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Spot on: using camera traps to individually monitor one of the world’s largest lizards

Authors :
Jacob L. Champney
Judy Dunlop
Dale G. Nimmo
Leonie E. Valentine
Harry Moore
Source :
Wildlife Research. 47:326
Publication Year :
2020
Publisher :
CSIRO Publishing, 2020.

Abstract

Abstract ContextEstimating animal abundance often relies on being able to identify individuals; however, this can be challenging, especially when applied to large animals that are difficult to trap and handle. Camera traps have provided a non-invasive alternative by using natural markings to individually identify animals within image data. Although camera traps have been used to individually identify mammals, they are yet to be widely applied to other taxa, such as reptiles. AimsWe assessed the capacity of camera traps to provide images that allow for individual identification of the world’s fourth-largest lizard species, the perentie (Varanus giganteus), and demonstrate other basic morphological and behavioural data that can be gleaned from camera-trap images. MethodsVertically orientated cameras were deployed at 115 sites across a 10000km2 area in north-western Australia for an average of 216 days. We used spot patterning located on the dorsal surface of perenties to identify individuals from camera-trap imagery, with the assistance of freely available spot ID software. We also measured snout-to-vent length (SVL) by using image-analysis software, and collected image time-stamp data to analyse temporal activity patterns. ResultsNinety-two individuals were identified, and individuals were recorded moving distances of up to 1975m. Confidence in identification accuracy was generally high (91%), and estimated SVL measurements varied by an average of 6.7% (min=1.8%, max=21.3%) of individual SVL averages. Larger perenties (SVL of >45cm) were detected mostly between dawn and noon, and in the late afternoon and early evening, whereas small perenties (SVL of

Details

ISSN :
10353712
Volume :
47
Database :
OpenAIRE
Journal :
Wildlife Research
Accession number :
edsair.doi...........986914e3d5a1e24806e7b3cbe7cd2a89
Full Text :
https://doi.org/10.1071/wr19159