Data poa scaberula distribucion en sudamérica

Autores
Scrivanti, Lidia Raquel; Anton, Ana Maria Ramona
Año de publicación
2022
Idioma
español castellano
Tipo de recurso
conjunto de datos
Estado
versión publicada
Descripción
Fil: Scrivanti, Lidia Raquel. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales; Argentina.
Fil: Anton, Ana Maria Ramona. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales; Argentina
Fil: Scrivanti, Lidia Raquel. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto Multidisciplinario de Biología Vegetal; Argentina.
Fil: Anton, Ana Maria Ramona. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto Multidisciplinario de Biología Vegetal; Argentina.
Grasslands play an important ecological role and are the dominant landscape in the whole extent of the Andes and high elevation regions of South America. Climate change models indicate a strong impact on mountain systems. The climatic conditions of mountain systems are greatly influenced by topography and elevation. Poa scaberula Hook. f. is an Andean grass and its habitat may be threatened by climate change and human practices. Species distribution models, using bioclimatic variables, are often used to predict the future distribution and environmental requirements of species. In this study we prepared two bioclimatic models for P. scaberula using the Maxent algorithm, the first based on the inclusion of the variable elevation (E +) and the second on the exclusion of elevation (E-) to identify the main environmental variables for habitat suitability shift, to examine changes in the extent of the area of suitable habitat under current and future climate scenarios, and to project and quantify the spatial pattern of shifts in the areal extent of suitable habitat under future climate conditions. We then compared both projections and evaluate the contribution of the elevation variable in the performance of the models. We observed that the inclusion of elevation decreased the performance of the models. In models with omission of the elevation mean cold hardiness, temperature seasonality and annual mean temperature emerge as the critical factors shaping habitat suitability for P. scaberula. Under the low and higher concentration greenhouse gas emissions scenario, the range of the species may decrease as global warming intensifies. The information gained from this study should be an useful reference for development biogeographic studies and the impact of global warming on regions of high elevations, and contribute to implement conservation and management strategies for Andean grassland and high elevation grasslands.
Fil: Scrivanti, Lidia Raquel. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales; Argentina.
Fil: Anton, Ana Maria Ramona. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales; Argentina
Fil: Scrivanti, Lidia Raquel. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto Multidisciplinario de Biología Vegetal; Argentina.
Fil: Anton, Ana Maria Ramona. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto Multidisciplinario de Biología Vegetal; Argentina.
Materia
Andes
Climate change
Current and future suitable habitat
Elevation
Poa scaberula
Species distribution
Nivel de accesibilidad
acceso abierto
Condiciones de uso
Repositorio
Repositorio Digital Universitario (UNC)
Institución
Universidad Nacional de Córdoba
OAI Identificador
oai:rdu.unc.edu.ar:11086/548629
Acceder
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oai_identifier_str oai:rdu.unc.edu.ar:11086/548629
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repository_id_str 2572
network_name_str Repositorio Digital Universitario (UNC)
spelling Data poa scaberula distribucion en sudaméricaScrivanti, Lidia RaquelAnton, Ana Maria RamonaAndesClimate changeCurrent and future suitable habitatElevationPoa scaberulaSpecies distributionhttps://purl.org/becyt/ford/1.6Fil: Scrivanti, Lidia Raquel. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales; Argentina.Fil: Anton, Ana Maria Ramona. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales; ArgentinaFil: Scrivanti, Lidia Raquel. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto Multidisciplinario de Biología Vegetal; Argentina.Fil: Anton, Ana Maria Ramona. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto Multidisciplinario de Biología Vegetal; Argentina.Grasslands play an important ecological role and are the dominant landscape in the whole extent of the Andes and high elevation regions of South America. Climate change models indicate a strong impact on mountain systems. The climatic conditions of mountain systems are greatly influenced by topography and elevation. Poa scaberula Hook. f. is an Andean grass and its habitat may be threatened by climate change and human practices. Species distribution models, using bioclimatic variables, are often used to predict the future distribution and environmental requirements of species. In this study we prepared two bioclimatic models for P. scaberula using the Maxent algorithm, the first based on the inclusion of the variable elevation (E +) and the second on the exclusion of elevation (E-) to identify the main environmental variables for habitat suitability shift, to examine changes in the extent of the area of suitable habitat under current and future climate scenarios, and to project and quantify the spatial pattern of shifts in the areal extent of suitable habitat under future climate conditions. We then compared both projections and evaluate the contribution of the elevation variable in the performance of the models. We observed that the inclusion of elevation decreased the performance of the models. In models with omission of the elevation mean cold hardiness, temperature seasonality and annual mean temperature emerge as the critical factors shaping habitat suitability for P. scaberula. Under the low and higher concentration greenhouse gas emissions scenario, the range of the species may decrease as global warming intensifies. The information gained from this study should be an useful reference for development biogeographic studies and the impact of global warming on regions of high elevations, and contribute to implement conservation and management strategies for Andean grassland and high elevation grasslands.Fil: Scrivanti, Lidia Raquel. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales; Argentina.Fil: Anton, Ana Maria Ramona. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales; ArgentinaFil: Scrivanti, Lidia Raquel. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto Multidisciplinario de Biología Vegetal; Argentina.Fil: Anton, Ana Maria Ramona. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto Multidisciplinario de Biología Vegetal; Argentina.https://orcid.org/0000-0002-0991-439X2022info:eu-repo/semantics/dataSetinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_ddb1info:ar-repo/semantics/conjuntoDeDatosapplication/vnd.openxmlformats-officedocument.wordprocessingml.documentimage/tiffapplication/vnd.openxmlformats-officedocument.spreadsheetml.sheetimage/tiffimage/tiffimage/tifftext/csvimage/tiffimage/tiffhttp://hdl.handle.net/11086/548629spainfo:eu-repo/semantics/openAccessreponame:Repositorio Digital Universitario (UNC)instname:Universidad Nacional de Córdobainstacron:UNC2025-09-29T13:44:19Zoai:rdu.unc.edu.ar:11086/548629Institucionalhttps://rdu.unc.edu.ar/Universidad públicaNo correspondehttp://rdu.unc.edu.ar/oai/snrdoca.unc@gmail.comArgentinaNo correspondeNo correspondeNo correspondeopendoar:25722025-09-29 13:44:20.135Repositorio Digital Universitario (UNC) - Universidad Nacional de Córdobafalse
dc.title.none.fl_str_mv Data poa scaberula distribucion en sudamérica
title Data poa scaberula distribucion en sudamérica
spellingShingle Data poa scaberula distribucion en sudamérica
Scrivanti, Lidia Raquel
Andes
Climate change
Current and future suitable habitat
Elevation
Poa scaberula
Species distribution
title_short Data poa scaberula distribucion en sudamérica
title_full Data poa scaberula distribucion en sudamérica
title_fullStr Data poa scaberula distribucion en sudamérica
title_full_unstemmed Data poa scaberula distribucion en sudamérica
title_sort Data poa scaberula distribucion en sudamérica
dc.creator.none.fl_str_mv Scrivanti, Lidia Raquel
Anton, Ana Maria Ramona
author Scrivanti, Lidia Raquel
author_facet Scrivanti, Lidia Raquel
Anton, Ana Maria Ramona
author_role author
author2 Anton, Ana Maria Ramona
author2_role author
dc.contributor.none.fl_str_mv https://orcid.org/0000-0002-0991-439X
dc.subject.none.fl_str_mv Andes
Climate change
Current and future suitable habitat
Elevation
Poa scaberula
Species distribution
topic Andes
Climate change
Current and future suitable habitat
Elevation
Poa scaberula
Species distribution
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.6
dc.description.none.fl_txt_mv Fil: Scrivanti, Lidia Raquel. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales; Argentina.
Fil: Anton, Ana Maria Ramona. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales; Argentina
Fil: Scrivanti, Lidia Raquel. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto Multidisciplinario de Biología Vegetal; Argentina.
Fil: Anton, Ana Maria Ramona. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto Multidisciplinario de Biología Vegetal; Argentina.
Grasslands play an important ecological role and are the dominant landscape in the whole extent of the Andes and high elevation regions of South America. Climate change models indicate a strong impact on mountain systems. The climatic conditions of mountain systems are greatly influenced by topography and elevation. Poa scaberula Hook. f. is an Andean grass and its habitat may be threatened by climate change and human practices. Species distribution models, using bioclimatic variables, are often used to predict the future distribution and environmental requirements of species. In this study we prepared two bioclimatic models for P. scaberula using the Maxent algorithm, the first based on the inclusion of the variable elevation (E +) and the second on the exclusion of elevation (E-) to identify the main environmental variables for habitat suitability shift, to examine changes in the extent of the area of suitable habitat under current and future climate scenarios, and to project and quantify the spatial pattern of shifts in the areal extent of suitable habitat under future climate conditions. We then compared both projections and evaluate the contribution of the elevation variable in the performance of the models. We observed that the inclusion of elevation decreased the performance of the models. In models with omission of the elevation mean cold hardiness, temperature seasonality and annual mean temperature emerge as the critical factors shaping habitat suitability for P. scaberula. Under the low and higher concentration greenhouse gas emissions scenario, the range of the species may decrease as global warming intensifies. The information gained from this study should be an useful reference for development biogeographic studies and the impact of global warming on regions of high elevations, and contribute to implement conservation and management strategies for Andean grassland and high elevation grasslands.
Fil: Scrivanti, Lidia Raquel. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales; Argentina.
Fil: Anton, Ana Maria Ramona. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales; Argentina
Fil: Scrivanti, Lidia Raquel. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto Multidisciplinario de Biología Vegetal; Argentina.
Fil: Anton, Ana Maria Ramona. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto Multidisciplinario de Biología Vegetal; Argentina.
description Fil: Scrivanti, Lidia Raquel. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales; Argentina.
publishDate 2022
dc.date.none.fl_str_mv 2022
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