Integration of mark–recapture and acoustic detections for unbiased population estimation in animal communities

Autores
Jarrett, Crinan; Haydon, Daniel T.; Morales, Juan Manuel; Ferreira, Diogo F.; Forzi, Francis Alemanji; Welch, Andreanna J.; Powell, Luke L.; Matthiopoulos, Jason
Año de publicación
2022
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Abundance estimation methods that combine several types of data are becoming increasingly common because they yield more accurate and precise parameter estimates and predictions than are possible from a single data source. These beneficial effects result from increasing sample size (through data pooling) and complementarity between different data types. Here, we test whether integrating mark–recapture data with passive acoustic detections into a joint likelihood improves estimates of population size in a multi-guild community. We compared the integrated model to a mark–recapture-only model using simulated data first and then using a data set of mist-net captures and acoustic recordings from an Afrotropical agroforest bird community. The integrated model with simulated data improved accuracy and precision of estimated population size and detection parameters. When applied to field data, the integrated model was able to produce, for each bird guild, ecologically plausible estimates of population size and detection parameters, with more precision compared with the mark–recapture model. Overall, our results show that adding acoustic data to mark–recapture analyses improves estimates of population size. With the increasing availability of acoustic recording devices, this data collection technique could readily be added to routine field protocols, leading to a cost-efficient improvement of traditional mark–recapture population estimation.
Fil: Jarrett, Crinan. University of Glasgow; Reino Unido. Biodiversity Initiative; Estados Unidos
Fil: Haydon, Daniel T.. University of Glasgow; Reino Unido
Fil: Morales, Juan Manuel. University of Glasgow; Reino Unido. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; Argentina
Fil: Ferreira, Diogo F.. Universidad de Porto. Facultad de Ciências. Centro de Investigação em Biodiversidade e Recursos Genéticos; Portugal. Biodiversity Initiative; Estados Unidos
Fil: Forzi, Francis Alemanji. Partners For Sustainable Development; Camerún
Fil: Welch, Andreanna J.. University of Durham; Reino Unido. Biodiversity Initiative; Estados Unidos
Fil: Powell, Luke L.. University of Durham; Reino Unido. University of Glasgow; Reino Unido. Universidad de Porto. Facultad de Ciências. Centro de Investigação em Biodiversidade e Recursos Genéticos; Portugal. Biodiversity Initiative; Estados Unidos
Fil: Matthiopoulos, Jason. University of Glasgow; Reino Unido
Materia
ACOUSTIC DATA
AFROTROPICS
BAYESIAN MODEL
BIRD
DATA INTEGRATION
HIERARCHICAL MODELING
MARK–RECAPTURE DATA
POPULATION SIZE
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/218118
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/218118
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Integration of mark–recapture and acoustic detections for unbiased population estimation in animal communitiesJarrett, CrinanHaydon, Daniel T.Morales, Juan ManuelFerreira, Diogo F.Forzi, Francis AlemanjiWelch, Andreanna J.Powell, Luke L.Matthiopoulos, JasonACOUSTIC DATAAFROTROPICSBAYESIAN MODELBIRDDATA INTEGRATIONHIERARCHICAL MODELINGMARK–RECAPTURE DATAPOPULATION SIZEhttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1Abundance estimation methods that combine several types of data are becoming increasingly common because they yield more accurate and precise parameter estimates and predictions than are possible from a single data source. These beneficial effects result from increasing sample size (through data pooling) and complementarity between different data types. Here, we test whether integrating mark–recapture data with passive acoustic detections into a joint likelihood improves estimates of population size in a multi-guild community. We compared the integrated model to a mark–recapture-only model using simulated data first and then using a data set of mist-net captures and acoustic recordings from an Afrotropical agroforest bird community. The integrated model with simulated data improved accuracy and precision of estimated population size and detection parameters. When applied to field data, the integrated model was able to produce, for each bird guild, ecologically plausible estimates of population size and detection parameters, with more precision compared with the mark–recapture model. Overall, our results show that adding acoustic data to mark–recapture analyses improves estimates of population size. With the increasing availability of acoustic recording devices, this data collection technique could readily be added to routine field protocols, leading to a cost-efficient improvement of traditional mark–recapture population estimation.Fil: Jarrett, Crinan. University of Glasgow; Reino Unido. Biodiversity Initiative; Estados UnidosFil: Haydon, Daniel T.. University of Glasgow; Reino UnidoFil: Morales, Juan Manuel. University of Glasgow; Reino Unido. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; ArgentinaFil: Ferreira, Diogo F.. Universidad de Porto. Facultad de Ciências. Centro de Investigação em Biodiversidade e Recursos Genéticos; Portugal. Biodiversity Initiative; Estados UnidosFil: Forzi, Francis Alemanji. Partners For Sustainable Development; CamerúnFil: Welch, Andreanna J.. University of Durham; Reino Unido. Biodiversity Initiative; Estados UnidosFil: Powell, Luke L.. University of Durham; Reino Unido. University of Glasgow; Reino Unido. Universidad de Porto. Facultad de Ciências. Centro de Investigação em Biodiversidade e Recursos Genéticos; Portugal. Biodiversity Initiative; Estados UnidosFil: Matthiopoulos, Jason. University of Glasgow; Reino UnidoEcological Society of America2022-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/218118Jarrett, Crinan; Haydon, Daniel T.; Morales, Juan Manuel; Ferreira, Diogo F.; Forzi, Francis Alemanji; et al.; Integration of mark–recapture and acoustic detections for unbiased population estimation in animal communities; Ecological Society of America; Ecology; 103; 10; 10-2022; 1-90012-9658CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1002/ecy.3769info:eu-repo/semantics/altIdentifier/url/https://esajournals.onlinelibrary.wiley.com/doi/10.1002/ecy.3769info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2026-08-25T14:42:15Zoai:ri.conicet.gov.ar:11336/218118instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982026-08-25 14:42:15.664CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Integration of mark–recapture and acoustic detections for unbiased population estimation in animal communities
title Integration of mark–recapture and acoustic detections for unbiased population estimation in animal communities
spellingShingle Integration of mark–recapture and acoustic detections for unbiased population estimation in animal communities
Jarrett, Crinan
ACOUSTIC DATA
AFROTROPICS
BAYESIAN MODEL
BIRD
DATA INTEGRATION
HIERARCHICAL MODELING
MARK–RECAPTURE DATA
POPULATION SIZE
title_short Integration of mark–recapture and acoustic detections for unbiased population estimation in animal communities
title_full Integration of mark–recapture and acoustic detections for unbiased population estimation in animal communities
title_fullStr Integration of mark–recapture and acoustic detections for unbiased population estimation in animal communities
title_full_unstemmed Integration of mark–recapture and acoustic detections for unbiased population estimation in animal communities
title_sort Integration of mark–recapture and acoustic detections for unbiased population estimation in animal communities
dc.creator.none.fl_str_mv Jarrett, Crinan
Haydon, Daniel T.
Morales, Juan Manuel
Ferreira, Diogo F.
Forzi, Francis Alemanji
Welch, Andreanna J.
Powell, Luke L.
Matthiopoulos, Jason
author Jarrett, Crinan
author_facet Jarrett, Crinan
Haydon, Daniel T.
Morales, Juan Manuel
Ferreira, Diogo F.
Forzi, Francis Alemanji
Welch, Andreanna J.
Powell, Luke L.
Matthiopoulos, Jason
author_role author
author2 Haydon, Daniel T.
Morales, Juan Manuel
Ferreira, Diogo F.
Forzi, Francis Alemanji
Welch, Andreanna J.
Powell, Luke L.
Matthiopoulos, Jason
author2_role author
author
author
author
author
author
author
dc.subject.none.fl_str_mv ACOUSTIC DATA
AFROTROPICS
BAYESIAN MODEL
BIRD
DATA INTEGRATION
HIERARCHICAL MODELING
MARK–RECAPTURE DATA
POPULATION SIZE
topic ACOUSTIC DATA
AFROTROPICS
BAYESIAN MODEL
BIRD
DATA INTEGRATION
HIERARCHICAL MODELING
MARK–RECAPTURE DATA
POPULATION SIZE
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Abundance estimation methods that combine several types of data are becoming increasingly common because they yield more accurate and precise parameter estimates and predictions than are possible from a single data source. These beneficial effects result from increasing sample size (through data pooling) and complementarity between different data types. Here, we test whether integrating mark–recapture data with passive acoustic detections into a joint likelihood improves estimates of population size in a multi-guild community. We compared the integrated model to a mark–recapture-only model using simulated data first and then using a data set of mist-net captures and acoustic recordings from an Afrotropical agroforest bird community. The integrated model with simulated data improved accuracy and precision of estimated population size and detection parameters. When applied to field data, the integrated model was able to produce, for each bird guild, ecologically plausible estimates of population size and detection parameters, with more precision compared with the mark–recapture model. Overall, our results show that adding acoustic data to mark–recapture analyses improves estimates of population size. With the increasing availability of acoustic recording devices, this data collection technique could readily be added to routine field protocols, leading to a cost-efficient improvement of traditional mark–recapture population estimation.
Fil: Jarrett, Crinan. University of Glasgow; Reino Unido. Biodiversity Initiative; Estados Unidos
Fil: Haydon, Daniel T.. University of Glasgow; Reino Unido
Fil: Morales, Juan Manuel. University of Glasgow; Reino Unido. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; Argentina
Fil: Ferreira, Diogo F.. Universidad de Porto. Facultad de Ciências. Centro de Investigação em Biodiversidade e Recursos Genéticos; Portugal. Biodiversity Initiative; Estados Unidos
Fil: Forzi, Francis Alemanji. Partners For Sustainable Development; Camerún
Fil: Welch, Andreanna J.. University of Durham; Reino Unido. Biodiversity Initiative; Estados Unidos
Fil: Powell, Luke L.. University of Durham; Reino Unido. University of Glasgow; Reino Unido. Universidad de Porto. Facultad de Ciências. Centro de Investigação em Biodiversidade e Recursos Genéticos; Portugal. Biodiversity Initiative; Estados Unidos
Fil: Matthiopoulos, Jason. University of Glasgow; Reino Unido
description Abundance estimation methods that combine several types of data are becoming increasingly common because they yield more accurate and precise parameter estimates and predictions than are possible from a single data source. These beneficial effects result from increasing sample size (through data pooling) and complementarity between different data types. Here, we test whether integrating mark–recapture data with passive acoustic detections into a joint likelihood improves estimates of population size in a multi-guild community. We compared the integrated model to a mark–recapture-only model using simulated data first and then using a data set of mist-net captures and acoustic recordings from an Afrotropical agroforest bird community. The integrated model with simulated data improved accuracy and precision of estimated population size and detection parameters. When applied to field data, the integrated model was able to produce, for each bird guild, ecologically plausible estimates of population size and detection parameters, with more precision compared with the mark–recapture model. Overall, our results show that adding acoustic data to mark–recapture analyses improves estimates of population size. With the increasing availability of acoustic recording devices, this data collection technique could readily be added to routine field protocols, leading to a cost-efficient improvement of traditional mark–recapture population estimation.
publishDate 2022
dc.date.none.fl_str_mv 2022-10
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/218118
Jarrett, Crinan; Haydon, Daniel T.; Morales, Juan Manuel; Ferreira, Diogo F.; Forzi, Francis Alemanji; et al.; Integration of mark–recapture and acoustic detections for unbiased population estimation in animal communities; Ecological Society of America; Ecology; 103; 10; 10-2022; 1-9
0012-9658
CONICET Digital
CONICET
url http://hdl.handle.net/11336/218118
identifier_str_mv Jarrett, Crinan; Haydon, Daniel T.; Morales, Juan Manuel; Ferreira, Diogo F.; Forzi, Francis Alemanji; et al.; Integration of mark–recapture and acoustic detections for unbiased population estimation in animal communities; Ecological Society of America; Ecology; 103; 10; 10-2022; 1-9
0012-9658
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1002/ecy.3769
info:eu-repo/semantics/altIdentifier/url/https://esajournals.onlinelibrary.wiley.com/doi/10.1002/ecy.3769
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Ecological Society of America
publisher.none.fl_str_mv Ecological Society of America
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
_version_ 1874774508667142144
score 13.265058

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