In most European countries, phenological data are collected or have been collected in the past over several decades. Within these different phenological programmes, the vegetation cycle of plants is usually observed (native, agricultural plants and fruits). Phenological phases reflect among other things the environmental characteristics of the climate in the region where they occur. Consequently, long series of phenological observations may be used for the detection of climate variability or climate change.
With its well maintained phenological observation network MeteoSwiss was an important partner in this COST action. The main focus was laid on the examination of trends with robust statistical methods. While most of the already existing studies were confined to one phenological phase at various locations, the new approach used a multispecies dataset of fifteen different phenological phases covering the Alpine region from 1971 to 2004.
The goal is to determine the impact of climate parameters such as Growing Degree Days (GDD) and Number of Wet Days (NWD) on phenological observations. With Principal Component Analysis (PCA) it was shown that the first spatial pattern for phenology is quite homogeneous and the corresponding averaged beginning of phenology has advanced by 1.8 days per decade. Regionally important, the second phenology and GDD patterns are clearly dominated by altitudinal gradients, meaning that plants in higher elevations tend to a later phenology with effectively less GDD than plants in the lowlands. GDD are found to be the main factor for this overall observed change in phenology. Compared to Switzerland, analogous climate change signals are found for the entire Alpine region.
COST 725 was merged into the Pan-European Phenology data base PEP725, a project funded by ZAMG (Zentralanstalt für Meteorologie und Geodynamik), the Austrian ministry for science & research and EUMETNET (the network of European meteorological services). The goal is to establish an open access database with plant phenology data sets for science, research and education.
Studer, S, Appenzeller, C and Defila,C (2005): Inter-annual variability and decadal trends in alpine spring phenology: a multivariate analysis approach. Climatic Change, 73, 395-414.
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