Proceedings of the Ninth Mountain Lion Workshop - Carnivore ...
Proceedings of the Ninth Mountain Lion Workshop - Carnivore ...
Proceedings of the Ninth Mountain Lion Workshop - Carnivore ...
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Refining <strong>the</strong> Use <strong>of</strong> GPS Telemetry Cluster Techniques to Estimate<br />
Cougar (Puma concolor) Kill Rate and Prey Composition<br />
Kyle H. Knopff, Department <strong>of</strong> Biological Sciences, University <strong>of</strong> Alberta, Edmonton,<br />
AB T6G 2E9, Canada kknopff@ualberta.ca<br />
Aliah Adams Knopff, Department <strong>of</strong> Biological Sciences, University <strong>of</strong> Alberta,<br />
Edmonton, AB T6G 2E9, Canada, aliah_ak@hotmail.com<br />
Mark S. Boyce, Department <strong>of</strong> Biological Sciences, University <strong>of</strong> Alberta, Edmonton,<br />
AB T6G 2E9, Canada<br />
ABSTRACT Recent advances in global positioning system (GPS) radio-telemetry<br />
technology have created promising new opportunities for increasing sample size and<br />
reducing field efforts when estimating parameters <strong>of</strong> predation for large carnivores.<br />
Clusters <strong>of</strong> relocations in close proximity obtained from GPS radiocollars deployed on<br />
cougar (Puma concolor) can be used to identify potential kill sites. The number <strong>of</strong> prey<br />
found by visiting all clusters in a monitoring period can be used to estimate kill rate<br />
directly, or models can be employed to indirectly estimate kill rate by identifying kill<br />
clusters from GPS data. Extending kill rate models to allow indirect estimation <strong>of</strong> prey<br />
composition in a multi-prey setting has been suggested, but not attempted. We used data<br />
from 1,735 visits to GPS telemetry clusters and 637 prey >10kg found at clusters in westcentral<br />
Alberta to fur<strong>the</strong>r explore and refine indirect and direct GPS telemetry cluster<br />
techniques for cougar. We developed logistic regression models to identify kill sites<br />
(prey >10kg) from GPS data and multinomial regression models to identify <strong>the</strong> prey<br />
species at a kill cluster. The predictive capacity <strong>of</strong> each model was assessed using k-fold<br />
cross validation. The top logistic regression model had good classification success<br />
(86%), and 5-fold cross-validation at this cut<strong>of</strong>f revealed that it was capable <strong>of</strong> estimating<br />
cougar kill rate to within an average <strong>of</strong> +8.67% (SD = 5.56) <strong>of</strong> true values. The top<br />
multinomial model also had reasonable classification success (75%), but it over-predicted<br />
<strong>the</strong> occurrence <strong>of</strong> primary prey (deer) in <strong>the</strong> diet and under-predicted <strong>the</strong> consumption <strong>of</strong><br />
alternate prey (e.g., elk and moose) by as much as 100%. Simulated visits to all clusters<br />
in our dataset with a model-estimated kill probability <strong>of</strong> 0.15 or higher revealed that we<br />
could reduce <strong>the</strong> number <strong>of</strong> clusters visited by as much as 50%, while still retaining<br />
91.6% <strong>of</strong> all kill clusters. Although indirect GPS telemetry cluster techniques can be<br />
usefully applied for overall kill rate estimation, <strong>the</strong>y poorly estimate diet composition.<br />
Therefore, we recommend using model-directed field visitation to estimate kill rate and<br />
prey composition for cougar in multi-prey systems.<br />
<strong>Proceedings</strong> <strong>of</strong> <strong>the</strong> <strong>Ninth</strong> <strong>Mountain</strong> <strong>Lion</strong> <strong>Workshop</strong><br />
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