The exploratory analysis of autocorrelation in animal-movement studies
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Studies of animal movements have been popularized for many large and shy species by the increasing use of radio telemetry methods (VHF and GPS technologies). Data are collected with high sampling frequency, and consist of successive observations of the position of an individual animal. The statistical analysis of such data poses several problems due to the lack of independence of successive observations. However, the statistical description of the temporal autocorrelation between successive steps is rarely performed by ecologists studying the patterns of animals movements. The aim of this paper is to warn ecologists against the consequences of failing to consider this aspect. We discuss the various issues related to analyzing autocorrelated data, and show how the exploratory analysis of autocorrelation can both reveal important biological insights and help to improve the accuracy of movement models. We suggest some tools that can be used to measure, test, and adjust for temporal autocorrelation. A short ecological illustration is presented.
KeywordsAutocorrelation function Independence test GPS Radio telemetry Permutation test
We are grateful to Jon Swenson and to the Scandinavian Brown Bear Research Project for kindly providing the data. Financial support has been provided by the ANR (project Mobilité ANR-05-BDIV-008) and the ONCFS. We would like to thank Jean-Michel Gaillard, Jodie Martin, and Dominique Allainé for their comments on earlier drafts of this paper.
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