Basis function models for animal movement

Journal of the American Statistical Association
By:  and 

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Abstract

Advances in satellite-based data collection techniques have served as a catalyst for new statistical methodology to analyze these data. In wildlife ecological studies, satellite-based data and methodology have provided a wealth of information about animal space use and the investigation of individual-based animal–environment relationships. With the technology for data collection improving dramatically over time, we are left with massive archives of historical animal telemetry data of varying quality. While many contemporary statistical approaches for inferring movement behavior are specified in discrete time, we develop a flexible continuous-time stochastic integral equation framework that is amenable to reduced-rank second-order covariance parameterizations. We demonstrate how the associated first-order basis functions can be constructed to mimic behavioral characteristics in realistic trajectory processes using telemetry data from mule deer and mountain lion individuals in western North America. Our approach is parallelizable and provides inference for heterogenous trajectories using nonstationary spatial modeling techniques that are feasible for large telemetry datasets. Supplementary materials for this article are available online.

Additional publication details

Publication type Article
Publication Subtype Journal Article
Title Basis function models for animal movement
Series title Journal of the American Statistical Association
DOI 10.1080/01621459.2016.1246250
Volume 112
Issue 518
Year Published 2017
Language English
Publisher Taylor & Francis
Contributing office(s) Coop Res Unit Seattle
Description 12 p.
First page 578
Last page 589