Progress in Phenology Monitoring, Data Analysis, and Global - TUM

International Conference
Progress in Phenology
Monitoring, Data Analysis, and Global
Change Impacts
October 4-6, 2000
Freising, Germany
Abstract Booklet
Organized in conjunction with the
First workshop of the 5th
Framework Programme
EU-project POSITIVE
International
Society of
Biometeorology
Dutch National
Research
Programme on
Global Air
Pollution and
Climate Change
Sponsored by
Deutsche
Forschungsgemeinschaft
Deutsche
Meteorologische
Gesellschaft
Edited by
A. Menzel
Technische
Universität
München
POSITIVE

PROGRAMME COMMITTEE
Elisabeth Beaubien, University of Alberta, Canada
Dr. Elisabeth Koch, Zentralanstalt für Meteorologie und Geodynamik, Austria
Dr. Annette Menzel, Technical University of Munich, Germany
Prof. Mark D. Schwartz, University of Wisconsin-Milwaukee, USA
Tim Sparks, Centre for Ecology and Hydrology, UK
Arnold van Vliet, Wageningen University/Maastricht University, The Netherlands
ORGANISING COMMITTEE
Dr. Annette Menzel, Dr. Michaela M. Hirschberg
Technical University of Munich
Department of Ecology / Bioclimatology and Pollution Research
Am Hochanger 13
85 354 Freising
Germany
e-mail: menzel@met.forst.tu-muenchen.de
Phone: (+49) 8161 714740
Fax: (+49) 8161 714753
EU-project POSITIVE:
http://www.forst.tu-muenchen.de/EXT/LST/METEO/positive/
Department of Ecology / Bioclimatology and Pollution Research:
http://www.forst.tu-muenchen.de/EXT/LST/METEO/index.html/
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CONTENTS
WELCOME ................................................................................................................................................... 9
SCHEDULE ................................................................................................................................................ 11
ABSTRACTS.............................................................................................................................................. 15
SESSION 1 PHENOLOGICAL MONITORING AND NETWORKS ........................................................... 15
METEOROLOGICAL AND PHENOLOGICAL OBSERVATIONS WITHIN THE PAN-EUROPEAN
PROGRAMME FOR THE INTENSIVE MONITORING OF FOREST ECOSYSTEMS (LEVEL II
OF EU/IPC FORESTS).............................................................................................................................................15
T. Preuhsler
GENERAL CONSIDERATIONS ABOUT PHENOLOGICAL OBSERVATIONS NETWORK IN
ALBANIA AND THE ACTUAL PROBLEMS.......................................................................................................16
P. Zorba
THE STRUCTURE OF THE CZECH PHENOLOGICAL DATABASE............................................................17
J. Nekovár
PHENOLOGICAL MAPS OF EUROPE ................................................................................................................18
Th. Roetzer, F.-M. Chmielewski
HOW TO MEASURE SEASONALITY - METHODS FOR PHENOLOGICAL CALENDARS AND
ANALYSIS OF EXTREME YEARS .......................................................................................................................19
R. Ahas, J. Jaagus, A. Aasa
NUMERICAL DATA ANALYSIS, QUALITY CONTROL AND MODELLING OF
PHENOLOGICAL OBSERVATIONS ON COMMERCIAL FRUIT TREES IN THE COLOGNE -
BONN - KOBLENZ AREA.......................................................................................................................................20
M. Müller, P. Braun, A. Hense, R. Glowienka-Hense
POLLEN SOURCES DETERMINING THE AEROBIOLOGICAL SITUATION IN ESTONIA AND
FLOWERING PHENOPHASES INFLUENCING THIS SITUATION...............................................................21
M. Saar
DIFFERENCES IN SEASONAL DYNAMICS BETWEEN CANOPY AND LOWER TRUNK
SPIDERS ON PINE TREES.....................................................................................................................................22
U. Simon
SESSION 2A ANIMAL PHENOLOGY AND GLOBAL CHANGE ............................................................. 23
MUSEUM EGG COLLECTIONS AS STORES OF LONG-TERM PHENOLOGICAL DATA ......................23
J.P.W. Scharlemann
THE EFFECTS OF TEMPERATURE, ALTITUDE AND LATITUDE ON THE ARRIVAL DATES
OF THE SWALLOW HIRUNDO RUSTICA IN THE SLOVAK REPUBLIC ....................................................24
T. H. Sparks, O. Braslavska
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THE CHANGE OF MIGRATION TIME OF THE ORDINARY BIRDS OF LAPLAND
ZAPOVEDNIK (KOLA PENINSULA, RUSSIA) OVER THE PERIOD OF 1931-1999 ...................................25
A. Gilyazov
ARRIVAL DATES OF BIRDS IN SW FINLAND 1748-1998 – DATA AND THE MESSAGE ........................26
E. Lehikoinen
PHENOLOGY OF BRITISH BUTTERFLIES AND CLIMATE CHANGE.......................................................27
D. Roy, T. Sparks
SESSION 1 PHENOLOGICAL MONITORING AND NETWORKS ........................................................... 28
CANADA PLANTWATCH: TRENDS TO EARLIER SPRING DEVELOPMENT..........................................28
E.G. Beaubien
EUROPEAN PHENOLOGY NETWORK – A NETWORK FOR INCREASING EFFICIENCY,
ADDED VALUE AND USE OF PHENOLOGICAL MONITORING RESEARCH, AND DATA IN
EUROPE.....................................................................................................................................................................29
A. J.H. van Vliet, R. S. de Groot
SESSION 2B PLANT PHENOLOGY AND GLOBAL CHANGE ............................................................... 30
PHYTOPHENOLOGICAL TRENDS IN SWITZERLAND.................................................................................30
C. Defila
LONG-TERM DEVELOPMENT OF CLIMATE AND PHENOLOGY OF BEECHES IN SOUTH-
WESTERN GERMANY ...........................................................................................................................................31
A. Kirchgäßner , H. Mayer
TRENDS IN PHENOLOGICAL STUDIES IN ARGENTINA .............................................................................32
A. Faggi, O. Scarpati and L. Spescha
OLIVE PHENOLOGY: INDICATOR OF GLOBAL WARMING IN THE MEDITERRANEAN ..................33
C. Osborne, I. Chuine, D. Viner & F.I. Woodward
REGIONAL TRENDS OF THE BEGINNING OF GROWING SEASON IN EUROPE AND
POSSIBLE CLIMATIC CAUSES ...........................................................................................................................34
F.-M. Chmielewski, Th. Rötzer
SESSION 3 PHENOLOGY AND REMOTE SENSING .............................................................................. 35
NORTHERN PHOTOSYNTHETIC AND GROWING SEASON TRENDS FROM 1981 TO 1999.................35
C. J. Tucker, D. Slayback, J. Pinzon, S. Los, R. Myneni, M. Paris
ASSESSING SATELLITE-DERIVED PHENOLOGY IN NORTH AMERICA ................................................36
M. D. Schwartz
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AN ANALYSIS OF TEMPORAL RELATIONSHIPS BETWEEN PLANT COMMUNITY
PHENOLOGY AND SEASONAL NDVI METRICS IN NORTHERN CHINA .................................................37
X. Chen
EUROPEAN GREEN WAVE OBSERVED IN NOAA/AVHRR NDVI DATA AND IN THE
INTERNATIONAL PHENOLOGICAL GARDENS.............................................................................................38
M.M. Hirschberg, A. Menzel and C.J. Tucker
THE IMPACT OF VEGETATION SEASONALITY ON GLOBAL CARBON BUDGETS: A
COMPARISON OF LPJ MODEL RESULTS WITH SATELLITE OBSERVATIONS....................................39
W. Lucht, A. Bondeau, S. Sitch and W. Cramer
TRENDS IN NOAA/AVHRR NDVI AND PHENOLOGICAL RECORDS IN GERMANY FROM
1981-1998....................................................................................................................................................................40
A. Menzel and C.J. Tucker
INTERANNUAL VARIATIONS OF BUDBURST OF DECIDUOUS FORESTS IN CENTRAL AND
WESTERN EUROPE DERIVED FROM A 10 YEARS DAILY NOAA/AVHRR 1KM ARCHIVE,
GROUND-BASED PHENOLOGICAL OBSERVATIONS AND ECOSYSTEM MODEL
SIMULATIONS.........................................................................................................................................................41
A. Bondeau, K. Böttcher, W. Lucht, E. Dufrêne, J. Schaber
EFFECTS OF URBANIZATION ON GROWING SEASON DYNAMICS AND GROSS PRIMARY
PRODUCTION IN MAJOR METROPOLITAN AREAS IN THE UNITED STATES. ....................................42
M.A. White, R.R. Nemani
SESSION 4 MODELLING PHENOLOGY .................................................................................................. 43
TESTING TEMPERATURE DATA FOR PHENOLOGICAL MODELS ..........................................................43
R. Snyder, D. Spano, C. Cesaraccio, P. Duce
AN IMPROVED MODEL FOR DEGREE DAYS FROM DAILY TEMPERATURE DATA...........................44
C. Cesaraccio, D. Spano, P. Duce, R. L. Snyder, and P. Deidda
IMPORTANCE OF PHENOLOGY AND PHENOLOGICAL MODELS ON AN INTEGRATED
EVALUATION OF FOREST ECOSYSTEM MONITORING DATA ................................................................45
S. Raspe
A BARLEY ONTHOGENIC MODEL AS A TIME-BASE FOR MONITORING ADVERSE
AGROMETEOROLOGICAL FACTORS..............................................................................................................46
J. Valter
FORECASTING AIRBORNE POLLEN CONCENTRATIONS: DEVELOPMENT OF LOCAL
MODELS....................................................................................................................................................................47
A.Ranzi, P. Lauriola, F. Zinoni, L.Botarelli
MODELLING THE PROBABILITY OF GYPSY MOTH ESTABLISHMENT IN NEW AREAS OF
NORTH AMERICA ON THE BASIS OF PHENOLOGY ....................................................................................48
J. Régnière, V.G. Nealis
ON MODELLING OF PHENOLOGICAL AUTUMN PHASES .........................................................................49
N. Estrella
ANALYSIS OF PHENOLOGICAL MODELS USING STATISTICAL RESAMPLING METHODS ............50
R. Häkkinen
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SESSION 5A APPLICATIONS OF PHENOLOGY IN AGRICULTURE AND FORESTRY....................... 51
REALISM IN PHENOLOGICAL MODELS FOR THE ANNUAL CYCLE OF TREES:
IMPORTANT FOR CLIMATE CHANGE IMPACT ASSESSMENT! ...............................................................51
K. Kramer, I. Leinonen, H. Hänninen
APPLICATION OF PHENOLOGY IN AGRICULTURAL PRODUCTION PLANNING IN
SLOVENIA ................................................................................................................................................................52
A.Sušnik
USE OF BIOCLIMATIC INDEXES TO CHARACTERIZE PHENOLOGICAL PHASES OF APPLE
VARIETIES IN NORTHERN ITALY ....................................................................................................................53
N. Valentini, G. Me, R. Ferrero, F. Spanna
PHENOLOGICAL PREDICTIONS IN PLANTS..................................................................................................54
F.E. Wielgolaski
GROWTH AND PHENOLOGY OF A SEMINATURAL GRASSLAND SUBMITTED TO
ELEVATED ATMOSPHERIC CARBON DIOXIDE CONCENTRATION .......................................................55
A.Raschi, F.Selvi, S. Marchi, S. Sforzi
SESSION 5B APPLICATIONS OF PHENOLOGY IN ECOLOGY ............................................................ 56
PHENOLOGICAL MONITORING OF INDIVIDUAL TREES ..........................................................................56
R. Brügger, A. Vassella, F. Jeanneret
INCREASING FROST DAMAGE RISK OF EARLY FLOWERING BOREAL TREE SPECIES:
WILL CLIMATE CHANGE MAKE THEM DECLINE? ....................................................................................57
T. Linkosalo
EVALUATING THE POTENTIAL FOR CLIMATE CHANGE INDUCED BARK BEETLE
INVASION OF HIGH ELEVATION ECOSYSTEMS ..........................................................................................58
J. A. Logan, J. A. Powell, B. J. Bentz
LOSS OF SYNCHRONY BETWEEN HIGH- AND LOW- ALTITUDE FLOWERING PHENOLOGY
DUE TO CLIMATE CHANGE................................................................................................................................59
D. W. Inouye
POSTERS................................................................................................................................................... 60
GIS ANALYSES FOR PHENOLOGICAL DATABASES IN ESTONIA............................................................60
A. Aasa, R. Ahas
PHENOLOGICAL PROGRAMS IN RUSSIAN NATURE ZAPOVEDNIKS.....................................................61
V.Barcan
PLANTWATCH: BIOMONITOR FOR CLIMATE CHANGE ...........................................................................62
E.G. Beaubien, T.C. Lantz
PLANTWATCH: CANADIANS TRACK THE ARRIVAL OF SPRING ...........................................................62
E.G. Beaubien, T.C. Lantz
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REMOTE ASSESSMENT OF PHENOLOGICAL EVENTS USING DIGITAL CAMERAS ..........................63
E. Beuker
PRINCIPAL PHENOLOGICAL GROWTH STAGES OF POME, STONE FRUIT AND
CURRANTS: CODING AND DESCRIPTION ACCORDING TO THE BBCH SCALE..................................64
E. Bruns
EXPERIENCE OF THE DENDROPHENOLOGICAL INDICATION OF SHORT-TERM CLIMATE
CHANGES AND OF CURRENT WARMING IN EASTERN EUROPE ............................................................66
N.E. Bulygin
FORECAST OF FULL FLOWERING DATES OF PEAR TREE (PYRUS COMMUNIS L.), APPLE
TREE (MALUS DOMESTICA BORKH) AND PLUM TREE (PRUNUS DOMESTICA L.) –
SIMILARITIES AND DIFFERENCES...................................................................................................................67
K. Bergant, Z. Crepinsek, L. Kajfez-Bogataj
CLIMATE AND APHID PHENOLOGY ................................................................................................................68
R. Harrington, M. Else, C. Denholm, J. Pickup, M. Hullé
RUSSIAN PHENOLOGY: HISTORY AND PRESENT DAY..............................................................................69
V.G. Fedotova
LARGE SCALE CLIMATE VARIABILITY AND ITS EFFECTS ON MEAN TEMPERATURE AND
FLOWERING TIME OF PRUNUS AND BETULA...............................................................................................70
A.K. Gormsen, T.B. Toldam-Andersen and P. Braun
LOSS OF SYNCHRONY BETWEEN HIGH- AND LOW- ALTITUDE FLOWERING PHENOLOGY
DUE TO CLIMATE CHANGE................................................................................................................................70
D. W. Inouye
ALPINE LONG TIME DATA SETS.......................................................................................................................71
E. Koch
A COMMON PHENOLOGICAL DATA BASE FOR THE EU PROJECT ‘POSITIVE’ .................................72
H. Scheifinger, W. Lipa
THE USE OF MODIS NADIR BRDF-ADJUSTED REFLECTANCES TO MONITOR
PHENOLOGICAL ACTIVITY................................................................................................................................73
A. H. Strahler, C. B. Schaaf, M. Friedl, W. Lucht, F. Gao, X. Zhang, D. McIver, and J. F. C. Hodges
PHENOLOGY AS GLOBAL CHANGE BIO-INDICATOR ................................................................................74
A.Menzel
EU-PROJECT POSITIVE: PHENOLOGICAL OBSERVATIONS AND SATELLITE DATA (NDVI):
TRENDS IN THE VEGETATION CYCLE IN EUROPE.....................................................................................76
A.Menzel, R. Ahas, I. Chuine, M. Hirschberg, E. Koch, C. Tucker
LIGHT AS A FACTOR AFFECTING THE FRUIT PHENOLOGY OF ATLANTIC RAIN FOREST
TREES: A CASE STUDY OF CRYPTOCARYA MOSCHATA (LAURACEAE) .................................................77
P. Moraes and L.P.C. Morellato
FLOWERING AND FRUITING PHENOLOGY IN ATLANTIC RAIN FOREST MYRTACEAE OF
BRAZIL: CLIMATIC AND PHYLOGENETIC CONSTRAINTS ......................................................................77
L.P.C. Morellato
ESTONIAN ICHTYOPHENOLOGICAL CALENDAR AS SOURCE FOR CLIMATE CHANGE
STUDIES ....................................................................................................................................................................78
V. Palm
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USE OF PHENOLOGY IN AGRICULTURE........................................................................................................79
Th. Roetzer, H. Häckel, R. Würländer
DETECTING OUTLIERS IN LARGE PHENOLOGICAL DATA SETS...........................................................80
J. Schaber and F. Badeck
ANALYSIS AND APPLICATION OF PHENOLOGY MODELS TO DATA OF THE GERMAN
WEATHER SERVICE (DWD) ................................................................................................................................80
J. Schaber
INTERACTION BETWEEN AGROMETEOROLOGICAL PATTERN AND PHENOLOGY IN
BAROLO WINE AREA............................................................................................................................................81
F. Spanna, C. Lovisolo
WINTER CLIMATE AND FLOWER BUD MORTALITY OF SOUR CHERRY (PRUNUS
CERASUS)..................................................................................................................................................................82
T.B. Toldam-Andersen, I. Dencker, P. Braun
DETECTION OF THE ARRIVAL DATE OF MIGRATING BIRDS IS DENSITY-DEPENDENT: A
CASE STUDY OF THE RED-BACKED SHRIKE LANIUS COLLURIO ...........................................................83
P. Tryjanowski
RECENT CHANGES IN NEST TIMING OF THE RED-BACKED SHRIKE LANIUS COLLURIO IN
POLAND ....................................................................................................................................................................83
P. Tryjanowski, S. Kuzniak, T.H. Sparks
EUROPEAN PHENOLOGY NETWORK – A NETWORK FOR INCREASING EFFICIENCY,
ADDED VALUE AND USE OF PHENOLOGICAL MONITORING RESEARCH, AND DATA IN
EUROPE.....................................................................................................................................................................83
A. J.H. van Vliet, R. S. de Groot
PHENOLOGICAL MODIFICATION IN PLANTS BY SOIL FACTORS .........................................................84
F.E. Wielgolaski
LIST OF PARTICIPANTS .......................................................................................................................... 87
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WELCOME
On behalf of the programme committee, it gives me great pleasure to welcome you to
the International Conference “Progress in Phenology – Monitoring, Data Analysis and
Global Change Impacts”, held at Freising, Germany, October 4-6 2000. This conference
is organized in conjunction with the first workshop of the 5 th framework EU project
POSITIVE and represents at the same time the yearly meeting of phenologists working
at several central European national weather services, the last meeting being at Prague
in 1999. It follows sessions of the Phenology Study Group of the ISB at the 14 th
International Congress of Biometeorology at Ljubljana (1996), a phenology session at
the meeting of the Association of American Geographers at Boston (1998) and a
phenology session at the 13 th International Botanical Congress at St. Louis (1999) as
well as at the 15 th International Congress of Biometeorology at Sydney (1999).
We are honoured by the presence of many distinguished participants here in Germany,
some of whom have travelled far to be with us for this meeting. We thank the persons
and institutions whose contributions and efforts have made this conference possible,
especially we wish to acknowledge the financial support of the organizations listed on
the front page and to express our gratitude to them.
The scientific programme of the conference reflects the excitement, great diversity and
application of phenology. It will address all aspects of plant and animal phenology with
a focus on monitoring and modelling phenology, and the assessment of future impacts
as well as applications of phenology in the context of global climate change. This
abstract booklet consists of 3 keynote lectures introducing the main topics, 43
presentations expanding these topics, and more than 30 posters representing a wide
range of themes and scientific studies. They are prepared and discussed by over 70
participants from countries all over the world.
We hope that students and scientists working in the field of phenology will benefit from
this abstract booklet. Manuscripts of several presentations will be published, under the
normal review process, in the International Journal of Biometeorology.
We have made great efforts to bring together phenologists from a wide range of
countries in order to present and share recent findings and to discuss the present state
and future contributions of phenology. We hope you will take the opportunity not only
to greet old friends, but also establish new collaborations and make the phenology
community “closer”.
Once again, welcome to you all!
Many thanks
Annette Menzel
9

SCHEDULE
Progress in Phenology - Monitoring, Data Analysis and Global Change
Impacts
Starting time 04.10.00
10:30 Registration (11:30 Meeting of the chairs )
12:00 Lunch
12:45 Welcome addresses
Prof. Peter Fabian, Department of Ecology, TU Munich
Prof. Mark D. Schwartz, Commission 1 Vegetation Dynamics, Climate and Biodiversity of ISB
Session 1 Phenological Monitoring and Networks Arnold Van Vliet Chairperson
13:00 Meteorological and phenological observations within the Pan-European Programme for Teja Preuhsler
intensive monitoring of forest ecosystems (Level II of EU/IPC Forests)
Keynote speaker
13:40 General Considerations about phenological observations network in Albania and the actual Zorba
problems
14:00 The structure of the Czech phenological database Nekovar
14:20 Phenological maps of Europe Rötzer, Chmielewski
14:40 How to measure seasonality - methods for phenological calendars
and analysis of extreme years
Ahas, Jaagus, Aasa
15:00 Numerical data analysis, quality control and modelling of phenological observations on Müller, Braun, Hense, Glowienka-Hense
commercial fruit trees in the Cologne-Bonn-Koblenz area
15:20 Pollen sources determining the aerobiological situation in Estonia and flowering Saar
phenophases influencing this situation
15:40 Differences in seasonal dynamics between canopy and lower trunk spiders on pine trees Simon
16:00 Coffee & Poster Presentation
Session 2 A Animal Phenology and Global Change Elisabeth Beaubien Chairperson
16:30 Museum egg collections as stores of long-term phenological data Scharlemann
16:50 The effects of temperature, altitude and latitude on the arrival dates of the swallow Hirundo Sparks, Braslavska
rustica in the Slovak Republic
17:10 Changes of migration time of hte ordinary birds of Lapland Zapovednik (Kola Peninsula, Gilyazov
Russia) over the period of 1931-1999
17:30 Arrival dates of birds in SW Finland 1748-1998 - data and the message Lehikoinen

12
17:50 Phenology of British butterflies and climate change Roy, Sparks
18:15 Dinner
Session 1 (cont.) Phenological Monitoring and Networks Peter Fabian Chairperson
19:20 Canada Plantwatch: trends to earlier spring development Beaubien
19:40 The European Phenological Network Van Vliet, de Groot
20:00 Discussion Phenological Monitoring and Networks
05.10.00
7:45 Breakfast
Session 2 B Plant Phenology and Global Change Annette Menzel Chairperson
8:30 Phytophenological trends in Switzerland Defila
8:50 Long-term Development of Climate and Phenology of Beeches in South-western Germany Kirchgäßner, Mayer
9:10 Trends in phenological studies in Argentina Faggi, Scarpati, Spescha
9:30 Olive phenology: indicator of global warming in the Mediterranean Osborne, Chuine, Viner, Woodward
9:50 Regional trends of the growing season in Europe and their possible climatological causes Chmielewski, Rötzer
10:10 Coffee & Poster Presentation
Session 3 Phenology and Remote Sensing Tim Sparks Chairperson
10:40 Northern photosynthetic and growing season trends from 1981-1999 Compton Tucker Keynote speaker
11:20 Assessing Satellite-derived Phenology in North America Schwartz
11:40 An analysis of temporal relationships between plant community phenology and seasonal Chen
NDVI metrics in Northern China
12:00 Lunch
13:00 European green wave observed in NOAA/AVHRR NDVI data and in the International Hirschberg, Menzel
Phenological Gardens
13:20 The Impact of Vegetation Seasonality on Global Carbon Budgets: A Comparison of LPJ Lucht, Bondeau, Sitch, Cramer
Model Results with Satellite Observations
13:40 Trends in NOAA/AVHRR NDVI and phenological records in Germany from 1981-1998 Menzel
14:00 Interannual variations of the budburst day of deciduous forests in central and western Bondeau, Böttcher, Lucht, Dufrêne, Schaber
Europe derived from a 10 years daily NOAA/AVHRR 1km archive, ground-based
phenological observations and ecosystem model simulations
14:20 Effects of urbanization on growing season dynamics and gross primary production in major
metropolitan areas in the United States
White, Nemani

14:40 Coffee & Poster Presentation
Session 4 Modelling Phenology Koen Kramer Chairperson
15:10 Testing temperature data for phenological models Snyder, Spano, Cesaraccio, Duce
15:30 An improved model for degree days from daily temperature data Cesaraccio, Spano, Duce, Snyder, Deidda
15:50 Importance of Phenology and Phenological Models on an Integrated Evaluation of Forest Raspe
Ecosystem Monitoring Data
16:10 A barley onthogenic model as a time-base for monitoring adverse agrometeorological factors Valter
16:30 Guided Tour through Freising
18:00 Dinner
Session 4 Modelling Phenology Koen Kramer Chairperson
19:00 Forecasting airborne pollen concentrations: development of local models Ranzi, Lauriola, Zinoni, Botarelli
19:20 Modeling the probability of Gypsy moth establishment in new areas of North America on the Régnière, Nealis
basis of phenology
19:40 About modelling of phenological autumn phases Estrella
20:00 Analysis of phenological models using statistical resampling methods Häkkinen
06.10.00
7:45 Breakfast
Session 5 A Applications of Phenology in Agriculture and Forestry Mark Schwartz Chairperson
8:30 Realism in phenological models for the annual cycles of trees: important for climate change Koen Kramer
impact assessment!
Keynote speaker
9:10 Application of phenology in agricultural production planning in Slovenia Susnik
9:30 Use of bioclimatic indexes to characterize phenological phases of apple varieties in Northern Valentini, Me, Ferrero, Spanna
Italy
9:50 Phenological prediction in plants Wielgolaski
10:10 Growth and phenology of a seminatural grassland submitted to elevated atmospheric carbon Raschi, Selvi, Marchi, Sforzi
dioxide concentration
13

14
10:30 Coffee & Poster Presentation
Session 5 B Applications of Phenology in Ecology Teja Preuhsler Chairperson
10:50 Phenological Monitoring of Individual Trees Brügger, Vassella, Jeanneret
11:10 Increasing frost damage risk of the early flowering boreal tree species: will climate change Linkosalo
make them decline ?
11:30 Evaluating the potential for climate change induced bark beetle invasion of high elevation Logan, Powell, Bentz
ecosystems
11:50 Loss of synchrony between high- and low-altitude flowering phenology due to climate Inouye
change
12:10 Statement at the closing of the conference Prof. Dr. H. Meyer, TU München, Dean of the
Life Science Center Weihenstephan
Dr. Peter Höppe, President of ISB
12:20 Concluding Remarks Dr. Annette Menzel
12:30 Lunch

ABSTRACTS
SESSION 1 PHENOLOGICAL MONITORING AND NETWORKS
METEOROLOGICAL AND PHENOLOGICAL OBSERVATIONS WITHIN THE
PAN-EUROPEAN PROGRAMME FOR THE INTENSIVE MONITORING OF
FOREST ECOSYSTEMS (LEVEL II OF EU/IPC FORESTS)
T. Preuhsler
Bavarian State Institute of Forestry, Freising, Germany
pre@lwf.uni-muenchen.de/Fax: +49-8161-714971
In order to gain a better understanding of the effects of air pollution and other stress factors on forests, a
Pan-European Programme for Intensive and Continuous Monitoring of Forest Ecosystems has been
implemented within the last 8 years (the so-called "Level II programme"). In this context 861 permanent
observation plots for Intensive Monitoring have been installed - 512 in the European Union and 351 in
several non-EU European countries.
The Intensive Monitoring Programme aims at the assessment of crown condition, increment and the
chemical composition of foliage and soil on all plots over a period of at least 15 to 20 years. On a limited
number of these plots additional measurements are foreseen or already carried out, like atmospheric
deposition, soil solution chemistry, ground vegetation and meteorological parameters, as well as
observations concerning phenology, phytopathology and litterfall.
Meteorological variables comprise the most decisive and variable parameters affecting structur, growth,
health and stability of forest ecosystems. They also contain the main factors guiding deposition into forest.
Within the aims of the Level II monitoring program, Forest Phenology is defined as the systematic
observation and recording of the biotic and abiotic (e.g. damaging) events and phenomena and of the yearly
development stages of forest trees. Main objective of phenological observation at the level II plots is to
provide supplementary and complementary information on the status and development of forest tree
condition during the year.
The meteorological and phenological programme parts started within the last few years, which was late
inside of the monitoring programme on Level II plots. The phase of installation or beginning of the
monitoring is not completed yet. The European Expert Group for Meteorology and Phenology for this
programme is still busy with the definition and formulation of their part of the programme and the gathering
and excange of experience in techniques and basic evaluations.
An overwiev of the objectives, sampling design, methods and parameters of both parts of the level II
programme will be given in this keynote lecture.

GENERAL CONSIDERATIONS ABOUT PHENOLOGICAL OBSERVATIONS
NETWORK IN ALBANIA AND THE ACTUAL PROBLEMS
P. Zorba
Hydrometeorological Institute, Tirana, Albania
aspetalb@yahoo.com/ Fax: ++355 4 238 214
The phenological observations network of Albania is created during the year 1958-1960. At that time started
the first work related to the collection of phenological data about some principal agricultural plants as wheat,
maize, etc. Actually, the phenological data in the archive of our institute includes the period from 1971 until
today, with data for 13 most important agricultural plants cultivated in Albania, which come from 17
observation stations. In each station (point of observation), generally the data are collected for 4 agricultural
plants, the most representative of the respective area. Every 2 days, the observed phenological data are
collected from the observers in some appropriate tables and send at the end of each month to the
agrometeorological section of Hydrometeorological Institute in Tirana. There are carried out regular
controls, the necessary selection and the archive process. The digitalization has started in the last years.
The phenological data are used to evaluate and forecast the period of maturity of wheat, sunflower or as in
many cases for different phenological phases of plant development, to determine the coefficient of biological
minimum for the potato, sunflower, etc, and for other agrometeorological estimations.
Looking at the data series, during the years are noted that only few stations (7) have remained the same
points of observation. Furthermore, the plants and their varieties have changed many times during the years.
The same variety remains for 3-4 years and after that is replaced with another variety of the same plant. At
least only 3 or 4 plants (the same variety) like wheat, maize, potato and sunflower can offer data for a long
time and that is for about half of phenological stations.
During the period of transition and system changes (regarding the last 10 years) there are noted a series of
difficulties for different reasons, that are reflected in a non-continuity of observations at some stations. The
change of agriculture orientation has brought new foreign plants and variety in agricultural economy that in
a lot of cases are not adequate for the agrometeorological conditions of Albania and the final product
failures.
The actual problems consist in the impossibility to realize frequent controls at the phenological stations, to
establish a list with plants that can not be changed for at least 6 years as a minimum request for some
agrometeorological studies and to assure an adequate minimum stipend for the observers of phenological
stations. Another problem is related to the digitalization of phenological data that needs a computer and an
established methodology for this process.
16

THE STRUCTURE OF THE CZECH PHENOLOGICAL DATABASE
J. Nekovár
Czech Hydrometeorological Institute, Prag, Czech Republic
jiri.nekovar@chmi.cz
CHMI Prague has maintained three phenological sub-networks:
Region Area Number of phenological stations Density
km 2 Field Fruit Forest Total km 2 /station
Middle Bohemia 11.428 11 5 10 26 440
South Bohemia 11.400 8 2 5 15 760
West Bohemia 10.370 9 1 8 18 576
North Bohemia 8.710 7 5 3 15 581
East Bohemia 9.979 12 4 8 24 416
South Moravia 15.548 23 7 9 39 399
North Moravia 11.427 14 4 3 21 544
Czech Republic 78.862 84 28 46 158 499
CHMI has issued the phenological guidebooks that determine observational methods. This paper allows to
describe only the specification of observed species and phenophases. Actually, guidebooks include detailed
definitions of phenophases, directions for the choice of plants and their localities, description of localities,
reporting supplementary kinds of information, filling in forms, terms of reports plus many classification and
code tables.
Station of field crops phenology observes 15 species or their varieties from the list of 19 species:
Wheat (winter&spring), Rye, Barley (winter&spring), Oats, Sugar beet, Turnip, Potato, Maize, Peas, Horsebean,
Bean, Flax, Rape, Poppy, Alfalfa, Clover, Hops. The list of observed phenophases is as follows:
Sowing and Emergence (all species except hops, alfalfa, clover), Bud-breaking (hops), First leaves (rape,
alfalfa, clover, hops), Tillering (cereals), Stem elongation (cereals, rape, poppy), First and Second node
(cereals), Heading (cereals, maize), Axial branches visible (hops), Decortication as first ruptures on the
surface of roots (sugar beet, turnip), First button visible (horse-bean, bean, peas, flax, alfalfa, clover),
Flowering (all species except sugar beet, turnip), Flowering of male and female flowers (maize), Full
flowering (horse-bean, bean, peas, poppy, rape, flax, potato), End of flowering (cereals, poppy, rape, flax,
potato), Green ripeness (horse-bean, peas), Milky ripeness (cereals, maize), Waxy ripeness (maize), Yellow
ripeness (cereals, horse-bean, peas, rape, flax), Full ripeness (cereals, maize, horse-bean, bean, peas, poppy),
Harvest ripeness (sugar beet, turnip), Leaf&stem degradation (potato), Harvest (all species except alfalfa,
clover), 1 st +2 nd +3 rd cutting (alfalfa,clover).
Fruit trees phenology observes 15 species or their varieties from the list: Apple, Pear, Greengage (plum),
Cherry, Morello, Apricot, Peach, Red and white currants, Black currant, Gooseberry, Walnut, Hazelnut,
Vine. The list of observed phenophases is following: Bud-break of leaves (all species except apple, pear),
Bud-break of flowers (plum, cherry, morello, apricot, peach, hazelnut), Bud-break of mixed buds (apple,
pear), First leaves (all species), First button visible (apple, pear, plum, cherry, morello, apricot, peach),
Beginning of flowering (all species except walnut, hazelnut), Beginning of flowering of male flowers
(walnut, hazelnut), Beginning of flowering of female flowers (hazelnut), Full flowering (all species except
hazelnut), Petals start to fall (apple, pear, plum, cherry, morello), End of flowering (all species except
currants, gooseberry), Buds formation (apple, pear, plum, cherry, morello, apricot, peach), End of growth of
annual shoots (apple, pear), Harvest ripeness (all species), Harvest (apple, pear, plum, cherry, morello,
apricot, peach), End of fall of leaves (all species except currants, gooseberry, vine), Grapes start to hook and
to soften (vine).
The list of observed wild plants consists of fixed 45 species: Common Spruce, Larch, Pine, Dwarf pine,
Wild cherry, Blackthorn, Mountain ash, Hawthorn, False acacia, Hornbeam, Hazelnut, Birch, Black and
Gray Alder, Beech, Summer oak, Sallow, Mountain and Common Maple, Lime tree, Red dogwood, Wild
cornel, Golden and Red Elder, Marshmarigold, Windflower, Liverwort, Buttercup, Wild strawberry, Trailing
clover, St.John‘s wort, Narrow-leaved willowherb, Heather, Bilberry, White dead-nettle, Chrysanthemum,
Coltsfoot, Common and White Butterbur, Meadow saffron, Lily of the valley, Snowdrop, Orchard grass,
Meadow foxtail, Reed. There are observed these phenophases: Sprouting, First leaves, Full-leaf area
reached, Flowers buttons visible, Flowering, End of flowering, Buds formation, Start of fructification, May
sprouts, Summer leaves yellowing, Turning of sprouts to wood, Autumn leaves yellowing, Defoliation,
Ripeness of fruits.
17

PHENOLOGICAL MAPS OF EUROPE
Th. Roetzer, F.-M. Chmielewski
Section of Agricultural Meteorology, Humboldt-University, Berlin, Germany
thomas.roetzer@rz.hu-berlin.de / Fax: +49-30-31471211
The annual courses of the seasons are reflected by the regularity of the starting dates of phenological phases
of plants, like e.g. the unfolding of leaves or the beginning of flowering. Phenological maps show the
geographical distribution of the starting dates of phenophases, thus reflecting the dynamics of seasons.
The International Phenological Gardens (IPG) were the data base of the phenological maps of Europe. The
IPG-net ranges across 28 latitudes from Scandinavia to Macedonia and across 37 longitudes from Ireland to
Finland in the North and from Portugal to Macedonia in the South. Since 1961 the phenophases of 26
genetically identical trees and shrubs planted in 74 IPGs across Europe have been observed. After checking
the data and supplementing missing values in the time series the phenophases can be analysed and mapped.
Using multiple regression models the dependencies of the beginning of leaf unfolding, beginning of
flowering, first ripe fruits etc. on altitude, longitude and latitude were determined. The factors of the
regression models for some phenophases are shown in figure 1.
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Fig.1: Dependencies of different
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longitude and latitude
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M: May shoot)
While the factor of altitude ranges from 2.0 d/100m (BO Fagus silvatica H -1961-98) to 4.56 d/100m (B
Robinia pseudoacaccia - 1961-98), the latitude-factors were within 1.81 d/°latitude (BO Fagus silvatica H -
1961-98) and 4.53 d/°latitude (BO Prunus avium L – 1970) and the longitude-factors within 0.23
d/°longitude (BO Fagus silvatica H -1961-98) and 0.83 d/°longitude (BO Prunus avium L – 1970).
Using a digital elevation model (DEM) with a horizontal grid spacing of 30 arc-seconds (approximately 1
km) and the results of the regression analysis phenological phases were mapped. Phenological maps
showing means, trends and starting dates of extreme years as well as maps of the beginning, the end and the
length of the growing season were created. For a better orientation national borders, cities and rivers were
added to the maps. The quality of the maps was checked by comparing the data of the maps with observed
data of the IPGs.
Averaged over the years 1961 – 1998 the growing season starts in most regions of Europe between the 15 th
and 20 th of April, whereas the British Isles - with the exception of Scotland - show a beginning of the
growing season between the 5 th and the 15 th of April. An earlier beginning of the growing season before the
5 th of April was calculated for France and South Europe. A later beginning of the growing season after the
20 th of April can be seen in Northern Europe and in mountainous regions like the Alps or the Dalmatian
Mountains.

HOW TO MEASURE SEASONALITY - METHODS FOR PHENOLOGICAL
CALENDARS AND ANALYSIS OF EXTREME YEARS
R. Ahas, J. Jaagus, A. Aasa
Institute of Geography, University of Tartu, Estonia
reina@ut.ee / Fax 372-7-375825
Objectives of our study were to 1) Compose phenological calendars for different parts of the Northern
hemisphere. 2) Develop and test methods for analysis of those calendars. 3) Apply methods for analysis of
extreme years of phenological calendars. 4) To group studied years and locations by types of seasonal
patterns. 5) Compare seasonality and detect possible effects of climate change for different regions of the
Northern hemisphere.
Measuring of the seasonality and modelling seasonal sequence of natural processes is an important part of
the modelling ecological processes. Seasonality has many measures and parameters as phenological dates,
intervals and duration or meteorological parameters such as air and soil temperature, moisture, radiation etc.
The phenological calendars, which are lists of annual sequences of phenological phases and duration or
intervals between them, are normally a combination of both: phenological and meteorological data.
Phenological calendars help to describe or compare seasonality of every individual year, ecosystem,
organism or region. There are different methods and historical schools for composition of phenological
calendars. Today, phenology has an important source for the measuring of seasonal aspects of global change
and recorded calendars are very important databases for this purpose.
The analysis of extreme years of phenological calendars shows the effects of natural variation and
fluctuations, climate change impact, and ecological or physiological limits of the studied objects. In some
cases, the upper or lower quartile is used for the determination of extreme events. In the current study, we
use the term extreme years only for absolute minimum or maximum values in the calendar. The analysis of
extreme years can be very important for climatic trend analyses. The influence of extreme years on the
regression and slope of the linear trend is very high and it also has an influence on the confidence level of
statistics. Also, the influence of extreme events on the following periods and phases was studied.
The data was used from different observation networks between 1948-1999: A local phenological calendar
with up to 50 species and a daily mean air temperature for the same site. The phenological calendars were
composed with all beginning dates and duration (intervals) included. Climatic seasons were determined
similar to ordinary phenological phases, determined and recorded according to starting dates. Dates when the
daily mean air temperature crosses certain thresholds (0, +5°C and +13° in this study) are determined,
following procedures used by meteorological services for many decades. Once the temperature threshold has
been reached positive and negative differences of daily temperature minus the threshold value are summed
separately. As soon as the absolute value of the sum of negative differences is higher than the sum of the
positive differences, the first cross over of the temperature threshold is not taken as the start of the respective
season and the search for the season’s start is continued from this day.
19

NUMERICAL DATA ANALYSIS, QUALITY CONTROL AND MODELLING OF
PHENOLOGICAL OBSERVATIONS ON COMMERCIAL FRUIT TREES IN THE
COLOGNE - BONN - KOBLENZ AREA
M. Müller (1), P. Braun (2), A. Hense (3), R. Glowienka-Hense (3)
(1) Institut für Obstbau und Gemüsebau, University of Bonn, Germany
(2) Royal Veterinary and Agricultural University, Dept. of Agric. Sci., Sct. Horticulture, Taastrup, Denmark
(3) Meteorologisches Institut der Universität Bonn, Germany
One of the prerequisites for studying the impact of regional climate variability (e.g. such as the North
Atlantic Oscillation in Mideurope) upon natural as well as agricultural systems are homogeneous data in
space and time. Phenological observations such as those collected by the German Weather Service (DWD)
are obtained from volunteer networks with numerous problems concerning data quality and
representativeness. We will describe a method based upon modern techniques from numerical weather
analysis to produce gridded fields of phenological dates for the Cologne - Bonn - Koblenz area with a
resolution of 1/12° x 1/12°. The method is done in two steps, each one supplemented with its own quality
control . At first, the long term mean field is estimated from all data using external information such as
height from a digital terrain model or longitude and latitude as predictors. In a second step, anomalies of a
specific year from this long term mean are analysed including information from the spatial autocorrelation
structure. Within this step a cross-validation method is embedded to perform the quality control between a
selected station and the observations of the surrounding ones. The result of the analysis is (1) a time series of
gridded phenological phases of various commercial fruit trees for the period 1951 - 1998 based on a quality
controlled data set and (2) a list of observations flagged out as erroneous or unrepresentative.
A second part of the studies in the Cologne - Bonn - Koblenz area is the development of a model for the
phenological development of fruit trees until flowering. This work is based on phenological and
climatological observations on two experimental farms from 1943 resp. 1957 to 1999.
The phenological time series - if still available in full length - are of good quality with an exact
documentation of cultivar and locality. The quality control of climatological observations has been more
elaborate. Due to changes in equipment, observation sites, staff members and restricted working hours and
holidays and many other problems, time series of climatological observations have numerous faults. All data
have been put in a database. Most of the faults have been extracted from the data by integrating several test
routines into the database.
The validated observations are the base for phenological models. This models try to separate local and plantbased
effects on plant development. Consequently, the tree-based part will be equal on both observation sites
and the second part will describe the local deviations.
It is planned to merge the spatial, gridded phenological fields with the description of the local part of the
phenological model.
20

POLLEN SOURCES DETERMINING THE AEROBIOLOGICAL SITUATION IN
ESTONIA AND FLOWERING PHENOPHASES INFLUENCING THIS
SITUATION
M. Saar
Institute of Zoology and Botany, Estonian Agricultural University, Estonia
maret@zbi.ee
All anemophilous and a part of entomophilous plants release pollen grains into the air during flowering.
They may be carried farther away from the plants by air fluxes. Therefore pollen can occur at a site of
aerobiological monitoring at a time when flowering of local plants has not yet started, or when it has already
been over. Whether one or both of these phenomena take place depends on the location of the monitoring
site within the plant’s distribution area. When it is located on this boundary of the area where spread of the
flowering phase terminates, only pre-flowering long-range transport is possible. When the monitoring site is
located on the boundary where the flowering phase started, only post-flowering long-range transport can be
observed. When, however, the monitoring site is located within the plants area far from the regions where
the flowering phase starts or terminates, both pre-flowering and post-flowering long-range transport are
possible. Besides within-area long-range transport also extra-area long-range transport, i. e. transport of
pollen into areas where the plant does not grow, is possible.
A survey is given of how the course of the season for pollen groups occurring in Estonia is influenced by
long-range transport as well as by the flowering of local plants. Pollen composition in Tartu at 14 m from
the ground in 1990-1999 was as follows:
47.92% Betula
13.35% Alnus
10.31% Urticaceae
10.23% Pinus
5.07% Poaceae
3.87% Artemisia
1.07% Salix
1.02% Populus
0.99% Picea
0.75% Corylus
0.60% Querqus
0.45% Chenopodiaceae-Amaranthaceae
0.42% Cupressaceae
0.31% Rumex
0.29% Plantago
0.27% Ulmus
0.26% Cyperaceae
0.18% Fraxinus
0.17% Rosaceae
0.17% Cannabaceae
0.13% Apiaceae
0.10% Asteraceae
0.33% others
1.29% unidentified
21

DIFFERENCES IN SEASONAL DYNAMICS BETWEEN CANOPY AND LOWER
TRUNK SPIDERS ON PINE TREES
U. Simon
Landuseplanning and nature conservation, Faculty of Forestry Sciences, Technical University
München, Germany
Ulrich.Simon@lrz.tu-muenchen.de
The canopy is the place where life in forests meets the atmosphere. Other than in the closed forest climatic
factors like radiation, water loss by wind and heating etc. are less buffered. Structure of and processes within
animal communities of forest canopies are thus more immediately influenced by climatic factors. Hitherto,
there has been only a little knowledge of forest organismic diversity and functions in particular in the high
canopy of temperate forests.
The first aspect of the presented results is that in an important group of predators in forests, the spiders,
diversity (species composition) and function (seasonality, prey capture mode) is different between lower
trunks and the canopy.
The spider community structures of the canopy completely differ from those of the lower trunks in species
number (lower), species composition (less individual-poor species), and prey capture mode (more hunters in
the canopy, many web-builders on the lower trunks).
Patterns of the seasonality of the spiders on pine tree trunks and pine tree crowns were differed drastically.
On the lower trunks adult spiders reveal a bimodal phenology with a peak of activity in spring/early
summer, a subsequent decrease of activity during summer, and another increase in autumn. This is a normal
and often described pattern. In the canopy, however, an autumn activity of adult spiders is lacking. Juveniles
on the lower parts of the trunk are mainly active during summer months, whereas in the canopy juvenile
spiders are mainly active in autumn and early spring.
All this are not simple differences in patterns but fundamental differences in the function of a predator guild
in forests. The results show that
the knowledge of functions in forests needs the regard of all compartments of a forest
functions and dynamics may differ between different compartments
studies of the canopy may reveal insights to the consequences of climate change to communities and
dynamics in ecosystems.
22

SESSION 2A ANIMAL PHENOLOGY AND GLOBAL CHANGE
MUSEUM EGG COLLECTIONS AS STORES OF LONG-TERM
PHENOLOGICAL DATA
J.P.W. Scharlemann
Department of Zoology, University of Cambridge & Bird Group, The Natural History Museum, United
Kingdom
jpws2@cam.ac.uk
Museum collections hold large amounts of data on collecting dates and localities of eggs collected over the
past 150 years. Egg collections hold the longest available time series for a wide range of Bird species on a
large spatial scale.
Using data for a suite of British species I investigate if egg collection data can be used in phenological
research. I will highlight problems with the data and possible pitfalls: Can the actual laying date be derived
from the information provided by the collectors? Could there be a bias in egg collecting for certain types of
eggs? How does the data from egg collections compare with previous studies based on nest record cards.
Further, I will present some analyses of long-term changes in a few species of British birds.
23

THE EFFECTS OF TEMPERATURE, ALTITUDE AND LATITUDE ON THE
ARRIVAL DATES OF THE SWALLOW HIRUNDO RUSTICA IN THE SLOVAK
REPUBLIC
T. H. Sparks (1), O. Braslavska (2)
(1) Centre for Ecology and Hydrology, Monks Wood, UK
(2) (2) Slovak Hydrometeorological Institute, Banska Bystrica, Slovak Republic.
ths@ceh.ac.uk/Fax +44 1487 773467
The (barn) swallow Hirundo rustica is a traditional harbinger of spring in many Northern Hemisphere
countries. Because of its widespread distribution and obvious appearance it has the potential to be an
excellent phenological indicator for international research.
This paper uses information on the arrival and departure dates of the swallow throughout the Slovak republic
for the 30 years 1961-1985 and 1996-2000. Records were taken at 19 locations throughout the republic
representing an altitude range from 105m to 760m. Monthly temperature data were constructed from 6
meteorological stations. Using regression techniques, effects of latitude, altitude and temperature are all
apparent. The following graph shows the response of average arrival time on April temperature; the
relationship is significant at p

THE CHANGE OF MIGRATION TIME OF THE ORDINARY BIRDS OF
LAPLAND ZAPOVEDNIK (KOLA PENINSULA, RUSSIA) OVER THE PERIOD
OF 1931-1999
A. Gilyazov
Lapland State Natural Biosphere Zapovednik,Russia
lapland@monch.mels.ru\Tel\Fax (815 -36) 5-71-99
Phenological observations has started during the autumn of 1930 and are conducted up to now. The maximal
period of observations is 65 years; the minimal one is 51 years. 27 phenomena concerning not only birds but
also the data of thaw of ice at the surface of Chuna lake and freezing of it. These parameters were taken as
indicators as they are the mostly easy registrated, reliable and demonstrative. These indicators are complex
for the weather of half year as the date of their occurrence depends not only from the temperature but also
from the amount of precipitation, force and intensity of winds during the previous half year as well. The rest
28 phenomena show the tendency of change. 15 spring phenomena from 19 investigated ones came in 2-13
days before in 1931-1941; 4 spring phenomena came in 1-6 days later. 4 early autumn phenomena came in
3-11 days later; the latest four autumn phenomena occur in 1-31 days earlier (Table 2). Breaking of ice of
lake Chuna is in 1 day later and freezing is in 8 days earlier than before that means that ice covers the lake in
9 days longer (199 and 208 days). Changes that were mentioned more often coincide with the change of the
time of phenomena in the period 1931-1982 . It means that spring migrants arrive earlier from year to year
and in autumn those migrants that usually leave earlier change the time of their leaving for the later one and
those who leave later change the time of their leaving for the earlier one. These changes can be explained by
the possibility to find food: warm long autumn keeps earlier migrants and earlier freezing date of the lakes
and establishing of snow cover force the late migrants flow away. The period of stay has increased during 70
years for the most part of the species that have data about both parameters: arrival and flowing away (7
ordinary species): for B. clangula it is 5 days, for S. paradisaea, T. iliacus, M. alba it is 8-9 days, for F.
montifrigilla it is 16 days. For late migrants this period has decreased: for C. cygnusit it is 12 days, for P.
enucleator it is 31 days. Taking into account only the parameter of flying away period of stay has also
increased by 5.1 day in average for 15 species from 20 investigated. As a whole during 70 years of
observations we can see the tendency of cooling the climate that was mentioned earlier . Birds’ species
reaction for change of climate conditions is different. Most of the species has increased the period of their
stay in Lapland and two species that are late migrants has decreased the time of their stay in Lapland during
the period under investigation.
25

ARRIVAL DATES OF BIRDS IN SW FINLAND 1748-1998 – DATA AND THE
MESSAGE
E. Lehikoinen
Section of Ecology, Department of Biology, University of Turku, Finland
esalehi@utu.fi
Phenological observations have been done nearly without interruption in Turku from 1748. The initiation of
this work came originally from Carl Linné and Anders Celsius in “mother”-Sweden. In Turku, Linné’s
student and friend Johan Leche started the research accompanied with detailed weather observations. His
major publication summarises the practical information of arrival dates as follows: “The White Wagtail is
always observed at the break of the ice. If it is seen earlier, the ice will break immediately. Of all the
Swallows, the Barn Swallow is the first to arrive. On average it arrives on 6 May. The House Martin arrives
on 10 May. On arrival of these species the water in coastal bays is 9 or 10 degrees (°C). He, who hasn’t
started to take care of his herb garden, shall not postpone it any further. The Swift is the last to arrive,
sometimes arriving before, sometimes after the 20 May. The real summer starts at the Swift’s arrival. You
can sow the seeds of portulaca and plant cucumbers and Turkish beans at this time even if the soil is cold
without a fear of frost. [Letters to the Royal Swedish Academy (Stockholm) 1763].
Nearly a hundred years later G.G. Hällström (1844, unpublished lecture, reviewed by Johansson in 1911)
made a detailed analysis of the phenological data collected during the ninety years elapsed since Leche. He
concluded e.g. that 1) arrival dates of migratory birds vary more than phenological events in plants, 2) larger
species migrate faster than smaller species, 3) species that arrive later migrate faster, 4) variability of arrival
dates is larger in early migrants, and 5) in autumn, cranes and geese of southern populations depart earlier
than those of northern populations. He also made a geographical comparison of migration speeds (km/d),
which are summarised below:
Latitude (N)
Species 50 60 70
Spring skylark 18 21 25
Spring swallow 36 45 56
Spring cuckoo 50 56 75
Autumn swallow 90 102 125
We have to credit Hällström’s inspiring lecture for the initiation of the large real phenology network. Shortly
after his death The Finnish Society of Science and Letters started it. The society distributed a detailed 70page
booklet where c. 4000 (!)phenological events, whereof 1400 biological and including migration dates
of 35 bird species, could be filled in. This inquiry to amateur nature observers is still going on, although
much reduced. Local and national ornithological societies have taken over the main responsibility of
collecting the migration data on birds.
I will present the Finnish history of phenological studies as far as arrival dates are concerned. I will also
show preliminary results of correlative studies, which aim at revealing the relationships between weather
variations and bird behaviour. In addition to arrival dates, a brief look at the effects of weather changes on
timing of the complete summer schedule of a migratory passerine, the Willow Warbler (Phylloscopus
trochilus) is made.
26

PHENOLOGY OF BRITISH BUTTERFLIES AND CLIMATE CHANGE
D. Roy (1), T. Sparks (1)
Centre for Ecology and Hydrology, Monks Wood, UK
dbr@ceh.ac.uk, Fax - +44 (0) 1487 773467
Butterflies are good organisms for studying the effects of environmental change. Their activity is closely
controlled by weather and many species are constrained by climate. Butterflies are also an ideal group for
phenological recording, as they are conspicuous and have a high public profile.
In the British Butterfly Monitoring Scheme (BMS), a national monitoring network, there is a large amount
of data on the flight periods of butterflies. Data from the BMS were analysed to test for relationships
between temperature and three phenological measures - duration of flight period and timing of both first and
peak appearance. The BMS was established in 1976 to monitor the abundance of butterflies in the British
Isles and there are currently over 120 sites in the scheme. Phenology parameters were calculated for almost
31,000 individual flight periods for 35 species.
First appearance of most British butterflies has advanced in the last two decades and is strongly related to
earlier peak appearance and, for multibrooded species, longer flight period. Mean dates of first and peak
appearance are examined in relation to a temperature series for central England, using regression techniques.
For almost all species, there is a highly significant relationship with temperature of both first appearance and
peak flight date: warmer weather tended to produce earlier first and peak appearance. The most striking
result is for earlier first and peak appearance with warm spring temperature, eg. the following graph for
Anthocharis cardamines (Orange tip) suggests a response of 5 days per ºC.
Recording week
10
9
8
7
6
5
3
4
5
Mean February-April Temperature
We predict that, in the absence of confounding factors, such as interactions with other organisms and landuse
change, climate warming of the order of 1ºC could advance first and peak appearance of most butterflies
by 2-10 days.
6
Peak appearance
First appearance
7
8
27

SESSION 1 PHENOLOGICAL MONITORING AND NETWORKS
CANADA PLANTWATCH: TRENDS TO EARLIER SPRING DEVELOPMENT
E.G. Beaubien
Devonian Botanic Garden, University of Alberta, Canada
e.beaubien@ualberta.ca/Fax 780.987.4141/Phone 780.987.5455
Extensive phenology surveys began in Canada in the 1890's with an ambitious program launched by the
Royal Society of Canada. The largest group of observers were students in Nova Scotia, who reported on up
to 100 events up until the 1920's. Alberta has considerable current data with volunteer observers reporting
on native species since 1973. Since 1987, the Alberta Wildflower Survey has involved about 200 volunteers
reporting 3 flowering stages for 15 native plants. Other provincial programs have started in the last 4 years
(Nova Scotia and Newfoundland).
Plantwatch (www.devonian.ualberta.ca/pwatch) began in 1995 and now receives North American bloom
dates for 7 native plant species plus international data for common purple lilac (Syringa vulgaris). Data
tables and maps of bloom times are updated regularly on the Internet. Environment Canada's Ecological
Monitoring and Assessment Network now considers plant phenology as a core variable for monitoring
environmental change. The Plantwatch program will thus expand in 2001, adding more plant species
suitable across wide areas of Canada, moving the website to Environment Canada, involving representatives
from all the provinces and territories, as well as gathering promotional help from the Canadian Nature
Federation. All the provinces and territories of Canada are being encouraged to start their own plant
phenology surveys, using the selected Plantwatch species and adding others suitable to their ecoregions.
Western Canada has shown significant warming over the last decades, as opposed to parts of eastern Canada.
Flowering data reflects this change, with spring bloom times now occurring earlier. Timing of first bloom
(10% pollen shed) of Populus tremuloides in Edmonton, Alberta now occurs almost a month earlier than it
did a century ago. Major climatic events such as El Nino events which cause ocean warming, result in earlier
bloom times in western Canada.
28

EUROPEAN PHENOLOGY NETWORK – A NETWORK FOR INCREASING
EFFICIENCY, ADDED VALUE AND USE OF PHENOLOGICAL MONITORING
RESEARCH, AND DATA IN EUROPE
A. J.H. van Vliet, R. S. de Groot
Environmental Systems Analysis Group, Wageningen University, The Netherlands
arnold.vanvliet@algemeen.cmkw.wau.nl / Tel: +31 317 485091
In February 2000 a proposal for a thematic network called European Phenology Monitoring (EPN) was
successfully submitted to subsection ‘Better exploitation of existing data and adaptation of existing
observing systems’ of the Energy, Environment and Sustainable Development Theme of the Fifth
Framework Programme.
EPN aims to improve monitoring, assessment and prediction of climate induced phenological changes and
their effects in Europe. Its overall objective is to increase the efficiency, added value and use of phenological
monitoring, phenological research and the practical application of phenological data in European member
states in the context of global (climate) change. More specific objectives of the Phenological Thematic
Network are:
1. To facilitate integration and co-operation between existing phenological monitoring networks and to
actively stimulate expansion of existing and creation of new monitoring networks.
2. To improve the integration of, and access to phenological data in Europe in a systematic, structural and
user-friendly way.
3. To exchange knowledge between phenologists of different scientific disciplines (ecology, agriculture,
human health) on tools and techniques used for phenological monitoring, database development,
(statistical) data analysis, model development, and impact assessment.
4. To demonstrate the wide variety of possible applications of phenological research and its benefits for
ecology, agriculture and society (human health and education) and realising a stronger involvement of
the end-users.
The vision of the EPN-project is that of a cost-efficient, productive, and long lasting network that is easy
accessible for everybody who is interested.
To realise the objectives and thus implement the Phenological Thematic Network the EPN-project will:
A. Co-ordinate the integration, co-operation, and further expansion of phenological networks in Europe
(sub-tasks include (among others): network management, clarification of definitions used, establishment
of links with educational programs, non-European networks, international organisations, and potential
funding organisations).
B. Establish an on-line phenological metadatabase and a phenological bibliographical database (to improve
acquisition, storage and accessibility).
C. Organise two European conferences on phenology involving data providers, scientists, (international)
organisations, commercial enterprises, policy makers and educational organisations.
D. Organise six specialists workshops on essential topics (modelling, use of earth observation data,
phenology and human health, phenology and agriculture, bird migration and communication,
dissemination and capacity building).
EPN will result in increased efficiency, added value and practical use of phenological research, monitoring,
and data-synthesis in Europe and will greatly enhance structural communication and co-operation between
science and end-users of phenological data.
29

SESSION 2B PLANT PHENOLOGY AND GLOBAL CHANGE
PHYTOPHENOLOGICAL TRENDS IN SWITZERLAND
C. Defila
claudio.defila@meteoschweiz.ch
Since 1951 there has been an observation network in Switzerland. Today, at about 160 observation stations
in different regions and at different levels of altitude, 69 phenological phases for 26 different plants are
observed and their occurrences registered. Since 1986, 17 phytophenological phases have been reported
from 40 stations. On the basis of these reports a weekly phenological bulletin is published during the
vegetation period and distributed via internet (www.meteoschweiz.ch).
Connected with a possible climate change linear trend analyses have been carried out for 895 phenological
time series at 68 stations and for 19 different phenological phases - this along with very old phenological
time series in Switzerland (emerging of the horse-chestnut in Geneva - 1808 until 2000 - and the full bloom
of the cherry in Liestal - 1894 until 2000). The significance has been tested by an F-test (P>0.05). A
significant linear trend could be found for 29,9 % of all the tested phenological phases. 11,1 % indicate a
positive trend (to later occurrences) and 18,9% a negative trend (to earlier occurrences). The average of the
premature spring phases amounts to –8,9 days and the average delay of all autumn phases amounts to +1,2
days. Within the 47 tested years a prolongation of the vegetation period of 10,1 days has been observed. At
the phenological spring and summer phases the negative trends predominate strongly, whereas for the
autumn phases the positive ones predominate slightly. By classifying Switzerland into 7 different climatic
regions, it is obvious to see that the ratio between the negative and the positive trends are different -
depending on the region. Thus in the region of Rheinbünden the negative trends predominate strongly
whereas in the Valais the positive ones are predominating. As far as the different levels of altitude are
concerned, there are important differences. It is quite interesting that at altitudes of 900 m to 1100 m and
over 1300 m above sea level the negative trends predominate. It is conceivable that the alpine plants, which
live in a climatic frontier region, react stronger to the climate change than the plants in the lowland, where
the temperature is not a limiting factor to the growing and developing of the plants.
The time series of the horse-chestnut in Geneva (1808 – 2000) show from 1900 on a clear trend to earlier
occurrences. This is due to the climate of the city of Geneva. For the full bloom of the cherry in Liestal,
1894 – 2000 (a rural district) such a strong trend could not be noticed.
Depending on the season, region, altitude and species of plants the phenological occurrences in Switzerland
show different trends. Also in Switzerland a tendency towards a prolonged vegetation period has been
observed.
30

LONG-TERM DEVELOPMENT OF CLIMATE AND PHENOLOGY OF BEECHES
IN SOUTH-WESTERN GERMANY
A. Kirchgäßner , H. Mayer
Meteorological Institute, University of Freiburg, Germany
kirchgam@uni-freiburg.de/ / Fax: +49-761-203 6922
Prior to man's disruption, beech forests constituted about 75 percent of Europe's woodland. Today, this
proportion has declined significantly. In Germany, there are now plans to partially reverse that trend. In spite
of the importance of beech ecosystems to the landscape of Central Europe, there is little information on the
development of beech trees and the underlying ecological and ecophysiological processes.
Beech forests are generally characterised by high adaptability to different climatic conditions. However,
knowledge of the various climatic factors that allow or foster the development of beech forests, their
interactions and their activities is still insufficient. This information is however of great interest in view of
predicted climate change in Central Europe, where beeches are mostly circulated.
Within the sub-project A1 of the collaborative research centre 433 (The influence of climate and
management on beech dominated deciduous forests) co-ordinated by the Faculty of Forestry, University of
Freiburg, the long-term influence of climate and weather on beech forests in a locally restricted area (app. 50
km * 50 km) in south-western Germany is being examined. The investigation is based on retrospective
analysis of long-term climate data and phenological data (bud burst, flowering, colouring of the leafs, full
ripe fruit, leaf fall). This data sets, covering the last 50 years, were obtained from German Weather Service
Stations in the vicinity of the main sample area. The sites are situated at an altitude ranging from 500 m
above sea level to 900 m above sea level.
In the first place beeches' response to climate conditions and the occurrence of stress situations like late frost
or dryness during their growing season on the respective locations has now been analysed. Present results
are as follows:
** the timing of bud burst and leaf fall didn't change significantly, although locally different trends
without statistical significance were observed
** the growing season with respect to beech is neither prolonged, shortened nor altered within the year
with statistical significance
** in most of the years with an extended growing season, the time span between bud burst and
flowering is shortened
** the sum of daily mean air temperature during the four weeks preceding the day of bud burst is
essentially the same for all stations and adds up to approximately 340°C
** the sum of daily mean air temperature below 0°C from 1 st of January till the day of the bud burst
increases with the elevation above sea level of the station. A comparable trend could not be
observed with the sum of the daily mean air temperature and the sum of daily means of air
temperature above 0°C.
31

TRENDS IN PHENOLOGICAL STUDIES IN ARGENTINA
A. Faggi (1), O. Scarpati (2) and L. Spescha (3)
(1) Flores University, Camacúa 282, 1406 Buenos Aires, Argentina
(2) CEFYBO-CONICET, Serrano 669, 1414 Buenos Aires, Argentina
(3) Agronomy Faculty UBA
Phenological studies in Argentina began at the end of the 19. Century. The first studies were carried out in
the main cities of the country in order to find correlation between perennial ornamental species and local
climate.
In the middle of the 20. Century a systematic network has been built up at the Agriculture Department of the
National Meteorological Service. The aim of this effort was to obtain the bioclimatic requirements of annual
species such as the main crops and perennials like fruit trees.
When this department was closed study groups with different scopes continued the phenological studies.
Each one focused different features like ecology, physiology and plant breeding.
Nowadays phenology is used in the election of cultivars and there is a revival of phenology regarding urban
ecology, in order to find biological indicators for climate studies and urban planning.
32

OLIVE PHENOLOGY: INDICATOR OF GLOBAL WARMING IN THE
MEDITERRANEAN
C. Osborne (2), I. Chuine (1), D. Viner (3) & F.I. Woodward (2)
(1) Institut des Sciences de l’Evolution de Montpellier, Université Montpellier II, France
(2) Department of Animal and Plant Sciences, University of Sheffield, UK
(3) Climatic Research Unit, University of East Anglia, Norwich, UK
chuine@isem.univ-montp2.fr/Fax: +33-4 67 04 20 32
Olive flowering phenology has been shown to be strongly influenced by Spring temperatures in
experimental and modelling work, as illustrated by Fig. 1. Since airborne pollen concentrations reflect the
flowering phenology of olive populations within a radius of 50 km, they may be a sensitive regional
indicator of climatic warming. We assessed this potential sensitivity with phenology models fitted to
flowering dates inferred from maximum airborne pollen data. Of four models tested, a thermal time model
gave the best fit for Montpellier, France, and was the most effective at the regional scale, providing
reasonable predictions for 10 sites in the western Mediterranean. This model was forced with replicated
future temperature simulations for the western Mediterranean from a coupled ocean-atmosphere general
circulation model (GCM). The GCM temperatures rose by 4.5°C between 1990 and 2099 with a 1% per year
increase in greenhouse gases, and modelled flowering date advanced at a rate of 6.2 d per °C. The results
indicated that this long-term regional trend in phenology might be statistically significant as early as 2030,
but with marked spatial variation in magnitude, with the calculated flowering date between the 1990s and
2030s advancing by 3–23 d (Fig.2). Future monitoring of airborne olive pollen may therefore provide an
early biological indicator of climatic warming in the Mediterranean.
Figure 2. Predicted change in olive flowering date
under Global Warming in the Mediterranean.
Flowering Date (DOY)
Mean Temperature (°C)
.
170
160
150
140
13
12
11
10
1975 1980 1985 1990
Year
Figure 1. Variations of temperature and olive
flowering dates in Montpellier, France from
1973.
33

REGIONAL TRENDS OF THE BEGINNING OF GROWING SEASON IN
EUROPE AND POSSIBLE CLIMATIC CAUSES
F.-M. Chmielewski, Th. Rötzer
Humboldt-University Berlin, Section of Agricultural Meteorology, Berlin, Germany
chmielew@agrar.hu-berlin.de / Fax: +49-30-31471211
In order to study relationships between climate changes and plant development phenological data from the
International Phenological Gardens (IPG), gridded surface temperatures (NCEP/NCAR reanalysis data 1 ) and
the North Atlantic Oscillation (NAO) Index 2 for the period 1969-1998 were used. For the investigation of
regional phenological trends in Europe twelve natural regions across Europe were defined 3 .
The aim of this investigation was to show whether the observed regional or Europe-wide trends in the
beginning of growing season 4 correspond with climatic trends on the same scale. In most European regions
the mean growing season a starts in April. In Scandinavia it is delayed up to one month and in Portugal it
already starts in March. In Europe the beginning of growing season has advanced 2.7 days per decade, for
the 1969-98 period altogether by 8 days. Most of the European regions show significant negative trends
which range between three and six days per decade. The strongest trends were observed in the natural
regions ‘British Isles/Channel Coast’, ‘North Sea and European Lowlands’, ‘Northern and Southern
European Highlands’ as well as in the ‘North Alpine Foreland’. Only weak trends were found in ‘North
Scandinavia’ and in southeast Europe. In the latter region even a positive trend has been noticed.
80
8 BGS = 149.4 - 6.68 T24
80
1965 1970 1975 1980 1985 1990 1995 2000 4 5 6 7 8
The advanced Year
Air temperature
beginning of
growing season corresponds well with positive trends in surface air temperature in Central Europe.
Significant correlation were calculated between average air temperature from February to April and the
beginning of growing season in nearly all natural regions. Depending on the region the temperature either in
February, March or April shows the highest correlation coefficient. The North Atlantic Oscillation
influences the annual climate on the North Atlantic ocean and in Central-Europe to a great extend. Positive
phases of the NAO from January to April tend to be associated with above-normal temperatures mainly in
northern Europe as well as below-normal temperatures in southeast Europe. The NAO-Index from January
to April shows a remarkably positive trend with predominant positive phases mainly since 1989. This can
explain the observed positive trends in air temperatures and as a result the premature beginning of growing
season in most natural regions.
34
BGS in Europe
130
130
120
110
100
90
BGS Air temperature BGS
°C)
0
2
4
120
110
)
)
)
)
) )
) )
)
)
)
) )
) )
) ) )
)
) )
)
)
r=-0.83
Fig.1:
Relationships
between air
temperature
from February
to April (T24 in
and the
T24
6
100
90
)
)
beginning of
growing season
in Europe (BGS
in days).
1 Kalnay et al. 1996: The NCEP/NCAR 40-Year Reanalysis Project. BAM, 437-471.
2 Hurrel, J.W., 1995: Decadal trends in the North Atlantic Oscillation and relationships to regional
temperature and precipitation. Science 269, 676-679.
3 Rötzer, Th.; Chmielewski, F.-M.: Trends of growing season in Europe. In: Arboreta Phaenologica -
Information of the IPG working group, 43, 2000, 3-13.
4 Menzel, A., Fabian, P. 1999: Growing season extended in Europe. Nature 397, 659.
a average date of leaf unfolding of Betula pubescens, Prunus avium, Sorbus aucuparia and Ribes alpinum

SESSION 3 PHENOLOGY AND REMOTE SENSING
NORTHERN PHOTOSYNTHETIC AND GROWING SEASON TRENDS FROM
1981 TO 1999
C. J. Tucker(1), D. Slayback(1), J. Pinzon(1), S. Los(1), R. Myneni(2), M. Paris(1)
(1)Laboratory for Terrestrial Physics, NASA/Goddard Space Flight Center, USA
(2)Department of Geography, Boston Univeristy, USA
Satellite data from 1981 to 1999 show increases in land photosynthesis and a lengthening of the growing
season at northern latitudes. Two distinct periods of increasing plant growth were apparent: 1981 to 1991
and 1992 to 1999, punctuated by a reduction in gross photosynthesis from 1991 to 1992 associated with
global cooling from the volcanic eruption of Mt. Pinatubo in June 1991. May-September gross
photosynthesis increased ~8-14% from 1992 to 1999 from 55 - 75o N. An earlier start of the growing
season of 6 ± 1 days from 55 - 75o N was also found. Our results show the response of northern vegetation
to spring and summer temperatures from 1981-1999 where temperature limits plant growth.
35

ASSESSING SATELLITE-DERIVED PHENOLOGY IN NORTH AMERICA
M. D. Schwartz
Department of Geography, University of Wisconsin-Milwaukee, USA
mds@uwm.edu/Fax: 414-229-3981
The renewal of vegetative growth during the onset of mid-latitude spring is a critical aspect of atmospherebiosphere
interaction, with implications for global climate change. Spring’s onset can be observed through a
variety of data including: native species phenology, indicator phenology, satellite-derived metrics, and
observed variations in meteorological data. While each of these components describes portions of the
“green wave,” none is sufficient alone to provide a comprehensive assessment of the phenomena. Thus, an
integrated approach, which allows for constructive interaction between the components, has the best
prospects for accurately tracking the onset of spring at a global scale.
Satellite-derived metrics provide global coverage capabilities, but are generally of limited temporal
resolution due to cloud-cover interference and other problems. In this paper, a new generation of start-ofseason
(SOS, developed by Bradley Reed and associates at the EROS Data Center) satellite-derived metrics
are evaluated at 627 surface weather station sites distributed across the continental USA. At each site a
10x10 window (100 one km-sized pixels) centered on the station is extracted, with modal SOS dates
developed for each land cover type present (BATS 28 class scheme). They are then compared to surface
phenological model output (spring indices) at all locations, and native species phenological data at a few
selected sites.
The results show that the SOS metric dates are earlier on average (40 days) than surface phenological model
output, but also more early in cooler northern regions (60 days) than in warmer southern areas (20 days).
Despite these differences, the new SOS metrics appear to be capturing part of the year-to-year departure
signal over all sites (Fig. 1), and even more when compared with native species and spring index model
output at a specific site (Fig. 2). Further comparative study, and the collection of native species
phenological data in an expanding world-wide network, will continue to improve global assessment of the
spring green wave phenomena.
36

AN ANALYSIS OF TEMPORAL RELATIONSHIPS BETWEEN PLANT
COMMUNITY PHENOLOGY AND SEASONAL NDVI METRICS IN NORTHERN
CHINA
X. Chen
Department of Urban and Environmental Sciences, Peking University, Beijing, China
cxq@urban.pku.edu.cn /Fax: +86-10-62751187
The objectives of this study are to reveal relationships between phenological development of local plant
communities and seasonal metrics of satellite sensor-derived greenness at the representative stations and the
pixels overlying them, and to explore the reliability for determining the growing season of land vegetation at
a regional scale, using threshold values of greenness obtained by a surface-satellite analysis. The cumulative
frequency of phenophases has been calculated for each plant community and each year in order to determine
the growing season at the three sample stations during 1982 and 1993. The precise thresholds were
arbitrarily set as the dates on which the phenological cumulative frequency reaches 5% and 10% (for the
beginning date) and 90% and 95% (for the end date). The beginning and end dates of the growing season
were then applied each year as time thresholds to determine the corresponding 10-day peak greenness values
on the NDVI curves for 8km 2 pixels overlying the phenological stations. The main relationships between the
beginning and end dates of the growing season and the corresponding greenness values, and their potential
applications in determining growing season are summarized as follows:
(1) There is a high positive correlation between the beginning dates (cumulative frequency of 5% and 10%)
and between the end dates (cumulative frequency of 90% and 95%) of the growing seasons, which indicates
that the beginning dates and end dates of the growing seasons have a consistent advance and delay trend,
respectively. In addition, there is a high negative correlation between the beginning and end dates of the
growing seasons, i.e. the earlier the beginning date occurs, the later the end date will appear. According to a
trend analysis, a lengthening of the growing seasons has been detected in the north and middle parts of the
research region during 1982 and 1993.
(2) The correlation between the beginning date of the growing season and the corresponding threshold value
of greenness is very low, which means that the satellite sensor-derived greenness is independent of the
beginning date of the growing season. If the fluctuation of greenness value is insignificant, we can assume
that whenever the growing season begins in a year and at a given site of the research region, the
corresponding greenness value would retain relative stable. In other words, we could use the average
threshold value of greenness to roughly determine the onset of the growing season for each year. In order to
estimate the onset of the growing season at sites without surface phenological data, the sample site and the
extrapolation site should have similar vegetation and similar temporal NDVI profile. So, we could use the
average threshold value of greenness obtained at the sample site to estimate the yearly onset of the growing
season on the NDVI curve of the extrapolation site. However, if the fluctuation of greenness value is
significant, the above extrapolation procedure could not be carried out.
(3) Other than in spring, the correlation between the end date of the growing season and the corresponding
threshold value of greenness is very high. The negative correlation shows that the earlier the growing season
terminates, the larger the corresponding threshold value of greenness would be. This result is probably due
to the radiative properties of other vegetation and environmental factors in the research region during the end
of the growing season. On the basis of this relation, regression equations could be established between the
end date of growing season and the corresponding greenness value for the sample sites, so that the end date
of the growing season could be estimated at other sites with similar vegetation, using the NDVI data. Under
this circumstance, we assume that the statistical relationships described by the regression equations are not
only suitable for the sample sites but also for other sites within the research region.
37

EUROPEAN GREEN WAVE OBSERVED IN NOAA/AVHRR NDVI DATA AND
IN THE INTERNATIONAL PHENOLOGICAL GARDENS
M.M. Hirschberg 1 , A. Menzel 1 and C.J. Tucker 2
(1) Chair of Bioclimatology and Pollution Research, Technical University of Munich, Germany
(2) Goddard Space Flight Center, NASA, USA
hirschberg@met.forst.tu-muenchen.de // Fax: (+49) 8161 – 714753
Europe has a very unique phenological net of ground stations (the International Phenological Gardens,
IPG, founded in 1957), where genetically identical clones of trees and shrubs can act as an indicator of
various climatic influences. The network covers a large European area from 69°N to 42°N, and from 10°W
to 27°E in all important climatic zones. Up to now more than 30 years of observations of phenological
phases, such as the day of leaf unfolding, May shoot, flowering, leaf coloring and leaf fall can show the
year-to-year variability of the seasonal active period in Europe. However, they are obtained only at single
sites.
On the other hand satellite data observed from a space platform like the Normalized Difference Vegetation
Index (NDVI) can also indicate the length of the growing season in Europe on a spatial scale. Specially in
Central Europe, where land cover is highly variable and large connected areas with the same vegetation type
are rare, it is important to combine ground and space observations. Detecting the real start, maximum and
the end of the growing period in the NDVI data is one aim of the investigation.
This study will show a comparison of trends of the European green wave observed in ground and satellite
data at different IPG sites. The calculated trends of the five observed phases of the IPG stations will be
compared with trends of a new available NOAA/AVHRR maximum NDVI land data set, produced by the
NASA/GSFC, with a resolution of 8×8 km and a temporal frequency of 15 days from 1981 to 1998. From
ground observations in southern Germany a mean entry day for the beginning of the different phenological
phases will be calculated and the corresponding NDVI value determined. We will discuss the beginning of
spring and autumn and the length of season in both data sets in Northern, Central and Southern Europe.
38

THE IMPACT OF VEGETATION SEASONALITY ON GLOBAL CARBON
BUDGETS: A COMPARISON OF LPJ MODEL RESULTS WITH SATELLITE
OBSERVATIONS
W. Lucht, A. Bondeau, S. Sitch and W. Cramer
Potsdam Institute for Climate Impact Research, Potsdam, Germany
Wolfgang.Lucht@pik-potsdam.de
Phenological dates provide markers for the timing of key stages in the seasonal development of plants. They
thus provide important constraints for models aiming to correctly simulate the temporal development of
vegetation throughout the year. One class of such models are biogeochemical models used to study the
important contribution of the terrestrial biosphere to the global carbon cycle, and hence to the atmospheric
concentrations of the greenhouse gas CO2.
The amount of carbon stored in vegetation, the amount transferred from vegetation to soil pools, and the
annual fluxes of carbon between the biosphere and the atmosphere depend on many variables. Most focus
has been on the influences of precipitation, temperature and atmospheric CO2 concentration, all of which are
subject to change under climate change. The importance of changes in available radiation, for example as a
consequence of changing cloudiness, has been studied much less. In this work, the emphasis is on the
important influence of the length and timing of the seasonal cycle upon the yearly accumulated radiation
available to plants for their photosynthesis, i.e. the influence of growing season length, timing of spring
greenup, and the detailed evolution of the canopy through the year.
Net primary productivity (NPP) is highly correlated with APAR, the absorbed photosynthetically active
radiation. APAR is a function of PAR, depending of cloudiness, latitude and time of year, and of fPAR, the
fraction absorbed by plants and used for photosynthesis. fPAR is a function of canopy structure and leaf area
index (LAI). The seasonal development of LAI determines at what times of the year PAR is effective for
photosynthesis. PAR is lower in winter because of shorter days and lower sun angle, and higher in summer.
The convolution of the temporal evolution of PAR and of the temporal evolution of fPAR, i.e., LAI, is
therefore of primary importance to the value of NPP achieved over a year.
The present research investigates the influence of seasonality upon the carbon stores and fluxes in the Lund-
Potsdam-Jena Dynamic Global Vegetation Model (LPJ-DGVM). LPJ is a state-of-the-art process model of
vegetation seasonal and annual dynamics, growth, mortality and establishment, soil dynamics and
disturbance that predicts the annual non-equilibrium productivity of the biosphere as a function of
meteorological variables and soil type by simulating biospheric carbon uptake and release. In the course of
the computation, the spatial and temporal patterns of vegetation activity of a few basic plant functional types
are calculated. Currently, seasonality is represented in the model in a very simple form. All plants are
assumed to begin greenup when a 5 degree growing degree day requirement is met, and the greenup
evolution is determined by a fixed number of growing degree days (200) ramping up to full foliage. Fall or
water stress senescense consists of an abrupt dropping of leaves. The sensitivity of the model to the
parameters governing these phenological phases, and hence the sensitivity to vegetation seasonality, is
examined to demonstrate the importance of timing in the global carbon cycle.
Long global time series of AVHRR satellite data are used to compare the seasonality achieved by the model
with that observed from space. Geographic areas where the model fails to reproduce the observed
phenological timing are identified. Improvements of the model can be achieved mainly for the Siberian larch
forests and South American raingreen forests. The interannual variability of phenological timing serves to
assess the importance of seasonality on the interannual variations of carbon fluxes between the biosphere
and the atmosphere. The results emphasize the importance of understanding the physiological basis, and of
observing the actual timing of vegetation seasonality on the ground and with satellites.
39

TRENDS IN NOAA/AVHRR NDVI AND PHENOLOGICAL RECORDS IN
GERMANY FROM 1981-1998
A. Menzel 1 and C.J. Tucker 2
(1) Chair of Bioclimatology and Pollution Research, Technical University of Munich, Germany
(2) Goddard Space Flight Center, NASA, USA
menzel@met.forst.tu-muenchen.de // Fax: (+49) 8161 – 714753
Plant and animal phenological observations as well as satellite data, analyses of yearly temperature
variations and proxy data such as river and lake ice cover suggest changes in the timing of events in the
seasonal cycle. This study compares results of trend analyses of phenological ground observations made
within the phenological network of the German Weather Service (DWD) to changes in the timing of start
and end of the growing season derived from NDVI data for Germany.
The NDVI (normalised difference vegetation index) data set used is the GIMMS standard 8-km continental
product, derived from AVHRR sensors on board of NOAA satellites, which extends from 1982-1998.
Methods of spatial averaging these bi-monthly NDVI maximum value composites for Germany and deriving
parameters for start and end of the growing season are discussed and first results are presented.
Spatial phenological averages for Germany are calculated by means of yearly anomalies for 16 phenological
phases and for the length of the growing season (time span from leaf unfolding to leaf colouring) of 4
deciduous tree species for the period 1951-1998. For these phenological key phases the trends of spatially
averaged yearly anomalies are compared to mean linear trends of single station records. The analysis of
spatial variability of these trends, as shown in maps and analysed by multiple linear regressions, do not
reveal any substantial regional differences.
40

INTERANNUAL VARIATIONS OF BUDBURST OF DECIDUOUS FORESTS IN
CENTRAL AND WESTERN EUROPE DERIVED FROM A 10 YEARS DAILY
NOAA/AVHRR 1KM ARCHIVE, GROUND-BASED PHENOLOGICAL
OBSERVATIONS AND ECOSYSTEM MODEL SIMULATIONS
A. Bondeau(1), K. Böttcher(1), W. Lucht(1), E. Dufrêne(2), J. Schaber(1)
(1) Potsdam Institute of Climate Impact Research, Potsdam, Germany
(2) Laboratoire d’Ecologie Végétale, Paris-Orsay, France
alberte@pik-potsdam.de/FAX: +49-331-288-2695
The detection of budburst of temperate deciduous forests from satellite observations provides new
opportunities for the study of regional variations in climatic variability, while simultaneously yielding a
powerful test of the ecosystem process models that are now used to predict the impacts of climatic changes.
Across a broad range of climatic conditions in central and western Europe, six deciduous forests were
selected that were i) homogeneous and large enough to be monitored using a 1km NOAA-AVHRR time
series (1989-1998), and ii) close enough to phenological gardens where ground observations are available
for this time period. We used a simple algorithm to retrieve a budburst date from the daily satellite data. For
the different forests, the satellite retrieved budburst dates compared well with the observed budburst dates on
the ground. These results add confidence to the potential use of satellite data of high spatial and temporal
resolution in the continental-scale monitoring of the phenology of temperate deciduous forests, especially
where no phenological observations are recorded.
The algorithm is applied to the analysis of budburst dates of temperate deciduous forests over a south-west /
north-east climatic gradient from Spain to Poland. A general trend does not appear over this area for the ten
years period studied. Interannual variations are largely dependent upon temperature. The satellite-derived
budburst date is used to check the ability of the vegetation model LPJ (Lund-Potsdam-Jena) to simulate a
reasonable phenological behavior over temperate deciduous forests. The interest of improving the modeled
phenology in carbon balance models and the way how to do it is discussed.
41

EFFECTS OF URBANIZATION ON GROWING SEASON DYNAMICS AND
GROSS PRIMARY PRODUCTION IN MAJOR METROPOLITAN AREAS IN THE
UNITED STATES.
M.A. White, R.R. Nemani
Numerical Terradynamic Simulation Group, University of Montana
mike@ntsg.umt.edu/Fax: 702-924-9263
Throughout the twentieth century, global populations have increasingly migrated to and concentrated in
urban areas. While many of the economic, social, and meteorological consequences of urbanization are well
studied, the effects of urbanization on growing season dynamics and the carbon cycle are less understood.
Here, using a ten-year satellite record from the Advanced Very High Resolution Radiometer (AVHRR), we
explore the consequences of urbanization in major metropolitan areas of the United States. We selected the
ten largest metropolitan areas and calculated average dates of onset and offset of greenness and gross
primary production (GPP) for urban and rural areas (pixels within a 50km radius and with no more than a
100-meter elevation difference from the city). We found that in mesic climates, such as in Pittsburgh and
Atlanta, urban and rural areas showed little difference in the dates of onset and offset but that peak greenness
and annual GPP were lower in urban than in rural areas by up to 20%. In more arid climates, metropolitan
areas commonly had a longer growing season, higher peak greenness, and larger annual GPP, presumably
due to irrigation and the planting of exotic species. Increases in arid climates were of a smaller magnitude
(approaching 10%) than were decreases in mesic climates. Our results suggest that the process of
urbanization does not produce consistent impacts on growing season dynamics and GPP. Rather, the
interaction of climate and sociological influences regulating irrigation and planting preferences are strong
controls.
42

SESSION 4 MODELLING PHENOLOGY
TESTING TEMPERATURE DATA FOR PHENOLOGICAL MODELS
R. Snyder (1), D. Spano (2), C. Cesaraccio (3), P. Duce (3)
(1) Atmospheric Science, University of California, Davis
(2) Dip. di Produzione Vegetale, Universita’ della Basilicata, , Potenza, Italy
(3) Consiglio Nazionale delle Ricerche, IMAes, Sassari, Italy
rlsnyder@ucdavis.edu/Fax: +001-530-752-1552.
It is well known that air temperature affects the phenological development of plants. However, errors in the
collection of temperature data can lead to inaccurate phenological predictions. This is especially true in a
Mediterranean climate (e.g., California and Italy) where advection and surface wetting (i.e., by rainfall or
irrigation) can affect the temperature measurements. In fact, model errors resulting from the use of bad
temperature data can be as large as the differences resulting from climate change. Temperature differences
near 2.0 o C have been observed between weather stations located over bare soil and over irrigated grass in the
desert of California. Consequently, temperature data sets should be scrutinized to insure that the data are
representative of the region and the application before using them to model phenology. Similarly, when the
environment around the plants is not considered, misleading phenological observations can result. The
environment surrounding the weather station and the plants being studied will affect the relationship
between the model and observed phenological development, and therefore only results from good locations
should be used. The choice of a "good" location depends on the purpose of the study. If the purpose is to
model phenology of irrigated crops, then the temperature data should be collected from a station that is
minimally affected by irrigation or rainfall. Placing a weather station within the study crop will give good
information for that particular crop in that year, but the results will not be useful for the same crop in other
locations within the region or in other years because of irrigation timing and amount differences. Collecting
the temperature data over an irrigated grass surface provides a reference value for the region that is little
affected by rainfall. This is true because the energy balance over well-watered grass is little affected by
rainfall frequency. If the purpose is to model the phenology of natural vegetation, then the temperature data
should be collected in an environment similar to the plants being studied. For natural vegetation, because
the temperature affecting the plants is affected by rainfall, the temperature data should be in an environment
where rainfall influences temperature. In this paper, weather station siting and the effects of evaporation on
temperatures used in phenological models in a Mediterranean climate will be discussed. Examples of edge
effects and weather station siting on temperature measurements will be presented. For example, using
temperature measured 180 m from the edge and on the edge of an irrigated grass field in the desert resulted
in about three days difference over 40 days in predicting 900 degree days. In the Central Valley of
California, measuring temperature over irrigated grass gives the same mean annual temperature as over bare
ground in some years but as much as 1.0 o C lower in other years. When measuring over bare soil, stage-1
evaporation is affected by evaporative demand and stage-2 soil evaporation rates are affected by soil type as
well as by the evaporative demand. Because difference in evaporation rate affect sensible heat flux density,
it is likely that soil differences will affect temperatures measured over bare soil. There are also soil effects
on the temperature around natural vegetation and hence phenology. Temperature measurements over bare
soil may provide good data for phenological models of natural vegetation growing similar soils but not
growing on soils with different surface evaporation properties. This is another reason for using temperature
data collected only over irrigated grass for long term assessment of climate change.
43

AN IMPROVED MODEL FOR DEGREE DAYS FROM DAILY TEMPERATURE
DATA
C. Cesaraccio (1), D. Spano (2), P. Duce (1), R. L. Snyder (3), and P. Deidda (4)
(1) Istituto per il Monitoraggio degli Agroecosistemi, CNR-IMAes, Sassari, Italy
(2) Dipartimento di Produzione Vegetale, Università della Basilicata, Potenza, Italy
(3) University of California, Department of Land, Air, and Water Resources Davis, CA, USA
(4) Dipartimento di Economia e Sistemi Arborei, Sassari, Italy
spano@unibas.it
Since biological response to temperature is nonlinear and temperature has a clear daily cycle, it is
fundamental to include this systematic temperature variation in the input to agricultural models, such as
those describing crop phenology and development based on the accumulation of growing degree days (°D).
Degree days (oD) are determined by first calculating degree hours (oH) for each hour of the day. The
number of °H for any given hour is calculated as the mean hourly temperature or the upper threshold,
whichever is smaller, minus the lower threshold. To calculate oD, the oH are summed over the 24-hour day
and the sum is divided by 24 hours per day.
Although using hourly weather data offers the greatest accuracy for estimating °D, daily maximum (Tx) and
minimum (Tn) temperature data are often used to estimate °D by approximating the diurnal temperature
trends. This paper presents a new empirical model (TM) for estimating hourly mean temperature using the
date, latitude, Tx and Tn recorded on the date, and the minimum temperature on the next day (Tp). The TM
model describes the diurnal variation using a sine function from Tn at sunrise until reaching Tx, another sine
function from Tx until sunset, and square root function from then until sunrise the next morning. The model
was developed and calibrated using several years of hourly data from five automated weather stations
located in California and representing a wide range of climate conditions. The model was tested versus an
additional data-set at each location. The temperature model gave good results with the root mean square
error less than 2.0°C for most years and locations.
The TM model was used to estimated hourly temperature and calculated degree-day values. A comparison
between °D calculations from TM, single-sine and single-triangle methods is presented. The oD estimates
calculated with hourly temperature were considerably better than the single-sine and single triangle methods
during periods when the threshold temperature was above the daily minimum temperature. The results were
similar for all oD calculation methods when the minimum was above the threshold temperature. In all cases,
the °D calculation showed a limited accuracy on overcast days.
44

IMPORTANCE OF PHENOLOGY AND PHENOLOGICAL MODELS ON AN
INTEGRATED EVALUATION OF FOREST ECOSYSTEM MONITORING DATA
S. Raspe
Bavarian Sate Institute of Forestry, Department of Forest Site and Environment, Freising, Germany
Ras@lwf.uni-muenchen.de / Fax: ++8161-714971
For an intensive and continuous observation and documentation of complex physical/chemical and
biological processes in forest ecosystems a network of 22 Forest Ecosystem Monitoring Stations were
established all over Bavaria. The program encompasses measurement of meteorological parameters and soil
temperature at an open field stations as well as surveys of throughfall, soil moisture, soil solution chemistry,
deposition of pollutants and nutrients, chemical and physical soil parameters, nutritional status and health
condition of trees, litterfall, ground vegetation, growth and phenological observation of tree species at forest
stand plots. Moreover, phenological observations of trees and shrub clones according to the criteria of
“International Phenological Gardens” are done in a small phenological garden near to the meteorological
measurements.
This comprehensive data basis offers the possibility for an integrated evaluation of the condition and
dynamic of forest stand, soil and water respectively. As many impact factors show seasonal variations, and
as the sensitivity of biological processes to different stress factors depend on the physiological status of the
systems, the definition of physiological seasons seams to be necessary. It is convenient that such a
distribution is not constant in different years and at different sites, because the physiological status of
different forest ecosystems are not constant in space and time.
Visible symptoms of those physiological processes are the phenological phases as being observed in the
Forest Ecosystem Monitoring Station program. On the other hand several models exists to calculate growing
season or the appearance of phenological phases from meteorological and some times hydrological data. An
application of such models at the Forest Ecosystem Monitoring Stations allows their validation with data
from the same forest areas. Moreover, evaluation of phenological observations and modeling of growing
season could be used for a physiological distribution of sensitive time periods to different impact factors on
the ecological status of forest sites.
The paper compares phenological observation data and modeling results from the Bavarian Forest
Ecosystem Monitoring Station program. The impact of the growing season on the response of ecosystem to
stress factors will be shown by some examples within the scope of water and nutrient availability and forest
growth or forest health. The results will be discussed with respect to the importance of phenology and
phenological models on an integrated evaluation of forest ecosystem monitoring data.
45

A BARLEY ONTHOGENIC MODEL AS A TIME-BASE FOR MONITORING
ADVERSE AGROMETEOROLOGICAL FACTORS
J. Valter
CHMI, Prag, Czech Republic
Valter@chmi.cz
The paper presents the model of the development of the spring barley in terms of its phenological stages.
The model, the name of which is ONTHO_SB, has been built as practical tools of the agrometeorological
service of CHMI in Prag. The attention is focussed to logical plan of the development simulation and
phenological timing, whereas problems of the code, meteorological input data, experience with the
maintenance of the model and other agrometeorological aspects are only briefly mentioned. The principle of
development-simulation stands generally on a slight1y adapted logistic function, applied individually on
each phenological stage of the crop, where temperature is the independent variable. The influence of soil
moisture on development of plants is involved, too. The model is designed to give three different types of
operational information : rate of seasonal development; leaf area estimates; soil moisture estimates;
occurrence of adverse agrometeorological events such as drought, lodging (plants lie down), irregular
emergence, waterlogging, floods etc. Using a predicted meteorological or climatological data to prolong real
rows of data, the system is able to give forecasts of plant development, too. An important attachment of this
paper ssems to be The Comparative Table of Phenological Scales that contains definitions of phases and
corresponding codes of three standard macro-phenological scales for cereals ( FEEKES - ZADOKS - CHMI
model). A relatively easy adjustment for oats and spring wheat is posssible. An analogue for winter wheat is
now under preparation.
46

FORECASTING AIRBORNE POLLEN CONCENTRATIONS: DEVELOPMENT
OF LOCAL MODELS
A.Ranzi (1), P. Lauriola (1), F. Zinoni (2), L.Botarelli (2)
(1) ARPA Emilia Romagna - Direzione Tecnica
(2) ARPA Emilia Romagna-Servizio Meteorologico
e-mail:f.zinoni@smr.arpa.emr.it
People's sensitivity to allergies may represent one of the most important sanitary factors of the next century.
Attention must be paid to this issue in order to reduce its incidence on social costs and improve the quality
of life.
A regional monitoring network has been established since the beginning of the 1980's. At the present ARPA
Emilia-Romagna (Regional Agency for Prevention and Environment) leads this network with the support of
the Italian Society of Aerobiology. The activities of the monitoring service include: monitoring of airspreaded
pollens, data management, forecasts, development of dedicated software and publication of a
weekly bulletin with results on monitoring and forecast. Pollen spreading forecast is developed using past
and present years data related with agrometeorological models.
Reliable predictive models of pollen concentrations are useful for allergists and physicians involved in
clinical trials. Our main goals are to improve seasonal forecasts and to analyse anomalous years.
Two statistical approaches have been used to develop models on gramineae pollen spreading, including
regression methods and neural networks. Input variables are the main meteorological data, i.e. daily
temperature (max., min. and average) and rainfall, in addition with some agrometeorological variables (i.e.
hydrological balance). The output of the first model is the day on which a pollen threshold (50 pollen/mc) is
reached. The output of the second model is the daily pollen concentration. Both models were able to identify
and predict anomalous years.
47

MODELLING THE PROBABILITY OF GYPSY MOTH ESTABLISHMENT IN
NEW AREAS OF NORTH AMERICA ON THE BASIS OF PHENOLOGY
J. Régnière (1), V.G. Nealis (2)
(1) Canadian Forest Service, Quebec City, Quebec, Canada
(2) Canadian Forest Service, Victoria, British Columbia, Canada
jregniere@cfl.forestry.ca
Gypsy moth is constantly being introduced into western North America. The extent of its possible range in
that part of the continent is not well known. A temperature-driven, multiple-generation simulation model of
Gypsy moth seasonality was used to determine the probability of establishment of persistent populations,
based strictly on the insect's ability to reach a feasible, stable seasonality. Southern British Columbia is used
as the area for this study. Maps of establishment probabilities can be generated by taking into account
regional climate, vertical thermal gradients and topography. Such maps can be used for pest-management
(e.g. eradication) decision support but also to address such ecological questions as the potential effect of
climate change on the insect's range. The approach can be easily applied to most poikilotherms for which a
suitable developmental model is available. A public-domain computer program called BioSIM was been
used to conduct this analysis (see Régnière, J. 1996. A generalized approach to landscape-wide seasonal
forecasting with temperature-driven simulation models. Environmental Entomology 25: 869-881). This
program is available upon request from JR.
48

ON MODELLING OF PHENOLOGICAL AUTUMN PHASES
N. Estrella
Technical University of Munich, Department of Ecology, Freising, Germany
Estrella@met.forst.tu-muenchen.de // Fax. (+49) 8161 714753
Phenological models trying to forecast the beginning of spring phases are common, but, up to now there are
no models that enable the prediction of autumn phases of deciduous trees. Mainly because for the modelling
of the length of the vegetation period there is a need to determine the beginning of the leaf colouring.
By the time being, there are attempts to predict the end of the vegetation period, for example the
photosynthesis rate is used in some Biosphere models. These models assume a sole dependence on
temperature and are not specific
There are numerous problems modelling autumn phases of deciduous trees:
autumn phases are harder to observe correctly, the data might have many mistakes
the scattering range is very broad
there is hardly to find any useful literature on the release of leaf colouring in nature
there are several hypotheses, most of them using as primary parameter the temperature
The hypotheses found in the literature for the end of the vegetation period are normally used to determine
the end of the growing season not only for one species, but for all the different plants of a region. It is
difficult to use these hypotheses as parameters for modelling. Then, to find the relevant factors for the
beginning of leaf colouring all the eligible parameters have to be proofed for local correctness
Analyses of phenological data supplied by the German weather service for the autumn phases of deciduous
trees covering time series with at least 30 years between 1951-1996 of observation show positive trends. The
leaf colouring postpone to a later date. Calculations of the data show shifts lying in the range of 0,03
Days/year for beech and 0,04 Days/year for birch.
49

ANALYSIS OF PHENOLOGICAL MODELS USING STATISTICAL
RESAMPLING METHODS
R. Häkkinen
Finnish Forest Research Institute, Helsinki, Finland
risto.hakkinen@metla.fi / Fax: +358 9 625308
Many phenological models describing the annual cycle of trees include components for the rate of
development. For example, according to one model the Spring bud burst takes place when the observed
value of ordinary temperature sum exceeds a critical threshold value. No standard statistical methods are
available for the analysis of the models because the sampling distributions of the parameters, and those of
the mean square errors of such dynamic models, are not known. Thus the evaluation of such models has
been mainly based on the numeric comparison of residual errors of the models only. However, modern
computers are so efficient that it is possible to use statistical inference based on resampling methods.
The underlying idea in obtaining the unknown sampling distributions with resampling is to treat the original
data set as a population and to draw samples from it repeatedly. The statistical null-hypothesis, that the mean
square errors (MSE) of two models are equal, for example, can be tested utilising the bootstrap-method. The
bootstrap-sample is formed by drawing items from the original sample (the ‘population’) at random, one at a
time with replacement, until the original sample size is reached. This procedure of drawing bootstrapsamples
is repeated many times. For every sample the two models are fitted and the difference of their MSEs
is calculated. The differences represent the bootstrap sampling distribution on which the inference is based.
The properties of the model parameters can also be studied using the bootstrap method and prediction errors
can be estimated using cross-validation.
-2
0
2
50
4
6
8
10
12
14
16
18
MSE2 - MSE1
mean=11.2
std.dev. = 3.7
n = 7000
20
22
24
26
28
In one example of this application the models predicting the bud burst timing of birch leaves were compared.
The data comprised a 55-year-long bud burst time series and daily temperature records. The bootstrap
sampling distribution, i.e. the distribution of differences of mean square errors of two models calculated
from 7.000 bootstrap-samples were used to test the statistical significance of the equality of MSEs (see
Figure). In the first model the ontogenetic bud development began on a fixed calendar date in the Spring,
and in the second model the beginning of bud development was dependent on the state of dormancy. In the
Figure the vertical lines at 2.5 % and 97.5 % percentile give the 95 % bootstrap confidence interval of MSE
difference. The zero does not belong to the confidence interval and this implies that the difference of the
mean square errors is statistically significant.

SESSION 5A APPLICATIONS OF PHENOLOGY IN AGRICULTURE AND
FORESTRY
REALISM IN PHENOLOGICAL MODELS FOR THE ANNUAL CYCLE OF
TREES: IMPORTANT FOR CLIMATE CHANGE IMPACT ASSESSMENT!
K. Kramer, I. Leinonen, H. Hänninen
K.Kramer@Alterra.wag-ur.nl
� If phenological models are to be used to assess the impacts of global warming then the modeller should
focus on the realism and generality of the model. The lowest error only is not a good criterium for
model selection. The principles of generality, realism and precision for the definition of modelling
concepts will be outlined.
� Much confusion in phenology modelling is still due to a wide array of sub-models, and differing
definitions make it difficult to communicate. A common notation of phenological concepts is now
emerging in the phenological literature. This will be used to give an outline for the principles for the
modelling of the annual cycle of trees.
� Good methodologies of data processing and parameter estimation are available and should be used to
avoid unneccesary bias between authors. These appoaches will be brought to attention and shortly
discussed.
� Future research should focus on both modelling and experiments. A realistic model cannot be selected
only because it works well on independent observed data. Original controlled experiments linking
theory to practice are urgently needed.
51

APPLICATION OF PHENOLOGY IN AGRICULTURAL PRODUCTION
PLANNING IN SLOVENIA
A.Sušnik
Hydrometeorological Institute of Slovenia, Ljubljana, Slovenia
andreja.susnik@rzs-hm.si
The majority of the models for the management and agricultural operations planning include a phenology
component which qualitatively indicates the development stages of crops. The set of phenological data are as
important as all the other input parameters for computing water balance and irrigation scheduling, preparing
warnings for various diseases and pests and optimal use of pesticides, for risk assessments (droughts), land
use evaluations and others. In the first part of the paper the phenological data for vine and some vegetables
were used as input data for operating agrometeorological models for irrigation and pest protection in the
vegetation periods 1999 and 2000 in two agricultural regions in Slovenia. The second part of the paper
describes the assessment of agricultural drought in the spring 2000 using phenological data for winter wheat
and water balance for 36 stations in Slovenia. The analyses are based on phenological data collected in the
phenological network of Hydrometeorological Institute. For the survey two types of agrometeorological
models were used: model for water balance (IRRFIB-2) and models for plant protection (AGROEXPERT
and PLASMO). Beside phenological data daily climatological data for 46 climatological stations were used.
The paper describes the practical use of information on crop development by verification and calculations of
agrometeorological models and drought risk assessments. The correctness and timeliness of phenological
data is of great importance in this kind of production planning.
52

USE OF BIOCLIMATIC INDEXES TO CHARACTERIZE PHENOLOGICAL
PHASES OF APPLE VARIETIES IN NORTHERN ITALY
N. Valentini (1), G. Me (1), R. Ferrero (1), F. Spanna (2)
(1) Dipartimento di Colture Arboree, Università di Torino
(2) Regione Piemonte - Settore Fitosanitario regionale
(1) me@agraria.unito.it (2) ufficio.agrometeo@regione.piemonte.it
The research was addressed to characterize the phenological behaviour of different apple varieties and to
compare different bioclimatic indexes in order to evaluate their adaptability in describing the phenological
phases of fruit species.
A field study on chilling units requirement (Winter Chilling Requirement) and growing degree hours
accumulation (G.D. H.°C) of 15 native apple cultivars adapted to climatic conditions was carried out in a
fruit area in northern-western Italy (Cuneo Province, Piedmont).
From 1991 to 1993, climatic data were measured using meteorological stations installed in an experimental
orchard (Verzuolo, Cuneo).
The temperature data were measured as hourly temperature from the end of the summer till fulll bloom.
Phenological data were determined in the orchard by weekly observations following Fleckinger stages
(INRA).
Four methods were compared to determine chilling units requirement (WCR): Hutchins, Weinberger-Eggert,
Utah e North Carolina. The growing degrees hour requirement (GDH) was estimated using only one method
with 2 different base temperatures: 4.4 and 6.1 °C.
The Utah method was applied to determine the time when accumulated chill units become effective in rest
requirements.Positive chill-units began to be accumulated just after the day in the fall when the first negative
accumulation is experienced.
The comparison among the different methods pointed out that Weimberger-Eggert is the best method: in fact
it shows the lowest statistical variability during the 3 years of observations.
More difficulties were found to determine the date of rest completion data and the begin of GDH
accumulation. The best base temperature to estimate GDH is 4.4°C .
Phenological and climatic characterizations are two basic tools that can give to farmers and agricultural
advisors, important indications about the varieties choice and the applications of the best and the most
correct cultivation practices.
53

PHENOLOGICAL PREDICTIONS IN PLANTS
F.E. Wielgolaski
Department of Biology, University of Oslo, Norway
f.e.wielgolaski@bio.uio.no /Fax: +47-22854664
In the present study correlations were carried out between timing of earlier and later phenophases in m plant
species studied at several sites through three years, mainly along a coastal-inland gradient in western
Norway. At all sites climatological observations were carried out, and detailed soil analyses were available
from all sites. If there were short periods (less than 3-4 weeks) between the phenophases compared, even
quite strong, significant correlations were found to be of limited interest, because it might just indicate some
sort of a persisting climatic trend. The earliness of spring phenophases in one species, however, generally
strongly influenced the timing of later stages in the same species, even when it was a relatively long period
between the phases (up to four months). In woody plants dates of the early flowering Salix caprea seemed to
be more important for later phenophases of many other woody plant species than the normally even earlier
flowering of Corylus avellana. The timing of many of the summer and autumn phenophases observed, were
also highly significantly correlated with timing of other, somewhat later spring phases, some with the time of
flowering in Prunus padus, others with for instance budbreak in Betula or apples. Possible reasons for this
are discussed using the available data on environmental factors. Similar dependencies were found between
early and late developing species of herbaceous plants. Regression coefficients indicated that one day earlier
or later in the spring phases, mainly changed the later summer phases between about 0.5 and nearly 1.5 days,
both in woody and herbaceous plants. The timing of some autumn phenophases also seemed to be of
importance for the time of various spring phases next year in perennial plants. In the present study this is
shown e.g. by the highly significant correlations often found between the flowering time of Aster novi-belgii
in the autumn (on an average at the end of September) and many phenophases the next spring, particularly
the flowering time of apple and Syringa vulgaris. Autumn phases taking place one month earlier showed
less importance for the phenology next year. It is suggested that one reason for this, may have been that
differentiation of many of the new organs was not really started at the time of the early autumn phenophases.
54

GROWTH AND PHENOLOGY OF A SEMINATURAL GRASSLAND
SUBMITTED TO ELEVATED ATMOSPHERIC CARBON DIOXIDE
CONCENTRATION
A.Raschi (1), F.Selvi (2), S. Marchi (3), S. Sforzi (3)
(1) C.N.R. - I.A.T.A., Firenze, Italy, (2) Dip. Biologia Vegetale, Università di Firenze, Italy,
(3) Ce.S.I.A. - Accademia dei Georgofili, Firenze, Italy.
raschi@sunserver.iata.fi.cnr.it/Fax +39055308910
The reported work is part of an ongoing research project aiming to assess the long term impacts of elevated
atmospheric carbon dioxide concentrations, on a semi-natural grassland community, analysing its effects on
the structure, the ecophysiology and the botanical composition of the grassland.
A grassland representative of long term abandoned hill cropland, or regrazing olive plantations, that
constitue now a relevant part of agricultural land in Central Italy, was exposed to elevated carbon dioxide
concentrations by means of a free-air CO2 enrichment facility (FACE system). The species composition
includes clovers together with C3 and C4 grasses.
Both LAI and dry matter values were increased under elevated carbon dioxide; the variability was high.
Both alive biomass and litter were incresed in the fumigated plots; the LAI values were rather low, yet
similar to what found by other authors on poor soils of the Mediterranean basin. Some species appeared in a
slightly more advanced phenological phase in the control rings, while, on the contrary, in some others the
phenological development appeared to have been speed up by elevated carbon dioxide. At the same time,
relative species abundance seems to have been affected by carbon dioxide concentration.
Stomatal conductance was significantly reduced only in some species (Avena barbata and Medicago
arabica), but not in others. In contrast with most of previous research, stomatal density of the abaxial leaf
surface was unaffected in all the species, while, on adaxial surfaces, it was reduced in clovers. The results
are discussed in the perspective of the possible effects of global change on Mediterranean ecosystems.
55

SESSION 5B APPLICATIONS OF PHENOLOGY IN ECOLOGY
PHENOLOGICAL MONITORING OF INDIVIDUAL TREES
R. Brügger, A. Vassella, F. Jeanneret
Geographical Institute, University of Berne, Hallerstr. 12, 3012 Bern
bruegger@giub.unibe.ch / Fax: +41-31-631 85 11
Phenological observations are a tool to get information about the seasonal development of the above ground
parts of the trees (especially leaf unfolding, flowering and colouring) in relation to climatic parameters. In
Switzerland the existing phenological networks have provided information for agricultural areas so far ( by
MeteoSwiss since 1951). In 1997, the Geographical Institute at the University of Berne, supported by the
Swiss Agency for Environment, Forests and Landscape, started a campaign with the goal to install an
observation network also in forests to improve the understanding of forest ecosystems. The campaign lasts
till the end of the year 2000.
An observation manual, which had been worked out earlier (Vassella 1997, unpublished), has been used for
the observations. Foresters and interested non-professionals have tested the manual and have given us
feedback with regard to the understanding of the description of the phenophases. The phenological
observations have been based on single trees or stands considering different tree species. Until summer 2000
we have observations from eighteen persons at forty-two stations ( totally 631 trees and 41 stands). Some
volunteers have started the observations in 1998, others in 1999.
At some stations the phenological development during the year will be compared with growth measurements
of the trees (shootlength and girth). The observations of single trees give us the possibility to compare the
individual phenological behaviour of the trees and to show the variability between them.
56

INCREASING FROST DAMAGE RISK OF EARLY FLOWERING BOREAL
TREE SPECIES: WILL CLIMATE CHANGE MAKE THEM DECLINE?
T. Linkosalo
University of Helsinki, Department of Forest Ecology, Helsinki, Finland
Tapio.Linkosalo@Helsinki.Fi, Fax. +358 9 191 7605
The boreal climate zone provides trees with several signals (like temperature, variations in light conditions,
changes in moisture, etc.) that they can utilise in timing their phenological events. So far it is unclear which
signals different species use and in what manner. There are several different models presented in the
literature describing phenological timing. Many of these perform satis-factorily in describing phenological
events in the prevailing climatic conditions, but give divergent results when extrapolated with simulated
climate change conditions.
In this study I tested three rather different phenological
models to predict the changes in the flowering date and frost
damage risk of Alnus glutinosa, Alnus incana, Betula sp. and
Populus tremula. The first model, as presented by Sarvas,
describes the dormancy that the trees fall into in the autumn,
and assumes that ontogenetic development in spring starts as
soon as dormancy is released. The second model, called the
light-climate-triggered model, assumes that the plants utilise
an additional signal from the light climate to start their
ontogenetic development later in spring, well after dormancy
is released. The third model, as presented by Cannell and
Smith, describes simultaneous ontogenetic and dormancy
development, with the threshold for the occurrence of
phenological events decreasing as dormancy proceeds.
The climate change was simulated by fitting the models to
historical phenological data from central Finland from 1896
to 1955 and temperature records (four per day) for 1883-
1981, and using the model parameters together with modified
temperature records to estimate the change in flowering
dates. The frost damage risk was estimated as the ratio of
years in which temperatures below a specific threshold were
recorded within the two weeks following the flowering date.
Although the predicted frost damage risk varies between the
three models, they all show considerable increase in risk with
a mean annual warming of 4 to 5 o C, especially for the two
species of Alnus. The results are more variable for the later
flowering species. Warming of 4 to 5 o C is expected to take
place within the next century in Finland. The simulations
suggest that a great decrease in the success rate of sexual
reproduction of early flowering tree species in the boreal
zone is possible. Although Alnus and Populus reproduce to
Fig. 1. The frost damage risk of Alnus
glutinosa (A), A. incana (B) and Populus
tremula (C) as a function of temperature
increase, according to Sarvas model
(open), light-climate-triggered model
(dotted) and Cannell model (solid).
great extent by suckering, in natural, unmanaged forests they are also pioneer species that first occupy the
bare woodlands exposed by forest fires or storms. As climate change proceeds, it may considerably change
the natural succession and ecology of boreal trees.
57

EVALUATING THE POTENTIAL FOR CLIMATE CHANGE INDUCED BARK
BEETLE INVASION OF HIGH ELEVATION ECOSYSTEMS
J. A. Logan (1), J. A. Powell (2), B. J. Bentz (1)
(1) USDA Forest Service, Logan UT, (2) Department of Mathematics, Utah State University, USA
jlogan@cc.usu.edu/FAX:435-755-3563
Some western US pine forests have evolved with bark beetle disturbance as an integral part of an adapted
system. Lodgepole pine (Pinus contorta), for example, has co-evolved a relationship with fire and mountain
pine beetle (Dendroctonus ponderosae) disturbances that serve to maintain it as a seral component of
spruce/fir climax forests. Without the interaction of these two disturbance agents, lodgepole pine would be
lost from much of its distribution. In contrast, other pine ecosystems have not evolved in consort with bark
beetle disturbance. The high-elevation, 5-needle pines, e.g. whitebark pine (Pinus albicaulis), are typically
found in environments lacking sufficient thermal input for maintaining synchronized, adaptive voltinism for
mountain pine beetle populations. Global warming of the magnitude projected by current global circulation
models has the potential to significantly impact the geographic distribution of many species. In this talk we
explore the potential consequence of global warming on the distribution and outbreak status of mountain
pine beetle with respect to high-elevation habitats. We begin this investigation by exploring the dynamical
properties of an existing model of mountain pine beetle phenology and seasonality. The dynamical
properties of the thermal habitat are characterized by regions of adaptive, synchronous seasonality separated
by regions of maladaptive, asynchronous seasonality. Global warming, by even conservative estimates of a
CO2 doubling scenario, is great enough to move high elevation habitats from a maladaptive thermal regime
to an adaptive regime, with potentially deviating consequences for whitebark pine. Climate change
translates to a latitudinal as well as an elevational shift in thermal habitat. A latitudinal shift by an amount
consistent with CO2 doubling would not only allow mountain pine beetles to occupy previously unoccupied
lodgepole pine habitat (range expansion), but would also allow invasion of previously unattacked jack pine
(Pinus banksiana), a commercial valuable species in Canada. Although model simulations of future
scenarios must be considered speculative, currently observed phonological adaptations by mountain pine
beetle populations are consistent with model predictions. (1) A well documented outbreak that occurred
during the 1930s in high elevation whitebark pine accompanied 10 years of exceptionally high temperature,
on the order of those predicted by CO2 doubling. (2) Mountain pine beetle activity is currently being
observed further north in Canada than previously recorded. This observation is concurrent with record
setting warm temperatures of the past several years. (3) Model simulations predicted regional populations
adapted to the prevailing regional climate. Laboratory experiments with beetles collected in central Idaho
(44ºN) and southern Utah (37ºN) resulted in finding differences consistent with those predicted by the
model.
Finally, we discuss implications of this analysis for exotic as well as native invasive species. In particular,
the modeling approaches we discuss can be applied for assessing the potential distribution of an exotic
introduction. Additionally, theoretical analysis of the model has provided insights into experimental
protocols for characterizing the potential geographical limits and seasonality of a new or hypothetical
introduction.
58

LOSS OF SYNCHRONY BETWEEN HIGH- AND LOW- ALTITUDE
FLOWERING PHENOLOGY DUE TO CLIMATE CHANGE
D. W. Inouye
Depart of Biology, University of Maryland, USA,
di5@umail.umd.edu, 301-405-6946; FAX 301-314-9358
A growing number of papers from both North America and Europe are reporting changes in the timing of
growing seasons and events such as the breaking of buds, flowering, bird migrations and nesting, etc. Most
of these reports are from low altitudes, and most of them have found evidence for earlier timing of
phenological events in recent decades. In contrast, my long-term study of flowering phenology (1973 -
present) at the Rocky Mountain Biological Laboratory (2,800 m) in Colorado, USA, indicates that there is
no evidence for earlier timing of the growing season or of flowering by many species of herbaceous or
shrubby wildflowers.
As is predicted by some models of global climate change, there is evidence of increasing winter
precipitation at the Rocky Mountain Biological Laboratory since 1975. Total winter snowfall averages
1,129 cm (range = 474-1,641 cm), and while the change since 1975 is not statistically significant, it may be
biologically significant because it has kept the first date of bare ground (which marks the beginning of the
growing season) from changing over this same period despite some evidence of warming temperatures.
First date of bare ground has ranged from 26 April to 19 June (mean = 24 May), and May temperatures have
been increasing (as measured at a weather station in Crested Butte, 9 km away and about 500 m lower). The
first date of flowering for all species that have been examined so far from my data is significantly correlated
with the date of bare ground. There do not appear to be any species whose timing of flowering is tied to
other environmental cues, such as day length or summer precipitation.
A long-term study of flowering phenology in the Washington D.C. area (by botanists from the Smithsonian
Institution; unpublished data) has found significantly earlier flowering since 1970 by many species of
wildflowers, including some congeners of species of I am studying. For example, Mertensia virginiana is
flowering 21 days earlier now than it did in 1970 near Washington, D.C. In contrast, the congener
Mertensia ciliata at my site has not changed flowering date significantly. Similarly, Aquilegia canadensis is
flowering 17 days earlier in the Washington, D.C. area but there is no trend for change in flowering by
Aquilegia coerulea at my site.
The lack of phenological change at high altitudes appears to be affecting some altitudinal migrants (e.g., see
Inouye et al. 2000. Proceedings of the National Academy of Sciences 97(4): 1630-1633). The growing
divergence in environmental cues such as temperature and snowpack that are no longer correlated the way
they have been historically may cause future changes in phenological events, and in migration and
hibernation behavior.
These data point out the value of long-term datasets for studying phenological events in the face of climate
change. Such data are relatively easy to collect, and although only one datum can be collected per year, it
may take as few as 7 - 8 years to indicate a significant trend if one exists. The uniform lack of change that I
have found at high altitude in flowering phenology contrasts with other temperate-region studies at lower
altitudes, and bioclimatic rules suggest that it would be interesting to look for latitudinal differences that
might mirror the altitudinal differences reported here.
59

POSTERS
GIS ANALYSES FOR PHENOLOGICAL DATABASES IN ESTONIA
A. Aasa, R. Ahas
Institute of Geography, University of Tartu, Estonia
antoa@ut.ee / Fax 372-7-375825
The main objective of the current study was to analyse the following aspects of the spatial distribution of
spring phenological phases in Estonia: 1) spatial pattern of phenological phases; 2) direction and speed of
the spread of phenological phases on the Estonian landscape; 3) spatial differences between different
phenological phases and years. We analysed the spatial distribution of the pollination of maple (Acer
platanoides L.) and bird cherry (Prunus padus L.) in Estonia.
The 46 observation points of the landscape phenological observation programme (1995-1999) were located
in continental Estonia (Figure 1). The objective of the observation programme was to study how the
phenological phases are distributed, and how they move, in the landscape. Therefore, the observation
programme has specific methodology and it does not describe many specific aspects of phenology - the
observers do not record dates of phenological phases, they only record the appearance of a phase, or not, in
the observation point. All together, the observation table standard included 6 development phases of 15
natural tree species for spring observations and 5 development phases of 8 natural tree species for autumn
observations in Estonia. The observation sites were selected on the basis of the following parameters:
landscape diversity and spatial coverage; visual distance from a road (binoculars were used); appearance of
more than 2 adult species of the studied tree species; exposition of the observation site. An additional time
series of the studied tree species for 1948-1996 came from the Estonian Meteorological and Hydrological
Institute (EMHI) and from the Estonian Naturalists Society (ENS) and these were used for analysis.
Figure 1. Location and numbers of field observation sites in Estonia and interpolation ellipses for SURFER
5.01
The interpolation of phenological data collected with a route method observation series had some specific
aspects. As the map of observation sites (Figure 1) shows, sited locations are aligned on three main axes:
North to South, East to West and Northwest to Southeast. This creates the need to use a special interpolation
model for spatial interpolation of data. For interpolation of data from filed observations, the Surfer 5.01 was
used, and the three interpolation ellipse model was used (Figure 2). The data was interpolated separately
with every three ellipses and the mean value of all three interpolations was used for the design of maps of 50
rows and 45 columns. Parameters of the three interpolation ellips: 1) R1=52000, R2=152000, A= -45º; 2)
R1=52000, R2=152000, A= 45º; 3) R1=52000, R2=152000, A= 90º. The distance between the northernmost
(No 20) and southernmost (No 4) observation points is 200 km, and between the westernmost (No 61) and
easternmost (No 21), 220 km.
The data was analysed by using standard modules of IDRISI, MGE and Surfer. For additional analyses and
bioclimatological mapping, the database of Estonian square kilometers was used. The statistical analyses of
phenological, climatic, landscape and vegetation parameters was made with this database.
60
R1=52000
R2=152000
A=-45°
R1=52000
R2=152000
A=90°
R1=52000
R2=152000
A=45°

PHENOLOGICAL PROGRAMS IN RUSSIAN NATURE ZAPOVEDNIKS
V.Barcan
Lapland State Natural Biosphere Reserve, Russia
lapland@monch.mels.ru\ Tel-fax (81536)5-71-99
The former Soviet Union has accumulated the rich experience of scientific investigations and permanent
observations in reserves. Observation series of Russian reserves number 70-80 and even 90 years. “Nature
Chronicle” is the document accumulating all original information about monitoring of ecosystem conditions.
It includes the results of collecting and primary treatment of the observed data. Accumulated fact material
must meet the following requirements: 1) to be reliable, 2) to be mass, 3) to be representative, 4) to keep the
many years continuity. Nature Calendar, i.e. division of one year's nature circle into periods, is the integrate
part of Nature Chronicle. Nature Calendar unites the materials of all other sections in the way to reflect the
typical biologic traits of given year and seasons. The main objects and phenomena were recommended for
observations in 60-s by common zonal phenological programs developed by phenological sector of
Geographical Society of USSR It is important for Nature Calendar not to use very many objects but to
select the typical ones in order to use them as phenological indicators. Lasting many years series of
observations are the initial material for the analysis of a year's and of many years dynamics of natural
seasonal phenomena and for prediction. The seasonal development of nature of given locality is the form of
display of phenological climate. An inherent ecological “chord”, i.e. complex of specific and interrelated
(causally or synchronously only) seasonal phenomena and processes, is unique to each phenological stage.
This gives the possibility to judge about latent phenomena by visual, easily observed ones.
Phytophenological phenomena are more reliable indicators of seasonal limits than temperature ones. About
230-240 phenological phenomena are fixed in Lapland zapovednik yearly. Phenological observations
occupy an important place in the process of education of conscious and careful consideration for nature. The
majority of Russian schools include the collecting of phenological information as the optional subject in
natural history programs. Elementary phenological observations are the first and major stage of activity in
nature protection.
61

PLANTWATCH: BIOMONITOR FOR CLIMATE CHANGE
E.G. Beaubien (1), T.C. Lantz(2)
(1) Devonian Botanic Garden, University of Alberta, AB, (2) University of Victoria, BC
e.beaubien@ualberta.ca/Fax 780.987.4141/Phone 780.987.5455
Spring flowering of perennials occurs primarily in response to accumulated temperature. Consequently,
global warming should be reflected by trends to earlier spring development. First flowering of Populus
tremuloides shows a dramatic trend to earliness in Edmonton, Alberta, Canada. Plantwatch
(www.devonian.ualberta.ca/pwatch) involves observers in tracking global change by reporting bloom times
for eight plant species.
Historical phenology records provide an essential baseline with which more recent records can be compared.
In Canada, observations 1893-1922 were published annually by the Royal Society of Canada, including 177
unique seasonal events made at 297 observation stations. This data has been used to rank 9 ecozones with
respect to earliness of development.
With Dr. Mryka Hall-Beyer, University of Calgary, we compared phenology data for five plant species with
satellite data for 1992 and 1995. Early flowering matched early green up as detected by satellite.
PLANTWATCH: CANADIANS TRACK THE ARRIVAL OF SPRING
(1) E.G. Beaubien, (2) T.C. Lantz
(1) Devonian Botanic Garden, University of Alberta, AB, (2) University of Victoria, BC
e.beaubien@ualberta.ca/Fax 780.987.4141/Phone 780.987.5455
Launched in 1995, Plantwatch (www.devonian.ualberta.ca/pwatch) is an Internet program based at the
University of Alberta Devonian Botanic Garden that links North American students and others as the „eyes
of science“. Interested observers track the spring blooming of eight key indicator species and report bloom
times over the Internet. Plantwatch also seeks observers internationally to report on lilac flowering.
Phenology (the seasonal timing of life cycle events) is an effective means of monitoring the onset of many
spring events that have important economic impacts. Historical records illustrate trends in response to
climate change.
Applications: Phenology can be used as a valuable predictive tool in a variety of contexts. It can assist
foresters and farmers in predicting the optimum timing of operations such as planting, fertilizing, crop
protection and harvest. In wildlife management, such data can assist in predicting deer population changes,
since the number of deer fawns that are successful is dependent on the relative earliness of spring. Other
applications include human health and tourism.
62

REMOTE ASSESSMENT OF PHENOLOGICAL EVENTS USING DIGITAL
CAMERAS
E. Beuker
egbert.beuker@metla.fi // Fax. + 358 15 644 333
In order to enable a high frequency of phenological observations without having to visit the plot on a daily
basis, a prototype of a remote system using digital cameras was tested at a Norway spruce Level II plot in
Punkaharju, Finland. Three digital surveillance cameras, each with a different angle or zooming rate, were
installed at the weather tower on the plot. The cameras were connected to a PC, which saved one picture
from each camera once a day at a fixed time. During spring 2000 it was found that such system is suitable to
assess phenological events. Timing of bud burst and flowering could be assessed from the pictures.
However, the technique used should be further refined to improve the quality of the pictures and to get a
better overview from the whole plot. Further developments are planned during the near future.
63

PRINCIPAL PHENOLOGICAL GROWTH STAGES OF POME, STONE FRUIT
AND CURRANTS: CODING AND DESCRIPTION ACCORDING TO THE BBCH
SCALE
E. Bruns
Deutscher Wetterdienst, Dept. Observing Network and Data, Offenbach/Main, Germany
ekko.bruns@dwd.de
The purpose of the detailed specific culture descriptions of the principal growth stages of fruit plants is to
provide national and international fruit cultivation as well as fruit growing experimentation with an
instrument for standardization. This numerical fine classification is not least required by science and in
practice when using electronic data processing. The principal phenological growth stages are therefore
presented in the form of a decimal code. The complete plant development is divided up into the “macro
stages” 0-9, from bud dormancy up to the end of leaf fall (e.g. 5: flower bud development). The micro stages
(according to the phenological phases) are represented by the 2 nd number of the code (0-9).
Comparable stages of different fruit plants are occupied by the same codes, the differences are expressed in
the descriptions of the phases/stages.
The BBCH scale has only indirect significance for traditional phenological observations. The phenological
phases were determined for the most part decades ago and it would be detrimental from a professional point
of view to “adjust” the phases to the newer decimal scale; this would cause artificial inhomogeneities in the
series.
In the table below the phenological phases of fruits are compared to the descriptions of the micro stages of
the BBCH scale, i.e. how near the phenological phases come to the code.
A further poster compares, in a similar manner, the phenological phases of indigenous cereals.
Phenological phase (observation programme of the DWD) and comments
Beginning of bud burst (A); apple. Two BBCH codes for bud burst. According to the understanding in the
DWD and the instructions, “A” is comparable to BBCH 53
Beginning of flowering, first flowers open (B); apple, pear, cherry, red currant.
Full flowering general flowering (AB); apple, pear, cherry. Virtual concurrence in definition.
End of flowering (EB); apple, pear, cherry. Little concurrence in the definition. “EB” is, however, de facto
very close to BBCH 69.
Fruit ripe for picking (F); apple, pear, cherry.
Concurrence in the description. De facto agreement can be assumed to a large extent.
Fruit ripe for picking (F); red currant. Concurrence in the description. De facto agreement can be assumed
to a large extent.
Colouring of leaves (BV); sweet cherry,
Leaf fall (BF); apple.
Differing definitions.
There ar no concurrent BBCH codes.
BBCH codes for pome and stone fruit as well as currants
BBCH 53 Bud burst: green leaves, which protect the cluster of blossoms, become visible. BBCH 07
Beginning of bud break: first green leaf tips just visible
BBCH 60 First flowers open
BBCH 61 Beginning of flowering: about
10 % of flowers open.
BBCH 65 At least 50 % of flowers open, first petals falling.
BBCH 69 End of flowering: all petals fallen.
64

BBCH 87 Fruit ripe for picking: fruits have developed sufficiently and have good keeping quality.
BBCH 87 Fruit ripe for picking: in
80 % of the bunches all berries are ripe; berries at base of racemes are soft.
BBCH 93 Beginning of leaf fall.
BBCH 95 50 % of leaves discoloured or fallen.
BBCH 97 All leaves fallen.
========== Agreement in the definitions
----------------- Agreement to a large extent
65

EXPERIENCE OF THE DENDROPHENOLOGICAL INDICATION OF SHORT-
TERM CLIMATE CHANGES AND OF CURRENT WARMING IN EASTERN
EUROPE
N.E. Bulygin
National Forest Management Academy, St-Petersburg, Russia
The Department of Botany and Dendrology of the St-Petersburg Forest Management Academy, the leading
Russian research centre in the area of phenology, has for more than 30 years studied the problem of the
dendrophenological indication of short-term climate changes. Using dendrophenological time-series
collected in St-Petersburg since 1841 (the flowering of Alnus incana, Padus avium, Syringa vulgaris, Tilia
cordata, etc.), it has been found that the powerful 19 th century temperature fall objectively reflects the
phenological trend described by a parabolic equation and the climate warming in the 20 th century refers to
the trend described by a straight equation. With the growing of the average temperature of the growingseason
by 0,08°C the season becomes a day longer. Ecologically, under the influence of the climate
warming the region of St-Petersburg has “moved” 200-250 km to the south. However, its has been found
that dendrophenological time-series have synchronous cycles manifesting themselves from early spring till
midsummer. The cycles last on average 2, 3.5, 7-8 and 31 years and have climatic analogies. The analysis of
century-long dendrophenological time-series collected in Moscow, Vologda, Kirov, Yekaterinburg and
Ukraine has shown that phenological cycles established in St-Petersburg can manifest themselves
simultaneously on the vast territories of the Russian Plain. The mathematical modelling of phenologytemperature
connections using the material of 200 phenological support units in the European part of the
former Soviet Union has allowed the researchers to work out an effective method of long-term weather
forecast for the territory stretching from forest tundra to the Ciscaucasian steppes. Dendrophenological
cycles are to some extent associated with solar activity cycles: statistically, early phenodates are observed
on average in the third year after the solar maximum and late ones in the second year after it. Ecological
adaptation and productivity of arboreal plants are greatly affected by bioclimatic cycles: a complicated set
of plants’ age reactions to short-term climate changes and phenological biorhythm changes caused by them.
The main phenoindicators of the arrival of various types of bioclimatic cycles (early-warm and late-cold)
are the flowering dates of Alnus incana or Corylus avellana.
66

FORECAST OF FULL FLOWERING DATES OF PEAR TREE (PYRUS
COMMUNIS L.), APPLE TREE (MALUS DOMESTICA BORKH) AND PLUM
TREE (PRUNUS DOMESTICA L.) – SIMILARITIES AND DIFFERENCES
K. Bergant, Z. Crepinsek, L. Kajfez-Bogataj
Center of Biometeorology, University of Ljubljana, Slovenia
zalika.crepinsek@bf.uni-lj.si / Fax:+386-61-1231088
Paper discusses the similarities and differences in predicting the full flowering of apple tree (cv. 'Bobovec'),
pear tree (cv.'Pastorjevka') and domestic plum tree. The study was conducted at University of Ljubljana
based on climatological and phenological observations of Hydrometeorological institute of Slovenia. First
average monthly air temperature and average monthly amount of precipitation from January to April were
used as predictors for flowering of fruit trees during the time period 1967-1996 and in second case input data
for models were phenological data of autochthon plants: first leaves unfolded of Betula pendula ROTH,
Fagus sylvatica L. and Tilia platyphyllos Scop. Two different approaches were employed for predicting of
full flowering of apple tree, pear tree and plum tree: the linear multiple regression and correlation analysis.
The date of full flowering for all tree species is strongly correlated with the first leaves unfolding of birch
(R2 is from 0.61 to 0.91) and in case of pear tree and apple tree also with first leaves unfolding of beech (R2
is from 0.62 to 0.66). Also strong correlation with combination of average March and April air temperature
was found for flowering of apple tree and plum tree, for pear tree the full flowering was correlated with
combination of average February and March air temperatures. In case of apple tree 76% of total variance
was explained by linear multiple regression model between fullflowering and air temperatures, for plum tree
55% and for pear tree even 91%. The multiple regression model for predicting the full flowering on the base
of March and April temperatures have great disadvantage, because the predictions can be made in case of
apple tree only 2 days ahead and in case of plum tree not even that. On the other hand, the prediction for
pear tree can be made 22 days ahead. The full flowering for apple tree and plum tree in our case were not
correlated to average monthly amount of precipitation at all. This could be expected since in Slovenia, water
availability in the spring
is sufficient for plant needs.
67

CLIMATE AND APHID PHENOLOGY
R. Harrington (1), M. Else (1), C. Denholm (1), J. Pickup (2), M. Hullé (3)
(1) IACR Rothamsted, Harpenden, Herts, UK. (2) SASA, East Craigs, Edinburgh. (3) INRA Laboratoire de
Zoologie, Domaine de la Motte au Vicomte, Le Rheu, France.
melissa.else@bbsrc.ac.uk
About 500 species of aphid have been monitored on a daily basis using a standardised trapping system since
1965. There is now a network of about 70 suction traps throughout Europe. Studies of selected species in the
UK and France reveal that migratory phenologies are advanced as a result of warmer winters. For example,
the economically important peach-potato aphid begins flying about 2 weeks earlier for every degree
centigrade rise in January-February mean temperature. The effect is consistent at most sites examined, but
there is a further effect (not related to temperature) that delays migration further north. The relationship
between phenology and temperature holds for many species which pass the winter as parthenogenetic
individuals, but not for most of those which overwinter in the more cold tolerant egg stage. Extension of the
analysis throughout Europe will be possible in the EU-funded project `EXAMINE' (2000-2003). This will
provide deeper insight into the influence of climate of aphid dynamics and allows inferences to be made on
the potential impacts of climate change.
68

RUSSIAN PHENOLOGY: HISTORY AND PRESENT DAY
V.G. Fedotova
V.L. Komarov Botanical Institute of the Russian Academy of Sciences, Museum Department, St-
Petersburg, Russia
The first phenological data collected in Russia can be found in medieval annals and chronicles.
Subsequent observations going on for many years resulted in the development of the so-called people’s
phenology based on people’s sayings about weather signs used since olden times by Russian peasants to
determine the best time for agricultural works. In the second half of the 18 th century systematic
observations were carried out by some enthusiast scientists (P.S. Pallas, I.P. Falk, A.T. Bolotov, P.
Kraft, F.E. Gerder et al.).
It is known that the Belgian A. Ketle worked out the first international programme for mass
phenological observations in Central and Eastern Europe. In 1848 the Russian Geographic Society
developed a similar programme for mass observations in Eastern Europe. The first summary of
phenological observations carried out by 120 correspondents in 1851 was published in Russia in 1854
under the name of Selskaya Letopis (“Countryside Annals”). In 1855 A.F. Middendorf published the
world’s first work providing an isophene map. A lot of material was also published in the collections of
the Geographic Society (N.Y. Danilevsky, 1858, V.I. Kovalevsky, 1884, et al.). In 1885 the climate
scientist L.I. Voyeikov created the first small network of phenological units in European Russia, and
from 1886 till 1924 a network of voluntary phenological correspondents worked on a vast territory
under the guidance of the scientist D.N. Kaigorodov. At present the network bears his name.
In the 1940s scientific phenology began to establish itself. The publications included phenological maps
of the USSR and Europe (Smirnov, 1937, 198, 1938) and the first article about the connection between
the seasonal dynamics of the atmosphere and phenological phenomena on the Earth (Vutakova, 1945).
These topics are also actively studied now (N.E. Bulygin, 1986, 1998 et al.). Since 1960, 4,000
phenological correspondents have been carrying out observations under 9 unified complex programmes
worked out (G.Z. Shchultz et al.) for all areas and provinces from the Russian Plain to the Pacific Ocean
including the territory of the former USSR. There are separate observation programmes for
hydrometeorological stations, agricultural stations and nature reserves. In some units observation timeseries
have been taken for more than 50 years. 600 units have been taking them for more that 25 years
and St-Petersburg for more than 150 years (LTA). Since 1939 long-term phenological observations
have been summarised in regular collections called Kalendari Prirody (“Weather Calendars”) providing
phenological information for St-Petersburg and the regions. Hundreds of such calendars have been
published. Phenological maps have also been included in the “Forest Atlas of the USSR” and regional
agroclimatic reference books.
The phenological science has been developing in several directions. These are general and particular
phenology and theoretical and applied phenology. General phenology studies space-time relations in the
seasonal development of natural habitats in Russia and neighbouring countries. Space-time relations
between seasonal atmospheric changes and phytosphere have been analysed and a method of
forecasting short-term climate changes on the basis of phytophenological information has been worked
out (N.E. Bulygin et al., 1986). Particular aspects of phenology involve the working out of regional
weather calendars based on indicational phenology in order to optimise economic activities. The least
studied territories in terms of phenology are the former Soviet Central Asia and Caucasus which have
not provided any observations for the past 10 years. Other neighbouring countries keep sending their
material to the Russian Geographic Society where data collected over a number of years are
concentrated in a special archive.
In Russia phenology is taught in some universities and colleges. Phenologists’ meetings and thematic
conferences are held regularly. Unfortunately, for certain reasons Russians phenologists practically do
not participate in international co-operation but we are prepared to support any initiative in phenology
and make a substantial contribution to the common cause.
69

LARGE SCALE CLIMATE VARIABILITY AND ITS EFFECTS ON MEAN
TEMPERATURE AND FLOWERING TIME OF PRUNUS AND BETULA
A.K. Gormsen, T.B. Toldam-Andersen and P. Braun
KVL, Inst. Agric. Sci, Sect. Horticulture, Copenhagen, Denmark
akg@kvl.dk / Fax: +45-35 28 34 78
Large scale climate variability greatly effects average climatic conditions and therefore is likely to influence
the phenology of plants as well. In NW-Europe, the North Atlantic Oscillation (NAO) particularly influences
winter climate and, through its effects on plants, flowering time of all tree species.
In Denmark, like in many other NW-European countries, flowering of most tree species appears to start
earlier since the beginning of the 1990`s compared to the time before. To quantify a possible relation
between NAO and flowering time of tree species, two sources of phenological information from the
Copenhagen area (Denmark)were analysed , i.e. pollen counts of the genus Betula for Copenhagen (data
from 1977-1994) and observed first bloom dates of Prunus avium ‘Bov’ from Taastrup west of Copenhagen
(data from the International phenological garden for the period 1980 - 1994). Both places have a climatic
station nearby, and temperature data was obtained from these station. Furthermore, air temperature data from
a weather station in Copenhagen were used for the period from 1955 - 1994. The NAO-Index, an index
describing the state of the NAO, was obtained from Bonn University. Simple correlation techniques were
employed using mean monthly or whole winter (Jan - April) data.
The influence of temperature on flowering time varied in this study from 30% to 56% depending on genus,
location and month. The NAO’s influence on temperatures was in Taastrup found to decrease from 48% in
January to 13% in April, with an influence on the whole period of 51%. In Copenhagen the correlation
coefficient decreases from 56% in January across 20% in March to 31% in April with an r 2 of 0.37 for the
whole period. These findings correspond well with the NAO having a decreasing influence on mean climatic
conditions from winter to spring. The direct correlation of NAO-index and flowering time also revealed a
decrease from Jan - April but with more noise (values from 52 down to 19% for the single months).
However, using whole period means (January-April) the correlation coefficient increased to 72% in Taastrup
(flowering time of Prunus) and 79% in Copenhagen (pollen counts for Betula).
This indicates a close relationship between natural climate variability, i.e. the NAO, and flowering time of
tree species for the eastern part of Denmark. This study also indicates that both sources of data, pollen
counts and observations of flowering time, were equally useful for analysing mean climate effects on plants.
LOSS OF SYNCHRONY BETWEEN HIGH- AND LOW- ALTITUDE
FLOWERING PHENOLOGY DUE TO CLIMATE CHANGE
D. W. Inouye
Depart of Biology, University of Maryland, USA
di5@umail.umd.edu, 301-405-6946; FAX 301-314-9358
(see page 59)
70

ALPINE LONG TIME DATA SETS
E. Koch
Central Institute for Meteorology and Geodynamics, Vienna, Austria
elisabeth.koch@zamg.ac.at / Fax: +43 1 3602672
Introduction
Plants in the moderate and cool climate zones have a dormancy period during winter. At the beginning of
spring the onset of vegetation is mostly triggered by temperature and daylight. Therefore the spring phases
can be looked as an indicator of changing environmental conditions being particularly sensitive to
temperature.
This paper deals with phenological spring phases of plants in the Swiss, Austrian and Slovenian alpine
regions during the period spanning in some observation sites from as early as1951 to 1999.
We regarded early spring phases as e.g. blossoming of Anemone hepatica, Galanthus nivalis, Tussilago
farfara etc. The spring phases are subdivided into blossoming and leaf unfolding. The observed plants are
e.g. Acer platanoides, Aesculus hippocastanus, Betula (pendula), Fagus sylvatica, Larix decidua, Malus
domestica, Prunus avium, Quercus, Syringa vulgaris and so on. For each plant and observations site the
deviations (days) from the corresponding mean value of the period 1975 to 1994 were calculated. The
negative values of the deviations were smoothed with a Gaussian low pass filter (filter width 10 years)
resulting in positive values for phases starting earlier than the mean and negative values for delayed phases.
In order to get complete time series missing values were calculated using linear regression-models either
with the same phenophase of the closest station or a similar terminated phenophase of the same location
(Rötzer, 2000).
The early spring phases have the greatest variability from one year to the other. Some warm days with high
insulation can trigger the blossoming of Galanthus nivalis, Anemona etc. The beginning of blossoming can
be as early as January or as late as April in higher altitudes with snow cover. These first signs of spring are
often followed by cold spells and thus are not real indicators for the beginning of the growing season
(Defila, 1991).
Despite the large differences even between the same phases in one region a general trend can be detected.
During the fifties and the late eighties and early nineties leaf unfolding and blossoming reached the earliest
values of the whole period. This fact shows good correlation with the temperature time series in the Alps for
the summer half year. Böhm et al. (2000) showed that temperature in the Alps reached its first 20th century
maximum near 1950 and after a cooling to the relative minimum in the 1970s summer temperature quickly
increased to the recent maximum. When regarding only the period 1960 to 1999 a tendency to an earlier start
of plant development can be found (Koch, 1999, Menzel 1999, Rötzer)
Switzerland Central: 10 years low passed filtered phenological time series relative to the mean 1975-1994;
positive values are earlier, negative values are delayed.
20
15
10
5
0
-5
-10
-15
-20
-25
-30
days
1951
1956
1961
1966
1971
1976
1981
1986
1991
1996
30
25
20
15
10
5
0
-5
-10
-15
-20
days
1951
1956
1961
1966
1971
1976
1981
early spring phases leaf unfolding blossoming
Acknowledgement: I have to thank the Swiss Meteorological Institute, esp. Claudio Defila and the
Hydrometeorological Institute of Slovenia esp. Ana ust and Andreja Sušnik providing the data from
Switzer-land and Slovenia. This work is part of the EU project POSITIVE (5 th Framework Programme RTD
/ EESD, EVK2-CT-1999-00012).
1986
1991
1996
days
20
15
10
5
0
-5
-10
-15
1951
1956
1961
1966
1971
1976
1981
1986
1991
1996
71

A COMMON PHENOLOGICAL DATA BASE FOR THE EU PROJECT
‘POSITIVE’
H. Scheifinger, W. Lipa
Central Institute for Meteorology and Geodynamics, Vienna, Austria
Wolfgang.Lipa@zamg.ac.at / Fax: +43 1 3602672
One of the main problems when compiling the common phenological data base consists in a reasonable
selection of phenological variables. To some extent this procedure is subjective and determined by the final
purpose. Following steps were applied:
Phase definitions of the different countries are compared and identical or similar phases are identified.
All observed species of all countries are compiled and species, which seem important enough and are
observed at least in two or more countries are selected.
Select phenological phases of the selected species and summarise them with a common coding system for
the data base.
Another very important aspect of the phenological data base concerns data quality. With an automated data
checking procedure most unreasonable data can be identified. The variation in temporal and spatial density
of the phenological data turned out to be very high. In some European regions this special feature could
pose restrictions to analysis procedures.
72

THE USE OF MODIS NADIR BRDF-ADJUSTED REFLECTANCES TO
MONITOR PHENOLOGICAL ACTIVITY
A. H. Strahler (1), C. B. Schaaf (1), M. Friedl (1), W. Lucht (2), F. Gao (1), X. Zhang (1), D. McIver (1),
and J. F. C. Hodges (1)
(1) Department of Geography and Center for Remote Sensing, Boston University, Boston MA, USA
(2) Potsdam Institute fur Klimafolgenforschung (PIK), Potsdam, Germany
schaaf@bu.edu/ Fax 617-353-3200
MODIS Standard Data Land Products began production in March 2000 in time to capture the spring
growing season in the northern hemisphere. Nadir BRDF-Adjusted Reflectances (one of the outputs of the
MODIS BRDF/Albedo Product -- MOD43B) are being evaluated for their utility in monitoring global
phenology. The MODIS BRDF/Albedo algorithm relies on multidate atmospherically corrected and cloudcleared
data and a semiempirical kernel-driven bidirectional reflectance model to determine a global set of
parameters describing the BRDF of the land surface for each 16 day period. These one kilometer gridded
parameters are then used to determine both albedo quantities and the Nadir BRDF-Adjusted Reflectance
(NBAR) for seven spectral bands. Since these surface reflectances have had view angle effects removed,
they can serve as uniform representations of the nadir reflectance for each 16 day period. Therefore they are
ideal for land cover classification and phenological studies and are being used as the primary input to the
MODIS Land Cover and Land Cover Change (MOD12Q) Products. These products will include parameters
to describe the phenological activity that occurs at a 16 day temporal resolution during each quarter of the
year. Imagery of the North American NBAR for the spring and summer of 2000 will be presented and
discussed.
73

PHENOLOGY AS GLOBAL CHANGE BIO-INDICATOR
A.Menzel
Department of Ecology, Technical University of Munich, Germany
Menzel@met.forst.tu-meunchen.de // Fax (+49) 8161 714753
The increases in air temperature due to the anthropogenic greenhouse effect can be detected easily in the
phenological data of Europe and Germany within the last four decades.
During the past 30 years of observation in the International Phenological Gardens in Europe with genetically
identical clones phase shifts are clearly noticeable. Spring events, such as leaf unfolding, have advanced by
6 days whereas autumn events, such as leaf colouring, have been delayed by 4.8 days – lengthening the
annual growing season by 10.8 days since the early 1960s. More than 70% of the variance can be attributed
mainly to changes in air temperature (Menzel 1999, 2000).
For Germany a comprehensive analysis of the main phenological seasons, represented by 16 phenological
key phases, such as flowering of snow drops indicating the start of the earliest spring, and an analysis of the
growing season, determined as the time span between leaf unfolding and leaf colouring of 4 deciduous tree
species, was made using phenological data of the network of the German Weather Service. This study
equally revealed an earlier beginning of spring in the last decades, whereas the key phases of late autumn
tend to be delayed in the past few decades. The whole growing season is also lengthened, but less than it was
revealed for the International Phenological Gardens.
Fig. 1: Linear trends of leaf unfolding of birch (Betula pendula Roth) in Germany. Data taken from the
phenological network of the German Weather Service are for long observational series (20 yeras and more)
during the 1061 to 1996 period.
Literature:
Menzel, A., Fabian, P. (1999) Growing season extended in Europe. Nature 397: 659
74

Menzel, A. (2000) Trends in phenological phases in Europe between 1951 and 1996. Int. J. Biomet. 44 (2)
76-81
75

EU-PROJECT POSITIVE: PHENOLOGICAL OBSERVATIONS AND
SATELLITE DATA (NDVI): TRENDS IN THE VEGETATION CYCLE IN
EUROPE
A.Menzel 1 , R. Ahas 2 , I. Chuine 3 , M. Hirschberg 1 , E. Koch 4 , C. Tucker 5
(1) Technical University of Munich, Germany (2) University of Tartu. Estonia (3) University of Montpellier
II, France (4) ZAMG, Austria (5) GSFC, NASA, USA
Menzel@met.forst.tu-meunchen.de // Fax. (+49) 8161 714753
POSITIVE is a 5th framework EU project funded by the European Commission which will last 2 years (Feb
1 2000 - Jan 31 2002). Further information can be found at
http://www.fw.tum.de/EXT/LST/METEO/positive/.
The idea
Phenological changes affect ecology, agriculture, forestry, human health and via feedback mechanism the
climate system. POSITIVE will study existing data sets of phenological observations in Europe and their
relationship with climate and AVHRR NDVI satellite data. Phenological monitoring has a long tradition in
many European countries and many long-term data sets exist. This makes Europe a particularly suitable
region for investigating phenology and phenological trends providing important ‘ground truth’ to earth
observation programmes and global change research.
The consortium
TUM Technical University Munich, Germany
GSFC Goddard Space Flight Center, NASA, USA
UMII Université Montpellier II, France
UT University of Tartu, Estonia
ZAMG Zentralanstalt f. Meteorologie u. Geodynamik, Vienna, Austria
Co-ordination Annette Menzel, TUM
The main objective
Main objective is to develop tools, such as phenological models, as well as techniques for integrating these
data for multi-purpose use in the field of global change research: Detection of climate change impacts with
phenological and satellite data, modelling phenology under GCM future scenarios, describing the present
and future temporal and spatial variability of phenological phases, and providing maps thereof, in order to
assess consequences for human health, biodiversity and natural systems.
The objectives
� to describe the geographical and temporal variability and trends of phenological phases in Europe
(1951-1998)
� to analyse the temporal and spatial variability of the green wave in Europe (AVHRR NDVI data 1981-
2000)
� to quantify large-scale growing season duration for the northern hemisphere
� to determine changes in the photosynthetic capacity.
� to develop and test autumn phenological models, to test springtime models found to be effective on a
regional scale
� to fit a new unified model for European temperate tree species
� to develop a new pollen shedding model for the main allergenic taxa in different European regions
� to study phenological shifts and changed gradients in the Alps
76

LIGHT AS A FACTOR AFFECTING THE FRUIT PHENOLOGY OF ATLANTIC
RAIN FOREST TREES: A CASE STUDY OF CRYPTOCARYA MOSCHATA
(LAURACEAE)
(1) P. Moraes and (2) L.P.C. Morellato
(1) Centro de Energia Nuclear na Agricultura – CENA, Piracicaba, SP – BRAZIL; (2) Departamento de
Botânica, Universidade Estadual Paulista, Rio Claro, SP – BRAZIL.
pmorella@rc.unesp.br
Fruiting patterns of animal-dispersed tropical forest trees have been regarded as aseasonal or not very
seasonal and closely related to the presence of seed dispersers, although some factors as high humidity and
mild temperatures would enhance fruit development and maturation. Recent studies have presented some
evidence supporting the importance of light for regulating phenological patterns of tropical plants, specially
flowering. We performed a the time series analysis of 8 years of fruiting phenological data from an animaldispersed
tropical tree characteristic from Brazilian Atlantic rain forest (ARF), Cryptocaria moschata
(Lauraceae). So far, this is the longest data series for ARF trees we know. The analyses revealed that the
model with day length is the best fit and explain about 79% of the variability of ripe fruit data, while unripe
fruit is linearly related to mean temperature. We demonstrate the influence of climatic variables, specially
light, determining the fruiting pattern of an animal-dispersed tree under a ratter aseasonal climate. The
regularity of fruiting patterns is important to define a species as predicted food resource to frugivores and
seed dispersers. [Financial Support by FAPESP – CNPq Research fellowship]
FLOWERING AND FRUITING PHENOLOGY IN ATLANTIC RAIN FOREST
MYRTACEAE OF BRAZIL: CLIMATIC AND PHYLOGENETIC CONSTRAINTS
L.P.C. Morellato (1)
(1) Departamento de Botânica, Universidade Estadual Paulista, Rio Claro, SP - BRAZIL
pmorella@rc.unesp.br
Phenological studies on tropical forests have traditionally focused on diverse taxonomic groups of species,
trying to investigate biotic and abiotic factors affecting the phenological patterns observed. Few studies have
tried to examine the evolutionary and ecological constraints on the phenological patterns of species within a
single family or genus. The Myrtaceae is one of the most important families in Brazil, and often the
dominant family in the Atlantic forest. We analyze and discuss the phenology of Myrtaceae species from
two different sites of Atlantic rain forest in the light of the current hypothesis that have been proposed to
explain flowering and fruiting pattern of taxonomically-related species. We explore these hypotheses as
explanations for flowering and fruiting phenology of Myrtaceae species from Atlantic rain forest, where
climatic constraints would not seem to impose restrictions to their phenological behavior. [Financial Support
by FAPESP – CNPq Research fellowship]
77

ESTONIAN ICHTYOPHENOLOGICAL CALENDAR AS SOURCE FOR
CLIMATE CHANGE STUDIES
V. Palm
Institute of Geography, University of Tartu, Estonia
vellop@ut.ee
Ichtyophenology investigates seasonal changes in behaviour of fishes – arrival to spawn, spawning,
migrations etc. In Estonia, the ichtyophenological observations are carried out from the 1951. The observers
are trustees of Estonian Naturalists’ Society. Over 500 phenophases (about 60 fish species) are observed in
368 observation posts (on rivers, lakes and the Baltic Sea, part of Estonia). Data have very many gaps,
therefore the data analysis is very difficult. There are only 113 long time-series (over 20 years), mostly
consisting of hydrological characteristics (ice drift, flood).
There are three observation posts with long time-series of ichtyophenophases - Tori (river Pärnu, south-west
of Estonia), the small lake Vagula (south of Estonia) and the great lake Peipsi (east of Estonia). In rivers, the
first phases are the begin and the end of ice drift (in March or April). The another phases become evident
after ice drift. In lakes, on the contrary, often the first phases are ichtyophenophases. The ice drift begins
later. Fishes spawn speeder in rivers as in lakes. For example, in Tori the first spawning of pike continues 3,
in Vagula 10 and in Vilusi 15 days. Differences are caused by greatness and depth of lakes. Great and deep
lakes become warm slower. The first spawn of pike begins on 9 th April in Vagula and on 14 th April in Vilusi.
Differences in territorial variability are determined by conditions of nature. In the early spring (March,
April), the sea is warmer as the land and phenophases are the earliest at the sea (west of Estonia). In April,
May and June the land becomes warm speeder as the sea, and phenophases are the latest at the sea. The
phenophases are the earliest in south-east of Estonia. For example, the two regions with the earliest arrival of
phenophases are existing by begin of the first spawning of pike. It is that the pike spawns on the boundary of
two seasons. The spawning of thermophilic bream is more homogenous - on the diagonal from south-east of
Estonia to north-west (to the sea).
The effect of climate changes to phenophases is different. The phenophases can become evident yearly very
differently. Trends of the observation period (in Tori, Vagula and Vilusi) indigate that phenophases of early
spring (ice drift, the first spawning of pike) go to earlier, and phenophases of later spring (the first spawning
of bream) go to later. There is also an effect of the last ten warm winters in Estonia. Changes in appearance
of phenophases in the observation period stretch to two weeks. Lakes (Tori) have greater changes as rivers
(Vagula, Vilusi).
78

USE OF PHENOLOGY IN AGRICULTURE
Th. Roetzer (1,2), H. Häckel, R (2), Würländer (3)
(1) Humboldt-University Berlin, Section of Agricultural Meteorology, Berlin,Germany
(2) German Weather Service, Weihenstephan, Germany
(3) TU Munich, Chair of Photogrammetry and Remote Sensing, Germany
thomas.roetzer@rz.hu-berlin.de / Fax: +49-30-31471211
The Environmental and Agroclimatological atlas of Bavaria forms a base for planing, consulting and
research in agriculture, forestry, landscaping and ecology. In 25 tables, 157 illustrations and 103 maps the
atlas treats the themes phenology, water balance, grassland growing, risk of late frost damage, climatological
suitability for growing crops, plant diseases and pests as well as production and yield. Explaining
commentaries for every chapter and methods of investigation complete the atlas.
Phenology is one of the main subjects in the atlas. In addition, phenological data are needed for most of the
other themes:
• For calculating the water balance of crops phenology is needed because crops require specific water
amounts according to their phenological phases.
• The risk of late frost damages of crops or fruit trees can be determined with the help of phenology.
• In order to map climatological suitability for growing crops, phenological data are often needed.
Depending on the phenological phases crops have specific climatic requirements.
• Phenological data are also usesful when computing climatic risks of plant diseases and pests affecting
crops.
These are a few examples where and how phenological data are needed in agriculture. At the conference
examples of the use of phenology in agriculture will be presented for every subject mentioned above.
E.g. figure 1 shows the risk of a late frost damage of the flowers of different fruit trees.
Fig.1: Percentage of frost
damage of peach, apple and
cherry in 4 South German
sites averaged over the years
1961-1990
Depending on site and plant species the percentage of a late frost damage of the flowers ranges from 0% for
apple in München-Riem and Metten up to 47 % for peach in München-Riem
79

DETECTING OUTLIERS IN LARGE PHENOLOGICAL DATA SETS
J. Schaber and F. Badeck
Potsdam Institute of Climate Impact Research, Potsdam, Germany
schaber@pik-potsdam.de / FAX: ++49-331-288-2695
A method is proposed to detect month-mistakes in large phenological datasets over a wide geographical
region. It is based on the theory that the superposition of interstational and interannual variablility can
explain a substantial fraction of the deviation of an observation from the overall average. The procedure is
stable with respect to the varying number of observations at the stations and non normal distributions
compared to classical outliers tests. The procedure defines an objective theory-based reference point and
plausability range of phenological observations rather than an arbitrary statistical threshold. It is applied to
time series of the German Weather Service (DWD) for beech (Fagus sylavtica), birch (Betula pendula) and
spruce (Picea abies). The results are compared with the original observer’s report sheets. The influence of
outlier omitting strategies on phenological model validation and fitting is demonstrated.
ANALYSIS AND APPLICATION OF PHENOLOGY MODELS TO DATA OF THE
GERMAN WEATHER SERVICE (DWD)
J. Schaber
Potsdam Institute of Climate Impact Research, Potsdam, Germany
schaber@pik-potsdam.de / FAX: ++49-331-288-2695
Phenological models considering temperature sums and chilling requirements were applied to bud burst
observations of beech (Fagus sylvatica), horse chestnut (Aesculus hippocastanum) and pine (Pinus
sylvestris) at 115 stations of the DWD all over Germany where weather information was available. The
temperature sum analysis shows that the period around one month before bud burst strongly influences the
day of bud burst but does not suffice to explain its large variation. The temperature sum models combined
with chilling tend to overestimate early observations and underestimate late observations, i.e. are not able to
cover the whole range of observed bud burst. The results obtained differ from the application of the same
models to other phenological data sets in earlier studies. This shows the difficulty of finding robust generally
applicable phenological models for European tree species.
80

INTERACTION BETWEEN AGROMETEOROLOGICAL PATTERN AND
PHENOLOGY IN BAROLO WINE AREA
F. Spanna (1) C. Lovisolo (2),
(1) Regione Piemonte - Settore Fitosanitario regionale, (2) Dipartimento di Colture Arboree, Università di
Torino
ufficio.agrometeo@regione.piemonte.it
The research was addressed to characterize the phenological behaviour of Nebbiolo grapevine in a wine
area located in northern-western Italy (Cuneo Province, Piedmont). The wine produced is named Barolo, as
the zone of provenience, and is one of the most appreciated wines of Piedmont in the world.
A project of characterization of grapevine and wine productions in the Barolo area was carried out during
the period 1994-1996; during these three years field studies on the aspects of climate, phenology and quality
and quantity of the production were assessed. Afterwards, all these aspects were correlated to understand
the vine behaviour and to identify, eventually, some sub-areas or significant differences among the wines.
From 1994 to 1996, climatic data were measured using meteorological stations installed in experimental
vineyards and, in the meantime phenological data were determined following Baggiolini stages. On
September and October the must analysis (pH, total acidity, sugar content) and the productive parameters
(number and weight of clusters per vine) were carried out.
To correlate climatic and phenological and productive data some bio-climatic indexes were used with
different base temperatures and using different starting dates.
A set of bio-climatic indexes to characterize vegetative vine growth and productive performances in Barolo
area is proposed.
81

WINTER CLIMATE AND FLOWER BUD MORTALITY OF SOUR CHERRY
(PRUNUS CERASUS)
T.B. Toldam-Andersen, I. Dencker, P. Braun
Royal Veterinary and Agricultural University, Dept. of Agric. Sci., Agrovej 10, 2630 Taastrup, Denmark,
id@kvl.dk
Sour cherry for industrial use is an important tree fruit crop in Denmark, and clonal selections of the old
Danish sour cherry cultivar called ‘Stevnsbær’ strongly dominate the commercial orchards. During the last
decade a reduced fruit-set ability and low total yields have been observed for this cultivar. The reasons for
the yield decline are not known, but the negative effects of fluctuating winter temperatures on flower bud
survival are suspected to have a major role. Bud dissections were set out in the early 1990s to investigate the
floral mortality rates, the development of flower necrosis and their relations with frost periods during endoand
ecodormancy. In this study data are reported from the winters 1994-95 and 1999-2000. Buds were
collected from five years old ‘Stevnsbær’ populations and from three year old potted trees. The potted trees
were wintered at either +4 o C or in the field on the same location as the old populations. Buds were dissected
under a stereo-microscope and the necrosis of different flower parts were recorded. Both of the winters
1994-95 and 1999-2000 had high average temperatures and brief freezing periods. The lowest recorded
minimum temperature was –12,1 °C (hourly means). Still, major bud damages occurred. In February-March
1995, flower mortality was close to only 10 per cent, but after a 4,7 freeze in late March, more than six
weeks before anthesis, stigma damages increased the mortality percentage to 40. In 1999, a cold night with a
minimum temperature of –9,0 °C was recorded in the middle of December. On January 10, a flower bud
mortality of 44 per cent had developed in the 5-year-old trees. In the potted trees, the flower mortality was
86 per cent in a sample from January 20, whereas potted trees wintered at +4 only had 8 per cent damaged
flowers. It is concluded, that Prunus cerasus cv ‘Stevnsbær’ suffers severely from floral bud injuries during
mild winters. It is suggested that frost damage is the principal cause of the observed floral mortality, and
especially low temperatures occurring after warm winter periods may be critical.
82

DETECTION OF THE ARRIVAL DATE OF MIGRATING BIRDS IS DENSITY-
DEPENDENT: A CASE STUDY OF THE RED-BACKED SHRIKE LANIUS
COLLURIO
P. Tryjanowski
Department of Avian Biology & Ecology, Poznañ, Poland
ptasiek@main.amu.edu.pl/Fax: +48-61-8523615
The timing of when birds return to their breeding area is a key factor in studies of the impact of climate
change upon bird populations. However, many current analyses do not consider the problems associated
with density-dependent processes. These should impact on the detection of bird arrival time through (1)
higher probability of observing earlier arrival when population size is bigger, (2) increased song activity of
birds relative to population size and hence earlier observation.
As a case study, I have analysed data from 1983-2000 of the Red-backed Shrike collected in Western
Poland. During this period the Red-backed Shrike’s return to breeding sites was significantly earlier (r=-
0.614, p=0.007), and contemporary population size increased significantly (r=0.750, p=0.001). I obtained a
significant negative correlation between arrival date and population size (r=-0.723, p=0.001). To give greater
confidence in the validity of this correlation, I also worked on standardised residuals of arrival time and
population size on years, after eliminating a linear trend. Correlation between residuals was still significantly
negative (r=-0.503, p=0.033), further supporting the link between arrival detection and population size.
This finding suggests that, in studies of avian migration and its changes over time, the relationship between
arrival date and population size should be considered in analyses.
This study was financially supported by UAM grant no. 517 00 001.
RECENT CHANGES IN NEST TIMING OF THE RED-BACKED SHRIKE
LANIUS COLLURIO IN POLAND
P. Tryjanowski (1), S. Kuzniak (1), T.H. Sparks (2)
(1) Department of Avian Biology & Ecology, Adam Mickiewicz University, Poznañ, Poland, (2) Centre
for Ecology and Hydrology, Monks Wood, UK
ptasiek@main.amu.edu.pl/Fax: +48-61-8523615
Over a 29 year observation period (1971-1999) the timing and performance of 289 nests of the red-backed
shrike Lanius collurio was recorded in western Poland. Nest timing was recorded in 5 day periods (pentads),
and the number of eggs, egg dimensions, number of hatchlings and number of fledglings were recorded.
Separating the effects of trends through time and changes in number of nests (recording intensity) in each
year are difficult to achieve but some trends and patterns are apparent. During this period there was a
tendency for earlier nesting and this pattern was associated with larger clutches with smaller eggs and lower
fledgling success.
The implications of earlier nesting as a consequence of climate warming on the population of this declining
species are discussed.
This study was financially supported by UAM grant no. 517 00 001.
EUROPEAN PHENOLOGY NETWORK – A NETWORK FOR INCREASING
EFFICIENCY, ADDED VALUE AND USE OF PHENOLOGICAL MONITORING
RESEARCH, AND DATA IN EUROPE
A. J.H. van Vliet, R. S. de Groot
Environmental Systems Analysis Group, Wageningen University, The Netherlands
83

arnold.vanvliet@algemeen.cmkw.wau.nl / Tel: +31 317 485091
(see page 29)
PHENOLOGICAL MODIFICATION IN PLANTS BY SOIL FACTORS
F.E. Wielgolaski
Department of Biology, Division of Botany and Plant Physiology, University of Oslo, Norway
f.e.wielgolaski@bio.uio.no /Fax: +47-22854664
Various mechanical and physical soil analyses are carried out in addition to weather observations through
three years at severals sites along an oceanic-continental gradient in a fjord district in western Norway. All
the environmental factors observed are correlated with earlier and a few late season phenophases of many
native and cultivated woody plants and some herbs by simple, linear correlations and by stepwise multiple
and partial analyses. It is tried to eliminate many intercorrelations between various environmental factors by
different techniques.
As expected air temperature measurements in nearly all analyses from these temperate region districts gave
the most significant correlations with phenology of the plants; the temperature during night generally being
the most important in mainly vegetative periods, e.g. to budbreak in spring, and the temperature during day
in more generative phases, as e.g. the period between budbreak and flowering. The other environmental
factors, however, showed strong variation in correlation significance with the various species studied and
also with different phenophases of the same species. Various hypotheses are put forward as reasons for such
variation. Air humidity (including precipitation) and /or soil moisture (including parameters intercorrelated
with it, e.g. soil grain size and bulk density) seemed to be factors relatively often found to be of importance.
In the stepwise multiple analyses for budbreak of birch (Betula pubescens, for instance the amount of
precipitation was the second factor to enter the analyses by a positive correlation with the developmental
rate, after the most important factor, the night temperature. Positive correlations with a high clay content and
bulk density in the soil indicated that also a high soil moisture is favourable for early bud break in birch.
Other phenophases that seemed to be favoured by a good water supply were leaf budbreak of bird cherry
(Prunus padus) and rowan (Sorbus aucuparia), and flowering of hazel (Corylus avellana), common lilac
(Syringa vulgaris), plum (’Victoria’) and currant (’Red Dutch’), to some degree also of goat willow (Salix
caprea). Chemical soil analyses (both P, K. Mg and Ca) often showed negative correlations with the
developmental rate, particularly of earlier phenophases of both native and cultivated plants (except for apple
’Gravenstein’ and pear ’Moltke’), may be indicating that a high nutrient level delayed the plant
development. Similar explanation might be given for the observation that high pH in the soil often seemed to
delay the plant development (leaf budbreak of Betula, Sorbus, Syringa and plum, and flowering of Corylus,
bluebell (Campanula rotundifolia) and red currant). There seemed to be a tendency that plants being
particularly dependent of warm weather for leaf budbreak, e.g. ash (Fraxinus excelsior, and flowering, e.g.
Prunus, pear, apple and to some degree also raspberry (’Preussen’), according to the analyses, were less
dependent of other environmental factors for their development. For instance, if there were any effects of
water for these plants, they were negative for moisture and soil factors intercorrelated with water.
84

LIST OF PARTICIPANTS
Anto Aasa
University of Tartu
Institute of Geography,
Vanemuise st. 46, Tartu, Estonia, 51014
antoa@ut.ee
Rein Ahas
University of Tartu
Institute of Geography
Vanemuise st. 46, Tartu, Estonia, 51014
reina@ut.ee
Valery Barcan
Lapland Biosphere Reserve
Zeleny, 8, 184505 Monchegorsk,
Murmansk province, Russia
lapland@monch.mels.ru
Elisabeth G. Beaubien
University of Alberta,
Devonian Botanic Garden, Edmonton,
Alberta, Canada, T6J 1Z1
e.beaubien@ualberta.ca
Egbert Beuker
Finnish Forest Research Institute
Punkaharju Research Station
Finlandiantie 18, FIN-58450 Punkaharju,
Finland
egbert.beuker@metla.fi
Alberte Bondeau
Potsdam-Institut für
Klimafolgenforschung
Postfach 60 12 03, 14412 Potsdam,
Germany
alberte.bondeau@pik-potsdam.de
Lucio Botarelli
S.M.R. - ARPA
Emilia Romagna Viale Silvani 6, 40122
Bologna, Italy
L.Botarelli@smr.arpa.emr.it
Olga Braslavska
Slovak Hydrometeorological Institute
Zelena 5, 97590 Banska Bystrica, Slovak
Repubic
olga@hmubbsco.shmu.sk
Peter Braun
Royal Veterinary and Agricultural
University
Dept. of Agric. Sci., Sect. Horticulture,
Agrovej 10, DK-2630 Taastrup, Denmark
PBR@KVL.DK
Robert Brügger
University of Bern
Department of Geography
Hallerstrasse 12, 3012 Bern, Switzerland
bruegger@giub.unibe.ch
Ekko Bruns
Deutscher Wetterdienst
Kaiserleistrasse 42, 63067 Offenbach,
Germany
ekko.bruns@dwd.de
N. Bulygin
Forestry Academy of St Petersburg
PO Box 64, St Petersburg, Russia 194295
Xiaoqiu Chen
Peking University
Dept. of Urban and Environmental
Science Dept. of Urban and
Environmental Science
Beijing 100871, P.R. China
cxq@urban.pku.edu.cn
Frank-M. Chmielewski
Humboldt-University Berlin
Institute of Crop Sciences, Section of
Agricultural Meteorology
Albrecht-Thaer-Weg 5, 14195 Berlin,
Germany
chmielew@agrar.hu-berlin.de
87

Isabelle Chuine
Université Montpellier 2
ISEM
case 61, place E. Bataillon, 34095
Montpellier cedex 5, France
chuine@isem.univ-montp2.fr
Zalika Crepinsek
University of Ljubljana
Biotechnical Faculty, Agronomy
Department
Jamnikarjeva 101, 1000 Ljubljana,
Slovenia
zalika.crepinsek@bf.uni-lj.si
Claudio Defila
MeteoSchweiz
Krähbühlstr. 58, 8044 Zürich, Switzerland
claudio.defila@meteoschweiz.ch
Noranne Ellis
Scottish Natural Heritage
Anderson Place, Edinburgh, EH6 5NP,
UK
noranne.ellis@snh.gov.uk
Melissa J. Else
IACR Rothamsted
Entomology Dept.
West Common, Harpenden, Herts AL5
2JQ, UK
melissa.else@bbsrc.ac.uk
Nicole Estrella
TU Munich
Department of Ecology
Am Hochanger 13, D-85 354 Freising,
Germany
estrella@met.forst.tu-muenchen.de
Peter Fabian
TU Munich
Department of Ecology
Am Hochanger 13, D-85 354 Freising,
Germany
fabian@met.forst.tu-muenchen.de
88
Ana Maria Faggi
Centro de Estudios Farmacologicos y
Bonaticos
Serrano 669, 1414 Buenos Aires,
Argentinia
amfaggi@mpero.cyt.edu.ar OR
afaggi@uflo.edu.ar
Violeta G Fedotova
Russian Academy of Sciences
Phenological Commission
Botanical Institue, , Russian Geographical
Society,
Preul. Grivtsova 10, 190 000 St.
Petersburg, Russia
Alex Gilyazov
Lapland Biosphere Reserve
Zeleny, 8 , 184505 Monchegorsk,
Murmansk province, Russia
lapland@monch.mels.ru
Anders Kay Gormsen
The Royal Veterinary and Agricultural
University
Department of Agricultural Sciences,
Sect. Horticulture,
Agrovej 10, DK-2630 Taastrup, Denmark
akg@kvl.dk
Risto Häkkinen
Finnish Forest Research Institute
Unioninkatu 40 A, FIN-00170 Helsinki,
Finland
risto.hakkinen@metla.fi
Michaela-Maria Hirschberg
TU Munich
Department of Ecology
Am Hochanger 13, D-85 354 Freising,
Germany
hirschberg@met.forst.tu-muenchen.de
David W. Inouye
University of Maryland
Department of Biology
College Park, MD 20742 USA
di5@umail.umd.edu

François Jeanneret
University of Bern
Department of Geography
Hallerstrasse 12, 3012 Bern, Switzerland
jeanneret@sis.unibe.ch
Amélie CR Kirchgäßner
University of Freiburg
Meteorological Institute
Werderring 10, 79085 Freiburg, Germany
kirchgam@uni-freiburg.de
Dag Klaveness
University of Oslo
Department of Biology
P. P. Box 1066 Blindern, 0316 Oslo,
Norway
dag.klaveness@bio.uio.no
Elisabeth Koch
Zentralanstalt für Meteorologie und
Geodynamik
Hohe Warte 38, 1190 Wien, Austria
e.koch@zamg.ac.at
Koen Kramer
Alterra Institute
Department of Ecology and Environment
P.O.Box 23, NL-6700 AA Wageningen,
The Netherlands
k.kramer@alterra.wag-ur.nl
Esa L Lehikoinen
University of Turku
Department of Biology
FIN 20014 Turku, Finland
esalehi@utu.fi
Tapio Linkosalo
University of Helsinki
Department of Forest Ecology
P.O. Box 24, FIN-00014 Helsinki, Finland
tapio.linkosalo@helsinki.fi
Wolfgang J. Lipa
Zentralanstalt für Meteorologie und
Geodynamik
Hohe Warte 38, 1190 Wien, Austria
lipa@zamg.ac.at
Jesse A. Logan
USDA Forest Service
Logan Forestry Sciences Laboratory
860 N 1200 East, Logan, UT 84321, USA
jlogan@cc.usu.edu
Wolfgang Lucht
Potsdam-Institut für
Klimafolgenforschung
Postfach 60 12 03, D-14412 Potsdam,
Germany
Wolfgang.Lucht@pik-potsdam.de
Annette Menzel
TU Munich
Department of Ecology
Am Hochanger 13, D-85 354 Freising,
Germany
menzel@met.forst.tu-muenchen.de
Patricia Morellato
Universidade Estadual Paulista - UNESP
Departamento de Botanica
C. P. 199, 13506-900 Rio Clara, SP,
Brazil
pmorella@rc.unesp.br
Markus Müller
University of Bonn
Institut für Obstbau und Gemüsebau
Auf dem Hügel 6, 53121 Bonn, Germany
GefaG@t-online.de
Gerhard Müller-Westermeier
Deutscher Wetterdienst
Abteilung Klima und Umwelt
Kaiserleistrasse 44, 63067 Offenbach,
Germany
gerhard.mueller-westermeier@dwd.de
Jiri Nekovar
Czech Hdyrometeorological Institute
Na Sabatce 17, 14306 Prag 4, Czech
Republic
jiri.nekovar@chmi.cz
89

Vello Palm
University of Tartu
Institute of Geography
Vanemuise 46, Tartu 51014, Estonia
vellop@ut.ee
Teja Preuhsler
Bavarian State Institute of Forestry
Am Hochanger 11, 85354 Freising,
Germany
pre@lwf.uni-muenchen.de
Antonio Raschi
C.N.R.-I.A.T.A.
Piazzale dell Cascine 18, 50144 Firenze,
Italy
raschi@sunserver.iata.fi.cnr.it
Stephan Raspe
Bavarian State Institute of Forestry
Am Hochanger 11, 85354 Freising,
Germany
ras@lwf.uni-muenchen.de
Jacques Régnière
Canadian Forest Service
1055 rue du P.E.P.S, (P.O. Box 3800),
Sainte Foy, Quebec, Canada, G1V 4C7
jregniere@cfl.forestry.ca
Thomas Rötzer
Humboldt-University Berlin
Institute of Crop Sciences, Section of
Agricultural Meteorology
Albrecht-Thaer-Weg 5, 14195 Berlin,
Germany
thomas.roetzer@rz.hu-berlin.de
David B. Roy
Centre for Ecology and Hydrology CEH
Monks Wood, Abbots Ripton,
Huntingdon, Cambridgeshire PE28 2LS,
UK
dbr@ceh.ac.uk
90
Maret Saar
Estonian Agricultural University
Institute of Zoology and Botany
181 Riia St.,Tartu 51014, Estonia
maret@zbi.ee
Crystal Barker Schaaf
Dept of Geography / Center for Remote
Sensing
Boston University, 675 Commonwealth
Avenue, Boston, MA 02215 USA
Jörg Schaber
PIK Potsdam
Institute of Climate Impact Research
PO Box 601203, 14412 Potsdam,
Germany
schaber@pik-potsdam.de
Jörn P.W. Scharlemann
University of Cambridge
Conservation Biology Group, Department
of Zoology,
Dowming Street, Cambridge, CB2 3EJ,
UK
jpws2@cam.ac.uk
Helfried Scheifinger
Zentralanstalt für Meteorologie und
Geodynamik
Hohe Warte 38, 1190 Wien, Austria
Helfried.Scheifinger@zamg.ac.at
Mark D. Schwartz
University of Wisconsin-Milwaukee
Department of Geography
P.O. Box 413, Milwaukee, WI 53201-
0413
mds@uwm.edu
Ulrich Simon
TU Munich
Chair of Land Use Planning and Nature
Conservation
Am Hochanger 13, 85354 Freising,
Germany
Ulrich.Simon@lrz.tu-muenchen.de

Richard L. Snyder
University of California
Dept. Of Land, Air and Water Resources
Davis, CA 956161, USA
RLSNYDER@UCDAVIS.EDU
Frederico Spanna
Regione Piemonte - Settore Fitosanitario
Regionale
Corso Grosseto, 71/6, 10100 Torino, Italy
ufficio.agrometeo@regione.piemonte.it
Donatella Spano
University of Basilicata
Dip. Di Produzione Vegetale
Via n. Sauro,75, Potenza 85100, Italy
spano@unibas.it
Tim H. Sparks
Centre for Ecology and Hydrology CEH
Monks Wood, Abbots Ripton,
Huntingdon, Cambridgeshire PE28 2LS,
UK
ths@ceh.ac.uk
Andreja Sušnik
Hydrometeorological Institute of Slovenia
Vojkova 1b, 1001 Ljubljana, Slovenia
andreja.susnik@rzs-hm.si
Piotr Tryjanowski
Adam Mickiewicz University
Department of Avian Biology
Fredry 10 PL 61 - 701 Poznan, Poland
ptasiek@main.amu.edu.pl
Compton J Tucker
NASA / Goddard Space Flight Center
Biospheric Sciences Branch, Code 923,
Laboratory for Terrestrial Physics
Greenbelt Maryland, 20 771USA
compton@kratmos.gsfc.nasa.gov
Nadia Valentini
Arboree-Universita di Torino
Dipartimento di Colture
Via Leonardo da Vinci, 44; 10095
Grugliasco (Torino), Italy
valentin@agraria.unito.it
Jarvoslav Valter
Czech Hdyrometeorological Institute
Na Sabatce 17, 14306 Prag 4, Czech
Republic
valter@chmi.cz
Arnold JH Van Vliet
Wageningen University
P.O. Box 9101, 6700 HB Wageningen,
The Netherlands
arnold.vanvliet@algemeen.cmkw.wau.nl
Frans-Emil Wielgolaski
Univerity of Oslo
Department of Biology
POB 1045 Blindern, N-0316 Oslo,
Norway
f.e.wielgolaski@bio.uio.no
Mike A White
University of Montana
NTSG, School of Forestry
Missoula, MT 59812, USA
mike@ntsg.umt.edu
Petrit Zorba
Academy of Science
Hydrometeorological Institute
Rr.Durresit, K.P.219,Tirana - Albania
aspetalb@yahoo.com
91