Uncovering periodic patterns of space use in animal tracking data with periodograms, including a new algorithm for the Lomb-Scargle periodogram and improved randomization tests.

摘要: Periodicity in activity level (rest/activity cycles) is ubiquitous nature, but whether and how these periodicities translate into periodic patterns of space use by animals much less documented. Here we introduce an analytical protocol based on the Lomb-Scargle periodogram (LSP) to facilitate exploration animal tracking datasets for patterns. The LSP accommodates missing observations variation sampling intervals location time series. We describe a new, fast algorithm compute LSP. gain speed compared other R implementations makes it tractable analyze long (>106 records). also give detailed primer periodicity analysis, focusing specificities movement data. In particular, warn against risk flawed inference when schedule creates artefactual new statistical test that temporally autocorrelated background noise. Applying our LSP-based data from three species revealed ungulate exhibited its not locations, central place-foraging seabird tracked moon phase, movements range-resident canid included daily patrolling component was initially masked stochasticity movements. tailored analysis now available R-package ctmm convenient exploratory tool detect