McIntyre, TrevorMajelantle, Tshepiso LesediSlip, D.J.Harcourt, R.G.2021-11-102021-11-102020-02McIntyre, 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/WR19040.1035-3712 (print)1448-5494 (online)10.1071/WR19040http://hdl.handle.net/2263/82632CONTEXT : 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© CSIRO 2020DetectabilityMark–recapturePerformanceRandom encounter modelPostprint Article