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climwin is a freely available software package designed in the R statistical environment used for conducting climate window analyses. With the greater availability of high resolution climatic data there has been a growing interest in understanding how biological systems respond to climatic variation. However, the sensitivity of organisms to climatic perturbations will tend to vary across a year making it necessary to specify a smaller ‘window’ within a year over which climatic data is measured and summarised. Often, this choice of climate window has involved the demarcation of climate along seasonal lines (e.g. mean spring temperature), yet this regularly occurs with little a priori knowledge on a systems climatic sensitivity making such decisions somewhat arbitrary. Arbitrary selection of climate windows can compromise our ability to make meaningful conclusions from our analyses, as we cannot be sure if the response of a biological system to climate in the chosen window represents the strongest or most relevant impact of climate across a year. climwin provides an exploratory approach for climate window analysis that tests and compares all potential climate windows, thus removing the need for arbitrary climate window decisions. This wiki will provide a guide on how to conduct analysis with climwin, from most basic to more advanced features.
When using climwin please cite both the below papers:
van de Pol, M., Bailey, L.D., McLean, N., Rijsdijk, L., Lawson, C. R. & Brouwer, L. (2016), Identifying the best climatic predictors in ecology and evolution. Methods Ecol Evol, 7: 1246–1257. doi:10.1111/2041-210X.12590
and
Bailey L.D. & van de Pol M. (2016) climwin: An R Toolbox for Climate Window Analysis. PLOS ONE, 11: e0167980. doi: 10.1371/journal.pone.0167980
If you haven’t done so already, install climwin for R! The current stable version of climwin is available for download from CRAN. climwin is an ongoing project and will be constantly updated. For the newest version of the package you can download the current github version.
See our "Getting started" page for a detailed guide to downloading and installing the package.
Our paper in Methods in Ecology and Evolution outlines a step-by-step workflow for approaching climate window analyses with climwin. We strongly recommend that users adhere to this workflow to avoid confusion and potential misidentification of false positive climate signals.
If you’re having trouble downloading, running or interpreting climwin first try our FAQ page where we have compiled a list of the most common issues encountered by users. If you still encounter problems hop over to our forum and ask a question to the climwin community. climwin is an ongoing project with many working parts. If you come across a bug or error in your analyses please let us know on this forum page. Your feedback is invaluable to keep the project running.