Optimising camera trap survey effort to reliably detect a threatened species, the black-footed tree-rat, Mesembriomys gouldii, in open forest and woodland of tropical savannas of the Top End, Northern Territory

  • Jennifer Anne Risler

    Student thesis: Coursework Masters - CDU

    Abstract

    Context: Imperfect detection, where a species remains undetected in surveys even though it is present, occurs in all wildlife surveys. The probability of detecting a species with different sampling designs can be assessed using occupancy modelling, then improved through employing the most appropriate survey effort and methods.

    Aims: My research applies analytical methods to determine optimal survey effort, by varying the number of camera traps per site and deployment time, for the detection of the threatened black-footed tree-rat, Mesembriomys gouldii.

    Methods: My analysis was applied to camera trap data collected by myself and others for a range of research objectives from 224 sites across eight regions in the Top End, Northern Territory, between 2013 and 2016. All data were collected using a five camera array and over a minimum six week period. Single-season occupancy models were applied to daily detection data over 42 days to assess the effect of altering the number of camera traps set per site on detection probability. Cumulative detection curves with 95% confidence intervals were calculated to determine the optimal length of deployment for each scenario of deploying one to five camera traps per site.

    Key Results: The detection probability for black-footed tree-rats was low (p = 0.15) for the one camera scenario, but increased with the number of cameras set per site, as did the precision around the detection probability estimate. The optimal length of deployment with a predefined precision (p* > 0.85) dropped from 21 days to 11 days with the addition of a second camera trap. The optimal survey design, that should reliably determine the presence of black-footed tree-rats if they are present, was identified as two camera traps per site for two weeks.

    Conclusions: The optimal survey effort required to reliably detect a target species can be derived from pre-existing data. Additional variation due to environmental, ecological and detection method, in this case using camera traps, will also influence detection probability and needs to be considered.

    Implications: The outcomes of this research will be incorporated into impact assessment guidelines to improve detectability and provide definitive and achievable methods for detecting the black-footed tree-rat prior to development activities. The guidelines will serve to standardise survey design and methods, providing a greater knowledge base for natural resource management and species conservation. The analytical methods outlined can also be applied to determine optimal survey design for other species using pre-existing data from past surveys.
    Date of AwardJun 2017
    Original languageEnglish
    SupervisorChristine Schlesinger (Supervisor)

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