The influence of the delay-period setting on camera-trap data storage, wildlife detections and occupancy models
Clara C. Lepard
A G , Remington J. Moll A , Jonathon D. Cepek B , Patrick D. Lorch C , Patricia M. Dennis D E , Terry Robison F and Robert A. Montgomery A
+ Author Affiliations
- Author Affiliations
A The Research on the Ecology of Carnivores and their Prey Laboratory, Department of Fisheries and Wildlife, Michigan State University, 480 Wilson Road, Room 13 Natural Resources Building, East Lansing, MI 48824, USA.
B Natural Resources, Cleveland Metroparks, 9485 Eastland Road, Strongsville, OH 44149, USA.
C Natural Resources, Cleveland Metroparks, 2277 West Ridgewood Drive, Parma, OH 44134, USA.
D Conservation and Science, Cleveland Metroparks Zoo, 3900 Wildlife Way, Cleveland, OH 44109, USA.
E Department of Veterinary Preventive Medicine, The Ohio State University, 1920 Coffey Road, Columbus, OH 43210, USA.
F Department of Planning, Design, and Natural Resources, Cleveland Metroparks, 4500 Valley Parkway, Fairview Park, OH 44126, USA.
G Corresponding author. Email: lepardcl@msu.edu
Wildlife Research 46(1) 37-53 https://doi.org/10.1071/WR17181
Submitted: 14 December 2017 Accepted: 15 October 2018 Published: 21 December 2018
Abstract
Context: The use of camera traps in ecological research has grown exponentially over the past decade, but questions remain about the effect of camera-trap settings on ecological inference. The delay-period setting controls the amount of time that a camera trap is idle between motion-activated triggers. Longer delay periods may potentially extend battery life, reduce data-storage requirements, and shorten data-analysis time. However, they might result in lost data (i.e. missed wildlife detections), which could bias ecological inference and compromise research objectives.
Aims: We aimed to examine the effect of the delay period on (1) the number of camera-trap triggers, (2) detection and site-occupancy probabilities for eight mammalian species that varied in size, movement rate and commonness and (3) parameter estimates of habitat-based covariates from the occupancy models for these species.
Methods: We deployed 104 camera traps for 4 months throughout an extensive urban park system in Cleveland, Ohio, USA, using a spatially random design. Using the resultant data, we simulated delay periods ranging from 10 s to 60 min. For each of these delay periods and for each of our eight focal species, we calculated the number of camera-trap triggers and the parameter estimates of hierarchical Bayesian occupancy models.
Key results: A simulated increase in the delay period from 10 s to 10 min decreased the number of triggers by 79.6%, and decreased detection probability and occupancy probability across all species by 1.6% and 4.4% respectively. Further increases in the delay period (i.e. from 10 to 60 min) resulted in modest additional reductions in the number of triggers and detection and occupancy probabilities. Variation in the delay period had negligible effects on the qualitative interpretations of habitat-based occupancy models for all eight species.
Conclusions: Our results suggest that delay-period settings ranging from 5 to 10 min can drastically reduce data-storage needs and analysis time without compromising inference resulting from occupancy modelling for a diversity of mammalian species.
Implications: Broadly, we provide guidance on designing camera-trap studies that optimally trade-off research effort and potential bias, thereby increasing the utility of camera traps as ecological research tools.
Additional keywords: data management, study design, urban ecology, wildlife monitoring.
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