Likelihood‐based photograph identification: Application with photographs of free‐ranging bison
ABSTRACT Using photographs to identify individual animals and monitor populations is becoming more common. However, photographic identification methods where measurements of morphological traits (e.g., horn length) are compared have received little attention. We present an approach for aiding with t...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2014-03-01
|
| Series: | Wildlife Society Bulletin |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/wsb.382 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1846120292939726848 |
|---|---|
| author | Jerod A. Merkle Daniel Fortin |
| author_facet | Jerod A. Merkle Daniel Fortin |
| author_sort | Jerod A. Merkle |
| collection | DOAJ |
| description | ABSTRACT Using photographs to identify individual animals and monitor populations is becoming more common. However, photographic identification methods where measurements of morphological traits (e.g., horn length) are compared have received little attention. We present an approach for aiding with the identification of individual animals from photographs. The approach incorporates measurement data, metadata from photographs, and multiple sources of error, and calculates a matching score between pairs of photographs using a likelihood‐based algorithm. We tested and identified the false‐rejection error rate using 91 photographs, representing 33 known free‐ranging bison (Bison bison), and 117 simulated data sets with varying numbers of unique individuals, morphological measurements, and photograph error. We then used the approach to estimate the adult population size of bison in Prince Albert National Park, Canada, in 2011. For bison, the false‐rejection rate of our approach was 0.055. Using a Huggins closed population model with misidentification, we estimated 103 (95% CI = 82–130) and 46 (95% CI = 37–58) adult female and male bison, respectively. After incorporating field‐based calf‐ and juvenile‐to‐female ratios, we estimated 202 (95% CI = 171.6–231.4) bison. We found this estimate to be plausible using 2 minimum‐count aerial surveys conducted in March 2011 and 2012 for comparison. With our approach, researchers and managers can build capture histories of individuals, which can be used for studies of population dynamics and habitat selection. This approach can incorporate any morphological measurements extracted from photographs (e.g., coat color), making it robust to a variety of species and study systems. © 2013 The Wildlife Society. |
| format | Article |
| id | doaj-art-8be2d2cdfa2a4f138fe1e63d62bdbf31 |
| institution | Kabale University |
| issn | 2328-5540 |
| language | English |
| publishDate | 2014-03-01 |
| publisher | Wiley |
| record_format | Article |
| series | Wildlife Society Bulletin |
| spelling | doaj-art-8be2d2cdfa2a4f138fe1e63d62bdbf312024-12-16T12:17:05ZengWileyWildlife Society Bulletin2328-55402014-03-0138119620410.1002/wsb.382Likelihood‐based photograph identification: Application with photographs of free‐ranging bisonJerod A. Merkle0Daniel Fortin1Département de Biologie, Centre d'Étude de la ForêtUniversité LavalPavillon Alexandre Vachon 1045Avenue de la MédecineQuébecQCCanadaG1V 0A6Département de Biologie, Centre d'Étude de la ForêtUniversité LavalPavillon Alexandre Vachon 1045Avenue de la MédecineQuébecQCCanadaG1V 0A6ABSTRACT Using photographs to identify individual animals and monitor populations is becoming more common. However, photographic identification methods where measurements of morphological traits (e.g., horn length) are compared have received little attention. We present an approach for aiding with the identification of individual animals from photographs. The approach incorporates measurement data, metadata from photographs, and multiple sources of error, and calculates a matching score between pairs of photographs using a likelihood‐based algorithm. We tested and identified the false‐rejection error rate using 91 photographs, representing 33 known free‐ranging bison (Bison bison), and 117 simulated data sets with varying numbers of unique individuals, morphological measurements, and photograph error. We then used the approach to estimate the adult population size of bison in Prince Albert National Park, Canada, in 2011. For bison, the false‐rejection rate of our approach was 0.055. Using a Huggins closed population model with misidentification, we estimated 103 (95% CI = 82–130) and 46 (95% CI = 37–58) adult female and male bison, respectively. After incorporating field‐based calf‐ and juvenile‐to‐female ratios, we estimated 202 (95% CI = 171.6–231.4) bison. We found this estimate to be plausible using 2 minimum‐count aerial surveys conducted in March 2011 and 2012 for comparison. With our approach, researchers and managers can build capture histories of individuals, which can be used for studies of population dynamics and habitat selection. This approach can incorporate any morphological measurements extracted from photographs (e.g., coat color), making it robust to a variety of species and study systems. © 2013 The Wildlife Society.https://doi.org/10.1002/wsb.382Bison bisoncapture–mark–recapturecomputer‐assisted photographic‐identificationlikelihoodmisidentificationphotogrammetry |
| spellingShingle | Jerod A. Merkle Daniel Fortin Likelihood‐based photograph identification: Application with photographs of free‐ranging bison Wildlife Society Bulletin Bison bison capture–mark–recapture computer‐assisted photographic‐identification likelihood misidentification photogrammetry |
| title | Likelihood‐based photograph identification: Application with photographs of free‐ranging bison |
| title_full | Likelihood‐based photograph identification: Application with photographs of free‐ranging bison |
| title_fullStr | Likelihood‐based photograph identification: Application with photographs of free‐ranging bison |
| title_full_unstemmed | Likelihood‐based photograph identification: Application with photographs of free‐ranging bison |
| title_short | Likelihood‐based photograph identification: Application with photographs of free‐ranging bison |
| title_sort | likelihood based photograph identification application with photographs of free ranging bison |
| topic | Bison bison capture–mark–recapture computer‐assisted photographic‐identification likelihood misidentification photogrammetry |
| url | https://doi.org/10.1002/wsb.382 |
| work_keys_str_mv | AT jerodamerkle likelihoodbasedphotographidentificationapplicationwithphotographsoffreerangingbison AT danielfortin likelihoodbasedphotographidentificationapplicationwithphotographsoffreerangingbison |