A general framework for the analysis of animal resource selection from telemetry data.
Devin S Johnson, Dana L Thomas, Jay M Ver Hoef, Aaron Christ
Author Information
Devin S Johnson: National Marine Mammal Laboratory, Alaska Fisheries Science Center, National Marine Fisheries Service, Seattle, Washington 98115, U.S.A.
Dana L Thomas: Department of Mathematics and Statistics, University of Alaska Fairbanks, Fairbanks, Alaska 99709, U.S.A.
Jay M Ver Hoef: National Marine Mammal Laboratory, Alaska Fisheries Science Center, National Marine Fisheries Service, Seattle, Washington 98115, U.S.A.
Aaron Christ: Alaska Department of Fish and Game, Anchorage, Alaska 99518, U.S.A.
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 autocorrelated; 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.
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