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Testing the consistency of wildlife data types before combining them: the case of camera traps and telemetry

Authors

  • Viorel D. Popescu,

    Corresponding author
    1. Department of Environmental Science, Policy and Management, University of California Berkeley, Berkeley, California
    • Correspondence

      Viorel D. Popescu, Earth to Ocean Research Group, Simon Fraser University, 8888 University Drive, Burnaby, BC, Canada V5A 1S6. Tel: (604) 340 4228; Fax: (778) 782 3496;

      E-mail: vioreldpopescu@gmail.com

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  • Perry de Valpine,

    1. Department of Environmental Science, Policy and Management, University of California Berkeley, Berkeley, California
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  • Rick A. Sweitzer

    1. Department of Environmental Science, Policy and Management, University of California Berkeley, Berkeley, California
    Current affiliation:
    1. The Great Basin Institute, Reno, Nevada
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Abstract

Wildlife data gathered by different monitoring techniques are often combined to estimate animal density. However, methods to check whether different types of data provide consistent information (i.e., can information from one data type be used to predict responses in the other?) before combining them are lacking. We used generalized linear models and generalized linear mixed-effects models to relate camera trap probabilities for marked animals to independent space use from telemetry relocations using 2 years of data for fishers (Pekania pennanti) as a case study. We evaluated (1) camera trap efficacy by estimating how camera detection probabilities are related to nearby telemetry relocations and (2) whether home range utilization density estimated from telemetry data adequately predicts camera detection probabilities, which would indicate consistency of the two data types. The number of telemetry relocations within 250 and 500 m from camera traps predicted detection probability well. For the same number of relocations, females were more likely to be detected during the first year. During the second year, all fishers were more likely to be detected during the fall/winter season. Models predicting camera detection probability and photo counts solely from telemetry utilization density had the best or nearly best Akaike Information Criterion (AIC), suggesting that telemetry and camera traps provide consistent information on space use. Given the same utilization density, males were more likely to be photo-captured due to larger home ranges and higher movement rates. Although methods that combine data types (spatially explicit capture–recapture) make simple assumptions about home range shapes, it is reasonable to conclude that in our case, camera trap data do reflect space use in a manner consistent with telemetry data. However, differences between the 2 years of data suggest that camera efficacy is not fully consistent across ecological conditions and make the case for integrating other sources of space-use data.

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