A General Framework for the Analysis of Animal Resource Selection from Telemetry Data

Authors

Devin S. Johnson, National Marine Mammal Laboratory, Alaska Fisheries Science Center, National Marine Fisheries Service
Dana L. Thomas, University of Alaska Fairbanks, Fairbanks
Jay M. Ver Hoef, National Marine Mammal Laboratory, Alaska Fisheries Science Center, National Marine Fisheries Service
Aaron Christ, Alaska Department of Fish and Game

Date of this Version

9-2008

Comments

Published in Biometrics 64, 968–976.

Abstract

We propose a general framework for the analysis of animal telemetry data through the use of weighted distributions. It is shown that several interpretations of resource selection functions arise when constructed from the ratio of a use and availability distribution. Through the proposed general framework, several popular resource selection models are shown to be special cases of the general model by making assumptions about animal movement and behavior. The weighted distribution framework is shown to be easily extended to readily account for telemetry data that are highly auto-correlated; as is typical with use of new technology such as global positioning systems animal relocations. An analysis of simulated data using several models constructed within the proposed framework is also presented to illustrate the possible gains from the flexible modeling framework. The proposed model is applied to a brown bear data set from southeast Alaska.