Advantages of combining generalized linear models and occupancy models to find indicators of habitat selection: Small mammals in agroecosystems as a case study

Autores
Gorosito, Irene Laura; Marziali Bermudez, Mariano; Busch, Maria
Año de publicación
2018
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Models of habitat variables can be used to find indicators for a quantitative prediction of the likeliness of species occurrence or abundance. Methodological bias due to variable detectability can be critical to properly determine habitat use and, thus, for understanding species ecology, distribution, and requirements for survival. In spite of recent advances in dealing with imperfect detection through detailed modeling, this approach requires large amounts of data and usually leads to larger standard errors in parameter estimates. In this work, we explore the advantages of combining generalized linear models (GLMs) and occupancy models (OMs) for the detection of variables that may be used as indicators of habitat suitability for rodent species. As a case study, we analyzed live trapping data of three rodent species that inhabit agroecosystems at micro- and macrohabitat scales. Both methods provided complementary information: while OMs revealed that some habitat features believed to be selected by studied species actually affected detectability, some effects could only be detected by GLMs. Moreover, for some covariates apparently affecting habitat selection at both scales, comparing results between scales allowed us to determine for which it was actually relevant rather than a reflection of the other. Therefore, we advise applying complementary modeling approaches at multiple scales for habitat selection studies. A variety of outcomes and their implications are thoroughly discussed and may guide other researchers facing similar situations.
Fil: Gorosito, Irene Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina
Fil: Marziali Bermudez, Mariano. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina
Fil: Busch, Maria. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina
Materia
GENERALIZED LINEAR MODELS
MACROHABITAT
MICROHABITAT
OCCUPANCY MODELS
SMALL MAMMAL
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/85703
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/85703
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network_name_str CONICET Digital (CONICET)
spelling Advantages of combining generalized linear models and occupancy models to find indicators of habitat selection: Small mammals in agroecosystems as a case studyGorosito, Irene LauraMarziali Bermudez, MarianoBusch, MariaGENERALIZED LINEAR MODELSMACROHABITATMICROHABITATOCCUPANCY MODELSSMALL MAMMALhttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1Models of habitat variables can be used to find indicators for a quantitative prediction of the likeliness of species occurrence or abundance. Methodological bias due to variable detectability can be critical to properly determine habitat use and, thus, for understanding species ecology, distribution, and requirements for survival. In spite of recent advances in dealing with imperfect detection through detailed modeling, this approach requires large amounts of data and usually leads to larger standard errors in parameter estimates. In this work, we explore the advantages of combining generalized linear models (GLMs) and occupancy models (OMs) for the detection of variables that may be used as indicators of habitat suitability for rodent species. As a case study, we analyzed live trapping data of three rodent species that inhabit agroecosystems at micro- and macrohabitat scales. Both methods provided complementary information: while OMs revealed that some habitat features believed to be selected by studied species actually affected detectability, some effects could only be detected by GLMs. Moreover, for some covariates apparently affecting habitat selection at both scales, comparing results between scales allowed us to determine for which it was actually relevant rather than a reflection of the other. Therefore, we advise applying complementary modeling approaches at multiple scales for habitat selection studies. A variety of outcomes and their implications are thoroughly discussed and may guide other researchers facing similar situations.Fil: Gorosito, Irene Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; ArgentinaFil: Marziali Bermudez, Mariano. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; ArgentinaFil: Busch, Maria. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; ArgentinaElsevier Science2018-05info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/85703Gorosito, Irene Laura; Marziali Bermudez, Mariano; Busch, Maria; Advantages of combining generalized linear models and occupancy models to find indicators of habitat selection: Small mammals in agroecosystems as a case study; Elsevier Science; Ecological Indicators; 85; 5-2018; 1-101470-160XCONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://linkinghub.elsevier.com/retrieve/pii/S1470160X17306271info:eu-repo/semantics/altIdentifier/doi/10.1016/j.ecolind.2017.10.003info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:58:09Zoai:ri.conicet.gov.ar:11336/85703instacron: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:34982025-09-03 09:58:09.849CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Advantages of combining generalized linear models and occupancy models to find indicators of habitat selection: Small mammals in agroecosystems as a case study
title Advantages of combining generalized linear models and occupancy models to find indicators of habitat selection: Small mammals in agroecosystems as a case study
spellingShingle Advantages of combining generalized linear models and occupancy models to find indicators of habitat selection: Small mammals in agroecosystems as a case study
Gorosito, Irene Laura
GENERALIZED LINEAR MODELS
MACROHABITAT
MICROHABITAT
OCCUPANCY MODELS
SMALL MAMMAL
title_short Advantages of combining generalized linear models and occupancy models to find indicators of habitat selection: Small mammals in agroecosystems as a case study
title_full Advantages of combining generalized linear models and occupancy models to find indicators of habitat selection: Small mammals in agroecosystems as a case study
title_fullStr Advantages of combining generalized linear models and occupancy models to find indicators of habitat selection: Small mammals in agroecosystems as a case study
title_full_unstemmed Advantages of combining generalized linear models and occupancy models to find indicators of habitat selection: Small mammals in agroecosystems as a case study
title_sort Advantages of combining generalized linear models and occupancy models to find indicators of habitat selection: Small mammals in agroecosystems as a case study
dc.creator.none.fl_str_mv Gorosito, Irene Laura
Marziali Bermudez, Mariano
Busch, Maria
author Gorosito, Irene Laura
author_facet Gorosito, Irene Laura
Marziali Bermudez, Mariano
Busch, Maria
author_role author
author2 Marziali Bermudez, Mariano
Busch, Maria
author2_role author
author
dc.subject.none.fl_str_mv GENERALIZED LINEAR MODELS
MACROHABITAT
MICROHABITAT
OCCUPANCY MODELS
SMALL MAMMAL
topic GENERALIZED LINEAR MODELS
MACROHABITAT
MICROHABITAT
OCCUPANCY MODELS
SMALL MAMMAL
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Models of habitat variables can be used to find indicators for a quantitative prediction of the likeliness of species occurrence or abundance. Methodological bias due to variable detectability can be critical to properly determine habitat use and, thus, for understanding species ecology, distribution, and requirements for survival. In spite of recent advances in dealing with imperfect detection through detailed modeling, this approach requires large amounts of data and usually leads to larger standard errors in parameter estimates. In this work, we explore the advantages of combining generalized linear models (GLMs) and occupancy models (OMs) for the detection of variables that may be used as indicators of habitat suitability for rodent species. As a case study, we analyzed live trapping data of three rodent species that inhabit agroecosystems at micro- and macrohabitat scales. Both methods provided complementary information: while OMs revealed that some habitat features believed to be selected by studied species actually affected detectability, some effects could only be detected by GLMs. Moreover, for some covariates apparently affecting habitat selection at both scales, comparing results between scales allowed us to determine for which it was actually relevant rather than a reflection of the other. Therefore, we advise applying complementary modeling approaches at multiple scales for habitat selection studies. A variety of outcomes and their implications are thoroughly discussed and may guide other researchers facing similar situations.
Fil: Gorosito, Irene Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina
Fil: Marziali Bermudez, Mariano. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina
Fil: Busch, Maria. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina
description Models of habitat variables can be used to find indicators for a quantitative prediction of the likeliness of species occurrence or abundance. Methodological bias due to variable detectability can be critical to properly determine habitat use and, thus, for understanding species ecology, distribution, and requirements for survival. In spite of recent advances in dealing with imperfect detection through detailed modeling, this approach requires large amounts of data and usually leads to larger standard errors in parameter estimates. In this work, we explore the advantages of combining generalized linear models (GLMs) and occupancy models (OMs) for the detection of variables that may be used as indicators of habitat suitability for rodent species. As a case study, we analyzed live trapping data of three rodent species that inhabit agroecosystems at micro- and macrohabitat scales. Both methods provided complementary information: while OMs revealed that some habitat features believed to be selected by studied species actually affected detectability, some effects could only be detected by GLMs. Moreover, for some covariates apparently affecting habitat selection at both scales, comparing results between scales allowed us to determine for which it was actually relevant rather than a reflection of the other. Therefore, we advise applying complementary modeling approaches at multiple scales for habitat selection studies. A variety of outcomes and their implications are thoroughly discussed and may guide other researchers facing similar situations.
publishDate 2018
dc.date.none.fl_str_mv 2018-05
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/11336/85703
Gorosito, Irene Laura; Marziali Bermudez, Mariano; Busch, Maria; Advantages of combining generalized linear models and occupancy models to find indicators of habitat selection: Small mammals in agroecosystems as a case study; Elsevier Science; Ecological Indicators; 85; 5-2018; 1-10
1470-160X
CONICET Digital
CONICET
url http://hdl.handle.net/11336/85703
identifier_str_mv Gorosito, Irene Laura; Marziali Bermudez, Mariano; Busch, Maria; Advantages of combining generalized linear models and occupancy models to find indicators of habitat selection: Small mammals in agroecosystems as a case study; Elsevier Science; Ecological Indicators; 85; 5-2018; 1-10
1470-160X
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://linkinghub.elsevier.com/retrieve/pii/S1470160X17306271
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.ecolind.2017.10.003
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier Science
publisher.none.fl_str_mv Elsevier Science
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
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score 13.13397

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