Can we detect a nonlinear response to temperature in European plant phenology?
Over a large temperature range, the statistical association between spring phenology and temperature is often regarded and treated as a linear function. There are suggestions that a sigmoidal relationship with definite upper and lower limits to leaf unfolding and flowering onset dates might be more realistic. We utilised European plant phenological records provided by the European phenology database PEP725 and gridded monthly mean temperature data for 1951–2012 calculated from the ENSEMBLES data set E-OBS (version 7.0). We analysed 568,456 observations of ten spring flowering or leafing phenophases derived from 3657 stations in 22 European countries in order to detect possible nonlinear responses to temperature. Linear response rates averaged for all stations ranged between −7.7 (flowering of hazel) and −2.7 days °C−1 (leaf unfolding of beech and oak). A lower sensitivity at the cooler end of the temperature range was detected for most phenophases. However, a similar lower sensitivity at the warmer end was not that evident. For only ∼14 % of the station time series (where a comparison between linear and nonlinear model was possible), nonlinear models described the relationship significantly better than linear models. Although in most cases simple linear models might be still sufficient to predict future changes, this linear relationship between phenology and temperature might not be appropriate when incorporating phenological data of very cold (and possibly very warm) environments. For these cases, extrapolations on the basis of linear models would introduce uncertainty in expected ecosystem changes.
KeywordsClimate change Europe Nonlinearity PEP725 Phenology Sigmoid Temperature response
- de Réaumur RAF (1735) Observations du thermomètre, faites à Paris pendant l’annee 1735, comparées avec celles qui ont été faites sous la ligne, á l’isle de France, á Alger et quelques unes des nos isles de l’Amérique. Mem Acad des Sci, Paris: 545Google Scholar
- European Environment Agency (EEA) (2010) CORINE Land Cover (CLC) 2006 raster data 100 × 100 m—version 13 (02/2010). Available at http://www.eea.europa.eu/data-and-maps/data/corineland-cover-2006-raster
- Holm S (1979) A simple sequentially rejective multiple test procedure. Scand J Stat 6:65–70Google Scholar
- IPCC (2013) Summary for policymakers. In: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Eds. Stocker TF, Qin D, Plattner G-K, Tignor M, Allen SK, Boschung J, Nauels A, Xia Y, Bex V, Midgley PM, Cambridge University PressGoogle Scholar
- Körner C (2004) Mountain biodiversity, its causes and functions. Ambio Special Report 13:11–17Google Scholar
- Landsberg HE (1981) The urban climate. Academic PressGoogle Scholar
- Meier U (Ed.) (2001) Entwicklungsstadien mono- und dikotyler Pflanzen. BBCH-Monograph. Biologische Bundesanstalt für Land und ForstwirtschaftGoogle Scholar
- Schwartz MD (1997) Spring index models: an approach to connecting satellite and surface phenology. In: Phenology of Seasonal Climates. Eds. Lieth H, Schwartz MD. Backhuys: 23–38Google Scholar
- Sparks TH, Menzel A, Peñuelas J, Tryjanowski P (2011) Species response to contemporary climate change. Millington AC, Blumler M, Schickhoff U (eds.), The SAGE handbook of biogeography. SAGE, pp. 231–242Google Scholar
- Walther G-R (2000) Climatic forcing on the dispersal of exotic species. Phytocoenologia 30(3–4):409–430Google Scholar
- Wolkovich EM, Cook BI, Allen JM, Crimmins TM, Betancourt JL, Travers SE, Pau S, Regetz J, et al. (2012) Warming experiments underpredict plant phenological responses to climate change. Nature 485:494–497Google Scholar
- Zhang XY, Tarpley D, Sullivan JT (2007) Diverse responses of vegetation phenology to a warming climate. Geophys Res Lett 34:1–5Google Scholar