Predicting Soil Organic Carbon Stocks Under Native Forests and Grasslands in the Dry Chaco Region of Argentina

Autores
Filip, Iván Daniel; Peri, Pablo Luis; Banegas, Natalia Romina; Nasca, Jose Andres; Sacido, Mónica; Faverin, Claudia; Vibart, Ronaldo
Año de publicación
2025
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Soil organic carbon (SOC) stocks play an important role in ecosystem functioning and climate regulation. These stocks are declining in many tropical dry forests due to land-use change and degradation. Data on topsoil (0–300 mm) organic C stocks from six experiments conducted in the Dry Chaco region, the world’s largest dry tropical forest, were used to test the predictive performance of the Rothamsted Carbon Model (RothC) after its implementation in an object-oriented graphical programming language. RothC provided promising predictions (i.e., precise and accurate) of the SOC stocks under two representative land covers in the region, native forest and Rhodes grass [relative prediction error (RPE) < 10%, concordance correlation coefficient (CCC) > 0.9, modelling efficiency (MEF) > 0.7]. Comparatively, model predictions of the SOC stocks under degraded Rhodes grass swards were suboptimal. The predictions were sensitive to C inputs; under native forests and Rhodes grass, a high C input improved the predictive performance of the model by reducing the mean bias and increasing the MEF values, compared with mean and low C inputs. Larger datasets and revisiting some of the underlying assumptions in the SOC modelling will be required to improve the model’s performance, particularly under the degraded Rhodes grass land cover.
EEA Las Breñas
Fil: Filip, Iván Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro de Investigación y Transferencia Formosa; Argentina
Fil: Filip, Iván Daniel. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Las Breñas; Argentina
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.
Fil: Banegas, Natalia Romina. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Investigación Animal del Chaco Semiárido; Argentina
Fil: Banegas, Natalia Romina. Universidad Nacional de Tucumán. Facultad de Agronomía, Zootecnia y Veterinaria; Argentina
Fil: Nasca, Jose Andres. Terratio; Argentina
Fil: Sacido, Mónica. Investigadora independientes; Argentina
Fil: Faverin, Claudia. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; Argentina
Fil: Faverin, Claudia. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales; Argentina
Fil: Vibart, Ronaldo. AgResearch. Grasslands Research Centre; Nueva Zelanda
Fuente
Sustainability 17 (11) : 5012 (June 2025)
Materia
Carbono Orgánico del Suelo
Bosques
Bosque Primario
Praderas
Estimación de las Existencias de Carbono
Soil Organic Carbon
Forests
Primary Forests
Grasslands
Carbon Stock Assessments
Bosque Nativo
Región Chaqueña, Argentina
Chaco Seco
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:20.500.12123/22478
Acceder
id INTADig_2aa06c096a8aada84b749cb5ae4bc5c7
oai_identifier_str oai:localhost:20.500.12123/22478
network_acronym_str INTADig
repository_id_str l
network_name_str INTA Digital (INTA)
spelling Predicting Soil Organic Carbon Stocks Under Native Forests and Grasslands in the Dry Chaco Region of ArgentinaFilip, Iván DanielPeri, Pablo LuisBanegas, Natalia RominaNasca, Jose AndresSacido, MónicaFaverin, ClaudiaVibart, RonaldoCarbono Orgánico del SueloBosquesBosque PrimarioPraderasEstimación de las Existencias de CarbonoSoil Organic CarbonForestsPrimary ForestsGrasslandsCarbon Stock AssessmentsBosque NativoRegión Chaqueña, ArgentinaChaco SecoSoil organic carbon (SOC) stocks play an important role in ecosystem functioning and climate regulation. These stocks are declining in many tropical dry forests due to land-use change and degradation. Data on topsoil (0–300 mm) organic C stocks from six experiments conducted in the Dry Chaco region, the world’s largest dry tropical forest, were used to test the predictive performance of the Rothamsted Carbon Model (RothC) after its implementation in an object-oriented graphical programming language. RothC provided promising predictions (i.e., precise and accurate) of the SOC stocks under two representative land covers in the region, native forest and Rhodes grass [relative prediction error (RPE) < 10%, concordance correlation coefficient (CCC) > 0.9, modelling efficiency (MEF) > 0.7]. Comparatively, model predictions of the SOC stocks under degraded Rhodes grass swards were suboptimal. The predictions were sensitive to C inputs; under native forests and Rhodes grass, a high C input improved the predictive performance of the model by reducing the mean bias and increasing the MEF values, compared with mean and low C inputs. Larger datasets and revisiting some of the underlying assumptions in the SOC modelling will be required to improve the model’s performance, particularly under the degraded Rhodes grass land cover.EEA Las BreñasFil: Filip, Iván Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro de Investigación y Transferencia Formosa; ArgentinaFil: Filip, Iván Daniel. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Las Breñas; ArgentinaFil: 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.Fil: Banegas, Natalia Romina. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Investigación Animal del Chaco Semiárido; ArgentinaFil: Banegas, Natalia Romina. Universidad Nacional de Tucumán. Facultad de Agronomía, Zootecnia y Veterinaria; ArgentinaFil: Nasca, Jose Andres. Terratio; ArgentinaFil: Sacido, Mónica. Investigadora independientes; ArgentinaFil: Faverin, Claudia. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; ArgentinaFil: Faverin, Claudia. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Vibart, Ronaldo. AgResearch. Grasslands Research Centre; Nueva ZelandaMDPI2025-06-04T10:39:33Z2025-06-04T10:39:33Z2025-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://hdl.handle.net/20.500.12123/22478https://www.mdpi.com/2071-1050/17/11/50122071-1050https://doi.org/10.3390/su17115012Sustainability 17 (11) : 5012 (June 2025)reponame:INTA Digital (INTA)instname:Instituto Nacional de Tecnología Agropecuariaenginfo:eu-repograntAgreement/INTA/2019-PD-E3-I062-001, Estrategias de producción que incrementen el secuestro de C en suelo para la mitigación del Cambio Climáticoinfo:eu-repograntAgreement/INTA/2019-PE-E1-I006-001, Respuestas tecnológicas para el manejo sustentable y eficiente de pasturas megatérmicas en sistemas ganaderos del norte y centro de Argentinainfo:eu-repograntAgreement/INTA/2023-PD-L02-I097, Emisiones de gases de efecto invernadero y captura de carbono en sistemas agropecuarios y forestalesinfo: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)2025-09-04T09:51:05Zoai:localhost:20.500.12123/22478instacron:INTAInstitucionalhttp://repositorio.inta.gob.ar/Organismo científico-tecnológicoNo correspondehttp://repositorio.inta.gob.ar/oai/requesttripaldi.nicolas@inta.gob.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:l2025-09-04 09:51:05.913INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuariafalse
dc.title.none.fl_str_mv Predicting Soil Organic Carbon Stocks Under Native Forests and Grasslands in the Dry Chaco Region of Argentina
title Predicting Soil Organic Carbon Stocks Under Native Forests and Grasslands in the Dry Chaco Region of Argentina
spellingShingle Predicting Soil Organic Carbon Stocks Under Native Forests and Grasslands in the Dry Chaco Region of Argentina
Filip, Iván Daniel
Carbono Orgánico del Suelo
Bosques
Bosque Primario
Praderas
Estimación de las Existencias de Carbono
Soil Organic Carbon
Forests
Primary Forests
Grasslands
Carbon Stock Assessments
Bosque Nativo
Región Chaqueña, Argentina
Chaco Seco
title_short Predicting Soil Organic Carbon Stocks Under Native Forests and Grasslands in the Dry Chaco Region of Argentina
title_full Predicting Soil Organic Carbon Stocks Under Native Forests and Grasslands in the Dry Chaco Region of Argentina
title_fullStr Predicting Soil Organic Carbon Stocks Under Native Forests and Grasslands in the Dry Chaco Region of Argentina
title_full_unstemmed Predicting Soil Organic Carbon Stocks Under Native Forests and Grasslands in the Dry Chaco Region of Argentina
title_sort Predicting Soil Organic Carbon Stocks Under Native Forests and Grasslands in the Dry Chaco Region of Argentina
dc.creator.none.fl_str_mv Filip, Iván Daniel
Peri, Pablo Luis
Banegas, Natalia Romina
Nasca, Jose Andres
Sacido, Mónica
Faverin, Claudia
Vibart, Ronaldo
author Filip, Iván Daniel
author_facet Filip, Iván Daniel
Peri, Pablo Luis
Banegas, Natalia Romina
Nasca, Jose Andres
Sacido, Mónica
Faverin, Claudia
Vibart, Ronaldo
author_role author
author2 Peri, Pablo Luis
Banegas, Natalia Romina
Nasca, Jose Andres
Sacido, Mónica
Faverin, Claudia
Vibart, Ronaldo
author2_role author
author
author
author
author
author
dc.subject.none.fl_str_mv Carbono Orgánico del Suelo
Bosques
Bosque Primario
Praderas
Estimación de las Existencias de Carbono
Soil Organic Carbon
Forests
Primary Forests
Grasslands
Carbon Stock Assessments
Bosque Nativo
Región Chaqueña, Argentina
Chaco Seco
topic Carbono Orgánico del Suelo
Bosques
Bosque Primario
Praderas
Estimación de las Existencias de Carbono
Soil Organic Carbon
Forests
Primary Forests
Grasslands
Carbon Stock Assessments
Bosque Nativo
Región Chaqueña, Argentina
Chaco Seco
dc.description.none.fl_txt_mv Soil organic carbon (SOC) stocks play an important role in ecosystem functioning and climate regulation. These stocks are declining in many tropical dry forests due to land-use change and degradation. Data on topsoil (0–300 mm) organic C stocks from six experiments conducted in the Dry Chaco region, the world’s largest dry tropical forest, were used to test the predictive performance of the Rothamsted Carbon Model (RothC) after its implementation in an object-oriented graphical programming language. RothC provided promising predictions (i.e., precise and accurate) of the SOC stocks under two representative land covers in the region, native forest and Rhodes grass [relative prediction error (RPE) < 10%, concordance correlation coefficient (CCC) > 0.9, modelling efficiency (MEF) > 0.7]. Comparatively, model predictions of the SOC stocks under degraded Rhodes grass swards were suboptimal. The predictions were sensitive to C inputs; under native forests and Rhodes grass, a high C input improved the predictive performance of the model by reducing the mean bias and increasing the MEF values, compared with mean and low C inputs. Larger datasets and revisiting some of the underlying assumptions in the SOC modelling will be required to improve the model’s performance, particularly under the degraded Rhodes grass land cover.
EEA Las Breñas
Fil: Filip, Iván Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro de Investigación y Transferencia Formosa; Argentina
Fil: Filip, Iván Daniel. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Las Breñas; Argentina
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.
Fil: Banegas, Natalia Romina. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Investigación Animal del Chaco Semiárido; Argentina
Fil: Banegas, Natalia Romina. Universidad Nacional de Tucumán. Facultad de Agronomía, Zootecnia y Veterinaria; Argentina
Fil: Nasca, Jose Andres. Terratio; Argentina
Fil: Sacido, Mónica. Investigadora independientes; Argentina
Fil: Faverin, Claudia. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; Argentina
Fil: Faverin, Claudia. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales; Argentina
Fil: Vibart, Ronaldo. AgResearch. Grasslands Research Centre; Nueva Zelanda
description Soil organic carbon (SOC) stocks play an important role in ecosystem functioning and climate regulation. These stocks are declining in many tropical dry forests due to land-use change and degradation. Data on topsoil (0–300 mm) organic C stocks from six experiments conducted in the Dry Chaco region, the world’s largest dry tropical forest, were used to test the predictive performance of the Rothamsted Carbon Model (RothC) after its implementation in an object-oriented graphical programming language. RothC provided promising predictions (i.e., precise and accurate) of the SOC stocks under two representative land covers in the region, native forest and Rhodes grass [relative prediction error (RPE) < 10%, concordance correlation coefficient (CCC) > 0.9, modelling efficiency (MEF) > 0.7]. Comparatively, model predictions of the SOC stocks under degraded Rhodes grass swards were suboptimal. The predictions were sensitive to C inputs; under native forests and Rhodes grass, a high C input improved the predictive performance of the model by reducing the mean bias and increasing the MEF values, compared with mean and low C inputs. Larger datasets and revisiting some of the underlying assumptions in the SOC modelling will be required to improve the model’s performance, particularly under the degraded Rhodes grass land cover.
publishDate 2025
dc.date.none.fl_str_mv 2025-06-04T10:39:33Z
2025-06-04T10:39:33Z
2025-06
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/20.500.12123/22478
https://www.mdpi.com/2071-1050/17/11/5012
2071-1050
https://doi.org/10.3390/su17115012
url http://hdl.handle.net/20.500.12123/22478
https://www.mdpi.com/2071-1050/17/11/5012
https://doi.org/10.3390/su17115012
identifier_str_mv 2071-1050
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repograntAgreement/INTA/2019-PD-E3-I062-001, Estrategias de producción que incrementen el secuestro de C en suelo para la mitigación del Cambio Climático
info:eu-repograntAgreement/INTA/2019-PE-E1-I006-001, Respuestas tecnológicas para el manejo sustentable y eficiente de pasturas megatérmicas en sistemas ganaderos del norte y centro de Argentina
info:eu-repograntAgreement/INTA/2023-PD-L02-I097, Emisiones de gases de efecto invernadero y captura de carbono en sistemas agropecuarios y forestales
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 MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv Sustainability 17 (11) : 5012 (June 2025)
reponame:INTA Digital (INTA)
instname:Instituto Nacional de Tecnología Agropecuaria
reponame_str INTA Digital (INTA)
collection INTA Digital (INTA)
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
_version_ 1842341440803307520
score 12.623145

Publicaciones similares