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Distance sampling with camera traps
Author(s) -
Howe Eric J.,
Buckland Stephen T.,
DesprésEinspenner MarieLyne,
Kühl Hjalmar S.
Publication year - 2017
Publication title -
methods in ecology and evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.425
H-Index - 105
ISSN - 2041-210X
DOI - 10.1111/2041-210x.12790
Subject(s) - camera trap , sampling (signal processing) , distance sampling , transect , estimator , density estimation , abundance estimation , abundance (ecology) , wildlife , statistics , environmental science , ecology , computer science , mathematics , biology , computer vision , filter (signal processing)
Summary Reliable estimates of animal density and abundance are essential for effective wildlife conservation and management. Camera trapping has proven efficient for sampling multiple species, but statistical estimators of density from camera trapping data for species that cannot be individually identified are still in development. We extend point‐transect methods for estimating animal density to accommodate data from camera traps, allowing researchers to exploit existing distance sampling theory and software for designing studies and analysing data. We tested it by simulation, and used it to estimate densities of Maxwell's duikers ( Philantomba maxwellii ) in Taï National Park, Côte d'Ivoire. Densities estimated from simulated data were unbiased when we assumed animals were not available for detection during long periods of rest. Estimated duiker densities were higher than recent estimates from line transect surveys, which are believed to underestimate densities of forest ungulates. We expect these methods to provide an effective means to estimate animal density from camera trapping data and to be applicable in a variety of settings.