Mitigating pseudoreplication and bias in resource selection functions with autocorrelation‐informed weighting

• Published in: Methods in ecology and evolution Vol. 14; no. 2; pp. 643 - 654
• Main Authors: Alston, Jesse M., Fleming, Christen H., Kays, Roland, Streicher, Jarryd P., Downs, Colleen T., Ramesh, Tharmalingam, Reineking, Björn, Calabrese, Justin M.
• Format: Journal Article
• Language: English
• Published: London John Wiley & Sons, Inc 01.02.2023; Wiley
• Subjects: Animals; Autocorrelation; Bias; Confidence intervals; continuous‐time movement models; Ecology; Environmental Sciences; Estimates; Global positioning systems; GPS; habitat selection; home range; Mathematical analysis; Missing data; Movement; Ornstein–Uhlenbeck process; Parameter estimation; space use; spatial point process; Statistical analysis; Statistics; stochastic process model; Tracking; utilization distribution; Weighting; Workflow; space use; spatial point process; habitat selection; utilization distribution; continuous-time movement models; Ornstein-Uhlenbeck process; stochastic process model; home range

Resource selection functions (RSFs) are among the most commonly used statistical tools in both basic and applied animal ecology. They are typically parameterized using animal tracking data, and advances in animal tracking technology have led to increasing levels of autocorrelation between locations...