dc.contributor.author |
McIntyre, Trevor
|
|
dc.contributor.author |
Majelantle, Tshepiso Lesedi
|
|
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 |