Estimating wolf (Canis lupus) densities using video camera traps and spatial capture–recapture analysis

Estimating population density is critical for effective species conservation, wildlife management planning, and long-term monitoring. Obtaining accurate estimates is especially important for the wolf (Canis lupus), a widely distributed northern hemisphere apex predator whose management and conservat...

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Detalles Bibliográficos
Autores: Jiménez, José, Cara, Daniel, García Domínguez, Francisco, Barasona García-Arévalo, José Ángel
Tipo de recurso: artículo
Fecha de publicación:2023
País:España
Institución:Universidad Complutense de Madrid (UCM)
Repositorio:Docta Complutense
Idioma:inglés
OAI Identifier:oai:docta.ucm.es:20.500.14352/104535
Acceso en línea:https://hdl.handle.net/20.500.14352/104535
Access Level:acceso abierto
Palabra clave:636.09
Camera trap
Canis lupus
Gregariousness
Heterogeneity
Identification
Population density
Spatial capture–recapture
Video
Wolf
Veterinaria
3109 Ciencias Veterinarias
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spelling Estimating wolf (Canis lupus) densities using video camera traps and spatial capture–recapture analysisJiménez, JoséCara, DanielGarcía Domínguez, FranciscoBarasona García-Arévalo, José Ángel636.09Camera trapCanis lupusGregariousnessHeterogeneityIdentificationPopulation densitySpatial capture–recaptureVideoWolfVeterinaria3109 Ciencias VeterinariasEstimating population density is critical for effective species conservation, wildlife management planning, and long-term monitoring. Obtaining accurate estimates is especially important for the wolf (Canis lupus), a widely distributed northern hemisphere apex predator whose management and conservation are highly controversial in most of its range, and whose presence usually generates high-profile media coverage. The peculiarities of wolf social spatial organization and behavior can violate the assumptions of capture–recapture models (uniformity and independence, respectively) to a greater or lesser extent and make it difficult to obtain precise and reliable density estimates. This paper presents a case study, which estimated the population density of the Iberian wolf in the Dorsal Gallega mountain ridge (Galicia, NW Spain) based on the identification of individual wolves from their traits and behavior using video camera traps and spatially explicit capture–recapture (SCR) analyses. The study followed three phases. Firstly, field data were collected by installing camera traps and changing their location until the entire area was sampled. Second, a complete morphological and behavioral study of the wolves recorded was performed to facilitate individual recognition. Third, overdispersion due to gregariousness and other sources of heterogeneity was modeled in the SCR analyses comparing Poisson and negative binomial observation models with different random effects on the baseline detection probability. We estimated a density of 2.88 (SD: 0.37) wolves/100 km2 in the study area. We concluded that estimating wolf population size using camera trap videos, individual identification, and SCR provides a feasible method and can be used for estimating the density in similar species.WileyUniversidad Complutense de Madrid20232023-07-0920232023-07-09journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/20.500.14352/104535reponame:Docta Complutenseinstname:Universidad Complutense de Madrid (UCM)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Attribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:docta.ucm.es:20.500.14352/1045352026-06-02T12:44:21Z
dc.title.none.fl_str_mv Estimating wolf (Canis lupus) densities using video camera traps and spatial capture–recapture analysis
title Estimating wolf (Canis lupus) densities using video camera traps and spatial capture–recapture analysis
spellingShingle Estimating wolf (Canis lupus) densities using video camera traps and spatial capture–recapture analysis
Jiménez, José
636.09
Camera trap
Canis lupus
Gregariousness
Heterogeneity
Identification
Population density
Spatial capture–recapture
Video
Wolf
Veterinaria
3109 Ciencias Veterinarias
title_short Estimating wolf (Canis lupus) densities using video camera traps and spatial capture–recapture analysis
title_full Estimating wolf (Canis lupus) densities using video camera traps and spatial capture–recapture analysis
title_fullStr Estimating wolf (Canis lupus) densities using video camera traps and spatial capture–recapture analysis
title_full_unstemmed Estimating wolf (Canis lupus) densities using video camera traps and spatial capture–recapture analysis
title_sort Estimating wolf (Canis lupus) densities using video camera traps and spatial capture–recapture analysis
dc.creator.none.fl_str_mv Jiménez, José
Cara, Daniel
García Domínguez, Francisco
Barasona García-Arévalo, José Ángel
author Jiménez, José
author_facet Jiménez, José
Cara, Daniel
García Domínguez, Francisco
Barasona García-Arévalo, José Ángel
author_role author
author2 Cara, Daniel
García Domínguez, Francisco
Barasona García-Arévalo, José Ángel
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidad Complutense de Madrid
dc.subject.none.fl_str_mv 636.09
Camera trap
Canis lupus
Gregariousness
Heterogeneity
Identification
Population density
Spatial capture–recapture
Video
Wolf
Veterinaria
3109 Ciencias Veterinarias
topic 636.09
Camera trap
Canis lupus
Gregariousness
Heterogeneity
Identification
Population density
Spatial capture–recapture
Video
Wolf
Veterinaria
3109 Ciencias Veterinarias
description Estimating population density is critical for effective species conservation, wildlife management planning, and long-term monitoring. Obtaining accurate estimates is especially important for the wolf (Canis lupus), a widely distributed northern hemisphere apex predator whose management and conservation are highly controversial in most of its range, and whose presence usually generates high-profile media coverage. The peculiarities of wolf social spatial organization and behavior can violate the assumptions of capture–recapture models (uniformity and independence, respectively) to a greater or lesser extent and make it difficult to obtain precise and reliable density estimates. This paper presents a case study, which estimated the population density of the Iberian wolf in the Dorsal Gallega mountain ridge (Galicia, NW Spain) based on the identification of individual wolves from their traits and behavior using video camera traps and spatially explicit capture–recapture (SCR) analyses. The study followed three phases. Firstly, field data were collected by installing camera traps and changing their location until the entire area was sampled. Second, a complete morphological and behavioral study of the wolves recorded was performed to facilitate individual recognition. Third, overdispersion due to gregariousness and other sources of heterogeneity was modeled in the SCR analyses comparing Poisson and negative binomial observation models with different random effects on the baseline detection probability. We estimated a density of 2.88 (SD: 0.37) wolves/100 km2 in the study area. We concluded that estimating wolf population size using camera trap videos, individual identification, and SCR provides a feasible method and can be used for estimating the density in similar species.
publishDate 2023
dc.date.none.fl_str_mv 2023
2023-07-09
2023
2023-07-09
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/20.500.14352/104535
url https://hdl.handle.net/20.500.14352/104535
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Wiley
publisher.none.fl_str_mv Wiley
dc.source.none.fl_str_mv reponame:Docta Complutense
instname:Universidad Complutense de Madrid (UCM)
instname_str Universidad Complutense de Madrid (UCM)
reponame_str Docta Complutense
collection Docta Complutense
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,300719

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