Abstract
Bird populations are known to be affected by climate and habitat change. Here we assess on a continental scale the relationship of a bird population index for the Pied Flycatcher (Ficedula hypoleuca) with spatially explicit long-term climate data. For 1971-2001 and using multiple linear regression and AIC selection methods for candidate models we found that log-transformed 30 year long-term fall bird monitoring data from Rybachy Station (Russia), Baltic Sea, can be explained by 40% with monthly mean temperatures in the West African wintering grounds; the positive relationship suggest that increasing bird numbers are explained by increasing mean November temperatures. Precipitation, European fall, spring and breeding range temperatures did not show a strong relationship, nor with bird monitoring data from two other international stations (Pape and Kabli). Our findings help to improve hypotheses to be tested in the poorly known wintering grounds. However, due to various biases care has to be taken when interpreting international long-term bird monitoring data.
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Chernetsov, N., Huettmann, F. (2005). Linking Global Climate Grid Surfaces with Local Long-Term Migration Monitoring Data: Spatial Computations for the Pied Flycatcher to Assess Climate-Related Population Dynamics on a Continental Scale. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2005. ICCSA 2005. Lecture Notes in Computer Science, vol 3482. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11424857_15
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DOI: https://doi.org/10.1007/11424857_15
Publisher Name: Springer, Berlin, Heidelberg
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