Mapping soil organic carbon content in Patagonian forests based on climate, topography and vegetation metrics from satellite imagery

Autores
Martínez Pastur, Guillermo José; Aravena Acuña, Marie Claire; Silveira, Eduarda M.O.; Von Müller, Axel; La Manna, Ludmila; González Polo, Marina; Chaves, Jimena Elizabeth; Cellini, Juan Manuel; Lencinas, María Vanessa; Radeloff, Volker C.; Pidgeon, Anna Michle; Peri, Pablo Luis
Año de publicación
2022
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Soil organic carbon (SOC) content supports several ecosystem services. Quantifying SOC requires: (i) accurate C estimates of forest components, and (ii) soil estimates. However, SOC is difficult to measure, so predictive models are needed. Our objective was to model SOC stocks within 30 cm depth in Patagonian forests based on climatic, topographic and vegetation productivity measures from satellite images, including Dynamic Habitat Indices and Land Surface Temperature derived from Landsat-8. We used data from 1320 stands of different forest types in Patagonia, and random forest regression to map SOC. The model captured SOC variability well (R2 = 0.60, RMSE = 22.1%), considering the huge latitudinal extension (36.4◦ to 55.1◦ SL) and the great diversity of forest types. Mean SOC was 134.4 ton C ha−1 ± 25.2, totaling 404.2 million ton C across Patagonia. Overall, SOC values were highest in valleys of the Andes mountains and in southern Tierra del Fuego, ranging from 53.5 to 277.8 ton C ha−1 for the whole Patagonia region. Soil organic carbon is a metric relevant to many applications, connecting major issues such as forest management, conservation, and livestock production, and having spatially explicit estimates of SOC enables managers to fulfil the international agreements that Argentina has joined.
EEA Esquel
Fil: Martínez Pastur, Guillermo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas (CADIC). Laboratorio de Recursos Agroforestales; Argentina
Fil: Aravena Acuña, Marie Claire. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas (CADIC). Laboratorio de Recursos Agroforestales; Argentina
Fil: Silveira, Eduarda M. O. University of Wisconsin. Department of Forest and Wildlife Ecology. SILVIS Lab.; Estados Unidos
Fil: von Müller, Axel. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agroforestal Esquel; Argentina
Fil: La Manna, Ludmila. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: La Manna, Ludmila. Universidad Nacional de la Patagonia San Juan Bosco. Facultad de Ingeniería. Centro de Estudios Ambientales Integrados; Argentina
Fil: González Polo, Marina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: González Polo, Marina. Universidad Nacional del Comahue. Instituto de Investigaciones en Biodiversidad y Medioambiente (INIBIOMA); Argentina
Fil: Chaves, Jimena E. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas (CADIC). Laboratorio de Recursos Agroforestales; Argentina
Fil: Cellini, Juan M. Universidad Nacional de La Plata. Laboratorio de Investigaciones en Maderas (LIMAD); Argentina
Fil: Lencinas, María V. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas (CADIC). Laboratorio de Recursos Agroforestales; Argentina
Fil: Radeloff, Volker C. University of Wisconsin. Department of Forest and Wildlife Ecology. SILVIS Lab.; Estados Unidos
Fil: Pidgeon, Anna M. University of Wisconsin. Department of Forest and Wildlife Ecology. SILVIS Lab.; Estados Unidos
Fil: Peri, Pablo Luis. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; Argentina.
Fil: Peri, Pablo Luis. Universidad Nacional de la Patagonia Austral; Argentina.
Fil: Peri, Pablo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.
Fuente
Remote Sensing 14 : 5702. (2022)
Materia
Soil Organic Carbon
Primary Forests
Satellite Imagery
Carbono Orgánico del Suelo
Bosque Primario
Imágenes por Satélites
Landsat-8
Región Patagónica
Dynamic Habitat Indices
Bosques Nativos
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
INTA Digital (INTA)
Institución
Instituto Nacional de Tecnología Agropecuaria
OAI Identificador
oai:localhost:20.500.12123/13417
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spelling Mapping soil organic carbon content in Patagonian forests based on climate, topography and vegetation metrics from satellite imageryMartínez Pastur, Guillermo JoséAravena Acuña, Marie ClaireSilveira, Eduarda M.O.Von Müller, AxelLa Manna, LudmilaGonzález Polo, MarinaChaves, Jimena ElizabethCellini, Juan ManuelLencinas, María VanessaRadeloff, Volker C.Pidgeon, Anna MichlePeri, Pablo LuisSoil Organic CarbonPrimary ForestsSatellite ImageryCarbono Orgánico del SueloBosque PrimarioImágenes por SatélitesLandsat-8Región PatagónicaDynamic Habitat IndicesBosques NativosSoil organic carbon (SOC) content supports several ecosystem services. Quantifying SOC requires: (i) accurate C estimates of forest components, and (ii) soil estimates. However, SOC is difficult to measure, so predictive models are needed. Our objective was to model SOC stocks within 30 cm depth in Patagonian forests based on climatic, topographic and vegetation productivity measures from satellite images, including Dynamic Habitat Indices and Land Surface Temperature derived from Landsat-8. We used data from 1320 stands of different forest types in Patagonia, and random forest regression to map SOC. The model captured SOC variability well (R2 = 0.60, RMSE = 22.1%), considering the huge latitudinal extension (36.4◦ to 55.1◦ SL) and the great diversity of forest types. Mean SOC was 134.4 ton C ha−1 ± 25.2, totaling 404.2 million ton C across Patagonia. Overall, SOC values were highest in valleys of the Andes mountains and in southern Tierra del Fuego, ranging from 53.5 to 277.8 ton C ha−1 for the whole Patagonia region. Soil organic carbon is a metric relevant to many applications, connecting major issues such as forest management, conservation, and livestock production, and having spatially explicit estimates of SOC enables managers to fulfil the international agreements that Argentina has joined.EEA EsquelFil: Martínez Pastur, Guillermo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas (CADIC). Laboratorio de Recursos Agroforestales; ArgentinaFil: Aravena Acuña, Marie Claire. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas (CADIC). Laboratorio de Recursos Agroforestales; ArgentinaFil: Silveira, Eduarda M. O. University of Wisconsin. Department of Forest and Wildlife Ecology. SILVIS Lab.; Estados UnidosFil: von Müller, Axel. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agroforestal Esquel; ArgentinaFil: La Manna, Ludmila. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: La Manna, Ludmila. Universidad Nacional de la Patagonia San Juan Bosco. Facultad de Ingeniería. Centro de Estudios Ambientales Integrados; ArgentinaFil: González Polo, Marina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: González Polo, Marina. Universidad Nacional del Comahue. Instituto de Investigaciones en Biodiversidad y Medioambiente (INIBIOMA); ArgentinaFil: Chaves, Jimena E. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas (CADIC). Laboratorio de Recursos Agroforestales; ArgentinaFil: Cellini, Juan M. Universidad Nacional de La Plata. Laboratorio de Investigaciones en Maderas (LIMAD); ArgentinaFil: Lencinas, María V. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas (CADIC). Laboratorio de Recursos Agroforestales; ArgentinaFil: Radeloff, Volker C. University of Wisconsin. Department of Forest and Wildlife Ecology. SILVIS Lab.; Estados UnidosFil: Pidgeon, Anna M. University of Wisconsin. Department of Forest and Wildlife Ecology. SILVIS Lab.; Estados UnidosFil: Peri, Pablo Luis. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; Argentina.Fil: Peri, Pablo Luis. Universidad Nacional de la Patagonia Austral; Argentina.Fil: Peri, Pablo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Multidisciplinary Digital Publishing Institute (MDPI)2022-11-15T10:36:43Z2022-11-15T10:36:43Z2022-11-11info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://hdl.handle.net/20.500.12123/13417https://www.mdpi.com/2072-4292/14/22/5702Martínez Pastur, G.; Aravena Acuña, M.-C.; Silveira, E.M.O.; Von Müller, A.; La Manna, L.; González-Polo, M.; Chaves, J.E.; Cellini, J.M.; Lencinas, M.V.; Radeloff, V.C.; et al. Mapping Soil Organic Carbon Content in Patagonian Forests Based on Climate, Topography and Vegetation Metrics from Satellite Imagery. Remote Sens. 2022, 14, 5702. https://doi.org/ 10.3390/rs142257022072-4292https://doi.org/10.3390/rs14225702Remote Sensing 14 : 5702. (2022)reponame:INTA Digital (INTA)instname:Instituto Nacional de Tecnología Agropecuariaenginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)2025-09-29T13:45:48Zoai:localhost:20.500.12123/13417instacron:INTAInstitucionalhttp://repositorio.inta.gob.ar/Organismo científico-tecnológicoNo correspondehttp://repositorio.inta.gob.ar/oai/requesttripaldi.nicolas@inta.gob.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:l2025-09-29 13:45:48.381INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuariafalse
dc.title.none.fl_str_mv Mapping soil organic carbon content in Patagonian forests based on climate, topography and vegetation metrics from satellite imagery
title Mapping soil organic carbon content in Patagonian forests based on climate, topography and vegetation metrics from satellite imagery
spellingShingle Mapping soil organic carbon content in Patagonian forests based on climate, topography and vegetation metrics from satellite imagery
Martínez Pastur, Guillermo José
Soil Organic Carbon
Primary Forests
Satellite Imagery
Carbono Orgánico del Suelo
Bosque Primario
Imágenes por Satélites
Landsat-8
Región Patagónica
Dynamic Habitat Indices
Bosques Nativos
title_short Mapping soil organic carbon content in Patagonian forests based on climate, topography and vegetation metrics from satellite imagery
title_full Mapping soil organic carbon content in Patagonian forests based on climate, topography and vegetation metrics from satellite imagery
title_fullStr Mapping soil organic carbon content in Patagonian forests based on climate, topography and vegetation metrics from satellite imagery
title_full_unstemmed Mapping soil organic carbon content in Patagonian forests based on climate, topography and vegetation metrics from satellite imagery
title_sort Mapping soil organic carbon content in Patagonian forests based on climate, topography and vegetation metrics from satellite imagery
dc.creator.none.fl_str_mv Martínez Pastur, Guillermo José
Aravena Acuña, Marie Claire
Silveira, Eduarda M.O.
Von Müller, Axel
La Manna, Ludmila
González Polo, Marina
Chaves, Jimena Elizabeth
Cellini, Juan Manuel
Lencinas, María Vanessa
Radeloff, Volker C.
Pidgeon, Anna Michle
Peri, Pablo Luis
author Martínez Pastur, Guillermo José
author_facet Martínez Pastur, Guillermo José
Aravena Acuña, Marie Claire
Silveira, Eduarda M.O.
Von Müller, Axel
La Manna, Ludmila
González Polo, Marina
Chaves, Jimena Elizabeth
Cellini, Juan Manuel
Lencinas, María Vanessa
Radeloff, Volker C.
Pidgeon, Anna Michle
Peri, Pablo Luis
author_role author
author2 Aravena Acuña, Marie Claire
Silveira, Eduarda M.O.
Von Müller, Axel
La Manna, Ludmila
González Polo, Marina
Chaves, Jimena Elizabeth
Cellini, Juan Manuel
Lencinas, María Vanessa
Radeloff, Volker C.
Pidgeon, Anna Michle
Peri, Pablo Luis
author2_role author
author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Soil Organic Carbon
Primary Forests
Satellite Imagery
Carbono Orgánico del Suelo
Bosque Primario
Imágenes por Satélites
Landsat-8
Región Patagónica
Dynamic Habitat Indices
Bosques Nativos
topic Soil Organic Carbon
Primary Forests
Satellite Imagery
Carbono Orgánico del Suelo
Bosque Primario
Imágenes por Satélites
Landsat-8
Región Patagónica
Dynamic Habitat Indices
Bosques Nativos
dc.description.none.fl_txt_mv Soil organic carbon (SOC) content supports several ecosystem services. Quantifying SOC requires: (i) accurate C estimates of forest components, and (ii) soil estimates. However, SOC is difficult to measure, so predictive models are needed. Our objective was to model SOC stocks within 30 cm depth in Patagonian forests based on climatic, topographic and vegetation productivity measures from satellite images, including Dynamic Habitat Indices and Land Surface Temperature derived from Landsat-8. We used data from 1320 stands of different forest types in Patagonia, and random forest regression to map SOC. The model captured SOC variability well (R2 = 0.60, RMSE = 22.1%), considering the huge latitudinal extension (36.4◦ to 55.1◦ SL) and the great diversity of forest types. Mean SOC was 134.4 ton C ha−1 ± 25.2, totaling 404.2 million ton C across Patagonia. Overall, SOC values were highest in valleys of the Andes mountains and in southern Tierra del Fuego, ranging from 53.5 to 277.8 ton C ha−1 for the whole Patagonia region. Soil organic carbon is a metric relevant to many applications, connecting major issues such as forest management, conservation, and livestock production, and having spatially explicit estimates of SOC enables managers to fulfil the international agreements that Argentina has joined.
EEA Esquel
Fil: Martínez Pastur, Guillermo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas (CADIC). Laboratorio de Recursos Agroforestales; Argentina
Fil: Aravena Acuña, Marie Claire. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas (CADIC). Laboratorio de Recursos Agroforestales; Argentina
Fil: Silveira, Eduarda M. O. University of Wisconsin. Department of Forest and Wildlife Ecology. SILVIS Lab.; Estados Unidos
Fil: von Müller, Axel. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agroforestal Esquel; Argentina
Fil: La Manna, Ludmila. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: La Manna, Ludmila. Universidad Nacional de la Patagonia San Juan Bosco. Facultad de Ingeniería. Centro de Estudios Ambientales Integrados; Argentina
Fil: González Polo, Marina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: González Polo, Marina. Universidad Nacional del Comahue. Instituto de Investigaciones en Biodiversidad y Medioambiente (INIBIOMA); Argentina
Fil: Chaves, Jimena E. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas (CADIC). Laboratorio de Recursos Agroforestales; Argentina
Fil: Cellini, Juan M. Universidad Nacional de La Plata. Laboratorio de Investigaciones en Maderas (LIMAD); Argentina
Fil: Lencinas, María V. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas (CADIC). Laboratorio de Recursos Agroforestales; Argentina
Fil: Radeloff, Volker C. University of Wisconsin. Department of Forest and Wildlife Ecology. SILVIS Lab.; Estados Unidos
Fil: Pidgeon, Anna M. University of Wisconsin. Department of Forest and Wildlife Ecology. SILVIS Lab.; Estados Unidos
Fil: Peri, Pablo Luis. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; Argentina.
Fil: Peri, Pablo Luis. Universidad Nacional de la Patagonia Austral; Argentina.
Fil: Peri, Pablo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.
description Soil organic carbon (SOC) content supports several ecosystem services. Quantifying SOC requires: (i) accurate C estimates of forest components, and (ii) soil estimates. However, SOC is difficult to measure, so predictive models are needed. Our objective was to model SOC stocks within 30 cm depth in Patagonian forests based on climatic, topographic and vegetation productivity measures from satellite images, including Dynamic Habitat Indices and Land Surface Temperature derived from Landsat-8. We used data from 1320 stands of different forest types in Patagonia, and random forest regression to map SOC. The model captured SOC variability well (R2 = 0.60, RMSE = 22.1%), considering the huge latitudinal extension (36.4◦ to 55.1◦ SL) and the great diversity of forest types. Mean SOC was 134.4 ton C ha−1 ± 25.2, totaling 404.2 million ton C across Patagonia. Overall, SOC values were highest in valleys of the Andes mountains and in southern Tierra del Fuego, ranging from 53.5 to 277.8 ton C ha−1 for the whole Patagonia region. Soil organic carbon is a metric relevant to many applications, connecting major issues such as forest management, conservation, and livestock production, and having spatially explicit estimates of SOC enables managers to fulfil the international agreements that Argentina has joined.
publishDate 2022
dc.date.none.fl_str_mv 2022-11-15T10:36:43Z
2022-11-15T10:36:43Z
2022-11-11
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/20.500.12123/13417
https://www.mdpi.com/2072-4292/14/22/5702
Martínez Pastur, G.; Aravena Acuña, M.-C.; Silveira, E.M.O.; Von Müller, A.; La Manna, L.; González-Polo, M.; Chaves, J.E.; Cellini, J.M.; Lencinas, M.V.; Radeloff, V.C.; et al. Mapping Soil Organic Carbon Content in Patagonian Forests Based on Climate, Topography and Vegetation Metrics from Satellite Imagery. Remote Sens. 2022, 14, 5702. https://doi.org/ 10.3390/rs14225702
2072-4292
https://doi.org/10.3390/rs14225702
url http://hdl.handle.net/20.500.12123/13417
https://www.mdpi.com/2072-4292/14/22/5702
https://doi.org/10.3390/rs14225702
identifier_str_mv Martínez Pastur, G.; Aravena Acuña, M.-C.; Silveira, E.M.O.; Von Müller, A.; La Manna, L.; González-Polo, M.; Chaves, J.E.; Cellini, J.M.; Lencinas, M.V.; Radeloff, V.C.; et al. Mapping Soil Organic Carbon Content in Patagonian Forests Based on Climate, Topography and Vegetation Metrics from Satellite Imagery. Remote Sens. 2022, 14, 5702. https://doi.org/ 10.3390/rs14225702
2072-4292
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Multidisciplinary Digital Publishing Institute (MDPI)
publisher.none.fl_str_mv Multidisciplinary Digital Publishing Institute (MDPI)
dc.source.none.fl_str_mv Remote Sensing 14 : 5702. (2022)
reponame:INTA Digital (INTA)
instname:Instituto Nacional de Tecnología Agropecuaria
reponame_str INTA Digital (INTA)
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instname_str Instituto Nacional de Tecnología Agropecuaria
repository.name.fl_str_mv INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuaria
repository.mail.fl_str_mv tripaldi.nicolas@inta.gob.ar
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