Human and biophysical drivers of fires in Semiarid Chaco mountains of Central Argentina

Autores
Argañaraz, Juan Pablo; Gavier Pizarro, Gregorio; Zak, Marcelo Román; Landi, Marcos Alejandro; Bellis, Laura Marisa
Año de publicación
2015
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Fires are a recurrent disturbance in Semiarid Chaco mountains of central Argentina. The interaction of multiple factors generates variable patterns offire occurrence in space and time. Understanding the dominantfire drivers at different spatial scales is a fundamental goal to minimize the negative impacts offires. Our aim was to identify the biophysical and human drivers offires in the Semiarid Chaco mountains of Central Argentina and their individual effects onfire activity, in order to determine the thresholds and/or ranges of the drivers at whichfire occurrence is favored or disfavored. We usedfire frequency as the response variable and a set of 28 potential predictor variables, which included climatic, human, topographic, biological and hydrological factors. Data were analyzed using Boosted Regression Trees, using data from near 10,500 sampling points. Our model identified thefire drivers accurately (75.6% of deviance explained). Although humans are responsible for most ignitions, climatic variables, such as annual precipitation, annual potential evapotranspiration and temperature seasonality were the most important determiners offire frequency, followed by human (population density and distance to waste disposals) and biological (NDVI) predictors. In general,fire activity was higher at intermediate levels of precipitation and primary productivity and in the proximity of urban solid waste disposals. Fires were also more prone to occur in areas with greater variability in temperature and productivity. Boosted Regression Trees proved to be a useful and accurate tool to determinefire controls and the ranges at which drivers favor fire activity. Our approach provides a valuable insight into the ecology offires in our study area and in other landscapes with similar characteristics, and the results will be helpful to develop management policies and predict changes infire activity in response to different climate changes and development scenarios.
Fil: Argañaraz, Juan Pablo. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Cordoba. Instituto de Diversidad y Ecologia Animal; Argentina
Fil: Gavier Pizarro, Gregorio. Instituto Nacional de Tecnología Agropecuaria. Centro Nacional de Investigaciones Agropecuarias. Centro de Investigación de Recursos Naturales. Instituto de Recursos Biológicos; Argentina
Fil: Zak, Marcelo Román. Universidad Nacional de Cordoba. Facultad de Cs.exactas Fisicas y Naturales. Departamento de Diversidad Biologica y Ecologica; Argentina
Fil: Landi, Marcos Alejandro. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Cordoba. Instituto de Diversidad y Ecologia Animal; Argentina
Fil: Bellis, Laura Marisa. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Cordoba. Instituto de Diversidad y Ecologia Animal; Argentina
Materia
Fire Drivers
Fire Ecology
Fire Frequency
Boosted Regression Trees
Semiarid Chaco
Chaco Serrano
Sierras de Córdoba
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:11336/7923
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/7923
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Human and biophysical drivers of fires in Semiarid Chaco mountains of Central ArgentinaArgañaraz, Juan PabloGavier Pizarro, GregorioZak, Marcelo RománLandi, Marcos AlejandroBellis, Laura MarisaFire DriversFire EcologyFire FrequencyBoosted Regression TreesSemiarid ChacoChaco SerranoSierras de Córdobahttps://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1https://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1Fires are a recurrent disturbance in Semiarid Chaco mountains of central Argentina. The interaction of multiple factors generates variable patterns offire occurrence in space and time. Understanding the dominantfire drivers at different spatial scales is a fundamental goal to minimize the negative impacts offires. Our aim was to identify the biophysical and human drivers offires in the Semiarid Chaco mountains of Central Argentina and their individual effects onfire activity, in order to determine the thresholds and/or ranges of the drivers at whichfire occurrence is favored or disfavored. We usedfire frequency as the response variable and a set of 28 potential predictor variables, which included climatic, human, topographic, biological and hydrological factors. Data were analyzed using Boosted Regression Trees, using data from near 10,500 sampling points. Our model identified thefire drivers accurately (75.6% of deviance explained). Although humans are responsible for most ignitions, climatic variables, such as annual precipitation, annual potential evapotranspiration and temperature seasonality were the most important determiners offire frequency, followed by human (population density and distance to waste disposals) and biological (NDVI) predictors. In general,fire activity was higher at intermediate levels of precipitation and primary productivity and in the proximity of urban solid waste disposals. Fires were also more prone to occur in areas with greater variability in temperature and productivity. Boosted Regression Trees proved to be a useful and accurate tool to determinefire controls and the ranges at which drivers favor fire activity. Our approach provides a valuable insight into the ecology offires in our study area and in other landscapes with similar characteristics, and the results will be helpful to develop management policies and predict changes infire activity in response to different climate changes and development scenarios.Fil: Argañaraz, Juan Pablo. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Cordoba. Instituto de Diversidad y Ecologia Animal; ArgentinaFil: Gavier Pizarro, Gregorio. Instituto Nacional de Tecnología Agropecuaria. Centro Nacional de Investigaciones Agropecuarias. Centro de Investigación de Recursos Naturales. Instituto de Recursos Biológicos; ArgentinaFil: Zak, Marcelo Román. Universidad Nacional de Cordoba. Facultad de Cs.exactas Fisicas y Naturales. Departamento de Diversidad Biologica y Ecologica; ArgentinaFil: Landi, Marcos Alejandro. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Cordoba. Instituto de Diversidad y Ecologia Animal; ArgentinaFil: Bellis, Laura Marisa. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Cordoba. Instituto de Diversidad y Ecologia Animal; ArgentinaElsevier Science2015-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/7923Argañaraz, Juan Pablo; Gavier Pizarro, Gregorio; Zak, Marcelo Román; Landi, Marcos Alejandro; Bellis, Laura Marisa; Human and biophysical drivers of fires in Semiarid Chaco mountains of Central Argentina; Elsevier Science; Science Of The Total Environment; 520; 7-2015; 1-120048-9697enginfo:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0048969715002338info:eu-repo/semantics/altIdentifier/doi/10.1016/j.scitotenv.2015.02.081info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T14:26:00Zoai:ri.conicet.gov.ar:11336/7923instacron: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:34982025-10-15 14:26:01.037CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Human and biophysical drivers of fires in Semiarid Chaco mountains of Central Argentina
title Human and biophysical drivers of fires in Semiarid Chaco mountains of Central Argentina
spellingShingle Human and biophysical drivers of fires in Semiarid Chaco mountains of Central Argentina
Argañaraz, Juan Pablo
Fire Drivers
Fire Ecology
Fire Frequency
Boosted Regression Trees
Semiarid Chaco
Chaco Serrano
Sierras de Córdoba
title_short Human and biophysical drivers of fires in Semiarid Chaco mountains of Central Argentina
title_full Human and biophysical drivers of fires in Semiarid Chaco mountains of Central Argentina
title_fullStr Human and biophysical drivers of fires in Semiarid Chaco mountains of Central Argentina
title_full_unstemmed Human and biophysical drivers of fires in Semiarid Chaco mountains of Central Argentina
title_sort Human and biophysical drivers of fires in Semiarid Chaco mountains of Central Argentina
dc.creator.none.fl_str_mv Argañaraz, Juan Pablo
Gavier Pizarro, Gregorio
Zak, Marcelo Román
Landi, Marcos Alejandro
Bellis, Laura Marisa
author Argañaraz, Juan Pablo
author_facet Argañaraz, Juan Pablo
Gavier Pizarro, Gregorio
Zak, Marcelo Román
Landi, Marcos Alejandro
Bellis, Laura Marisa
author_role author
author2 Gavier Pizarro, Gregorio
Zak, Marcelo Román
Landi, Marcos Alejandro
Bellis, Laura Marisa
author2_role author
author
author
author
dc.subject.none.fl_str_mv Fire Drivers
Fire Ecology
Fire Frequency
Boosted Regression Trees
Semiarid Chaco
Chaco Serrano
Sierras de Córdoba
topic Fire Drivers
Fire Ecology
Fire Frequency
Boosted Regression Trees
Semiarid Chaco
Chaco Serrano
Sierras de Córdoba
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.5
https://purl.org/becyt/ford/1
https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Fires are a recurrent disturbance in Semiarid Chaco mountains of central Argentina. The interaction of multiple factors generates variable patterns offire occurrence in space and time. Understanding the dominantfire drivers at different spatial scales is a fundamental goal to minimize the negative impacts offires. Our aim was to identify the biophysical and human drivers offires in the Semiarid Chaco mountains of Central Argentina and their individual effects onfire activity, in order to determine the thresholds and/or ranges of the drivers at whichfire occurrence is favored or disfavored. We usedfire frequency as the response variable and a set of 28 potential predictor variables, which included climatic, human, topographic, biological and hydrological factors. Data were analyzed using Boosted Regression Trees, using data from near 10,500 sampling points. Our model identified thefire drivers accurately (75.6% of deviance explained). Although humans are responsible for most ignitions, climatic variables, such as annual precipitation, annual potential evapotranspiration and temperature seasonality were the most important determiners offire frequency, followed by human (population density and distance to waste disposals) and biological (NDVI) predictors. In general,fire activity was higher at intermediate levels of precipitation and primary productivity and in the proximity of urban solid waste disposals. Fires were also more prone to occur in areas with greater variability in temperature and productivity. Boosted Regression Trees proved to be a useful and accurate tool to determinefire controls and the ranges at which drivers favor fire activity. Our approach provides a valuable insight into the ecology offires in our study area and in other landscapes with similar characteristics, and the results will be helpful to develop management policies and predict changes infire activity in response to different climate changes and development scenarios.
Fil: Argañaraz, Juan Pablo. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Cordoba. Instituto de Diversidad y Ecologia Animal; Argentina
Fil: Gavier Pizarro, Gregorio. Instituto Nacional de Tecnología Agropecuaria. Centro Nacional de Investigaciones Agropecuarias. Centro de Investigación de Recursos Naturales. Instituto de Recursos Biológicos; Argentina
Fil: Zak, Marcelo Román. Universidad Nacional de Cordoba. Facultad de Cs.exactas Fisicas y Naturales. Departamento de Diversidad Biologica y Ecologica; Argentina
Fil: Landi, Marcos Alejandro. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Cordoba. Instituto de Diversidad y Ecologia Animal; Argentina
Fil: Bellis, Laura Marisa. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Cordoba. Instituto de Diversidad y Ecologia Animal; Argentina
description Fires are a recurrent disturbance in Semiarid Chaco mountains of central Argentina. The interaction of multiple factors generates variable patterns offire occurrence in space and time. Understanding the dominantfire drivers at different spatial scales is a fundamental goal to minimize the negative impacts offires. Our aim was to identify the biophysical and human drivers offires in the Semiarid Chaco mountains of Central Argentina and their individual effects onfire activity, in order to determine the thresholds and/or ranges of the drivers at whichfire occurrence is favored or disfavored. We usedfire frequency as the response variable and a set of 28 potential predictor variables, which included climatic, human, topographic, biological and hydrological factors. Data were analyzed using Boosted Regression Trees, using data from near 10,500 sampling points. Our model identified thefire drivers accurately (75.6% of deviance explained). Although humans are responsible for most ignitions, climatic variables, such as annual precipitation, annual potential evapotranspiration and temperature seasonality were the most important determiners offire frequency, followed by human (population density and distance to waste disposals) and biological (NDVI) predictors. In general,fire activity was higher at intermediate levels of precipitation and primary productivity and in the proximity of urban solid waste disposals. Fires were also more prone to occur in areas with greater variability in temperature and productivity. Boosted Regression Trees proved to be a useful and accurate tool to determinefire controls and the ranges at which drivers favor fire activity. Our approach provides a valuable insight into the ecology offires in our study area and in other landscapes with similar characteristics, and the results will be helpful to develop management policies and predict changes infire activity in response to different climate changes and development scenarios.
publishDate 2015
dc.date.none.fl_str_mv 2015-07
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/11336/7923
Argañaraz, Juan Pablo; Gavier Pizarro, Gregorio; Zak, Marcelo Román; Landi, Marcos Alejandro; Bellis, Laura Marisa; Human and biophysical drivers of fires in Semiarid Chaco mountains of Central Argentina; Elsevier Science; Science Of The Total Environment; 520; 7-2015; 1-12
0048-9697
url http://hdl.handle.net/11336/7923
identifier_str_mv Argañaraz, Juan Pablo; Gavier Pizarro, Gregorio; Zak, Marcelo Román; Landi, Marcos Alejandro; Bellis, Laura Marisa; Human and biophysical drivers of fires in Semiarid Chaco mountains of Central Argentina; Elsevier Science; Science Of The Total Environment; 520; 7-2015; 1-12
0048-9697
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0048969715002338
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.scitotenv.2015.02.081
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
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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