Vegetation Type mapping in Southern Patagonia and its relationship with ecosystem services, soil carbon stock, and biodiversity

Autores
Peri, Pablo Luis; Gaitán, Juan José; Diaz, Boris Gastón; Almonacid, Leandro; Morales, Cristian; Ferrerer, Francisco; Lasagno, Romina; Rodriguez Souilla, Julian; Martínez Pastur, Guillermo José
Año de publicación
2024
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Vegetation Type (VT) mapping using Optical Earth observation data is essential for the management and conservation of natural resources, as well as for the evaluation of the supply of provisioning ecosystem services (ESs), the maintenance of ecosystem functions, and the conservation of biodiversity in anthropized environments. The main objective of the present work was to determine the spatial patterns of VTs related to climatic, topographic, and spectral variables across Santa Cruz province (Southern Patagonia, Argentina) in order to improve our understanding of land use cover at the regional scale. Also, we examined the spatial relationship between VTs and potential biodiversity (PB), ESs, and soil organic content (SOC) across our study region. We sampled 59,285 sites sorted into 19 major categories of land cover with a reliable discrimination level from field measurements. We selected 31 potential predictive environmental dataset covariates, which represent key factors for the spatial distribution of land cover such as climate (four), topography (three), and spectral (24) factors. All covariate maps were generated or uploaded to the Google Earth Engine cloud-based computing platform for subsequent modeling. A total of 270,292 sampling points were used for validation of the obtained classification map. The main land cover area estimates extracted from the map at the regional level identified about 142,085 km2 of grasslands (representing 58.1% of the total area), 38,355 km2 of Mata Negra Matorral thicket (15.7%), and about 25,189 km2 of bare soil (10.3%). From validation, the Overall Accuracy and the Kappa coefficient values for the classification map were 90.40% and 0.87, respectively. Pure and mixed forests presented the maximum SOC (11.3–11.8 kg m−2), followed by peatlands (10.6 kg m−2) and deciduous Nothofagus forests (10.5 kg m−2). The potential biodiversity was higher in some shrublands (64.1% in Mata Verde shrublands and 63.7% in mixed shrublands) and was comparable to those values found for open deciduous forests (Nothofagus antarctica forest with 60.4%). The provision of ESs presented maximum values at pure evergreen forests (56.7%) and minimum values at some shrubland types (Mata Negra Matorral thicket and mixed shrubland) and steppe grasslands (29.7–30.9%). This study has provided an accurate land cover and VT map that provides crucial information for ecological studies, biodiversity conservation, vegetation management and restoration, and regional strategic decision-making.
Fil: Peri, Pablo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro de Investigaciones y Transferencia de Santa Cruz. Universidad Tecnológica Nacional. Facultad Regional Santa Cruz. Centro de Investigaciones y Transferencia de Santa Cruz. Universidad Nacional de la Patagonia Austral. Centro de Investigaciones y Transferencia de Santa Cruz; Argentina
Fil: Gaitán, Juan José. Universidad Nacional de Luján; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Diaz, Boris Gastón. Instituto Nacional de Tecnología Agropecuaria; Argentina
Fil: Almonacid, Leandro. Instituto Nacional de Tecnología Agropecuaria; Argentina
Fil: Morales, Cristian. Instituto Nacional de Tecnología Agropecuaria; Argentina
Fil: Ferrerer, Francisco. Universidad Nacional de la Patagonia Austral; Argentina
Fil: Lasagno, Romina. Instituto Nacional de Tecnología Agropecuaria; Argentina
Fil: Rodriguez Souilla, Julian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas; Argentina
Fil: Martínez Pastur, Guillermo José. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas; Argentina
Materia
RANGELAND
LIVESTOCK
PLANT BIODIVERSITY
ECOSYSTEM SERVICES
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:11336/230669

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network_name_str CONICET Digital (CONICET)
spelling Vegetation Type mapping in Southern Patagonia and its relationship with ecosystem services, soil carbon stock, and biodiversityPeri, Pablo LuisGaitán, Juan JoséDiaz, Boris GastónAlmonacid, LeandroMorales, CristianFerrerer, FranciscoLasagno, RominaRodriguez Souilla, JulianMartínez Pastur, Guillermo JoséRANGELANDLIVESTOCKPLANT BIODIVERSITYECOSYSTEM SERVICEShttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1Vegetation Type (VT) mapping using Optical Earth observation data is essential for the management and conservation of natural resources, as well as for the evaluation of the supply of provisioning ecosystem services (ESs), the maintenance of ecosystem functions, and the conservation of biodiversity in anthropized environments. The main objective of the present work was to determine the spatial patterns of VTs related to climatic, topographic, and spectral variables across Santa Cruz province (Southern Patagonia, Argentina) in order to improve our understanding of land use cover at the regional scale. Also, we examined the spatial relationship between VTs and potential biodiversity (PB), ESs, and soil organic content (SOC) across our study region. We sampled 59,285 sites sorted into 19 major categories of land cover with a reliable discrimination level from field measurements. We selected 31 potential predictive environmental dataset covariates, which represent key factors for the spatial distribution of land cover such as climate (four), topography (three), and spectral (24) factors. All covariate maps were generated or uploaded to the Google Earth Engine cloud-based computing platform for subsequent modeling. A total of 270,292 sampling points were used for validation of the obtained classification map. The main land cover area estimates extracted from the map at the regional level identified about 142,085 km2 of grasslands (representing 58.1% of the total area), 38,355 km2 of Mata Negra Matorral thicket (15.7%), and about 25,189 km2 of bare soil (10.3%). From validation, the Overall Accuracy and the Kappa coefficient values for the classification map were 90.40% and 0.87, respectively. Pure and mixed forests presented the maximum SOC (11.3–11.8 kg m−2), followed by peatlands (10.6 kg m−2) and deciduous Nothofagus forests (10.5 kg m−2). The potential biodiversity was higher in some shrublands (64.1% in Mata Verde shrublands and 63.7% in mixed shrublands) and was comparable to those values found for open deciduous forests (Nothofagus antarctica forest with 60.4%). The provision of ESs presented maximum values at pure evergreen forests (56.7%) and minimum values at some shrubland types (Mata Negra Matorral thicket and mixed shrubland) and steppe grasslands (29.7–30.9%). This study has provided an accurate land cover and VT map that provides crucial information for ecological studies, biodiversity conservation, vegetation management and restoration, and regional strategic decision-making.Fil: Peri, Pablo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro de Investigaciones y Transferencia de Santa Cruz. Universidad Tecnológica Nacional. Facultad Regional Santa Cruz. Centro de Investigaciones y Transferencia de Santa Cruz. Universidad Nacional de la Patagonia Austral. Centro de Investigaciones y Transferencia de Santa Cruz; ArgentinaFil: Gaitán, Juan José. Universidad Nacional de Luján; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Diaz, Boris Gastón. Instituto Nacional de Tecnología Agropecuaria; ArgentinaFil: Almonacid, Leandro. Instituto Nacional de Tecnología Agropecuaria; ArgentinaFil: Morales, Cristian. Instituto Nacional de Tecnología Agropecuaria; ArgentinaFil: Ferrerer, Francisco. Universidad Nacional de la Patagonia Austral; ArgentinaFil: Lasagno, Romina. Instituto Nacional de Tecnología Agropecuaria; ArgentinaFil: Rodriguez Souilla, Julian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas; ArgentinaFil: Martínez Pastur, Guillermo José. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas; ArgentinaMDPI2024-02info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/230669Peri, Pablo Luis; Gaitán, Juan José; Diaz, Boris Gastón; Almonacid, Leandro; Morales, Cristian ; et al.; Vegetation Type mapping in Southern Patagonia and its relationship with ecosystem services, soil carbon stock, and biodiversity; MDPI; Sustainability; 16; 2025; 2-2024; 1-152071-1050CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.3390/su16052025info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:05:56Zoai:ri.conicet.gov.ar:11336/230669instacron: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:34982025-09-29 10:05:57.192CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Vegetation Type mapping in Southern Patagonia and its relationship with ecosystem services, soil carbon stock, and biodiversity
title Vegetation Type mapping in Southern Patagonia and its relationship with ecosystem services, soil carbon stock, and biodiversity
spellingShingle Vegetation Type mapping in Southern Patagonia and its relationship with ecosystem services, soil carbon stock, and biodiversity
Peri, Pablo Luis
RANGELAND
LIVESTOCK
PLANT BIODIVERSITY
ECOSYSTEM SERVICES
title_short Vegetation Type mapping in Southern Patagonia and its relationship with ecosystem services, soil carbon stock, and biodiversity
title_full Vegetation Type mapping in Southern Patagonia and its relationship with ecosystem services, soil carbon stock, and biodiversity
title_fullStr Vegetation Type mapping in Southern Patagonia and its relationship with ecosystem services, soil carbon stock, and biodiversity
title_full_unstemmed Vegetation Type mapping in Southern Patagonia and its relationship with ecosystem services, soil carbon stock, and biodiversity
title_sort Vegetation Type mapping in Southern Patagonia and its relationship with ecosystem services, soil carbon stock, and biodiversity
dc.creator.none.fl_str_mv Peri, Pablo Luis
Gaitán, Juan José
Diaz, Boris Gastón
Almonacid, Leandro
Morales, Cristian
Ferrerer, Francisco
Lasagno, Romina
Rodriguez Souilla, Julian
Martínez Pastur, Guillermo José
author Peri, Pablo Luis
author_facet Peri, Pablo Luis
Gaitán, Juan José
Diaz, Boris Gastón
Almonacid, Leandro
Morales, Cristian
Ferrerer, Francisco
Lasagno, Romina
Rodriguez Souilla, Julian
Martínez Pastur, Guillermo José
author_role author
author2 Gaitán, Juan José
Diaz, Boris Gastón
Almonacid, Leandro
Morales, Cristian
Ferrerer, Francisco
Lasagno, Romina
Rodriguez Souilla, Julian
Martínez Pastur, Guillermo José
author2_role author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv RANGELAND
LIVESTOCK
PLANT BIODIVERSITY
ECOSYSTEM SERVICES
topic RANGELAND
LIVESTOCK
PLANT BIODIVERSITY
ECOSYSTEM SERVICES
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Vegetation Type (VT) mapping using Optical Earth observation data is essential for the management and conservation of natural resources, as well as for the evaluation of the supply of provisioning ecosystem services (ESs), the maintenance of ecosystem functions, and the conservation of biodiversity in anthropized environments. The main objective of the present work was to determine the spatial patterns of VTs related to climatic, topographic, and spectral variables across Santa Cruz province (Southern Patagonia, Argentina) in order to improve our understanding of land use cover at the regional scale. Also, we examined the spatial relationship between VTs and potential biodiversity (PB), ESs, and soil organic content (SOC) across our study region. We sampled 59,285 sites sorted into 19 major categories of land cover with a reliable discrimination level from field measurements. We selected 31 potential predictive environmental dataset covariates, which represent key factors for the spatial distribution of land cover such as climate (four), topography (three), and spectral (24) factors. All covariate maps were generated or uploaded to the Google Earth Engine cloud-based computing platform for subsequent modeling. A total of 270,292 sampling points were used for validation of the obtained classification map. The main land cover area estimates extracted from the map at the regional level identified about 142,085 km2 of grasslands (representing 58.1% of the total area), 38,355 km2 of Mata Negra Matorral thicket (15.7%), and about 25,189 km2 of bare soil (10.3%). From validation, the Overall Accuracy and the Kappa coefficient values for the classification map were 90.40% and 0.87, respectively. Pure and mixed forests presented the maximum SOC (11.3–11.8 kg m−2), followed by peatlands (10.6 kg m−2) and deciduous Nothofagus forests (10.5 kg m−2). The potential biodiversity was higher in some shrublands (64.1% in Mata Verde shrublands and 63.7% in mixed shrublands) and was comparable to those values found for open deciduous forests (Nothofagus antarctica forest with 60.4%). The provision of ESs presented maximum values at pure evergreen forests (56.7%) and minimum values at some shrubland types (Mata Negra Matorral thicket and mixed shrubland) and steppe grasslands (29.7–30.9%). This study has provided an accurate land cover and VT map that provides crucial information for ecological studies, biodiversity conservation, vegetation management and restoration, and regional strategic decision-making.
Fil: Peri, Pablo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro de Investigaciones y Transferencia de Santa Cruz. Universidad Tecnológica Nacional. Facultad Regional Santa Cruz. Centro de Investigaciones y Transferencia de Santa Cruz. Universidad Nacional de la Patagonia Austral. Centro de Investigaciones y Transferencia de Santa Cruz; Argentina
Fil: Gaitán, Juan José. Universidad Nacional de Luján; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Diaz, Boris Gastón. Instituto Nacional de Tecnología Agropecuaria; Argentina
Fil: Almonacid, Leandro. Instituto Nacional de Tecnología Agropecuaria; Argentina
Fil: Morales, Cristian. Instituto Nacional de Tecnología Agropecuaria; Argentina
Fil: Ferrerer, Francisco. Universidad Nacional de la Patagonia Austral; Argentina
Fil: Lasagno, Romina. Instituto Nacional de Tecnología Agropecuaria; Argentina
Fil: Rodriguez Souilla, Julian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas; Argentina
Fil: Martínez Pastur, Guillermo José. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas; Argentina
description Vegetation Type (VT) mapping using Optical Earth observation data is essential for the management and conservation of natural resources, as well as for the evaluation of the supply of provisioning ecosystem services (ESs), the maintenance of ecosystem functions, and the conservation of biodiversity in anthropized environments. The main objective of the present work was to determine the spatial patterns of VTs related to climatic, topographic, and spectral variables across Santa Cruz province (Southern Patagonia, Argentina) in order to improve our understanding of land use cover at the regional scale. Also, we examined the spatial relationship between VTs and potential biodiversity (PB), ESs, and soil organic content (SOC) across our study region. We sampled 59,285 sites sorted into 19 major categories of land cover with a reliable discrimination level from field measurements. We selected 31 potential predictive environmental dataset covariates, which represent key factors for the spatial distribution of land cover such as climate (four), topography (three), and spectral (24) factors. All covariate maps were generated or uploaded to the Google Earth Engine cloud-based computing platform for subsequent modeling. A total of 270,292 sampling points were used for validation of the obtained classification map. The main land cover area estimates extracted from the map at the regional level identified about 142,085 km2 of grasslands (representing 58.1% of the total area), 38,355 km2 of Mata Negra Matorral thicket (15.7%), and about 25,189 km2 of bare soil (10.3%). From validation, the Overall Accuracy and the Kappa coefficient values for the classification map were 90.40% and 0.87, respectively. Pure and mixed forests presented the maximum SOC (11.3–11.8 kg m−2), followed by peatlands (10.6 kg m−2) and deciduous Nothofagus forests (10.5 kg m−2). The potential biodiversity was higher in some shrublands (64.1% in Mata Verde shrublands and 63.7% in mixed shrublands) and was comparable to those values found for open deciduous forests (Nothofagus antarctica forest with 60.4%). The provision of ESs presented maximum values at pure evergreen forests (56.7%) and minimum values at some shrubland types (Mata Negra Matorral thicket and mixed shrubland) and steppe grasslands (29.7–30.9%). This study has provided an accurate land cover and VT map that provides crucial information for ecological studies, biodiversity conservation, vegetation management and restoration, and regional strategic decision-making.
publishDate 2024
dc.date.none.fl_str_mv 2024-02
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/11336/230669
Peri, Pablo Luis; Gaitán, Juan José; Diaz, Boris Gastón; Almonacid, Leandro; Morales, Cristian ; et al.; Vegetation Type mapping in Southern Patagonia and its relationship with ecosystem services, soil carbon stock, and biodiversity; MDPI; Sustainability; 16; 2025; 2-2024; 1-15
2071-1050
CONICET Digital
CONICET
url http://hdl.handle.net/11336/230669
identifier_str_mv Peri, Pablo Luis; Gaitán, Juan José; Diaz, Boris Gastón; Almonacid, Leandro; Morales, Cristian ; et al.; Vegetation Type mapping in Southern Patagonia and its relationship with ecosystem services, soil carbon stock, and biodiversity; MDPI; Sustainability; 16; 2025; 2-2024; 1-15
2071-1050
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.3390/su16052025
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 MDPI
publisher.none.fl_str_mv MDPI
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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