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

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...

Full description

Bibliographic Details
Main Authors: 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
Format: Artículo
Language:Inglés
Published: Multidisciplinary Digital Publishing Institute (MDPI) 2022
Subjects:
Online Access:http://hdl.handle.net/20.500.12123/13417
https://www.mdpi.com/2072-4292/14/22/5702
https://doi.org/10.3390/rs14225702
_version_ 1855485165314244608
author 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_browse Aravena Acuña, Marie Claire
Cellini, Juan Manuel
Chaves, Jimena Elizabeth
González Polo, Marina
La Manna, Ludmila
Lencinas, María Vanessa
Martínez Pastur, Guillermo José
Peri, Pablo Luis
Pidgeon, Anna Michle
Radeloff, Volker C.
Silveira, Eduarda M.O.
Von Müller, Axel
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_sort Martínez Pastur, Guillermo José
collection INTA Digital
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.
format Artículo
id INTA13417
institution Instituto Nacional de Tecnología Agropecuaria (INTA -Argentina)
language Inglés
publishDate 2022
publishDateRange 2022
publishDateSort 2022
publisher Multidisciplinary Digital Publishing Institute (MDPI)
publisherStr Multidisciplinary Digital Publishing Institute (MDPI)
record_format dspace
spelling INTA134172022-11-15T10:52:28Z Mapping soil organic carbon content in Patagonian forests based on climate, topography and vegetation metrics from satellite imagery 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 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 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. 2022-11-15T10:36:43Z 2022-11-15T10:36:43Z 2022-11-11 info:ar-repo/semantics/artículo info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion 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 eng 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) application/pdf Multidisciplinary Digital Publishing Institute (MDPI) Remote Sensing 14 : 5702. (2022)
spellingShingle 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
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
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
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_short 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
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
url http://hdl.handle.net/20.500.12123/13417
https://www.mdpi.com/2072-4292/14/22/5702
https://doi.org/10.3390/rs14225702
work_keys_str_mv AT martinezpasturguillermojose mappingsoilorganiccarboncontentinpatagonianforestsbasedonclimatetopographyandvegetationmetricsfromsatelliteimagery
AT aravenaacunamarieclaire mappingsoilorganiccarboncontentinpatagonianforestsbasedonclimatetopographyandvegetationmetricsfromsatelliteimagery
AT silveiraeduardamo mappingsoilorganiccarboncontentinpatagonianforestsbasedonclimatetopographyandvegetationmetricsfromsatelliteimagery
AT vonmulleraxel mappingsoilorganiccarboncontentinpatagonianforestsbasedonclimatetopographyandvegetationmetricsfromsatelliteimagery
AT lamannaludmila mappingsoilorganiccarboncontentinpatagonianforestsbasedonclimatetopographyandvegetationmetricsfromsatelliteimagery
AT gonzalezpolomarina mappingsoilorganiccarboncontentinpatagonianforestsbasedonclimatetopographyandvegetationmetricsfromsatelliteimagery
AT chavesjimenaelizabeth mappingsoilorganiccarboncontentinpatagonianforestsbasedonclimatetopographyandvegetationmetricsfromsatelliteimagery
AT cellinijuanmanuel mappingsoilorganiccarboncontentinpatagonianforestsbasedonclimatetopographyandvegetationmetricsfromsatelliteimagery
AT lencinasmariavanessa mappingsoilorganiccarboncontentinpatagonianforestsbasedonclimatetopographyandvegetationmetricsfromsatelliteimagery
AT radeloffvolkerc mappingsoilorganiccarboncontentinpatagonianforestsbasedonclimatetopographyandvegetationmetricsfromsatelliteimagery
AT pidgeonannamichle mappingsoilorganiccarboncontentinpatagonianforestsbasedonclimatetopographyandvegetationmetricsfromsatelliteimagery
AT peripabloluis mappingsoilorganiccarboncontentinpatagonianforestsbasedonclimatetopographyandvegetationmetricsfromsatelliteimagery