Sampling bias in multiscale ant diversity responses to landscape composition in a human-disturbed rainforest

Detalhes bibliográficos
Autor(a) principal: Ahuatzin, D. A.
Data de Publicação: 2022
Outros Autores: González-Tokman, D., Valenzuela-González, J. E., Escobar, F., Ribeiro, M. C. [UNESP], Acosta, J. C.L., Dáttilo, W.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1007/s00040-021-00844-2
http://hdl.handle.net/11449/222915
Resumo: Recent studies have shown that several sources of variation can influence our ability to quantify biological responses to environmental variables, and that spatial scales are important in this process. For instance, sampling methods may differ in their efficiency or specificity, leading to different inferred relationships between community responses and landscape composition—i.e., forest cover (%), landscape heterogeneity, edge effects, and functional connectivity. Consequently, this can also influence the predictive power of the models when evaluating organisms as bioindicators of habitat loss and land use modification. Here, we evaluated how sampling methods (i.e., Winkler, pitfall, beating, and baits) influence our capacity to assess the scale of effect of two landscape composition metrics on ant diversity. We conducted ant sampling in 16 landscapes within a Mexican tropical rainforest and assessed the relationship between species richness and landscape composition metrics through buffers with 12 different spatial extents (from 50 to 1000 m). We found that the sampling method influenced the scale of effect when evaluating the relationships between ant species richness and forest cover and landscape heterogeneity. Combining all sampling methods, we found that the scales that best explained ant species richness were 700 m for forest cover and 900 m for landscape heterogeneity. Therefore, we highlight that our ability to detect ant-based diversity responses to environmental variables depends on the sampling method and spatial extent used in the study.
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spelling Sampling bias in multiscale ant diversity responses to landscape composition in a human-disturbed rainforestForest coverFormicidaeLandscape heterogeneitySampling methodSpatial extentRecent studies have shown that several sources of variation can influence our ability to quantify biological responses to environmental variables, and that spatial scales are important in this process. For instance, sampling methods may differ in their efficiency or specificity, leading to different inferred relationships between community responses and landscape composition—i.e., forest cover (%), landscape heterogeneity, edge effects, and functional connectivity. Consequently, this can also influence the predictive power of the models when evaluating organisms as bioindicators of habitat loss and land use modification. Here, we evaluated how sampling methods (i.e., Winkler, pitfall, beating, and baits) influence our capacity to assess the scale of effect of two landscape composition metrics on ant diversity. We conducted ant sampling in 16 landscapes within a Mexican tropical rainforest and assessed the relationship between species richness and landscape composition metrics through buffers with 12 different spatial extents (from 50 to 1000 m). We found that the sampling method influenced the scale of effect when evaluating the relationships between ant species richness and forest cover and landscape heterogeneity. Combining all sampling methods, we found that the scales that best explained ant species richness were 700 m for forest cover and 900 m for landscape heterogeneity. Therefore, we highlight that our ability to detect ant-based diversity responses to environmental variables depends on the sampling method and spatial extent used in the study.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Consejo Nacional de Ciencia y TecnologíaCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Red de Ecoetología Instituto de Ecología A.C., VeracruzCONACYTRed de Ecología Funcional Instituto de Ecología A.C, VeracruzSpatial Ecology and Conservation Lab (LEEC) Biodiversity Department Bioscience Institute Universidade Estadual Paulista, SPCentro de Investigaciones Tropicales Universidad Veracruzana, VeracruzSpatial Ecology and Conservation Lab (LEEC) Biodiversity Department Bioscience Institute Universidade Estadual Paulista, SPFAPESP: 2013/50421-2CNPq: 312045/2013-1CNPq: 312292/2016-3Consejo Nacional de Ciencia y Tecnología: 584340CAPES: 88881.068425/2014-0Instituto de Ecología A.C.CONACYTInstituto de Ecología A.CUniversidade Estadual Paulista (UNESP)Universidad VeracruzanaAhuatzin, D. A.González-Tokman, D.Valenzuela-González, J. E.Escobar, F.Ribeiro, M. C. [UNESP]Acosta, J. C.L.Dáttilo, W.2022-04-28T19:47:35Z2022-04-28T19:47:35Z2022-02-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article47-58http://dx.doi.org/10.1007/s00040-021-00844-2Insectes Sociaux, v. 69, n. 1, p. 47-58, 2022.1420-90980020-1812http://hdl.handle.net/11449/22291510.1007/s00040-021-00844-22-s2.0-85119891286Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengInsectes Sociauxinfo:eu-repo/semantics/openAccess2022-04-28T19:47:35Zoai:repositorio.unesp.br:11449/222915Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462022-04-28T19:47:35Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Sampling bias in multiscale ant diversity responses to landscape composition in a human-disturbed rainforest
title Sampling bias in multiscale ant diversity responses to landscape composition in a human-disturbed rainforest
spellingShingle Sampling bias in multiscale ant diversity responses to landscape composition in a human-disturbed rainforest
Ahuatzin, D. A.
Forest cover
Formicidae
Landscape heterogeneity
Sampling method
Spatial extent
title_short Sampling bias in multiscale ant diversity responses to landscape composition in a human-disturbed rainforest
title_full Sampling bias in multiscale ant diversity responses to landscape composition in a human-disturbed rainforest
title_fullStr Sampling bias in multiscale ant diversity responses to landscape composition in a human-disturbed rainforest
title_full_unstemmed Sampling bias in multiscale ant diversity responses to landscape composition in a human-disturbed rainforest
title_sort Sampling bias in multiscale ant diversity responses to landscape composition in a human-disturbed rainforest
author Ahuatzin, D. A.
author_facet Ahuatzin, D. A.
González-Tokman, D.
Valenzuela-González, J. E.
Escobar, F.
Ribeiro, M. C. [UNESP]
Acosta, J. C.L.
Dáttilo, W.
author_role author
author2 González-Tokman, D.
Valenzuela-González, J. E.
Escobar, F.
Ribeiro, M. C. [UNESP]
Acosta, J. C.L.
Dáttilo, W.
author2_role author
author
author
author
author
author
dc.contributor.none.fl_str_mv Instituto de Ecología A.C.
CONACYT
Instituto de Ecología A.C
Universidade Estadual Paulista (UNESP)
Universidad Veracruzana
dc.contributor.author.fl_str_mv Ahuatzin, D. A.
González-Tokman, D.
Valenzuela-González, J. E.
Escobar, F.
Ribeiro, M. C. [UNESP]
Acosta, J. C.L.
Dáttilo, W.
dc.subject.por.fl_str_mv Forest cover
Formicidae
Landscape heterogeneity
Sampling method
Spatial extent
topic Forest cover
Formicidae
Landscape heterogeneity
Sampling method
Spatial extent
description Recent studies have shown that several sources of variation can influence our ability to quantify biological responses to environmental variables, and that spatial scales are important in this process. For instance, sampling methods may differ in their efficiency or specificity, leading to different inferred relationships between community responses and landscape composition—i.e., forest cover (%), landscape heterogeneity, edge effects, and functional connectivity. Consequently, this can also influence the predictive power of the models when evaluating organisms as bioindicators of habitat loss and land use modification. Here, we evaluated how sampling methods (i.e., Winkler, pitfall, beating, and baits) influence our capacity to assess the scale of effect of two landscape composition metrics on ant diversity. We conducted ant sampling in 16 landscapes within a Mexican tropical rainforest and assessed the relationship between species richness and landscape composition metrics through buffers with 12 different spatial extents (from 50 to 1000 m). We found that the sampling method influenced the scale of effect when evaluating the relationships between ant species richness and forest cover and landscape heterogeneity. Combining all sampling methods, we found that the scales that best explained ant species richness were 700 m for forest cover and 900 m for landscape heterogeneity. Therefore, we highlight that our ability to detect ant-based diversity responses to environmental variables depends on the sampling method and spatial extent used in the study.
publishDate 2022
dc.date.none.fl_str_mv 2022-04-28T19:47:35Z
2022-04-28T19:47:35Z
2022-02-01
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1007/s00040-021-00844-2
Insectes Sociaux, v. 69, n. 1, p. 47-58, 2022.
1420-9098
0020-1812
http://hdl.handle.net/11449/222915
10.1007/s00040-021-00844-2
2-s2.0-85119891286
url http://dx.doi.org/10.1007/s00040-021-00844-2
http://hdl.handle.net/11449/222915
identifier_str_mv Insectes Sociaux, v. 69, n. 1, p. 47-58, 2022.
1420-9098
0020-1812
10.1007/s00040-021-00844-2
2-s2.0-85119891286
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Insectes Sociaux
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 47-58
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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