Abstract
Weather has often been associated with fluctuations in population sizes of species; however, it can be difficult to estimate the effects satisfactorily because population size is naturally measured by annual abundance indices whilst weather varies on much shorter timescales. We describe a novel method for estimating the effects of a temporal sequence of a weather variable (such as mean temperatures from successive months) on annual species abundance indices. The model we use has a separate regression coefficient for each covariate in the temporal sequence, and over-fitting is avoided by constraining the regression coefficients to lie on a curve defined by a small number of parameters. The constrained curve is the product of a periodic function, reflecting assumptions that associations with weather will vary smoothly throughout the year and tend to be repetitive across years, and an exponentially decaying term, reflecting an assumption that the weather from the most recent year will tend to have the greatest effect on the current population and that the effect of weather in previous years tends to diminish as the time lag increases. We have used this approach to model 501 species abundance indices from Great Britain and present detailed results for two contrasting species alongside an overall impression of the results across all species. We believe this approach provides an important advance to the challenge of robustly modelling relationships between weather and species population size.
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Acknowledgements
This work was undertaken for a project funded jointly by Defra, Natural Resources Wales (NRW), Natural England (NE), Scottish Natural Heritage (SNH) and the Joint Nature Conservation Committee (JNCC). Subsequent methodological development was funded by the Scottish Government Rural and Environment Science and Analytical Services Division. We thank members of the project Steering Group, colleagues (particularly Nick Isaac, CEH) two external reviewers and the Associate Editor for constructive comments. We are grateful to all volunteers and organisations contributing to the data sets used in this work, namely: the National Bat Monitoring Programme (Bat Conservation Trust, in partnership with JNCC and supported and steered by NE, NRW, Northern Ireland Environment Agency and SNH); the former CBC and current BBS (a partnership between the BTO, JNCC (on behalf of NRW, NE, Council for Nature Conservation and Countryside and SNH) and Royal Society for Protection of Birds); and the UK Butterfly Monitoring Scheme operated by CEH, Butterfly Conservation and funded by a consortium of government agencies.
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Elston, D.A., Brewer, M.J., Martay, B. et al. A New Approach to Modelling the Relationship Between Annual Population Abundance Indices and Weather Data. JABES 22, 427–445 (2017). https://doi.org/10.1007/s13253-017-0287-4
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DOI: https://doi.org/10.1007/s13253-017-0287-4