Analysis and Interpretation of Long-Term Studies Investigating Responses to Climate Change
Section snippets
Summary
Effects of recent climate change in mean phenotypic values of different traits in wild bird populations are already apparent, but we are still largely ignorant about the mechanism underlying these changes. Likewise, numerous methodological issues complicating the interpretation of the observed patterns have emerged, but few of these have been widely recognised. Here, we review some of these problems inherent to long-term studies of wild bird populations in the context of understanding climate
Choice of Phenological Variables
Many studies have investigated first arrival date, first breeding date or other measures of earliness in terms of phenology. A smaller number of studies have investigated means, medians or other measures of centrality of frequency distributions. The approach of using first dates has a number of potential problems. First, with only a single observation contributing to the estimate, sampling errors for first dates are considerably larger than for means or medians. Second, measures of first dates
Interpretational Considerations
Three different mechanisms may give rise to directional change in time in the mean phenotype of a population. These include (1) phenotypic plasticity, (2) micro-evolutionary change and (3) gene flow from genetically distinct populations (Hoffmann and Parsons, 1997). All these mechanisms, which are not mutually exclusive, may cause a shift in the mean phenotype of a population and serve as a means of coping with climate change (Hoffmann and Parsons, 1997). Consequently, our understanding of
Conclusions and Further Directions
In our treatment, we have focused on how the patterns seen in analyses of long-term time series can only be understood when pattern and process are considered simultaneously. Thus, in order to understand causes and consequences of climate change on bird populations, we need not only high quality long-term data sets but also rigorous analytical protocols and methods to account for possible biases in the data. Likewise, our understanding of the mechanisms underlying observed changes (or lack
Acknowledgements
P. Berthold, W. Fiedler and two reviewers kindly provided constructive comments on earlier version of this manuscript. J. M. has been supported by Academy of Finland.
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