used for developing the agri-environmental accounting system 

dealing with environmental, agricultural and socio-economic data at farm level. 

The agri-environmental accounting had to be developed according to the local agri-environmental measures 

proposed. 

Below are two examples of the kind of environmental accounting that is expected to be achieved. 

Example 1: the agri-environmental measure is relative to the refugium function and consists of planting 

hedgerows at field margins of a certain width, height and length, and maintaining them for at least ten years; 

then the agri-environmental accounting will focus on the following information (please note to be integrated 

with further information or adjust according to case study requirements): 

Tab. 53 - Agri-environmental data (farm level) 

Environmental data 

Hedgerows status 

Unit of measurement Year 

1 

Hedgerows width, height and length (older than 10 meter 

years) 

Hedgerows width and length (younger than 10 meter 

years) 

Plant used in new hedgerows (local shrubs) species 

Hedgerows of 2 meter width total length 

Associated biodiversity 

meter 

Bird key specie X (increasing, stable, decreasing) Individuals seen in one 

(old hedgerow) 

week during spring time 

Bird Key specie Y (increasing, stable, decreasing) Individuals seen in one 

(new hedgerow) 

month during summer time 

Reptile Key specie Z (increasing, stable, Individuals seen in one 

decreasing) 

week during spring time 

Plant Key specie W (increasing, stable, decreasing) 

Agricultural data 

Number of individuals in 

100 meters lenght 

Hours spent on field margins hours 

Hours spent on hedgerows hours 

Reduced inputs Kg/ha 

Reduced yields 

Socio-economic data 

Kg/ha 

Agri-environmental payments received per ha Euros/ha 

Agri-environmental payments total 

Hedgerows management 

Euros 

Undertaking costs of restoring and managing Euros 

habitat 

Costs of planting new hedgerows Euros 

Opportunity costs (reduced yields on field margins) Euros 

Saved costs (reduced inputs) Euros 

Employment changes Hours/person 

Training hours Hours 

Example 2: The agri-environmental measure is relative to the aesthetic function of the landscape, and 

consists of a progressive reduction of field size through semi-natural strips and/or introducing different crops 

cultivation in order to performed coherence with the traditional landscape patchiness; then the agrienvironmental 

accounting will focus on the following information (please note to be integrated with further 

information or adjusted according to case study requirements): 

127 

Year 

2 

Year 

3 

Year 

…. 

Year 

9 

Year 

10

Tab. 54 - Agri-environmental accounting system (Farm level) Unit of Year Year 

Environmental data 

Field size status 

measurement 1 2 

Fields size on farm ha 

Fields extension Reduced 

Associated biodiversity 

Ha/square meters 

Birds key specie X (increasing, stable, decreasing) (old Number of 

hedgerow) Individuals seen in one week during spring time individuals/ha 

Birds Key specie Y (increasing, stable, decreasing) (new Number of breeding 

hedgerow) Breeding pairs seen in one month during summer pairs/ha 

time 

Reptiles Key specie Z (increasing, stable, decreasing) Number of 

Individuals seen in one week during spring time 

individuals/ha 

Plants Key specie W (increasing, stable, decreasing) Number Number of 

of individuals in 100 meters length 

Associated Aesthetic attractiveness 

individuals/ha 

Agri-tourism 

Associated cultural/scientific events 

Number of 

presence/year 

Documentaries, movies, pictures on the habitat; 

Number of 

Educational/demonstration visits and scientific research events/year 

carried out on the habitat 

Agricultural data 

Hours spent on reducing fields size hours 

Reduced yields Q/ha 

Reduced inputs (labour, fertilasers, etc.) Kg/ha 

Different crops cultivation introduced ha 

Length and width of natural strips 

Socio-economics data 

Square meter 

Agri-environmental compensation payments received per m2 

reduced 

Euros/mt 

Agri-environmental payments total Euros 

Undertaking costs of reducing field size Euros 

Opportunity cost lost (lost income on reduced yields) Euros 

Saved costs (reduced inputs) Euros 

Employment changes Hours/person 

Box 58 – AEMBAC Project: Identification of farms’ agri-environmental accounting systems related to 

the agri-environmental measures in Chianti, Italy 

To keep the paper work to a minimum, it is strongly recommended to focus only on the most important and easilyreported 

data. The analysis carried out (e.g. state indicators describing the performance of the environmental function at 

farm level and their relative EMR values) helps in the construction of the indicator for the accountability but here other 

indicators are also utilised. The guidelines suggest employing three classes of data related to the environment, to the 

agricultural practices and to the socio-economic aspects. However, in the following tables we decided to consider few 

aspects connected with socio-economic aspects, useful to increase, in our opinion, the awareness of farmers on 

environmental data. 

For any agri-environmental measure we will suggest indicators able to be monitored by farmers once in a year. Some of 

those indicators will be specific for the related measure; others will be more comprehensive: total field size, field size 

under measure, cost of implementation and the presence of swallows. 

BirdLife International estimated that the European population of swallows has fallen by 40% between 1970 and 1990. 

Many are the causes: the intensification of the agricultural practice reduced the quantity of hedgerows, ditches and grass 

fields, (their natural hunting area); the use of pesticides damages the swallows also indirectly by killing small insects 21 

(their food); the restoration of rural buildings (as sheds) does not permit them to nest. (Tucker & Heath, 1994) 

21 Every day a barn swallow hunts insect for 7-8 times its weight, for a total of about 170gr of insects. 

128 

Year 

3 

Year 

…. 

Year 

9 

Year 

10

Agri-environmental measures on Grass Soil cover 

This measure consists of producing a lateral grass strip at least 3m wide as well as of grass soil cover between vine rows 

and olive groves both already existing or newly introduced and in maintaining them for at least five years. 

The agri-environmental measure’s accounting scheme is based on the information of the following table. 

In the agri-environmental report no reptile is considered but only active swallow nests’ presence (Hirundo rustica), 

because they are easy to be monitored and, at the same time, they can help the farmer to discover the direct effects of 

the agricultural practice on biodiversity. Such an indicator is indirectly related to the grass soil cover and can also be 

used for other measures. 

Plant diversity indicators are also avoided here, because in five years (last of the measure) it is very unlikely that 

orchids or other key species will be found in vineyards. The only indicator able to be monitored and connected to the 

landscape is a change in grass colour in different seasons. Applied to Soil erosion indicators, the visual estimation of 

soil grass cover, made by the farmer, can be utilised for the calculation of C factor in the USLE model. 

It would be significant at the moment of the application of this measure to provide the farmer, together with the 

agricultural report, with an educational handbook containing the necessary information to implement and report agrienvironmental 

data. It would be interesting, for example, to show different pictures of Barn Swallow nests (Hirundo 

rustica) and Houses Martin 22 nests (Delicon urbica) as a lesson of biodiversity, (see below). 

This is the scheme to be fulfilled every year: 

Tab. 55 - Agri-environmental data at farm level Unit of Year 1 Year 2 Year 3 Year 4 Year 5 

for grass soil cover 

measurement 

Total Field size ha x x x x x 

Field size under measure / UAA 

BIODIVERSITY 

% x x x x x 

How many active* swallow nest are in the farm? Number x x x x x 

How many young fledged swallows are born in your farm Number 

each year? 

LANDSCAPE 

x x x x x 

Is the grass growing without problem? Yes/NO x x x x x 

Is there some surface where the grass is scarce or yellow? Yes/NO x x x x x 

Can you define the surface affected by the problem? < % 

30%, 30-50%, 50-70%, >70% 

SOIL 

x x x x x 

Can you define the % of grass soil cover? 

10%, 30-50%, 50-70%, >70% 

SOCIOECONOMIC DATA 

x x 

Hours spent on planting and maintenance of grass soil Hours/ha 

cover 

x x x x x 

Costs of operation (Labour include) Euro/ha x x x x x 

* active nest = nest regularly occupied during breeding season, regardless of reproductive success’. 

22 

The house martin lives more in cities: it usually nest under the roofs. It is a common species but, like the barn swallows, it 

decreased in number. 

129

A guide to species identification for farmers - Birds / 1: Barn Swallow and House Martin 

These two species are common in towns and farmland, where they play an important role as specialized feeders of 

insects captured during flight. Only a few attention is required to identify the two species and their nests. 

Fig. 30 House Martin 

From above: white rump evident and contrasting with black upper-parts. Tail shorter and less forked than Barn 

Swallow. From below: all under-parts white, throat also. 

Nest: a rounded half-cup built on to a vertical surface, so close to the overhanging projection above that only a narrow 

entrance is present at the top. Nest generally found on outer walls of a building under the caves 

Fig. 31 Barn Swallow 

From above: all upper-parts blue-blackish, pointed wings, long and well forked tail with small white spots (only seen at 

closer range). From below: red throat contrasting with white breast (red appearing dark at distance). Nest: an open cup 

stuck against a vertical surface, but requiring some support. Nest generally found inside buildings, barns, sheds 

appearing more ‘muddled’ than House Martin’ one. 

3.7 Step 7 – Studying agri-environmental measures implementation: Definition 

of monitoring, evaluation procedures and contracts; analysis of administrative 

and transaction costs and overall economic and financial aspects 

In order to accomplish the development of the AEMBAC methodology, it was necessary to define the 

procedures to monitor and evaluate the effectiveness and efficiency of the agri-environment measures in 

reaching their policy targets. 

In case of implementation of AEMs, the information obtained through the monitoring and evaluation 

procedures has to allow to understand if the agri-environmental measures are effective as they have been 

developed, or have to be reoriented and ameliorated. 

3.7.1 Definition of monitoring procedures 

Two main objectives can be identified in relation to the definition of monitoring: 

• the first concerning the agri-environmental objectives of the measures (e.g. associated biodiversity or 

130

landscape benefits), but also the impacts that the implementation of the measure can exert on 

agricultural and socio-economics aspects. 

• the second regarding the operational objectives of the measures (e.g. number of demands to enrol 

presented, number of farmers enrolling the scheme, cost of implementing the measures, etc.) 

3.7.1.1 Monitoring on achievements of agri-environmental objectives 

To fulfil the first objective, the definition of monitoring requirements was carried out for environmental, 

agricultural and socio-economic aspects. The data identified as those to be gathered through the agrienvironmental 

accounting system, developed for the farm level (see section 3.6.7 above) and data to be 

gathered by experts on-farms and study area level, were analysed in relation to the overall agrienvironmental 

objectives to be achieved at the level of the area where the scheme should be implemented. 

The selection of what environmental objectives have to be monitored came out straightforwardly thanks to 

the methodology developed to build up locally tailored agri-environmental measures. In fact, by looking at 

the pressure/s addressed by the agri-environmental measure and at the correlated impacts (identified in the 

matrix developed in Step 4) on relative state indicators (these latest analysed for agro-ecosystem and farm 

levels Step 2), researchers immediately identified the most important environmental aspects to be monitored. 

On the agricultural production side, the indicators to be defined in order to be monitored were those directly 

affected by the implementation of the agri-environmental measure proposed, and varied from production 

quantity and quality, to inputs used, from technological innovations applied to land use conversions, etc. 

Such indicators were already analysed in Step 3 for the analysis of the local agricultural system, in section 

3.4.3 to identify agri-environmental practices and in section 3.6.7 above. 

On the socio-economic side, the indicators more directly affected by the implementation of the agrienvironmental 

measure should also be monitored. These, as the others indicators to be monitored, will 

depend on the agri-environmental measures developed, however aspects such as farm income, employment, 

farmers environmental awareness, training, etc. are likely to be common to many agri-environmental 

monitoring schemes. These aspects were already analysed In Step 1, Step 6 at area level and in Step 2 at 

farm level. Here they were just “converted ” into socio-economic indicators to be monitored. 

Researchers made a list of data requirements to be monitored at farm and study area levels and commented 

on these through the use of the state-pressures matrix. Please note that an overall estimation of monitoring 

costs relative to the agri-environmental measures proposed was provided in Step 7, section 3.7.4 when the 

analysis of administrative costs relative to the AEMs developed was carried out. 

Below are two examples (built on those of sections above) of what kind of environmental data to be 

monitored are presented for the refugium and landscape aesthetic functions respectively: 

Box 59 – Monitoring Agri-environmental Measures 

Example 1: Environmental data monitoring on biodiversity function 

At Farm Level, Monitoring of the data gathered by farmers following the accounting system and integrated by other 

field monitoring on biodiversity by experts whereas necessary (some indicators to be monitored could be too 

“technical” for non-experts) 

At an Area level, if the measure proposed is addressing the pressure “management of semi-natural habitats and 

hedgerows”, envisaging that hedgerows of a certain type and dimension should be present in at least X% of the total 

field margins in the area, the matching of this target will have to be monitored at this level. Further monitoring on the 

expected environmental benefits will have to be carried out at the area level. So, for instance if the measure proposed is 

thought to be sufficient to reduce the gap (detected in Step 2) on the state indicator “species abundance” at the area 

level, when applied for 5 or 10 years, at the end of the period, the monitoring should allow the success of the 

implementation of the agri-environmental measure in reaching the relative environmental goal to be assessed. This 

means that “species abundance” should also be monitored (see the example in fig. 32a below where the pressures 

addressed by the agri-environmental measure and the correlated state indicators, corresponding to those to be 

monitored, are in italics). 

131

Fig. 32a Pressure addressed by the agri-environmental measure and the correlated state indicators to be 

monitored (in italics) 



(AE) pressure indicators 

(data from questionnaire and 

bibli hi /fi ld h) 

Example 2: Environmental data monitoring on landscape aesthetic function 



At Farm Level, Monitoring of the data gathered by farmers following the accounting system and integrated by other 

field monitoring on biodiversity by experts (some indicators to be monitored could be too “technical” for not experts). 

If the measure proposed addressing the pressure “management of fields” has been developed in order to maintain or 

enhance the landscape aesthetic quality of agri-ecosystems in the area, through a maximum field size allowed, then the 

matching of this target will have to be monitored at the farm level. 

At the area level, further monitoring of the expected environmental benefits will have to be carried out. So, for instance 

if the measures proposed is thought to be sufficient in reducing the gap (detected in Step 2) on the state indicators 

“traditional land use”, “traditional crops diversity”, “Ecosystem patchiness” and “habitat diversity/heterogeneity” at the 

area level, when achieving the desired field size, at the end of the period of implementation, the monitoring should 

allow the success of the implementation of the agri-environmental measures in reaching the relative environmental goal 

to be assessed. This means that “traditional land use”, “traditional crops diversity”, “Ecosystem patchiness” and “habitat 

diversity/heterogeneity” (in red italics) should be monitored. 

132 











Ecosystem and/or 

agroecosystem (NE) state 

indicators 


Plant genetic and species diversity 


Key species abundance - 

Number of varieties for each plant specie - 


Key species abundance - - - 

Number of rare species - 

Number of endemic species - 


Ecosystem quantity as % of the 

area unit 

Ecosystem quality as 

- - 

Biotopes/Habitats variability and 

heterogeneity 

- + 


habitats 



- 

S 0 0 NS -2 -2 0 -1 A NS -2 

c) Irrigation and water manage 





S=Sustainable no impact significant impact 

NS=Not Sustainable low impact high impact 

A=Absent 



Fig. 32b Pressure addressed by the agri-environmental measure and the correlated state indicators to be 

monitored (in italics) 

Aesthetic function 


Ecosystem and/or 

agroecosystem (NE) 

indicators t t 

(data from bibliographic/field 

Landscape h) puntual and linear 

fNumber t of isolated trees in fields 


(AE) pressure indicators 

Data from questionnaire 





133 




Length of stone walls 

Length of natural corridors - 

Landscape coherence 

Traditional land use 

Tradition crops diversity on farm 

Traditional rotations 

Ecosystems and habitats 

di it 

Ecosystem patchiness - 




b3) Management of field 

b4) i Livestock density 

(LU/h ) 

(stone walls, isolated trees, etc. 

c) Irrigation and water 

management 

Biotopes/Habitats variability and 

heterogeneity 

- 

Ranking tiers of agricultural sustainability 

- 

ireference to pressure indicators S 0 0 NS 0 0 -2 0 -1 A 



c3) Drainage/diversion/extractio 

no impact significant im 

low impact high impact 

S=Sustainable 

NS=Not Sustainable 

A=Absent 

+ - 

- 

- 

- 

-

Fig. 33 – AEMBAC project: Identification of monitoring indicators by looking at agri-environmental measures 

proposed on pressure and state indicators concerning the Refugium function in the study area Greifensee, 

Switzerland 


State Indicators 

Pressure indicators 

Percentage of area of organic 

production 

Cultivated grassland intensity 

Cultivated arable land intensity, 

Mechanical stress 

Plant species indicators 0 - - - - + 0 0 - - 0 

Animal species indicators 0 - - - 0 - + 0 0 + - - 0 

Umbrella plant species 0 - - - 0 0 + - 0 - - 0 

Umbrella animal species 0 - - - 0 - + - 0 + - - 0 

Area of biotope types valuable 

0 - - - - 0 + - 0 - - 0 

for biodiversity 

Linear landscape elements 0 0 - 0 0 0 - 0 0 

Punctual landscape elements 0 - 0 0 0 - 0 0 

Natural Capital Index 0 0 0 0 0 0 - 0 

Accessibility 0 - - 0 0 0 0 - 0 0 

Fragmentation 0 

SUSTAINABILITY 0 NS NS NS NS 0 0 NS 0 0 NS NS 0 

Tiers of sustainability 0 -2 -2 -2 -1 0 0 -1 0 0 -1 -1 0 

3.7.1.2 Monitoring on agri-environmental measures functioning 

Nitrogen balance on the farm 

In order to assess the rate of implementation and the functioning of the agri-environmental measure some 

data on its operational aspects have to be identified in order to fulfil monitoring requirements (see tab.58 

below to be considered not exhaustive). 

This is the only type of monitoring usually carried out by administrations at present. 

Tab. 56 - Operational indicators Unit of 

Area eligible for the measure 

measurement 

Square meter 

or ha 

Area covered by the measure Square meter 

or ha 

Number of holdings in the area Number 

Number of eligible farmers Number 

Number of beneficiaries Number 

Number of enrolled farms/number of farms in 

the area 

Ratio 

Main type of farms enrolling the scheme (size, Type of farms 

structure, production typology, etc.) 

Average payment per unit Euro 

Total payments Euro 

134 

Year 

1 

Phosphate balance on the farm 

Year 

2 

Soil cover index of arable crops per 

farm 

Year 

3 

Diversity of land use on the farm 

Year 

4 

Number of arable crops and area share 

of major crop species 

Plot size 

Year 

5 

Relation annual/perennial crops 

Year 

6 

Percentage of area and number of 

ecological compensation areas 

Year 

7 

Perc. of area with synthetic chemical 

pest and disease control 

Year 

8 

Livestock density 

Year 

9 

Year 

10

3.7.2 Evaluation procedures 

The evaluation procedures are meant to verify the relevance, effectiveness and efficiency of the agrienvironmental 

measures proposed (as well as other programmes under reg. 1257/99). Evaluation is usually 

carried out by independent advisors, local administrators and Commission services. Obviously in AEMBAC 

these evaluations could not be carried out given that the project was not developed to implement, but only to 

identify local AEMs. 

It was, however, useful to have a clear idea on evaluation procedures in order to select the most appropriate 

data to be monitored in the section above and to assess how the AEMBAC methodology was fulfilling 

evaluation procedures requirements. 

In Box 60 below, some aspects of evaluation procedures are described for this scope. 

In the following sections researchers were asked to highlight the feasibility of the AEMBAC methodology in 

reference to the evaluation requirements relative to effectiveness and efficiency aspects. 

Box 60 – Evaluation procedures 

Reg. (EC) 1750/1999, art.41, points out the obligations for Member States to carry out monitoring and evaluations 

reporting. Art.49 of Reg. (EC) 1257/1999 (replaced by Reg. (EC) 445/2002), states that the evaluation of agrienvironmental 

measure has to follow the rules defined in Reg. (EC) 1260/1999 arts. 40-43 and it has to cover 

environmental, socio-economic and agricultural aspects. 

The evaluation process is usually divided in 5 steps: structuring, data collection, analysis, judgement and reporting. 

Regarding structuring (i.e. what are the effects to be evaluated, criteria and observation tools,) and data collection 

system, the AEMBAC methodology it is clearly of help in defining both. Previous WPs have analysed in detail the 

impacts to be addressed by the agri-environmental measures, and what are relevant data to be gathered (see wp3 and 

wp4) following the criteria of assessing sustainability of the local agricultural system in relation to some environmental 

functions performance. For what concerns the analysis, having assessed baselines (e.g. EMR values for state indicators) 

already in wp3, pays back now in terms of having a benchmark for comparisons against which the effectiveness of agrienvironmental 

measures can be measured. This will consequently facilitate the formulation of a judgement on the 

results of implementation of measures and its reporting for what regards agri-environmental objectives to be achieved. 

Evaluation has to be ex-ante, mid-term and ex-post and has to consider the relevance, the effectiveness and the 

efficiency of the agri-environmental measure proposed. 

Ex-ante evaluation concerns mainly the relevance and validity of the state and pressure indicators selected for 

describing the analysed environmental function and the local agricultural system respectively, and the agrienvironmental 

objectives and measures presented. This evaluation is supposed to be carried out by independent experts 

and Commission services to assess the validity of the agri-environmental measures presented by the local 

administrations. 

Mid-term evaluation assesses the effectiveness and efficiency of the agri-environmental measure by looking at the first 

measurable results 23 and the correctness of measures implementation. It offers the opportunity to eventually reorient the 

objectives and tools of the measures. 

Ex-post evaluation has to assess both the effectiveness and efficiency of the implementation of the agri-environmental 

measure. 

For these last two types the evaluation of effectiveness and efficiency is the basis of the evaluation process and has to be 

carried out by independent advisors, local administrators and Commission services. 

23 

Please note that it maybe often the case that some results would materialise only time after the agri-environmental 

measure implementation. 

135

3.7.2.1 Effectiveness 

In order to assess the effectiveness of the agri-environmental measures, farmers, local administrators, 

independent evaluators and Commission officers, should be supplied with the necessary information 

regarding environmental objectives to be reached by the agri-environmental measure and against which to 

compare and evaluate the results of agri-environmental measure implementation. 

The AEMBAC methodology has been developed in a way that facilitates the evaluation of effectiveness on 

achieving agri-environmental targets. In fact by following the environmental problems/opportunities oriented 

approach of AEMBAC, already in phase one, state indicators describing environmental function 

performance were defined, their actual and EMR values assessed (to be used as a baseline for monitoring), 

the impacts resulting from local agricultural system were identified, and the correlation with agricultural 

pressures envisaged. Building upon this information the agri-environmental policy targets and measures were 

proposed in Step 6, in such a way that they were supposed to reduce the negative gap between actual value of 

state indicators and their EMR values (negative impacts) or enhance further the positive gap between EMR 

and actual values (positive impacts). 

So, for instance, starting from a current situation ranking Tier –1, if the policy target for the agrienvironmental 

measure of example 1 (see section above) was set at Tier 0 after the first 5 years of 

implementation, and Tier +1 after ten years of implementation, evaluators would automatically have the 

intensity of the pressure and the envisaged correlated impact against which to make their evaluation of the 

achievement of the environmental targets. 

Tier +2 = Presence of high positive impact (red)= 20% of existing UAA reconverted to (semi-)natural 

habitat 

Tier +1 = Presence of positive impact (yellow) = 5% of existing UAA reconverted to (semi-)natural 

habitat 

Tier 0 = respect of EMR = agriculture ecological sustainability = no impacts or only low 

positive/negative impacts exerted by agricultural practices = field margins with hedgerows 3 meters wide 

for at least a length equal to 30 % of existing total field margins in the area, 

Tier -1 = Presence of negative impact exerted by agricultural pressures (yellow) = current situation = 

field margins with hedgerows 3 meters wide for at least a length equal to 10 % of existing total field 

margins in the area 

Tier –2 = Presence of high negative impact (red) = very sporadic field margins with hedgerows 

It is important to point out the advantages that the AEMBAC methodology offers for the assessment of 

effectiveness in the case of agri-environmental measures implementation on the following points: 

• Identification of indicators to be monitored; 

• Definition of locally tailored baselines against which to evaluate the effectiveness of AEMs proposed; 24 

24 It is worth also pointing out how the AEMBAC methodology will facilitate comparisons to be carried out in the evaluation process 

following the three main types of comparisons proposed by the Commission (European Commission, STAR Document VI/12004/00 

Final and STAR document VI/43517/02): 

• Temporal: having selected the agro-environmental targets on the basis of the analysis of positive/negative impacts detected 

as gap between actual and EMR values for relevant indicators, allows to have a clear idea on what is the starting situation 

against which to compare the results achieved after 5, 10 or more years of implementation; 

• Counterfactual situation: having identified relevant state indicators to measure the performance of the environmental 

function of interest, allows to measure the same indicators also in farms not enrolling in the agro-environmental scheme 

and compare the results achieved in those farms who instead are implementing the measure. 

• Benchmarking: having assessed Environmental Minimum Requirements values for relevant state indicators allows a direct 

comparisons with the values of the same indicators after agri-environmental measure implementation, so providing a direct 

measure of its effectiveness both at farm and area levels. Moreover this comparison will also serve to assess the possible 

presence of exogenous factors in changing the value of state indicators to be evaluated (see below in effects 

contextualisation), or if this would not be the case and the measurement of their actual or EMR values was not assessed 

with sufficient scientific precision, it will provide useful new scientific information to re-orient the analysis. 

136

• Whereas baselines were determined without enough scientific precision because of lack of data, the 

AEMBAC methodology will signal the need for further scientific research to be carried out on specific 

topics; 

• Definition of objectives to be reached and evaluated; and 

• Transparent logic on how those objectives have been defined and evaluation carried out; 

The socio-economic effectiveness of the agri-environmental measures also has to be assessed. These impacts 

are usually called collateral effects (European Commission, document VI/12004/00 Final). The evaluation of 

these aspects concerns the analysis of combined effects (direct and indirect) resulting from the 

implementation of the agri-environmental measures: 

• Regarding the agricultural data, the results achieved after a certain time span of implementation have to 

be checked and interpreted against the envisaged changes on agricultural systems such as productivity 

and reduced yields, reduced inputs, land use conversion, etc. (These aspects were already taken into 

account in general in previous Step 6). 

• Regarding socio-economic data, the results achieved after a certain time span of implementation have to 

be checked and interpreted against the envisaged changes. The aspects to be evaluated depend on the 

agri-environmental measure implemented and concern aspects such as employment, environmental 

growing awareness, income, competitiveness and markets, etc. (These aspects were already taken into 

account in general in previous Step 6) 

Other very important issues to be considered in assessing the feasibility of the AEMBAC methodology for 

evaluation procedures were: 

1. Synergies/conflicts in achieving the agri-environmental policy targets with other agricultural and 

rural development policies, and other socio-economic sectors’ policies: 

When proceeding with the evaluation of effectiveness of the agri-environmental measure, it is important to 

acknowledge also the possible effects that other factors could have on the achievement of the policy targets. 

In fact the agri-environmental measures will not be implemented in a vacuum, but rather in very complex 

realities where other factors such as different policies operate. Some of these factors capable of influencing 

the effectiveness of agri-environmental measures implementation have been dealt with in Steps 1, 3 and 6. 

2. Collateral benefits on environmental multifunctionality 

By the same token it may be the case that the results of the implementation of an agri-environmental measure 

for a specific environmental function, would bring also benefits to the performance of other environmental 

functions. This could be the case, for instance, if the maintenance of a semi-natural habitat for the 

performance of the refugium function, simultaneously brought benefits to the performance of the aesthetic 

quality of the landscape (as it is in the two examples above in section 3.7.1), or to the soil erosion function 

and so on. In this case to evaluate only the targets achieved for the refugium function would underestimate 

the real benefits of the implementation of the agri-environmental measure. 

It was therefore appropriate for researchers to indicate what were other environmental multifunctional 

benefits which could be expected to materialise by the eventual implementation of the agri-environmental 

measures proposed (e.g. planting hedgerows on hill slopes will enhance biodiversity and reduce the water 

run off). (These aspects were already taken into account in general in previous section 3.4.5) 

3.7.2.2 Efficiency 

Efficiency concerns the analysis of the most important elements of the measure implemented through the 

relationships between key outputs (possibly results) and the inputs necessary to produce them (EU Document 

137

VI/43517/02). It is worth pointing out that as for effectiveness, also for efficiency the evaluation could be 

meaningful only once the agri-environmental measure has fully expressed its results. 

It was suggested to separate the analysis of the efficiency in achieving the objectives of the agrienvironmental 

measure from the efficiency in administering it. It was considered important to assess the unit 

of costs for both the above-suggested analyses, and compare these with a suitable baseline, but lack of data 

impaired this analysis. 

As regards efficiency in achieving the agri-environmental objectives, the ideal benchmark against which to 

make comparisons is the costs resulting from the implementation of other measures to achieve the same 

objective. A probable feasible benchmark for efficiency comparisons would be the cost unit of agrienvironmental 

measures already implemented in the area. These costs however would have to be weighted 

against the importance of the results achieved. This is probably a tricky point because it is unlikely that in the 

same area the existing agri-environmental measure would have presented measurable results as it is instead 

proposed for those developed through the AEMBAC methodology (i.e. the measures proposed are more in 

depth and targeted and it is more likely that their unit costs would be higher, but on the other hand, their 

effectiveness would also probably be greater). 

As regards efficiency of the administering of the agri-environmental measure (this point is treated in more 

detail in section 3.7.4), the cost unit could probably be measured against the benchmark of the average 

administrative cost unit of other public policy implemented by the same administration. It must, however, be 

borne in mind, that analysis of efficiency also in this case should take into account the effectiveness of the 

implementation of results (more effective policies would probably have higher administering costs). 

Conclusions on the feasibility of the AEMBAC methodology for the evaluation of the agri-environmental 

measure have been drawn out linking the results on terms of effectiveness and efficiency. 

3.7.3 Studying procedures for drawing up contracts for the supply of environmental goods and 

services by farmers 

On the basis of the agri-environmental measures which were identified in section 3.6, and fine tuned taking 

into account stakeholders points of view, it was then possible to identify the procedures for drawing up 

contracts to deliver agri-environmental goods and services for the local situation. 

Following up the three approaches identified in section 6.5, the following situations regarding the need for 

issuing contracts to deliver the agri-environmental goods and services were envisaged: 

Command and control: 

No needs for contracts but of 

regulations or laws (e.g. EU Nitrate 

Directive) 

Fig. 34 Agri-environmental policy instruments 

Delivering Agri-environmental goods 

and services 

Quasi-market: 

This type involves contracting 

between governments and farmers 

(e.g. UK Countryside Stewardship 

Scheme) 

138 

Market: 

This type involves an exchange of agrienvironmental 


between Producers and Consumers 

through market mechanisms (e.g. 

Organic production)

As shown in figure 34, in the case that from Section 6.5, the approach selected to deliver the specific agrienvironmental 

good or service (i.e. the instrument identified to achieve the policy target) would have been 

one of command and control, it was obvious that no contract between governments and farmers would have 

been needed. Similarly also for the case that the approach selected was that of using the market mechanism, 

contracts between governments and farmers would not have been necessary (some caution regarding this has 

to be pointed out because it may be the case that certain quality standards or codes of practice to operate in 

the market would be set up by agreements between Institutions and Farmers Associations as is the case for 

organic product labelling). 

On the contrary, if the approach selected to deliver the environmental good and/or service could be included 

in the category of quasi-market then a situation where farmers act as suppliers of the agri-environmental 

goods or services and governments act as consumers (i.e. representing the interests of the client “public 

society”) would have materialised, so requiring some type of contract to be issued. 

Therefore in the case of quasi-market, the most suitable type of contracts for the “purchase” by governments 

of the specific agri-environmental good or service delivered by farmers in the local situation was studied. 

In carrying out this analysis, some crucial aspects in defining the most suitable type of contract were pointed 

out by looking at the “what, where, who and when” characteristics of the object of transaction between 

farmers and public administrations. 

What: Starting from what was the agri-environmental measure defined in Step 6 (e.g. planting hedgerows, 

reducing fertilisers or pesticide use, maintaining a semi-natural pasture or a stone wall, etc.), it was necessary 

to define clearly the object of the transaction and how this had to be written down in the contract. This could 

range for example from just a constraint on quantity and quality of pesticides to be used or simply on not 

cultivating some hectares on the farm, to more complex and integrated operations such as respecting specific 

rotations and mowing operations in the fields. 

Depending on the complexity of the operation also some training hours could be envisaged in the contracts 

beside a well-defined list of undertakings to be carried out at specific times. 

For each operation requiring the farmers to do or deliver something, the corresponding payment had to be 

stated clearly in the contract, linking it to the appropriate unit of measurement (e.g. Euros per meter length of 

hedgerows 3 meters wide planted). 

Also the routine and occasional controls of compliance had to be considered in the contracts, envisaging the 

availability of farmers to collaborate, for instance by keeping an environmental accounting book (see section 

3.6.7 above) and allowing inspectors within their farms. 

Penalties for non-compliance also should have been clearly stated and linked to the object of transaction. 

Eventual further conditions for enrolling in the agri-environmental measure (such as following an 

environmentally friendly general behaviour and respecting existing relevant legislation), as well as 

specifications to collateral activities ineligible for enrolling, must be stated in the contracts. 

Where (on-farm): depending on the spatial characteristics of the agri-environmental measure (zonal or 

horizontal measures) identified in Step 6, and of the good or service to be exchanged, contracts had to 

address where the agri-environmental measure was to be implemented within the farm. In fact some 

measures may interest specific sites (e.g. contracts addressing only specific ecosystems such as riparian ones 

or planting hedgerows at fields margins) or on the contrary the whole farm area (e.g. reduce tilling operation 

or fertilizers-use). 

Who: Depending on the social characteristics of the local community it could have been possible to deal 

with a group or associations of farmers (e.g. the French system of Contracts Terretoriaux d’Exploitation) 

instead of with single farmers. Clearly the former case would allow savings on transaction costs given that 

the government agency would deal with fewer actors instead of many) and probably also savings on 

compliance controlling costs, being part of these would be passed on to the farmers association side. 

When: In the contract it was also important that the time of implementation of the agri-environmental 

139

measure would have been put forward explicitly as well as the time of the operations to be undertaken and 

the time of payments to be done. 

For each agri-environmental measure to be implemented through the quasi-market approach, researchers 

were asked to develop the following contract format type: 

Tab. 57 – Agri-environmental measure’s contract type 

Agri-environmental 

measure title: 

Implementation 

requirements to 

achieve the desired 

tier: 

Object of transaction 

(what): 

Agricultural practice 

required 

(undertakings and/or 

constraints): 

Eventual further 

collateral 

conditions/practices 

for enrolling 

Compensation paid 

for income foregone 

(per meter/square 

meter/ha etc): 

Payments for 

additional costs 

incurred (per 

meter/square meter/ha 

etc): 

Incentive paid (per 

meter/square meter/ha 

etc): 

Implementation site 

(where): (whole farm 

or specific sites) 

Contracting subject 

(who): 

(single farmer or 

groups) 

Time plan of 

implementation 

(When): 

Inspections on farms 

Penalties for noncompliance 

Relevant 

Environmental 

legislation related to 

the AEM 

Other 

Tier –1 

(to be considered only 

if politically 

determined “Good 

Farming Practice” is 

coincident with Tier – 

2 despite this not 

being ecologically 

sustainable) 

Tier 0 

(to be considered only 

if politically 

determined “Good 

Farming Practice” is 

coincident with Tier – 

1 despite this not 

being ecologically 

sustainable) 

140 

Tier +1 

(real ecological 

supply of 

environmental goods 

and services) 

Tier +2 

(real ecological 

supply of 

environmental goods 

and service)

Box 61 - AEMBAC project: Issuing contracts: example from the Jahna study area, Germany 

The most important kind of intervention for achieving environmental improvements that are above GAP is the payment 

of premiums in combination with supportive measures such as information and advisory services or the provision of 

relevant tools (fertiliser planning software; calculation sheets). 

Typical examples where incentive payments appear most suitable are the re-conversion of arable land to grassland, 

incentives for wider crop rotations and an increase in cropping diversity, incentives for a reduction in field sizes, the 

maintenance new biotopes, soil conservation tillage, the lowering of agri-chemical use and the establishment of buffer 

strips. 

In all these examples, the necessary adjustments go beyond to what is required in regulations or laws (e.g. the EU 

Nitrate Directive and its national implementation). Ordinary market mechanisms again will not work alone because in 

all these instances we are dealing with public goods (i.e. they are not operational in private markets). Organic farming is 

an example where a market mechanism significantly contributes to achieving environmental improvements (because 

consumers pay more for organic products and this in turn leads to some compensation of the higher costs of organic 

production). 

It follows that we are clearly in a situation of a quasi-market that requires contracting between governments and 

farmers. In this situation the farmers have the role of suppliers of agri-environmental goods or services and the 

government represents the interest of public society. 

The relationship between the farmer and the government is expressed in a contract that is to be issued. The contents of 

the contracts must comprise the kind of management services and environmental goods to be delivered, the spatial 

characteristics of the goods and services (e.g. a particular field, the entire utilised agricultural area, the agricultural 

landscape at communal level), the precise definition of the contract parties (commune, district, state on the one hand, 

and farmer or farmers group on the other), and finally, the time of implementation and the time of payments. Table 60 

provides an example from the Jahna study area. 

Tab. 58 - Specification of the contracts in the Jahna study area: (1) Lowering agri-chemical use and (2) 

Establishment of buffer strips (two examples) 

Aspect Kind of information Example (1) Example (2) 

What Kind of management services Lowering agri-chemical use 

and environmental goods to 

be delivered 

Establishment of buffer strips 

Corresponding payment 114 € per hectare and year 92 € per hectare and year 

Documentation and control Fertiliser accounts and field records; Map and field records; random field 

receipts for fertiliser purchases visits (checks) by inspectors from local 

administration or accredited advisors 

/agencies 

Where Spatial characteristics of the Particular field or the entire utilised Along rivers and valuable biotopes; to be 


agricultural area; to be clearly clearly specified in map 

specified in farm level field parcel 

register and administration level 

IACS 

Participation is only possible if land is 

located in assigned regions 

Who Precise definition of the Individual farmer and Federal state Individual farmer (or farmer group, e.g. 

contract parties 

(Saxony) represented by the regional Landschaftspflegeverband) and Federal 

administration (agricultural office) state (Saxony) represented by the 

regional administration (agricultural 

When Time of implementation and Cropping season (with 

office) or water authorities 

the Calendar year or, preferably, multi- 

time of payments 

possibility of multi-annual annual contracts; payment after contract 

contracts); payment after contract has been signed 

has been signed 

Source: Karlheinz Knickel (subcontractor); IACS: Integrated Administration and Control System 

141

3.7.4 Analysis of administrative and transaction costs. 

Depending on the type of instruments used in the agri-environmental measure, on the ownerships of rights of 

resources use (e.g. to pollute or to not be polluted), on the level where “good farming practices” references 

are politically set in order to be entitled to receive agri-environmental payments (e.g. coincident or not with 

the ecological sustainability level for the environmental performance set at tier 0 in AEMBAC), on the level 

of asymmetric information, etc., different administrative and transactions costs may arise. 

For each type of approach used (i.e. command and control, quasi-market and market) the detailed assessment 

of the fixed-variable entities of relative private-public costs (i.e. from the side of the farmer and of the 

institution) amongst the following administrative and transaction issues was necessary 25 : 

Agri-environmental measure design: these costs refer to scientific research and information gathering 

associated costs, integration of ecological and socio-economic information, definition of agri-environmental 

measures, etc.; 

Application to EU for approval of agri-environmental measures proposed and reporting (quasi-market 26 

approach): these costs refer to the drafting of the proposal, submitting to EU and following the process with 

EU liaison Officers, etc.; 

Gathering/giving information and advice from/to farmers, institutions and general public (command and 

control, quasi-market and market approaches): These costs refer to consultation with farmers, 

environmental, consumers associations and the like, on the draft programme, promotion of the measure (farm 

visits and publicity, extension services, training to farmers), information gathering about the agrienvironmental 

good and/or service in quasi-markets and markets 27 approaches, etc.; 

Dealing with applications (quasi-market approach): these costs refer to provide assistance to applicants, 

gathering applications submitted, examination and approval, etc.; 

Contracting and management of payments (quasi-market approach): these costs refer to negotiations with 

farmers, administrations and control of payments, etc. 

Compliance controlling (command and control, quasi-market and market where standards and certifications 

are set up): these costs refers to farm inspections, monitoring by experts by remote sensing, farm 

environmental accounting cross checks, etc. (see also wp12); 

Evaluation of policy effectiveness (command and control, quasi-market and market approaches): these costs 

refer to evaluation of impacts on environmental, agricultural and socio-economic aspects (see wp12), writing 

the evaluations reports, etc. 

Feedback on policy design and development (command and control, quasi-market and market approaches): 

these costs refer to the rethinking of the agri-environmental policy design after implementation has been 

evaluated. 

For each agri-environmental measure to be dealt with, through one or more of the three types of approaches 

proposed (Command and control, quasi-market and market), researchers were asked to assess and comment 

in detail on the above administrative and transaction fixed and variable costs 28 , using the table below: 

25 Under Reg. (EC) 1257/99 only agri-environmental measures based on voluntary agreements rewarding farmers for providing 

environmental goods and services going beyond “Good Farming Practices” are envisaged, and therefore only the approach “quasimarket”, 

in principle would need such analysis. However, in AEMBAC it was decided that also other types of instruments would be 

considered to deliver agri-environmental goods and services (such as command and control and markets), and therefore the costs 

assessment has to be carried out also for these. 

26 Following the above this kind of expenditure would occur only when local government has to submit application to EU (i.e. quasi- 

market approach). 

27 Please note that gathering information costs would be incurred in also privately by farmers both in quasi-market and market 

options and by consumers in market option. 

28 Fixed costs: permanent personnel/hours, durable equipment, office rent, overheads, personnel training hours, travel costs, etc. 

Variable costs: Temporary personnel employed (e.g. Consultants)/hours, extra equipment hired, extra office space, overheads, 

personnel training hours, travel costs, etc. 

142

Tab. 59 – Administrative and transaction costs 

Agri-environmental measures 

title: 

Agri-environmental measure approaches (Assessment of the costs for the feasible 

instruments) 

Administrative and Command and control Quasi-market 

Market 

transaction costs 

(Public costs) 

(Public and private costs) (Private and Public costs) 

Agri-environmental measure Fixed costs: 

Fixed costs: 

design 

Variable costs: 


Application to EU for approval 

Fixed costs: 

of agri-environmental measures 

proposed and reporting 


Gathering/giving information Fixed costs: 

Fixed costs: 

and advice from/to farmers, 

institutions and general public 



Dealing with applications Fixed costs: 


Contracting and management 

Fixed costs: 

of payments 


Compliance controlling Fixed costs: 

Fixed costs: 



Monitoring policy effectiveness Fixed costs: 

and evaluation 


Feedback on policy design and Fixed costs: 

development 


Total administrative and Fixed costs: 



Fixed costs: 


Fixed costs: 


Fixed costs: 


143 

Fixed costs: 


Fixed costs: 


Checking Market functioning 

Fixed costs: 


Fixed costs: 


Fixed costs: 


Fixed costs: 


Box 62 - AEMBAC project Analysis of administrative and transaction costs in the Dutch case study, 

Netherlands (for references in the box see WU-NL report) 

This section aims to quantify the administrative and transaction costs 29 that arise as a consequence of the 

implementation of the proposed agri-environmental measures. Transaction costs can be considered as the costs of 

running the economic system (Williamson, 1985); goods or services being transferred across a technologically 

separable interface (Williamson, 1981). Basically, they comprise costs of information gathering, contract making and 

control. In the case of agri-environmental policy, such transactions are organised through the use of contracts, which 

have been discussed in section two. The presence of transaction costs causes certain transactions not to be carried out, 

that otherwise would have been, because costs of these transactions do not outweigh their benefits. This explains the 

absence of private markets for agri-environmental goods and public goods in general. Government intervention is 

therefore desirable and ‘should be structured to remove impediments to voluntary transactions, especially by reducing 

transaction costs’ (Coase, 1960). 

As a result, when transaction costs are decreased, resource allocation will become more efficient. This decrease 

demands an adaptation of the institutional arrangements that cover the relevant resource. In the case of agrienvironmental 

policy this implies that the contracts used should be set up in such a way that transaction costs are 

minimised. However, the issue is not to minimise transaction costs solely, but to minimise the total costs of achieving a 

specific objective. When only transaction costs are minimised, the precision of a contract may decrease and the 

transaction will be less effective. ‘Hence there is a trade-off to resolve: transaction costs should be optimised jointly 

with other costs (namely payments to farmers) to fulfil all the objectives of policy-making’ (Falconer et al., 2001). It 

might not be beneficial to decrease transaction costs by for instance cutting on monitoring efforts when the resulting 

costs of lost precision are higher (due to an increased number of violations of the terms of contract). 

Transaction costs – by their nature – are not incurred by only one party, but instead by both the government and 

farmers. Both parties will have to spend time on for instance information gathering and administrative tasks. For this 

reason, this analysis of transaction costs includes both farmers’ and government’s transaction costs. 

A general problem that we face when estimating transaction costs for the proposed measures is the selection of a 

reference situation. When the current situation is chosen as a reference, transaction costs of the proposed measures are 

very low, because the complete infrastructure for communication, implementation and monitoring is already in place 

29 From here on, when the term ‘transaction costs’ is used, this includes administrative costs as well.

under current regulations. The other way around, when the reference situation is one without any agri-environmental 

policy, transaction costs would be very high. The latter option does not seem to be very realistic although it offers a 

better insight into the absolute level of transaction costs of different policy measures. Here, we will focus on the first 

option, assuming that the following presentation of transaction costs of current regulations suffices to have a good 

overview of the absolute level of transaction costs. 

Mowing dates 

Farmers’ transaction costs: The mowing dates measure is based on contracts as they are currently applied in the SAN 

regulation. Farmers’ transaction costs of the SAN regulation have been studied by Polman (2002). In his survey among 

farmers in the Netherlands he assessed and monetarised the amount of time spent on contract-making before and after 

concluding a contract. This is one of four methods of determining transaction costs, described by McCann & Easter 

(2002). Tables 42 and 43 provide an overview of the results. Using the salary level from the collective agreement for 

the agricultural sector, approximately EUR 20/hour, it is possible to calculate transaction costs to the farmer. Onetime 

transaction costs equal EUR 180, while annual transaction costs equal EUR 50 (Polman, 2002). 

These results are slightly contrasting with a large survey among farmers in the Netherlands by Hilhorst et al. (2003) 

who estimate onetime transaction costs at EUR 214 and annual transaction costs at EUR 216. Although both studies 

have made use of the method of estimating the opportunity costs of time spent on transacting, especially the annual 

transaction costs differ quite a bit, see tables 62 and 63. 

Tab. 60 - Farmers’ onetime transaction costs of the current SAN regulation 

Category Average time involved 

(hours/contract) 

Costs according to 

Polman (2002) 

(EUR/contract) 

144 

Costs according to 

Hilhorst et al. (2003) 


Average 

Information gathering 1.8 36.00 N/A 39.40 

Analysis of possibilities 1.9 38.00 N/A 41.58 

Analysis of opportunity 

costs 

1.0 20.00 N/A 21.89 

Negotiation and 2.2 44.00 48.16 

discussion 

{214.00 

Finalising contract 2.1 42.00 

45.97 

Total onetime 

180.00 214.00 197.00 


Source: Elaboration on Polman (2002) and Hilhorst et al. (2003) 

Tab. 61 - Farmers’ annual transaction costs of the current SAN regulation 

Category Average time involved 

(hours/contract) 

Transaction costs 


according to 

Polman (2002) 

Transaction costs 


according to 

Hilhorst et al. (2003) 

Average 

Administration of 0.8 16.00 42.56 

results 

Administration 

labour input 

of 1.2 24.00 

{216.00 

63.84 

Consultation 0.5 10.00 N/A 26.60 

Total annual 

50.00 216.00 133.00 


Source: Elaboration on Polman (2002) and Hilhorst et al. (2003) 

The last column in tables 62 and 63 shows the average transaction costs of both surveys. The distribution of average 

transaction costs over different categories is done proportionally according to Polman’s (2002) distribution. For reasons 

of practicality, in the remainder of this report we will use these average values for both the onetime and annual 

transaction costs (last column in tables 62 and 63). From tables 62 and 63, we know that farmers’ transaction costs 

equal EUR 197 onetime costs and EUR 133 annual costs. Using the current management contract duration of six years, 

it is possible to calculate the total transaction costs of concluding one contract: EUR 995 (EUR 197 + 6 times EUR 133) 

divided by 6 is EUR 166. 

The increase in farmers’ transaction costs – as a result of implementation of the proposed measure – is solely based on 

an increase of the number of participating farmers from 10% to 50%, see WP 9. The transaction costs per farmer are not 

expected to change, because the proposed ‘mowing practices-measure’ fits well into the current SAN regulation. For

this reason, it is also no problem to use the data from tables 42 and 43 to calculate the additional transaction costs. An 

increase of 40% of total farmers (40% times 537 is 215) will have to switch to the new measure. This implies an 

increase of farmers’ transaction costs by 215 times EUR 166 is EUR 35,690. 

Government’s transaction costs: The government, being the contract-making party, covers a substantial part of total 

transaction costs. Transaction costs to the government of agri-environment schemes have been studied by Falconer & 

Whitby (1999) in a broad survey covering eight European countries. Although this study does not cover the 

Netherlands, it is possible to draw some general conclusions from the study. First, the transaction costs per agreement 

made fall with time over the period since scheme implementation. Second, there exist economies of scale in agrienvironmental 

scheme administration. 

A comparable evaluation of transaction costs to the government in the Netherlands of the current agri-environment 

scheme has not yet been conducted. It would have been useful to perform this evaluation for the AEMBAC-project, but 

this was not possible due to time and means constraints. However, a recent evaluation of the Dutch programme for 

nature conservation can serve as a baseline to assess the level of transaction costs (Hilhorst et al., 2003). The level of 

transaction costs that is mentioned in this study covers both contracts for agri-environmental measures as well as 

contracts for conventional nature conservation. Therefore we have to use the rough assumption that transaction costs 

for both types of contracts are equal per hectare and calculate the percentage of total transaction costs that is 

attributable to agri-environmental contracts (column three of table 64). Calculated transaction costs are presented in 

table 64. Transaction costs of the Dutch programme are comparable with other European schemes. Obviously, one 

would expect a decrease in transaction costs over time, because the number of participants will stabilise. Nevertheless, 

it is clear from table 64 that transaction costs have risen rapidly in the second year. 

Tab. 62 - Government’s transaction costs of the current SAN regulation 

Year Total transaction 

costs (EUR) 

Share of transaction costs 

attributable to agrienvironment 

schemes (%) 

Number of agrienvironmental 

contracts 

2000 5,000,000 17.6 1,968 447 

2001 7,900,000 43.3 3,512 974 

2002 11,900,000 26.9 5,073 631 

Source: Elaboration on Hilhorst et al. (2003) 

145 

Estimated annual 



Causes for the high level of transaction costs and the rapid increase in the second year are found in both the available 

data and some explanatory circumstances (Hilhorst et al., 2003), see WP 13 for details. 

Estimating the change in government’s transaction costs is, for simplicity reasons, based on the assumption that 50% of 

government’s transaction costs is fixed and 50% is variable (50% times EUR 631 is EUR 315), see table 64). The 

increase in government’s transaction costs – as a result of implementation of the proposed measure – is solely based on 

an increase of the number of participating farmers from 10% to 50%, see WP 9. Increasing the number of participants 

to 50% of the total number of farms, the following calculation can be made. The increase of government’s transaction 

costs of the proposed measure equals 285 (see WP 13) times EUR 315 is EUR 67,725, see table 65. 

Total transaction costs: The hereunder table provides an overview of the change in transaction costs as a result of 

implementing the proposed measure in mowing practices. 

Tab. 63 - Transaction costs of the proposed measure in mowing practices 

Total annual 

transaction costs per 

contract (EUR) 

Additional number of 

farms participating 

Farmers’ transaction costs 166 285 47,310 

Government’s 


variable 315 285 89,775 

Total administrative and 


481 30 285 137,085 

Source: Elaboration on Polman (2002), Hilhorst et al. (2003) and this report 

Additional transaction costs in 

Northwest Overijssel (EUR) 

30 In the Netherlands, the agricultural sector takes up 2,326,047 ha of agricultural land and includes 89,580 farms (CBS, 2003). Thus, 

the average farm size is approximately 26.0 ha. Approximately 62,843 ha of this land is managed under SAN regulation, involving 

5,073 contracts (Hilhorst et al., 2003). Hence, the average number of hectares per contract equals 12.4 ha. Taking into account that 

annual transaction costs per contract equal EUR 481, average national transaction costs per ha equal approximately EUR 38.8 for the 

mowing practices measure.

The increase in total transaction costs as a result of the proposed measure equals EUR 137,085 of which almost 2/3 is 

incurred by the government. This number should be used with care, especially because the estimated government’s 

transaction costs are solely based on the very rough assumption that 50% of transaction costs is variable (e.g. costs 

related to contracting and monitoring). The increase in farmers and government’s transaction costs – as a result of 

implementation of the proposed measure – is solely based on an increase of the number of participating farmers from 

10% to 50%. Hence, both farmers’ and government’s transaction costs do not show an increase of these costs per 

contract as a result of the proposed measure. 

3.7.5 Analysis of overall economic and financial aspects for the local implementation of agrienvironmental 

measures. 

In this section, the assessment of the overall direct, indirect and induced costs and benefits related to 

development and implementation of proposed agri-environmental measures, was carried out. Whereas it 

would have been difficult to assess the quantitative order of magnitude of benefits, it was suggested to 

indicate and comment in detail on the qualitative nature of these. 

For each agri-environmental measure proposed for the relative case study, and considering the minimum 

critical mass of enrolment necessary to make AEM effective in delivering the agri-environmental goods and 

services, researchers assessed and commented the following orders of economic costs and benefits: 

Costs 

• Total amount of compensation costs for reduced yields and other foregone income, required 

undertakings operation, land use conversion and so on; 

• Total amount of incentives envisaged to enhance the uptake of agri-environmental measures; 

• Other indirect and induced costs according to the local situation; and 

• Administrative and Transaction costs (see section above). 

Benefits 

• Agri-environmental goods and services provided (i.e. beyond tier 0); 

• Agri-environmental negative impacts which would arise if not dealt with through agri-environmental 

measure including also command and control based AEM (i.e. actual and foreseen impacts below 

tier 0); 

• Reduced production costs (e.g. reduced inputs used); 

• Diversification of the rural economies; 

• Enhanced scientific research and ecological knowledge; and 

• Other indirect or induced benefits according to the local situation. 

Comments on the overall costs and benefits related to the implementation of the measure were to be included 

here. 

Box. 63 - AEMBAC project: Costs and benefits of agri-environmental measures implementation in the 

case studies from Germany 

In this section the direct, indirect and induced costs of the proposed agri-environmental measures are contrasted with 

the expected benefits. Since it is not possible to assess the benefits in monetary terms, they are described in qualitative 

terms. 

The relations between costs and benefits are discussed on the basis of a comparison with the present AEP in Saxony. 

The main questions asked are where there are additional costs and benefits or reduced costs and benefits. A more 

quantitative assessment would require additional data that in general are not available. 

In Table 64 the expected changes in costs of implementation of AE measures are given on the basis of a comparison 

with the present AEP in Saxony. Reference is made to compensation costs (reduced yields, other income foregone, 

undertaking costs), the incentives that are to be paid to encourage uptake, administrative and transaction costs, and other 

indirect and induced cost items specific to the local situation. 

146

Tab. 64 - Comparison of the expected changes in costs of AE measures implementation as compared with the 

costs of the present AEP in Saxony 

Cost aspect 'New' AEP in comparison with existing AEP 

Total amount of compensation 

costs for reduced yields and other 

foregone income 

Total amount of incentives 

envisaged to enhance AE measures 

uptake; 

Other indirect and induced costs 

• additional information 

• additional marketing 

schemes 

Administrative and transaction 

costs 

• administration 

• compliance control 

• evaluation 

It is expected that the total amount of compensation costs could be reduced 

by 15-20% as compared with present levels of compensation. The decrease 

is achieved by a more precise targeting of measures and the renunciation of 

measures that have little positive environmental benefits. In the past, 

regions with higher uptake often had less intensive production systems 

already before the introduction of the schemes. a 

The total amount of incentives is expected to decrease slightly in line with 

the total amount of compensation costs (the assumption is that a maximum 

of 20% of compensation for reduced yields and other foregone income can 

be added as incentive element and that this is sufficient). It is also taken 

into account that cross-compliance regulations will substantially increase 

farmers motivation to participate in AEM 

It is estimated that the costs of additional information gathering and 

processing could increase by as much as 30-50%. The main reason for this 

increase is the more precise targeting if AEM. 

The costs of additional marketing schemes can not be estimated because 

more precise analysis would be needed. It is expected, however, that a 

substantial proportion of these costs can be covered by the GAK (Federal 

level RDP) and the Saxon RDP (with co-financing from the EU, Reg. 

1257/99) 

Total administrative and transaction costs per contract were estimated to be 

at least 250 - 350 € per contract. It is estimated that this is 40-60% higher 

than costs at present. The main reason for this increase is the more precise 

targeting if AEM, the more stringent compliance controls that should be 

envisaged and the increased emphasis on providing AE consultations and 

AE advisory services for farmers 

Source: Karlheinz Knickel (subcontractor); a Knickel & Schramek (1999); Knickel et al. (2000) 

Table 65 gives a breakdown of the benefits of implementing AEMs and a comparison with the present AEP in Saxony. 

Reference is made to the AE goods and services provided, the negative AE impacts that are avoided because the AEMs 

are being implemented, the reduced production costs, the expected positive impacts on the diversification of the rural 

economies, the enhanced research and ecological knowledge, and other indirect or induced benefits according to the 

particular situation in Saxony. 

The main additional benefits that are expected are: First, the measures are more precisely targeted at the particular 

agricultural and production structures as well as the particular AE situation and problems. It is expected that this will 

lead to a very considerable increase in direct and longer-term environmental benefits. The main criticism against present 

schemes is that many AEMs are insufficiently targeted. Closely related with that, uptake in intensively used regions, 

with greater proportions of fertile arable land, tends to be relatively low. In particular, measures which require 

significant adjustments, and/or a significant level of investment, find less acceptance. Conversely, the uptake of AE 

measures is clearly concentrated in the less favoured areas such as the ULHPL study area where many farms that get 

support have production systems that had been extensive even before the introduction of the scheme. Environmental 

improvements therefore tend to be small. To improve the schemes it is necessary to target scarce budgets more 

carefully. 

Second, the positive impact on the diversification of the rural economies. Until now little efforts are being made to 

actively construct synergies between a higher level of environmental quality and the development of economic activities 

that build on this potential (gastronomy, tourism, leisure businesses) (Knickel, 2001). 

147

Tab. 65 - Benefits of implementing AEMs and comparison with the present AEP in Saxony 

Cost aspect Existing AEP 'New' AEP 

AE goods and Some measures are not sufficiently targeted at The AEM that have been proposed are 

services provided the particular agricultural and production based on a more profound analysis of the 

(beyond tier 0) structures as well as the particular AE situation particular AE situation and problems. It is 

and problems (e.g. the support given to expected that they will be more effective 

environmentally-friendly arable farming / in terms of environmental improvements 

integrated arable production (Umweltgerechter 

Ackerbau; UA; Grundförderung), 

and actual outcomes. 

AE negative Longer term changes are not sufficiently taken There are several measures proposed that 

impacts avoided into account. An example is the decrease in also address longer term structural 

(below tier 0) high-nature-conservation-value systems on improvements: the reduction in field sizes 

marginal mountainous land (dry meadows), as and increase in linear landscape 

well as in lowland areas (wetlands and structures, the support given to the 

seasonally flooded areas). Both have had been maintenance of valuable wet meadows, 

decreasing significantly resulted in very the establishment and maintenance of new 

substantial reductions in flora and fauna 

biotopes, the reintroduction of livestock 

and/or raising of livestock density, and the 

establishment of buffer strips along 

running waters and valuable biotopes 

Reduced 

The AEM lowering of fertiliser application and nutrient surpluses significantly reduce input 

production costs costs (costs of fertiliser and joint inputs such as PPP). The same applies to the AEM increase in 

cropping diversity that will lead to a reduction in PPP use 

Diversification of Until now little efforts are being made to Reference has been made to the 

the rural actively construct synergies between a higher importance of actively constructing 

economies 

level of environmental quality and the synergies. The more precise linkages, 

development of economic activities that build however, have not been examined because 

on this potential (gastronomy, tourism, leisure this had been outside the scope of this 

businesses) (Knickel, 2001) 

project 

Enhanced research Accompanying research so far has been It is hoped that the results of this project 

and ecological relatively scarce. Continuous AEP improvement have shown that there is a need for 

knowledge 

is not yet understood as a learning process. 

Most available research relates to high-naturevalue 

land and not to agriculturally used land 

accompanying research. 

Other indirect or Income and employment opportunities that can The more precise effects could not be 

induced benefits be expected as a spin-off from environmental examined because this had been outside 

management activities (Knickel, 2001) 

the scope of this project 

Source: Karlheinz Knickel based on several Work Package reports carried out by the SAW and subcontractors 

3.7.5.2 Studying of the most suitable financing source for the agri-environmental measures proposed 

Once the overall costs and benefits of each agri-environmental measure proposed for the relative study area 

were identified and commented, the next and final task was to envisage the possible financing sources for 

implementing the AEMs. 

The definition of the most suitable and realistic sources of funding served the scope of finally assessing the 

financial feasibility for the agri-environmental programme developed. 

In this section it was asked to highlight if the developed AEM consisted of a revision of an already existing 

measure or of a new one. 

In the former case, by looking at the current sources of funding for the existing agri-environmental 

programmes, it had to be assessed what would be the differences in the financial requirements needed by the 

implementation of proposed AEM for each case study, both in quantitative and qualitative terms. 

In the latter case, for each new AEM proposed for the local case study, the suitability of the use of the 

existing financial instruments had to be assessed, both in quantitative and qualitative terms. 

It was suggested to carry out this analysis by keeping separate what the European, National and Regional 

financing sources were. 

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For both the new and the already existing AEMs, in case the usual financial sources were not suitable or 

sufficient, researchers were asked to put forward some hypothesis on new financial sources. These could be 

for instance: 

• Using the funds coming from application of the Polluter Pays Principle; 

• Using fiscal incentives; 

• Adopt green taxes; 

• Reducing agricultural production incentives (moving funds from the first to the second pillars of the 

CAP); and 

• Others. 

Box 64 - Studying of the most suitable financing source for the agri-environmental measures proposed 

in Estonia 

The definition of the most suitable and realistic sources of funding will serve the scope of finally assessing the financial 

feasibility for the agri-environmental programme developed. 

Existing agri-environmental measures are so far funded only by the Estonian state budget. The total budget for agrienvironmental 

support in 2000 was 0.3 mln EUR, increased to 2.4 mln EUR in 2003 (administrated by the Ministry of 

Agriculture). Besides that, 1.2 mln EUR for management and restoration of semi-natural habitats (under Ministry of 

Environment) was spent in 2003. 

From 2004, after joining the EU and implementing Rural Development Plan, 80% of agri-environment measures (and 

other rural development measures) expenditures are financed by EU. By the preliminary information 14 mln EUR is 

foreseen for implementation of agri-environmental measures in Estonia in 2004 (Ministry of Agriculture). It means 

basically, that there is no need to increase national funds for agri-environment measures and increase of total budget 

foreseen for agri-environmental measures is possible using EU co-financing. Average EU contribution planned for agrienvironmental 

measures in 2004 - 2006 is 19.1 mln EUR per year (table 3). 

Tab. 66: Financing of agri-environmental measures of RDP 2004 - 2006 

2004 2005 2006 

National 2.8 3.9 4.8 

EU co-financing 11.2 15.3 19.4 

TOTAL, EUR 14 19.2 24.2 

Proposed measures will fit within current agri-environment scheme and there is also no need to search for a “new” 

financing system i.e. combination of national funds (20% of total budget) and EU co-financing (80%) can be used also 

for proposed agri-environmental measures. 

Implementation of “new” financial sources like fiscal incentives, adoption of green taxes etc. is not foreseen in the near 

future in Estonia. Reducing agricultural production incentives (moving funds from the First to the Second Pillar of the 

CAP) is unlikely as well (rather it could be the opposite). 

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4. Discussion 

Partners’ work has shown that the overall approach of the project, based on the study of the functioning of 

natural and agricultural ecosystems by looking at the state of agro-ecosystems ecological processes and 

components, is a very promising method to address the identification and measurement of the impacts 

exerted on the environment by agricultural activities. 

This approach in fact, while looking at the performance of environmental functions), is capable of providing 

information on the state (processes, structures and components) of the (semi-)natural and agricultural 

ecosystems studied, and also on the environmental goods and services supplied. 

One of the most interesting aspects of the work carried out has been the dialogue between experts of 

different scientific disciplines such as landscape ecologists, biologists, agronomists, foresters, economists, 

geologists, etc. This has resulted in looking at the issues to be addressed by the project from very different 

perspectives which have brought, after mutual understanding was reached, an enrichment of the answers 

given to the scientific tasks required. 

The eight meetings (minutes available on the project web site) provided the scope to analyse in detail the work to 

be done, clarifying the topics for research and an understanding of what was the purpose of the project in the 

light of the overall objectives to be reached. 

Also interesting was the almost straightforward confirmation by the work of Partners of the possibility of 

describing and analysing the environmental functions by indicators measuring the most important attributes, 

processes and components of the ecosystems necessary for their performance. The definition of what values 

(Environmental Minimum Requirements) have to be matched by the selected key state indicators, in order to 

allow for the performance of the environmental functions, and how the different state indicators used to describe 

the most important attributes of the functions shall be seen in relation to each other, was a less straightforward 

aspect to be analysed and raised very interesting debates. 

This work focussed mainly on the analysis of information required to assess with precision the exact 

Environmental Minimum Requirement (EMR) values that have to be matched by the state indicators selected in 

order to be sufficiently confident that the relevant environmental function would be performed. 

From the very beginning it emerged by exchange of opinions and experiences between partners, that the 

information needed to assess exact EMRs was high and that in some cases there was insufficient scientific 

knowledge to achieve a definitive result. It was also pointed out that a risk analysis would have to be carried out 

in order to assess, with scientific precision, what the value of state indicators would have to be in order to 

“guarantee” the environmental performance. This was the case, for instance, with the subjective nature of 

evaluating the attractiveness of landscape features as well as the difficulties of assessing minimum 

requirements for these in order to have environmental function related to landscape performed. 

However, this fact has not impaired the overall validity of results and conclusions achieved regarding the 

analytical framework developed, but only the assessment of precise environmental minimum requirements of 

state indicators describing some ecological and landscape aspects. In fact, when values for EMR of indicators 

could not be identified with more scientific rigour, these were assessed anyway on the basis of Best 

Professional Judgement by using the scientific information, data and expertise available. The confirmation of 

the proposed tentative values of EMRs to achieve the performance of selected environmental functions 

locally, could be the object of further scientific studies, and in some cases the EMR values pointed out in 

AEMBAC will provide the first step to address certain ecological aspects. 

Beside the acknowledgement of the difficulties in assessing some EMR values, the work carried out led to the 

conclusions that baselines for the values of indicators were necessary anyway, both to assess the impacts of 

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agricultural activities and to develop effective agri-environmental measures (e.g. monitoring and evaluation), 

even if in some cases lack of data or sufficient scientific knowledge limited their exact definition. 

To have reached an agreement on the necessity of defining environmental minimum requirement values to be 

matched by indicators describing environmental functions performance, allowed to set up the work, from the 

very beginning, with the recognition of the existence of thresholds in order to achieve environmental functions 

performance. This recognition can be interpreted as the adoption in AEMBAC of the concept of strong 

sustainability, where natural and man-made “capital” are substitutable only up to a limit. The consequences of 

this for the next phases of the project focussing on translating ecological analysis into economics were very 

important but probably not so obvious. 

In fact, in order to satisfy the preferences expressed by the general public on conserving biodiversity (through for 

instance the ratification of the Convention on Biological Diversity by governments), environmental thresholds 

(i.e. environmental minimum requirements) will have to be respected. This condition will allow a trade-off 

between natural and man-made “capital” only up to the point at which those environmental minimum 

requirements are not in danger of being breached. 

Other problems encountered in Phase 1 also related to lack of existing data and/or of sufficient scientific 

knowledge for some ecological aspects to be analysed. 

Regarding the problem of using a scale of analysis based on ecological boundaries different from the 

administrative level (i.e. commune, province/county, region) where usually socio-economic data are gathered, 

the solution used by some Partners was to adapt data at commune and province level if these were considered 

also representative for the same topics analysed in the study areas. Other Partners obtained data through field 

research and the use of an agri-environmental questionnaire built to gather data at farm level through interviews 

with farmers (see annex 1). Given the resource constraints to making a complete survey of local farms, use of a 

crucial sampling method was suggested, using a few farms which were considered very representative of the 

local agricultural system. 

Concerning the lack of historical data time series for some environmental aspects it can be said that this problem 

affected mainly the analysis of the dynamic dimension of (semi-)natural and agricultural ecosystem extent and 

uses. Where it was feasible the use of old maps showing past land cover and uses was a valid substitute for data. 

Where old maps were missing some Partners used old literature on agriculture carried out in the region of the 

study areas in the past to formulate hypothesis on past land cover and use of the territory. 

For the problem of lack of existing scientific knowledge on some environmental aspects, in this circumstance, 

all that AEMBAC Partners could do was to point out the need for further scientific research indicating in 

some cases what should be done. However, the lack of scientific knowledge on some ecological and 

landscape aspects was already known. 

The work undertaken to accomplish the tasks of AEMBAC Phase 2, was built on the results of Phase 1 and 

followed the interdisciplinary approach, based on environmental functions and the DPSIR (Driving Pressure 

State-Impact Response) analysis. 

This approach, while looking at the performance of environmental functions is capable of providing information 

on the state (processes, structures and components) of the (semi-)natural and agricultural ecosystems studied, by 

looking at the impacts exerted by local agricultural practices on these, and it also enables to point out the 

environmental goods and services actually being supplied. 

Taking the perspective of looking at ecosystem functioning through the provision of environmental goods and 

services has offered the opportunity to concentrate on what value exists for human kind. This approach, already 

utilitarian and anthropocentric, has enabled integration between the natural and social sciences, and has been 

very useful to “translate” the results of the ecological analysis of Phase 1 into economic values for the 

development of agri-environmental measures in Phase 2. 

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The work done in Phase 1 on the identification of Environmental Minimum Requirements (EMR) values for 

selected state indicators describing the environmental functions performance; on the measurement of their actual 

values through field and bibliographic research in the study areas; and on the analysis of causal relationships 

between most significant pressures and impacts detected on the value of state indicators (i.e. gaps between EMR 

and actual values), have represented the corner stones upon which to build, in Phase 2, a ranking system to 

associate degrees of sustainability to pressures and corresponding impacts. 

This ranking system has resulted in a practical tool, useful to expand the analysis further to envisage different 

impacts correlated to different intensities of the most important pressures, and to propose recommendations on 

how to change current agricultural practices in order to lessen/eliminate negative impacts and enhance positive 

ones. 

It is important to point out that in some cases, scientists have found difficulties in assessing the degrees of 

sustainability to be ranked amongst tiers. This was because of a lack of sufficient scientific information and of 

current scientific knowledge on certain aspects (mainly on dose-effect relationships), to assess with scientific 

accuracy the exact correlation between causal pressures and corresponding impacts. Therefore the conclusions 

achieved have to be considered as only indicative, not definitive. 

Despite these difficulties, which where largely expected given the complexities of the topics studied (e.g. doseeffect 

relationships between pressures and state of agro-ecosystems), the ranking system proposed has proved to 

be a very promising approach to connect scientific analysis and policy recommendations. In fact, it clearly 

indicates, at least qualitatively, what are the environmental aspects and agricultural pressures relevant for the 

development of local agri-environmental policy and where further scientific analyses are needed because of lack 

of scientific knowledge (e.g. on dose-effect relationships). 

Clearly, in the current research project, the basis for this future analysis could only be pointed out, but the 

identification of particular fields where further research is recommended can be considered an added value of 

AEMBAC results. Formulating indications of dose-effects relationships and assessment of sustainability of 

agricultural pressures can be seen as a starting point for future empirical analyses to be carried out in order to 

deepen scientific knowledge regarding some specific environmental aspects not yet well studied or known (see 

Partners final reports). 

Regarding the economic valuation of the impacts (both positive and/or negative) exerted by local agricultural 

practices on the supply of environmental goods and services, two options were offered to researchers: that of 

calculating both the costs and benefits of reducing the negative impacts and/or enhancing the positive ones; and 

that of calculating only the costs to allow the provision of the environmental goods and services analysed, 

assuming the societal demand for these goods is positive (e.g. using the ratification of the Convention on 

Biological Diversity by the EU and European Governments as a proxy). 

Given the time and funding constraints in carrying out a comprehensive valuation of the benefits of providing 

environmental goods and services (e.g. through for instance the contingent valuation method), or the difficulties 

of using other techniques prone to criticism (e.g. benefits transfer), researchers opted for the second option of 

calculating only the costs of reducing/eliminating negative impacts or enhancing positive ones. (FiBL analysed a 

list of Contingent Valuation studies on landscape carried out around Europe.) 

The ecological and socio-economic information gathered through the analyses carried out was then used to 

define the agri-environmental policy targets and measures at local level. This information proved to be far more 

detailed and substantial both in the identification of targets and instruments to developed agri-environmental 

policy at local level than that currently used. Moreover, the fact that in all the 15 case studies, Partners, building 

upon this information, have identified suitable AEMs can be regarded as the confirmation of the feasibility of 

using the analytical framework developed and of its flexibility in taking into account the ecological, social and 

economic diversity of the European Union. 

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The feasibility of the methodology to develop agri-environmental measures was interestingly confirmed also by 

the involvement of local stakeholders (i.e. local farmers and administrators) who in the majority of interviews 

demonstrated a good awareness of the environmental problems and/or opportunities in their area and an 

understanding of the proposed recommendations to overcome the former and enhance the latter. 

The environmental function approach proposed, being based on indicators and baselines identified in Phase 1, 

has proved to be very suitable also in promoting a far better definition in Phase 3 of monitoring and evaluation 

procedures to assess the effectiveness of the agri-environmental measures compared to the actual status quo. In 

fact if the developed AEMs are eventually implemented in the case study areas then indicators and baselines to 

carry out counterfactual, benchmarking and temporal comparisons to assess their effectiveness in the supply of 

environmental goods and services would already be available. 

Regarding the assessment of overall costs and benefits of an eventual implementation of agri-environmental 

measures developed by using the AEMBAC methodology, the analyses carried out in case studies did not 

show greater public expenditure administrative and transaction costs than current ones for zonal agrienvironmental 

measures, and showed similar or little greater expenditure in reaching tier 0, while a possible 

greater amount of money was envisaged to achieve upwards tiers (i.e. tiers +1 and +2). 

Obviously to pay farmers to reach tier 0, which in the AEMBAC methodology is considered the 

sustainability level and not the one which allows for the supply of environmental goods and services (set 

from tier +1 and +2) would be a political decision. However in case the principle of rewarding farmers only 

from tier 0 (assimilated in AEMBAC to the reference level of “good farming practices”) upwards is 

maintained, this would free extra financial resources to pay those farmers that supply real environmental 

goods and services (also those who already are doing so without being paid at present). 

It is also very important to point out that, on the benefits side, from the analyses carried out far greater 

environmental benefits can be expected in case so detailed and locally tailored agri-environmental measures 

would be implemented in the study areas. 

In phase 3, the most important problem encountered was the impossibility of carrying out economic valuations 

of benefits in supplying environmental goods and services due mainly to constraints in funding and time. 

However, also for economic valuation future research could be carried out in identifying the economic value of 

benefits resulting from the supply of environmental goods and services, by using the appropriate monetary 

evaluation techniques. 

Considering the complexity of the topic analysed, and for certain aspects the innovative character of the research 

carried out, it can be said that the problems encountered throughout the whole duration of the project in the 

definition and testing of the methodology proposed were physiological in nature, largely not unexpected, and did 

not undermine the theoretical basis, and most importantly, the eventual practical use of the analytical framework 

defined. 

As mentioned above, the most important problems related to lack of existing data and/or of sufficient scientific 

knowledge for some ecological aspects to be analysed (such as the exact definition of EMRs for some State 

indicators and the dose-effects relationships between pressure and state indicators). However it was noted that 

formulating tentative values can be seen as a starting point for empirical analysis to be carried out in future 

research to augment the scientific knowledge regarding some specific environmental aspects not yet well studied 

or known. Clearly, in the current research project, the basis for this future analysis could only be pointed out, but 

the identification of particular fields where further research is needed can be considered an added value of 

AEMBAC results. 

The work carried out by Partners is available on the project web site www.AEMBAC.org (intranet section, 

password: project). 

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5. Conclusions 

The AEMBAC project has defined a common European analytical framework for the development of local 

agri-environmental programmes for biodiversity and landscape conservation. This result can be sub-divided 

in three main results according to the three main phases of the project: 

• Definition of a methodology to assess the impacts exerted by agricultural pressures on the local 

environment: 

Phase 1 (Steps 1, 2, and 3) of the project has resulted in advanced research in the area of integration of 

biodiversity and landscape conservation into the agricultural sector. This result was achieved through a 

wide range of activities from bibliographic research and data gathering in the field to the development of 

tools and instruments. The main result of phase 1 is a methodology to build a DPSIR model to identify 

impacts exerted by pressures of the local agricultural systems on the performance of environmental 

functions. 

• Definition of a methodology to develop Agri-environmental measures at local level: 

Phase 2 has built on the outcomes of the first phase, starting from the analysis and identification of 

causality relationships between detected impacts on environmental functions performances and locally 

most relevant agricultural pressures. The main outcome of Phase 2 (steps 4, 5 and 6) has resulted in a 

methodology to connect science and policy in order to develop agri-environmental measures, locally 

tailored to the most relevant impacts exerted by agriculture, to fostering the supply of environmental 

goods and services by farmers (and to discourage unsustainable agricultural practices). 

This has been achieved by developing a detailed, flexible and transparent methodology to integrate 

scientific results, economic values, social aspects, ecological objectives and stakeholders’ points of view 

into agri-environmental policy formulation. 

Policy targets and instruments have been defined by the scientific analyses carried out in the study areas, 

taking into account both the ecological and socio-economic sustainability of the local agri-environmental 

situation in relation to the performance of environmental functions studied, of the agri-environmental 

targets and measures identified and recommended and of existing agri-environmental policies through 

comparison with those proposed. Following this approach a clear distinction has been made between 

ecological thresholds in agriculture and realistically achievable results for the short term (i.e. agrienvironmental 

policy targets) at the local level. 

• Definition of a methodology to implement the Agri-environmental measures developed: 

The methodology developed in previous phases 1 and 2 have clearly demonstrated in Phase 3 its validity 

in identifying indicators for monitoring the correct implementation of agri-environmental measures 

developed and baselines (i.e. reference values) for evaluating the effectiveness of AEMs in achieving 

environmental benefits. The results of Phase 3 have included the analysis of transaction costs and overall 

economic and financial aspects for the eventual implementation of agri-environmental measures 

developed. 

Beside the above, the work carried out has allowed scientific topics to be identified where further research 

will have to be carried out in order to enhance the scientific rigour of the results achieved. The most 

important topics are the following: 

• Integration of different scales of analysis and of socio-economic data with environmental ones (e.g. 

ecological and administrative boundaries, FADN); 

• Validation of EMR and of dose-effect relationships between pressures and impacts by field research (e.g. 

Ecosystems functioning and resilience); and 

• Integration of ecological thresholds in economic evaluations and valuation of environmental benefits 

(e.g. consequences of irreversible ecological situations). 

The results obtained from the testing of the analytical framework defined in 15 study areas in the seven 

countries, show that the analytical framework for the development of local agri-environmental programmes 

154

is very promising in its foreseeable practical implementation and that it can be applied to very different 

ecological, economic, social, etc. situations. In fact, feedback from case studies has indicated that: 

• The AEMBAC methodology is a flexible and practical European tool to develop local AEM for 

biodiversity and landscape conservation tailored to site specific ecological, social and economic 

needs/opportunities; 

• In all 15 case studies the testing of the methodology has allowed clear policy targets and instruments for 

implementing AEMs to be identified (e.g. recommendations on how to halt soil erosion caused by 

planting vineyards in Italy, on mowing dates to be partly adapted to suit bird life in the Dutch case 

studies); 

• No particular new technological undertakings are required by AEMs developed in AEMBAC compared 

with the existing ones (e.g. managing landscape in the traditional way in Estonia and Sweden, change 

from rotational to mowing bars in meadows in Switzerland, reduce fertilisers inputs Germany and 

Netherlands, etc.). However, more efforts and longer time implementation may be needed to achieve real 

supply of environmental goods and services than in current AEMs (e.g. increasing semi-natural areas by 

biotope maintenance, by ecological corridors and/or by planting hedgerows in Germany, Hungary, Italy, 

Switzerland, Netherlands); 

• There is sufficient awareness among farmers of local Environmental problems/opportunities, but also 

there is a tendency to underestimate consequences; The less the long term commitment and required 

changes to farm management the greater the acceptance of AEMs which apparently is in contrast with 

the need of more lasting AEMs to achieve environmental benefits (but securing long-term payments may 

change this attitude); 

• Payments are important but also other factors concur in deciding to participate in AEMs (e.g. age, 

environmental awareness, AEMs flexibility, etc.); 

• In achieving EMRs, developed AEMs show similar or slightly higher payments (per ha) and similar 

transaction costs (per contract) than current ones 31 , but far greater benefits can be expected from more 

environmental effectiveness and overall efficiency; However, in case the principle of rewarding farmers 

only from tier 0 (assimilated in AEMBAC to the reference level of “good farming practices”) upwards is 

confirmed, this would free extra financial resources to pay those farmers that supply real environmental 

goods and services (also those who already are doing so without being paid at present). 

6. Exploitation and dissemination of results 

IUCN and the seven European Partners participating in the project have benefited from the results of the 

project, gaining in experience and knowledge. Apart from being useful to Partners, the results coming out 

from the project clearly will be of use to other universities, farmers’ organisations, environmental 

organisations, producer co-operatives, processing industry, local authorities, policy-makers and the EU 

institutions. 

It is important to note that the methodology developed by the AEMBAC project, would need to be made 

operative before becoming a standardised tool in the agri-environmental policy development process. This 

could be done by building on the AEMBAC project results in at least four ways: 

1. The high value nature sites approach: by adapting the AEMBAC methodology to the definition of agrienvironmental 

measures in high natural value sites. This could be done for instance by a research project 

aiming at defining indicators, EMR values, recommendations and socio-economics aspects for the 

development of agri-environmental measures necessary to finance the implementation of NATURA 

2000 in designated sites by member states. 

2. The agro-ecosystem typologies approach: by adapting the AEMBAC methodology to the definition of 

31 Only in the German case studies it is estimated that transacton costs would be 40-60% higher than costs at present. The 

main reason for this increase is the more precise targeting of AEM, the more stringent compliance controls that should 

be envisaged and the increased emphasis on providing AE consultations and AE advisory services for farmers 

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agri-environmental measures for the main European agro-ecosystem typologies in relation to the most 

important environmental functions to be performed locally. This could be done by a project aiming to 

define the indicators, EMR values, recommendations, and socio-economics aspects to be taken into 

account while developing AEMs throughout Europe according to the agro-ecosystem type to be 

addressed. 

3. The multifunctionality approach: by studying further the adaptation of the AEMBAC methodology to 

assess and enhance the multifunctional character of the European agriculture. 

4. The multisectoral approach: by a project adapting the AEMBAC methodology to different socioeconomic 

sectors such as forestry, fisheries, tourism, etc. 

Regarding dissemination of the results: 

An AEMBAC booklet on introductory guidelines for administrators and policy makers will be published in 

September 

A publication special issue in a scientific Journal on the scientific topics analysed in AEMBAC is foreseen 

for the first months of 2005 

The AEMBAC web site will be maintain and administered by IUCN and the final reports will be made 

public in the near future. 

An AEMBAC workshop and conference has been held at the European Parliament in Brussels on 5 th 

February 2004 

The Scientific Co-ordinator presented the AEMBAC project at the following international and national/local 

conferences and workshops has been as follows: 

• OECD expert meeting on agri-environmental indicators, held in Zurich, 5–8 November 2001; 

• Workshop “Research for Sustainable Land Use and Regional Development”, 3 rd – 4 th April, 2003, 

European Commission Joint Research Centre, Ispra, Italy; 

• Workshop on Rural Development organised by DG Research, held in Brussels 18 November 2003; 

7. Policy related benefits 

As the AEMBAC project aims at the “definition of an analytical framework for the development of local 

agri-environmental programmes for biodiversity and landscape conservation”, there could be many benefits 

through integrating the scientific results into policy development. 

The AEMBAC methodology is based on the idea of a knowledge-driven Agro-environmental policy and 

Sustainable Rural Development. It is therefore logical that the scientific results achieved present clear policy 

related benefits both European and local level as follows: 

At European level: 

• The research results, besides clearly being useful for the development of agri-environmental policy and 

rural development in the EU (Reg. (EC) 1257/99), will also be very useful in the context of the European 

Directive 2001/42/EC on the assessment of the effects of certain plans and programmes on the 

environment (art.12, point 4, where the Commission is asked to report on the relationship between this 

directive and Reg. (EC) 1257/99), the Birds Directive (79/409/EEC), the Habitats Directive (92/43/EEC), 

the Convention on Biodiversity, the Convention on Landscape, and the Water and Nitrogen Directives. 

• Regarding the wider objective of conserving biodiversity and landscapes, the project focuses on studying 

the feasibility and opportunities of linking biodiversity conservation to the maintenance of ecological 

processes and to the performance of human activities. These are seen as interrelated, not conflicting, 

156

aspects. This approach is very promising in the further study and understanding of the interdependencies 

between the natural environment and the quality of life for human populations. The development of 

dynamic programmes for agricultural sustainability and conservation of European biodiversity and 

landscapes would benefit from the adoption of the AEMBAC methodology for instance in the 

implementation of NATURA 2000; 

• The AEMBAC methodology would favour a smooth transition from compensation payments coupled to 

production to a more socially acceptable agri-environmental payments for supply of environmental goods 

and services, in line with the recent CAP reform. 

• The AEMBAC methodology will also enhance the transparency and a wider application of the subsidiary 

principle in managing agri-environment programmes and will increase of environmental awareness 

amongst EU citizens; 

• The AEMBAC methodology will provide scientific support to the concept of multifunctionality in 

agriculture (e.g. in relevant international fora such as WTO) by measuring the real supply of 

environmental goods and services; and 

• The results of such research will also foster European agricultural competitiveness in a scenario of 

growing liberalisation of global agricultural markets, in which it is expected that payments to farmers will 

only be allowed in return for supplying real environmental goods and services which do not distort trade. 

At the local level, scientific results will allow policy related benefits through providing: 

• The selection of scientifically based suitable indicators to analyse and measure the supply of 

environmental goods and services by agriculture; 

• Clear distinction between ecological sustainability in agriculture (i.e. respect of EMR) and realistically 

achievable results for the short term considering socio-economic aspects (i.e. agri-environmental policy 

targets). (i.e. scientific based definition of “good farming practices” at local level); 

• More precise ecological, economic and social information to make trade offs between different rural 

development objectives (i.e. clearer definition of risks and uncertainties with regard to unsustainable 

agricultural practices) and therefore achieving a sustainable diversification of rural economies; 

• The possibility to take into account the assessment of Environmental Minimum Requirements (EMR) 

while developing agri-environmental policy, which will guarantee a better monitoring and evaluation of 

the AEM effectiveness and efficiency; 

• Devolution to local farmers and administrators of the fine-tuning of policy measures in local agriculture, 

thereby creating an "evaluation culture”; and 

• The assessment of the sustainability of the agricultural systems in relation to the performance of 

environmental functions studied, and the project methodologies integrating ecological goals within the 

development of socio-economic sectors will set the foundations for analysing environmental topics with 

a comprehensive and holistic approach; this could become a routine procedure to be applied throughout 

Europe. The approach adopted could also be used for studying the sustainability use of natural resources 

by other socio-economic sectors (e.g. forestry, fisheries, tourism, etc.). 

8. Literature 

Avalon, Veen Ecology, Institute for European Environmental Policy, Agri-environmental programmes in 

CEECs, EU Project 2078 CEE 78, 1998. 

157

Bähr, H.-P. and Vögtle, T. (1999). GIS for Environmental Monitoring. – Stuttgart, Schweizerbart. 

Baldock David, Bennet Harriet, Petersen Jan-Erik, Veen Peter and Verschuur, Developing agrienvironmental 

programmes in Central and Eastern Europe – A Manual, final draft, personnel 

communication, May 2002. 

Balmford Andrew et al., Economic Reasons for Conserving Wild Nature, in Science Magazine, Volume 297, 

Number 5583, Issue of 9 Aug 2002 

Barbier B.E. (1989). Economics of Natural Resource Scarcity and Development: Conventional and 

Alternative Views, London, Earthscan Publications Limited. 

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