Quantifying imperfect camera-trap detection probabilities : implications for density modelling

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dc.contributor.author McIntyre, Trevor
dc.contributor.author Majelantle, T.L. (Tshepiso)
dc.contributor.author Slip, D.J.
dc.contributor.author Harcourt, R.G.
dc.date.accessioned 2021-11-10T11:49:42Z
dc.date.available 2021-11-10T11:49:42Z
dc.date.issued 2020-02
dc.description.abstract CONTEXT : Data obtained from camera traps are increasingly used to inform various population-level models. Although acknowledged, imperfect detection probabilities within camera-trap detection zones are rarely taken into account when modelling animal densities. AIMS : We aimed to identify parameters influencing camera-trap detection probabilities, and quantify their relative impacts, as well as explore the downstream implications of imperfect detection probabilities on population-density modelling. METHODS : We modelled the relationships between the detection probabilities of a standard camera-trap model (n = 35) on a remotely operated animal-shaped soft toy and a series of parameters likely to influence it. These included the distance of animals from camera traps, animal speed, camera-trap deployment height, ambient temperature (as a proxy for background surface temperatures) and animal surface temperature. We then used this detection-probability model to quantify the likely influence of imperfect detection rates on subsequent population-level models, being, in this case, estimates from random encounter density models on a known density simulation. KEY RESULTS : Detection probabilities mostly varied predictably in relation to measured parameters, and decreased with an increasing distance from the camera traps and speeds of movement, as well as heights of camera-trap deployments. Increased differences between ambient temperature and animal surface temperature were associated with increased detection probabilities. Importantly, our results showed substantial inter-camera (of the same model) variability in detection probabilities. Resulting model outputs suggested consistent and systematic underestimation of true population densities when not taking imperfect detection probabilities into account. CONCLUSIONS : Imperfect, and individually variable, detection probabilities inside the detection zones of camera traps can compromise resulting population-density estimates. IMPLICATIONS : We propose a simple calibration approach for individual camera traps before field deployment and encourage researchers to actively estimate individual camera-trap detection performance for inclusion in subsequent modelling approaches. en_ZA
dc.description.department Mammal Research Institute en_ZA
dc.description.department Zoology and Entomology en_ZA
dc.description.librarian hj2021 en_ZA
dc.description.sponsorship The Department of Science and Technology through the National Research Foundation of South Africa. en_ZA
dc.description.uri http://www.publish.csiro.au/nid/144.htm en_ZA
dc.identifier.citation McIntyre, T., Majelantle, T.L., Slip, D.J. et al. 2020, 'Quantifying imperfect camera-trap detection probabilities: implications for density modelling', Wildlife Research 47(2): 177-185, https://doi.org/10.1071/WR19040. en_ZA
dc.identifier.issn 1035-3712 (print)
dc.identifier.issn 1448-5494 (online)
dc.identifier.other 10.1071/WR19040
dc.identifier.uri http://hdl.handle.net/2263/82632
dc.language.iso en en_ZA
dc.publisher CSIRO Publishing en_ZA
dc.rights © CSIRO 2020 en_ZA
dc.subject Detectability en_ZA
dc.subject Mark–recapture en_ZA
dc.subject Performance en_ZA
dc.subject Random encounter model en_ZA
dc.title Quantifying imperfect camera-trap detection probabilities : implications for density modelling en_ZA
dc.type Postprint Article en_ZA


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