Landscapes Forest and Global Change - ESA - Escola Superior ...

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S. M. Carvalho-Ribeiro & T. Pinto-Correia 2010. Forests in landscapes: modelling forest land cover patterns suitability 694 the land cover pattern, as expression of the landscape composition and change. The IFS is based on the use of indicators for gauging the differences between best possible land cover pattern for a certain function and the land cover patterns likely to occur in contrasting scenario storylines. Therefore, it is a step further in the provision of ex-ante evaluations of the impacts of different trends of change in the provision of different functions (Fig 2). By using the same set of indicators to characterize both the best possible land cover pattern for a certain activity and the land cover pattern likely to occur in different scenario storylines, the IFS allows for a quantification of the distance in the provision of functions, from one to another land cover pattern. As such, it provides an indication of the suitability of landscapes and their respective land cover combinations, in the future, in delivering selected functions. The IFS is still under development and has so far been used exclusively for amenity functions. Throughout the present project, an improvement of the tool is expected, as well as a further adaptation to this Index, incorporating also “ecological” functions such as carbon sequestration, water flow regulation and flood protection by means of ecological modelling and expert based knowledge. Fig. 2 – The Index of Function Suitability is calculated measuring the distance between thepreferred landscape (denominated as best possible land cover pattern, as it depends on the existing lands cover classes and possible combinations and compostions of those) to develop a given non-commodity function, and the landscape being tested. 2. Methodology This project uses a territorial approach looking at the Cávado and Sado catchments as Socio- Ecological Systems (Folke et al., 2005). The spatial nature of this analysis is needed, as the goods and services here considered are provided at the landscape scale. The watershed has been defined as the unit of analysis, as it is the most comon and acknowledged level of organization of the landscape per se, when all factors, both physical, biological and human, are considered (Selman, 2006). Both watersheds have rural-urban gradients from inland to sea coast, and a landscape composed of both urban, agricultural and forest land covers, with predominance of forest and silvo-pastoral systems. Across these watersheds, the forests contribution for the lansdcape pattern and thus for human well-being certainly differ. By conducting a comparative study Sado catchment in South, Mediterrranean Portugal, and Cávado catchment in the Atlantic Forest Landscapes and Global Change-New Frontiers in Management, Conservation and Restoration. Proceedings of the IUFRO Landscape Ecology Working Group International Conference, September 21-27, 2010, Bragança, Portugal. J.C. Azevedo, M. Feliciano, J. Castro & M.A. Pinto (eds.) 2010, Instituto Politécnico de Bragança, Bragança, Portugal.
S. M. Carvalho-Ribeiro & T. Pinto-Correia 2010. Forests in landscapes: modelling forest land cover patterns suitability 695 Minho) the diversity of roles forest might play are highlighted. It is acknowledged that the landscape functions forests contribute to will be prioritized in different ways in each of the catchments. The criteria, factors and importance of forests to different landscape functions can be revealed by contrasting region characteristics. 2.1 Identifying appropriate forest spatial patterns for different landscape functions 2.1.1. Assess the landscape pattern, through the application of landscape metrics for Cávado and Sado catchments. The land cover base maps will be created in Arc/GIS and following exported to a spatial pattern software in order to quantify land cover patterns. A set of landscape metrics (Botequilha Leitao and Ahern, 2002) will be computed in FRAGSTAT (McGarigal et al., 2002) based on the Carta de Ocupacao do Solo COS 90. By computing the landscape metrics such as mean patch size (PS), number of patches (NP), patch density (PD) and percentage of landscape (PLAND) for agriculture, forests (by tree species) and urban, an understanding of the landscape pattern of the studied regions will be gained and a comparative analysis become possible. After quantifying the land cover patterns within the two catchments a modelling approach will be undertaken in order to create the best land cover pattern for different types of landscape function. This will be carried out in two different ways as there will be focus on ecological related functions such as water flow regulation, flood protection and carbon sequestration that require expert knowledge in order to identify a best land cover patterns within the catchments. On the contrary in the case of functions related with public preferences namely recreation and cultural identity a preferred landscape pattern will be based on questionnaire surveys assessing preferences of different groups of users of the landscape (hunters, farmers). 2.1.2. Expert panels. The best possible landscape patterns for the provision of landscape functions such as water flow regulation, carbon sequestration and flood protection will be created based on expert panels at the catchment scale. “Experts” are defined as “representatives of organisations which are affected by, or which significantly affect, interactions between regional landscapes and forests, or have skills and knowledge about the issue, or influence implementation instruments relevant to the topic”. This task will be also based on a literature review. 2.1.3. Ecological modelling. Based on the data gathered suitability maps for carbon sequestration, flood protection and water regulation, will be created. Land use suitability analysis aims at identifying the most appropriate spatial pattern for land uses according to given suitability criteria (Malczewski, 2004). Based on the ecological thresholds for different tree species suitability maps will be first created for broadleaves (oak), coniferous (pine), eucalyptus, agriculture and pastures. The land use modelling criteria, as well as the weightings for factors will be discussed by the expert panels. These suitability maps will be combined through a Multi-Objective Land Use Allocation (MOLA) command in the IDRISI ANDES GIS (Eastman, 2006) creating optimal landscape patterns for carbon sequestration, water regulation and flood protection. 2.1.4.) Public preferences. The best possible land cover patterns for recreation and for cultural and identity preservation will be assessed through surveys to specific groups of landscape users. This survey is to be done through direct enquiries based on landscape photos used as visual stimuli for the expression of preferences. The results will be translated into the best possible landscape pattern, adapting themethodology of Pinto-Correia et al. (2009b). Data has already been, or is being collected in research projects such as Agrorreg, Mural, Rosa (Pinto-Correia et al., 2009b) and in the work by Carvalho Ribeiro (Carvalho-Ribeiro, 2009; Carvalho-Ribeiro and Lovett, 2009, 2010; Carvalho-Ribeiro et al., 2010) . Forest Landscapes and Global Change-New Frontiers in Management, Conservation and Restoration. Proceedings of the IUFRO Landscape Ecology Working Group International Conference, September 21-27, 2010, Bragança, Portugal. J.C. Azevedo, M. Feliciano, J. Castro & M.A. Pinto (eds.) 2010, Instituto Politécnico de Bragança, Bragança, Portugal.
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Landscapes Forest and Global Change
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The contributions to this volume ha
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Table of contents Foreword Preface
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Fine-scale mapping of High Nature V
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Characterization of a Maculinea alc
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Urban tree inventory and socio-econ
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xiii Foreword Twenty years ago, Dr.
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Section 1 Scaling in landscape anal
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V. Cortes et al. 2010. Environmenta
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D. S. de Ron et al. 2010. Habitat s
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B. Bożętka 2010. Recent relations
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S.F. Chen et al. 2010. A physiotope
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V.D. de Campos & S M. Carvalho 2010
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N.S. Evseeva & Z.N. Kvasnikova 2010
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N.S. Evseeva & Z.N. Kvasnikova 2010
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S. Frank et al. 2010. A regionally
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M. García et al. 2010. The effect
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M. García et al. 2010. The effect
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S. Gholami et al. 2010. Spatial pat
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P. González-Moreno et al. 2010. Th
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T. Höbinger et al. 2010. Impact of
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P. Matos et al. 2010. Can lichen fu
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E.S. Meier et al. 2010. Projections
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E.S. Meier et al. 2010. Projections
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H. Moutahir et al. 2010. Applicatio
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H. Moutahir et al. 2010. Applicatio
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C. Palaghianu 2010. The use of Voro
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F. Peña-Cortés et al. 2010. Spati
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F.M. Rabenilalana et al. 2010. Mult
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A. Ruskule et al. 2010. Patterns of
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E. Sayad 2010. Nitrogen retrancloca
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E. Sayad 2010. Nitrogen retrancloca
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G. Zhelezov 2010. Evaluation of the
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Section 3 Disturbances in changing
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A. Altamirano et al. 2010. Human-ca
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A. Altamirano et al. 2010. Human-ca
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T. Curt & J. Pausas 2010. Are chang
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R.A Fleming et al. 2010. Forest man
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R.A Fleming et al. 2010. Forest man
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P.C. Goebel et al. 2010. How import
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L.R. Iverson et al. 2010. Merger of
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T.-C. Lin et al. 2010. Immediate ef
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K. L. Martin & P.C. Goebel 2010. Im
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G.M. Pastur et al. 2010. Indirect e
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E.W Saragih et al. 2010. Effects of
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L.R.P. Williamson et al. 2010. Anth
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N. Zurbriggen et al. 2010. Modeling
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Section 4 Biodiversity conservation
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Akbarzadeh et al. 2010. Ecotourism
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Akbarzadeh et al. 2010. Ecotourism
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C. Carvalho-Santos 2010. Fine-scale
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I. Catalano et al. 2010. Wood macro
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R.A. Diaz-Varela et al. 2010. Exten
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R.A. Diaz-Varela et al. 2010. Asses
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P.A.E. Diogo & J. Aranha 2010. GIS
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P.A.E. Diogo & J. Aranha 2010. GIS
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V. Etemad & N. Avani 2010. Investig
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A.E. Eycott et al. 2010. The impact
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E. Fernández-Núñez et al. 2010.
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N. Fracassi & D. Somma 2010. Partic
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J. Hartter et al. 2010. Fortresses
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M.B. Horta et al. 2010. Landscape S
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J.O. López-Martínez et al. 2010.
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Sara Marques et al. 2010. Impact of
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M.G.C. Martins & J. Aranha 2010. El
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M.G.C. Martins & J. Aranha 2010. El
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J.-F. Mas et al. 2010. Modeling lan
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R.S. Moro & T.K. Pereira 2010. Eval
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R.S. Moro & C.H Rocha 2010. A metho
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V. Núñez et al. 2010. Landscape i
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S.G. Plexida & A.I. Sfougaris 2010.
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A. Poljanec & A. Boncina 2010. Chan
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M. Redon & S. Luque 2010. Tengmalm
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M.C.C. Rodrigues et al. 2010. Contr
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M.C. Silva et al. 2010. Using Busin
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T.N. Terra & R.F dos Santos 2010. L
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E. Tetetla-Rangel et al. 2010. Rela
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M. Tsibulnikova 2010. Economic esti
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M. Akbarzadeh & E. Kouhgardi 2010.
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B. Baran-Zgłobicka & W. Zgłobicki
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B. Baran-Zgłobicka & W. Zgłobicki
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J. Beldade & T. Panagopoulos 2010.
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S.M. Carvalho & A.R. de Freitas 201
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R.A. Diaz-Varela et al. 2010. Quant
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I. Duarte & F.C. Rego 2010. Land us
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J.S.V. Filho & M.L. Leite 2010. Sim
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F.J. Gómez et al. 2010. Land use c
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M.L. Leite & J.S.V. Filho2010. Anal
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M.L. Leite & J.S.V. Filho2010. Anal
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M.L.Leite & J.S.V. Filho 2010. Iden
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M. Ortega et al. 2010. Monitoring v
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G. Puddu et al. 2010. Landscape tra
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H.R. Ratsimba et al. 2010. Multi-sc
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M.C. Rodrigues et al. 2010. Charact
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M.C. Rodrigues et al. 2010. Charact
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M.T.C. Rodrigues & V. Silva 2010. L
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J. Schaefer-Santos & C. Lingnau 201
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S.M. Scheffer & E. Schimanski 2010.
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S.M. Scheffer & E. Schimanski 2010.
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J. Superson et al. 2010. The defore
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A.L. Teixido et al. 2010. Impacts o
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H. Viana & J. Aranha 2010. Assessin
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H. Viana & J. Aranha 2010. Mapping
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Section 6 Tools of landscape assess
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N. Avani et al. 2010. Investigation
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J.C. Azevedo et al. 2010. Spatial d
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T. Batista et al. 2010. The third d
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V. Caboun 2010. New classification
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A.M. Carvalho et al. 2010. Connecti
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M. Deconchat et al. 2010. Identific
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J. Gaspar et al. 2010. Visibility a
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J. Gaspar et al. 2010. Visibility a
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A.M. Geraldes 2010. Landscape runof
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A.M. Geraldes & M.J. Boavida 2010.
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K. Koschke et al. 2010. Using a mul
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J.-F. Mas et al. 2010. Assessing
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A. Matos et al. 2010. Economic valu
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A. Migliozzi et al. 2010. Land-use
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M.L Porto et al. 2010. Naturalness
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M.L Porto et al. 2010. Naturalness
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M. Rehor & V. Ondracek 2010. Applic
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J. Russell et al. 2010. Developing
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Section 7 Management and sustainabi
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P. Angelstam & M. Elbakidze. 2010.
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M. Castro et al. 2010. Relationship
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M. Elbakidze et al. 2010. Does fore
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F. Fonseca & T. de Figueiredo 2010.
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A. Gil-Tena et al. 2010. Disentangl
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M.B. Horta & E. Keizer 2010. Assess
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E. Kouhgardi & M. Akbarzadeh 2010.
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E. Kouhgardi et al. 2010. Values of
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E. Kouhgardi et al. 2010. Values of
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E. Schimanski 2010. The importance
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L.A.M. da Silva & E. Shimanki 2010.
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N. Stryamets et al. 2010. Role of n
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E. Volkova 2010. The regional analy
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Section 9 Symposia
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Z.L. Urech & J.P. Sorg 2010. Taking
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Measures of landscape structure as
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J.L. Hernández-Stefanoni et al. 20
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Page 744 and 745: A. Ouin et al. 2010. Do wooded elem
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Page 756 and 757: J.M. Rey Benayas 2010. Restoration
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