Abstract

AbstractCounts of independent photo events from camera traps are commonly used to make inference about species occupancy, the density of unmarked populations, and the relative abundance of species across time and space. These applications rest on the untested assumption that data collected from individual cameras are representative of the landscape location in which they are placed, and that nearby cameras would record similar data when any additional micro‐site differences are accounted for. We established a high‐density camera trapping grid (100 × 100 m; 27 cameras) in Virginia, USA, to explicitly test these assumptions, investigating variation in capture rates and detection probabilities for a range of terrestrial mammals during four 2‐month seasonal surveys. Despite controlling for numerous habitat and placement factors, we documented, across all 5 focal species, large ranges and coefficients of variation in both capture rate and detection probabilities, which were similar to those seen across 2 sets of independent forest sampling sites from a larger, more typical camera trap sampling design. We also documented a lack of spatial autocorrelation in capture rate at any distance. Measured local covariates relevant to the camera viewshed (stem density, camera height, log presence, effective detection distance [EDD], total dbh of oak trees) rarely explained any significant portion of observed variation in capture rates or detection probabilities across the grid. The influence of EDD, measured here for the first time for individual camera stations, was inconsistently important and varied in direction of effect depending on species and season. Our study indicates single‐camera stations may fail to sample animal presence and frequency of use in a robust and repeatable way, primarily resulting from the influence of both idiosyncrasies in animal movement and measured and unknown micro‐site characteristics. We recommend spatial replication within sites (e.g., small‐scale shifting of cameras or use of multiple stations) should be considered to minimize impacts of relevant micro‐site characteristics, some of which may be difficult to identify.

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