Individual identification via remote video verified by DNA analysis: a case study of the American black bear

Context Researchers and managers often use DNA analysis and remote photography to identify cryptic animals and estimate abundance. Remote video cameras are used less often but offer an increased ability to distinguish similar-looking individuals as well as to observe behavioural patterns that cannot be adequately captured with still photography. However, the use of this approach in species with minimally distinguishing marks has not been tested. Aims To determine the utility and accuracy of distinguishing characteristics of American black bears, Ursus americanus, observed on remote video for identifying individuals in an open population. Methods We compared individuals identified on video with individuals and their sex identified by DNA analysis of hairs collected from hair traps visited by the bears. Key results We found that remote video could be used to determine the number of male and female black bears sampled by the video cameras. Specifically, we matched 13 individual bear genotypes with 13 video identifications, one genotype for each individual. We correctly matched ~82% of video identifications with all 38 genotypes collected from hair traps. Conclusions We demonstrated that distinguishing characteristics of a cryptic animal in remote video can be used to accurately identify individuals. Remote video complements genetic analysis by providing information about habitat use and behaviour. Implications When remote video cameras can be used to identify individuals, a wealth of other information will subsequently be obtained. Multi-year video-based studies can show sex ratios, and relative physical condition; shed light on fine-scale habitat use, such as when and where animals feed and what they eat; and display social interactions and rare behaviours.

• Publication year

  2019

• Venue

  Wildlife research (East Melbourne)

• Publication date

  2019-07-04

• Fields of study

  Biology, Environmental Science

• Identifiers
  DOI 10.1071/WR18049
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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