A flexible framework for spatial capture-recapture with unknown identities
Abstract
Camera traps or acoustic recorders are often used to sample wildlife populations. When animals can be individually identified, these data can be used with spatial capture-recapture (SCR) methods to assess populations. However, obtaining animal identities is often labor-intensive and not always possible for all detected animals. To address this problem, we formulate SCR, including acoustic SCR, as a marked Poisson process, comprising a single counting process for the detections of all animals and a mark distribution for what is observed (eg, animal identity, detector location). The counting process applies equally when it is animals appearing in front of camera traps and when vocalizations are captured by microphones, although the definition of a mark changes. When animals cannot be uniquely identified, the observed marks arise from a mixture of mark distributions defined by the animal activity centers and additional characteristics. Our method generalizes existing latent identity SCR models and provides an integrated framework that includes acoustic SCR. We apply our method to estimate density from a camera trap study of fisher (Pekania pennanti) and an acoustic survey of Cape Peninsula moss frog (Arthroleptella lightfooti). We also test it through simulation. We find latent identity SCR with additional marks such as sex or time of arrival to be a reliable method for estimating animal density.
Citation
Van Dam-Bates , P , Papathomas , M , Stevenson , B C , Fewster , R M , Turek , D , Stewart , F E C & Borchers , D L 2024 , ' A flexible framework for spatial capture-recapture with unknown identities ' , Biometrics , vol. 80 , no. 1 , ujad019 . https://doi.org/10.1093/biomtc/ujad019
Publication
Biometrics
Status
Peer reviewed
ISSN
0006-341XType
Journal article
Description
Funding: We acknowledge the funding support of the Natural Sciences and Engineering Research Council of Canada (NSERC) and the University of St Andrews. The fisher study was funded by InnoTech Alberta grants, Government of Alberta (Environment and Parks), The Beaver Hills Initiative, Alberta Conservation Association, NSERC, Royal Canadian Geographic Society, TD Friends of the Environment Foundation, and the Fur Institute of Canada scholarships.Collections
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