European phenological response to climate change matches the warming pattern

Global Change Biology - Tập 12 Số 10 - Trang 1969-1976 - 2006
Annette Menzel1, Tim H. Sparks2, Nicole Estrella1, Elisabeth Koch3, Anto Aasa4, Rein Ahas4, KERSTIN ALM‐KÜBLER5, Peter Bissolli6, OL'GA BRASLAVSKÁ7, Agrita Briede8, Frank‐M. Chmielewski9, Zalika Črepinšek10, Yannick Curnel11, Åslög Dahl12, Claudio Defila13, Alison Donnelly14, YOLANDA FILELLA15, K. Jatczak16, F. Måge17, Antonio Mestre18, Øyvind Nordli19, Josep Peñuelas15, Pentti Pirinen20, Viera Remisová7, Helfried Scheifinger3, Martin Stříž21, Andreja Sušnik22, A.J.H. van Vliet23, FE Wielgolaski24, SUSANNE ZACH3, Ana Žust22
1Department of Ecology, Technical University Munich, 85350 Freising, Germany,
2NERC Centre for Ecology and Hydrology, Monks Wood, Cambridgeshire PE28 2LS, UK
3Central Institute for Meteorology and Geodynamics, 1190 Vienna, Austria
4University of Tartu, 51014 Tartu, Estonia,
5Swedish Museum of Natural History, 10405 Stockholm, Sweden
6German Meteorological Service, 63067 Offenbach, Germany,
7Slovak Hydrometeorological Institute, 83315 Bratislava 37, Slovak Republic,
8Faculty of Geography and Earth Sciences, University of Latvia, Riga LV-1586, Latvia,
9Faculty of Agriculture and Horticulture, Humboldt-University, Berlin, 14195 Berlin, Germany,
10Biotechnical Faculty, University of Ljubljana, Ljubljana, Slovenia
11Centre Wallon de Recherches Agronomiques, 5030 Gembloux, Belgium,
12Botaniska Analysgruppen i Göteborg, 40530 Göteborg, Sweden,
13MeteoSwiss, 8044 Zürich, Switzerland,
14Department of Botany, Trinity College, Dublin 2, Ireland
15Center for Ecological Research and Forestry Applications CEAB‐CSIC, Universitat Autònoma de Barcelona, 08193 Bellaterra, Catalonia, Spain,
16Institute of Meteorology and Water Management, 01‐673 Warszawa, Poland,
17Norwegian University of Life Sciences, 1432 Ås, Norway
18Instituto Nacional de Meteorología, 28040 Madrid, Spain,
19The Norwegian Meteorological Institute, 0313, Oslo, Norway
20Finnish Meteorological Institute, 00101, Helsinki, Finland
21Czech Hydrometeorological Institute, Ostrava 70800, Czech Republic,
22Environmental Agency of the Republic of Slovenia, Ljubljana, Slovenia
23Wageningen University, 6700 AA, Wageningen, the Netherlands
24University of Oslo, 0316 Oslo, Norway

Tóm tắt

Abstract

Global climate change impacts can already be tracked in many physical and biological systems; in particular, terrestrial ecosystems provide a consistent picture of observed changes. One of the preferred indicators is phenology, the science of natural recurring events, as their recorded dates provide a high‐temporal resolution of ongoing changes. Thus, numerous analyses have demonstrated an earlier onset of spring events for mid and higher latitudes and a lengthening of the growing season. However, published single‐site or single‐species studies are particularly open to suspicion of being biased towards predominantly reporting climate change‐induced impacts. No comprehensive study or meta‐analysis has so far examined the possible lack of evidence for changes or shifts at sites where no temperature change is observed. We used an enormous systematic phenological network data set of more than 125 000 observational series of 542 plant and 19 animal species in 21 European countries (1971–2000). Our results showed that 78% of all leafing, flowering and fruiting records advanced (30% significantly) and only 3% were significantly delayed, whereas the signal of leaf colouring/fall is ambiguous. We conclude that previously published results of phenological changes were not biased by reporting or publication predisposition: the average advance of spring/summer was 2.5 days decade−1 in Europe. Our analysis of 254 mean national time series undoubtedly demonstrates that species' phenology is responsive to temperature of the preceding months (mean advance of spring/summer by 2.5 days°C−1, delay of leaf colouring and fall by 1.0 day°C−1). The pattern of observed change in spring efficiently matches measured national warming across 19 European countries (correlation coefficient r=−0.69, P<0.001).

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