Effects of weather and climate on the dynamics of animal population time series
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Weather is one of the most basic factors impacting animal populations, but the typical strength of such impacts on population dynamics is unknown. We incorporate weather and climate index data into analysis of 492 time series of mammals, birds and insects from the global population dynamics database. A conundrum is that a multitude of weather data may a priori be considered potentially important and hence present a risk of statistical over-fitting. We find that model selection or averaging alone could spuriously indicate that weather provides strong improvements to short-term population prediction accuracy. However, a block randomization test reveals that most improvements result from over-fitting. Weather and climate variables do, in general, improve predictions, but improvements were barely detectable despite the large number of datasets considered. Climate indices such as North Atlantic Oscillation are not better predictors of population change than local weather variables. Insect time series are typically less predictable than bird or mammal time series, although all taxonomic classes display low predictability. Our results are in line with the view that population dynamics is often too complex to allow resolving mechanisms from time series, but we argue that time series analysis can still be useful for estimating net environmental effects.
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Climate variables are often highly correlated and can generate spurious results when used in regression.
“Climate variables are often highly correlated and can generate spurious results when used in regression (34, 134).”
From Climate-driven declines in arthropod abundance restructure a rainforest food web (2018) · cites this paper as [134]
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Climate-driven declines in arthropod abundance restructure a rainforest food web
Lister, B. C., & Garcia, A. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1722477115 · Cited by 730 · see citing works
Stapley, J., Garcia, M., & Andrews, R. M. (2015) · PLOS ONE · doi:10.1371/journal.pone.0115450 · Cited by 30 · see citing works
- Authors
- Knape, J., & de Valpine, P.
- Affiliations
- University of California, Berkeley (US)
- Department of Environmental Science, Policy and Management, University of California, 137 Mulford Hall 3114, Berkeley, CA 94720, USA
- ORCID
- Knape, Jonas
- Venue
- Proceedings of the Royal Society B: Biological Sciences
- Publisher
- The Royal Society
- Published
- 2010-09-29
- Volume
- 278
- Issue
- 1708
- Pages
- 985-992
- ISSN
- 0080-4649 (ISSN-L)
- 0962-8452
- 1471-2954
- PMC
- PMC3049023
- OpenAlex
- W2166500635
- Cited by
- 107
- References
- 42
- Citations by year
- 2026: 4 · 2025: 8 · 2024: 3 · 2023: 4 · 2022: 7 · 2021: 5 · 2020: 8 · 2019: 6 · 2018: 12 · 2017: 9 · 2016: 2 · 2015: 7 · 2014: 10 · 2013: 8 · 2012: 8
- FWCI
- 6.34
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Proceedings of the Royal Society B Biological Sciences (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Environmental Science › Ecology › Animal Ecology and Behavior Studies
- Physical Sciences › Environmental Science › Ecology › Avian ecology and behavior
- Physical Sciences › Environmental Science › Ecological Modeling › Species Distribution and Climate Change
- Keywords
- climate indices, population dynamics, overfitting, model selection, North Atlantic Oscillation, insects, birds, mammals
- MeSH terms
- Animals, Birds, Climate, Data Interpretation, Statistical, Insecta, Mammals, Models, Theoretical, Population Dynamics, Weather, Databases, Factual
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