Representativeness of point-wise phenological Betula data collected in different parts of Europe

• Published in: Global ecology and biogeography 2008-07, Vol.17 (4), p.489-502
• Main Authors: Siljamo, Pilvi, Sofiev, Mikhail, Ranta, Hanna, Linkosalo, Tapio, Kubin, Eero, Ahas, Rein, Genikhovich, Eugene, Jatczak, Katarzyna, Jato, Victoria, Nekovář, Jiří, Minin, Alexander, Severova, Elena, Shalaboda, Valentina
• Format: Article
• Language: English
• Subjects: Betula; Biogeography; Climate change; Climate models; Europe; flowering; leaf unfolding; Meteorology; Microclimates; Pendulums; phenological observations; phenological stages; Phenology; Plants; Pollen; station representativeness; sub-grid variability
• ISSN: 1466-822X; 1466-8238; 1466-822X
• DOI: 10.1111/j.1466-8238.2008.00383.x

We examine issues of uncertainty regarding the spatial and temporal representativeness of phenological observations using a newly compiled Europe-wide data base of phenological observations for Betula species. Europe. A new data base was compiled from national phenological observations covering 15 European countries, with the longest observational periods exceeding several decades for some sites. From this, the spatial and temporal representativeness of phenological observations were evaluated via statistical analysis. The results showed that there was a significant and irreducible uncertainty related to the use of data of a single station, which varied from 3 to 8 days depending on the station location. In more continental and northern climatic zones the uncertainty was lower, probably due to faster spring-time weather developments. In mild climatic conditions, the uncertainty of dates of the phenological phases registered by a single station exceeded 1 week. The considerable number of data allowed us to preliminarily estimate the features of some stations, marking them as 'late', 'early', 'representative' or 'random', depending on the dates reported by these sites and the corresponding regional means. The uncertainties discovered in single-site phenological observations are significant for virtually any potential application. Possible approaches for handling the uncertainty problem are station pre-averaging and spatial regularization of the data set, pre-selection (down-sampling) or changing the description of the phenomena from deterministic to probabilistic.