Short Communication
Challenges and opportunities for monitoring wild Nile crocodiles with scute mark-recapture photography
Submitted: 07 November 2017 | Published: 19 July 2018
About the author(s)
Bernard W.T. Coetzee, Global Change Institute, University of the Witwatersrand, South Africa; Scientific Services, Organisation for Tropical Studies, South AfricaSam M. Ferreira, Scientific Services, SANParks, Skukuza, South Africa
Kristine Maciejewski, Centre for Complex Systems in Transition, Stellenbosch University, South Africa
Abstract
The global conservation status of Nile crocodiles (Crocodylus niloticus) was last assessed in 1996. The species presents particular difficulty in monitoring because it can be cryptic, require expertise to handle, and caudal tail tags and transmitters are often lost. Some studies advocate mark-recapture techniques based on photograph identification of the unique scute markings of crocodile tails as a non-invasive means of monitoring their populations. Researchers developed this method with crocodiles in captivity. In this study, we test the technique under field conditions by monitoring crocodiles from 2015 to 2017 in the Sunset Dam in the Kruger National Park. Using a Cormack-Jolly-Seber open population model, we found that the dam may host 15–30 individuals, but that there is a high turnover of individuals and much uncertainty in model outputs. The dam’s population thus has high rates of immigration and emigration. The method proved challenging under field conditions, as there was bias in identifying scute markings consistently. The efficient use of the method requires an exceptional quality of photographic equipment. Animal crypsis, however, remains an issue. In this study, we discuss how to improve the mark-recapture photography methodology, especially to adapt the technique for citizen science initiatives.
Conservation implications: Using scute mark-recapture photography presents challenges under field conditions. These challenges require innovative, practical and analytical solutions to successfully use the technique before monitoring programmes, aimed at ensuring the persistence of crocodiles in the wild, can be implemented.
Keywords
Metrics
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Crossref Citations
1. Transforming crocodile traceability: Deep metric learning for identifying Siamese crocodiles
Kriengsak Treeprapin, Kantapon Kaewtip, Worapong Singchat, Nattakan Ariyaraphong, Thitipong Panthum, Prateep Duengkae, Yosapong Temsiripong, Kornsorn Srikulnath, Suchin Trirongjitmoah
Ecological Informatics vol: 82 first page: 102771 year: 2024
doi: 10.1016/j.ecoinf.2024.102771