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Accounting for location uncertainty in azimuthal telemetry data improves ecological inference

View ORCID ProfileBrian D. Gerber, Mevin B. Hooten, Christopher P. Peck, Mindy B. Rice, James H. Gammonley, Anthony D. Apa, Amy J. Davis
doi: https://doi.org/10.1101/281584
Brian D. Gerber
1Colorado Cooperative Fish and Wildlife Research Unit, Department of Fish, Wildlife, and Conservation Biology, Colorado State University, Fort Collins, CO 80523, USA
2Department of Natural Resources, University of Rhode Island, Kingston, RI 02881, USA.
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  • For correspondence: bgerber@uri.edu
Mevin B. Hooten
3U.S. Geological Survey, Colorado Cooperative Fish and Wildlife Research Unit, Departments of Fish, Wildlife, and Conservation Biology and Statistics, Colorado State University, Fort Collins, CO 80523-1484, USA.
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Christopher P. Peck
1Colorado Cooperative Fish and Wildlife Research Unit, Department of Fish, Wildlife, and Conservation Biology, Colorado State University, Fort Collins, CO 80523, USA
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Mindy B. Rice
4Colorado Division of Parks and Wildlife, 317 West Prospect, Fort Collins, CO 80526, USA.
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James H. Gammonley
4Colorado Division of Parks and Wildlife, 317 West Prospect, Fort Collins, CO 80526, USA.
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Anthony D. Apa
5Colorado Division of Parks and Wildlife, 711 Independent Avenue, Grand Junction, CO 81505, USA.
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Amy J. Davis
6National Wildlife Research Center, United States Department of Agriculture, 4101 La porte Avenue, Fort Collins, CO 80521, USA.
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Abstract

Characterizing animal space use is critical to understand ecological relationships. Despite many decades of using radio-telemetry to track animals and make spatial inference, there are few statistical options to handle these unique data and no synthetic framework for modeling animal location uncertainty and accounting for it in ecological models. We describe a novel azimuthal telemetry model (ATM) to account for azimuthal uncertainty with covariates and propagate location uncertainty into ecological models. We evaluate the ATM with commonly used estimators in several study design scenarios using simulation. We also provide illustra-tive empirical examples, demonstrating the impact of ignoring location uncertainty within home range and resource selection analyses. We found the ATM to have good performance and the only model that has appropriate measures of coverage. Ignoring animal location un-certainty when estimating resource selection or home ranges can have pernicious effects on ecological inference. We demonstrate that home range estimates can be overly confident and conservative when ignoring location uncertainty and resource selection coefficients can lead to incorrect inference and over confidence in the magnitude of selection. Our findings and model development have important implications for interpreting historical analyses using this type of data and the future design of radio-telemetry studies.

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Posted March 13, 2018.
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Accounting for location uncertainty in azimuthal telemetry data improves ecological inference
Brian D. Gerber, Mevin B. Hooten, Christopher P. Peck, Mindy B. Rice, James H. Gammonley, Anthony D. Apa, Amy J. Davis
bioRxiv 281584; doi: https://doi.org/10.1101/281584
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Accounting for location uncertainty in azimuthal telemetry data improves ecological inference
Brian D. Gerber, Mevin B. Hooten, Christopher P. Peck, Mindy B. Rice, James H. Gammonley, Anthony D. Apa, Amy J. Davis
bioRxiv 281584; doi: https://doi.org/10.1101/281584

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