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climwin: An R Toolbox for Climate Window Analysis

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  • Liam D Bailey
  • Martijn van de Pol

Abstract

When studying the impacts of climate change, there is a tendency to select climate data from a small set of arbitrary time periods or climate windows (e.g., spring temperature). However, these arbitrary windows may not encompass the strongest periods of climatic sensitivity and may lead to erroneous biological interpretations. Therefore, there is a need to consider a wider range of climate windows to better predict the impacts of future climate change. We introduce the R package climwin that provides a number of methods to test the effect of different climate windows on a chosen response variable and compare these windows to identify potential climate signals. climwin extracts the relevant data for each possible climate window and uses this data to fit a statistical model, the structure of which is chosen by the user. Models are then compared using an information criteria approach. This allows users to determine how well each window explains variation in the response variable and compare model support between windows. climwin also contains methods to detect type I and II errors, which are often a problem with this type of exploratory analysis. This article presents the statistical framework and technical details behind the climwin package and demonstrates the applicability of the method with a number of worked examples.

Suggested Citation

  • Liam D Bailey & Martijn van de Pol, 2016. "climwin: An R Toolbox for Climate Window Analysis," PLOS ONE, Public Library of Science, vol. 11(12), pages 1-27, December.
    • Handle: RePEc:plo:pone00:0167980
    DOI: 10.1371/journal.pone.0167980
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    References listed on IDEAS

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    1. Arild Husby & Marcel E Visser & Loeske E B Kruuk, 2011. "Speeding Up Microevolution: The Effects of Increasing Temperature on Selection and Genetic Variance in a Wild Bird Population," PLOS Biology, Public Library of Science, vol. 9(2), pages 1-9, February.
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    Cited by:

    1. Liam D. Bailey & Martijn Pol & Frank Adriaensen & Aneta Arct & Emilio Barba & Paul E. Bellamy & Suzanne Bonamour & Jean-Charles Bouvier & Malcolm D. Burgess & Anne Charmantier & Camillo Cusimano & Bla, 2022. "Bird populations most exposed to climate change are less sensitive to climatic variation," Nature Communications, Nature, vol. 13(1), pages 1-10, December.

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