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Abstract
Country-specific soil organic carbon (SOC) estimates are the baseline for the Global SOC Map of the Global Soil Partnership (GSOCmap-GSP). This endeavor is key to explaining the uncertainty of global SOC estimates but requires harmonizing heterogeneous datasets and building country-specific capacities for digital soil mapping (DSM).We identified country-specific predictors for SOC and tested the performance of five predictive algorithms for mapping SOC [ver mas...]
dc.contributor.authorGuevara, Mario
dc.contributor.authorOlmedo, Guillermo Federico
dc.contributor.authorStell, Emma
dc.contributor.authorYigini, Yusuf
dc.contributor.authorAguilar Duarte, Yameli
dc.contributor.authorArellano Hernández, Carlos
dc.contributor.authorArévalo, Gloria E.
dc.contributor.authorArroyo-Cruz, Carlos Eduardo
dc.contributor.authorBolivar, Adriana
dc.contributor.authorBunning, Sally
dc.contributor.authorBustamante Cañas, Nelson
dc.contributor.authorCruz-Gaistardo, Carlos Omar
dc.contributor.authorDavila, Fabian
dc.contributor.authorDell Acqua, Martín
dc.contributor.authorEncina, Arnulfo
dc.contributor.authorFigueredo Tacona, Hernán
dc.contributor.authorFontes, Fernando
dc.contributor.authorHernández Herrera, José Antonio
dc.contributor.authorIbelles Navarro, Alejandro Roberto
dc.contributor.authorLoayza, Verónica
dc.contributor.authorManueles, Alexandra
dc.contributor.authorMendoza Jara, Fernando
dc.contributor.authorOlivera, Carolina
dc.contributor.authorOsorio Hermosilla, Rodrigo
dc.contributor.authorPereira, Gonzalo
dc.contributor.authorPrieto, Pablo
dc.contributor.authorRamos, Iván Alexis
dc.contributor.authorRey Brina, Juan Carlos
dc.contributor.authorRivera, Rafael
dc.contributor.authorRodríguez-Rodríguez, Javier
dc.contributor.authorRoopnarine, Ronald
dc.contributor.authorRosales Ibarra, Albán
dc.contributor.authorRosales Riveiro, Kenset Amaury
dc.contributor.authorSchulz, Guillermo Andres
dc.contributor.authorSpence, Adrián
dc.contributor.authorVargas, Ronald R.
dc.contributor.authorVargas, Rodrigo
dc.contributor.authorVasques, Gustavo M.
dc.date.accessioned2019-04-01T10:58:05Z
dc.date.available2019-04-01T10:58:05Z
dc.date.issued2018-08
dc.identifier.otherhttps://doi.org/10.5194/soil-4-173-2018
dc.identifier.urihttp://hdl.handle.net/20.500.12123/4788
dc.identifier.urihttps://www.soil-journal.net/4/173/2018/
dc.description.abstractCountry-specific soil organic carbon (SOC) estimates are the baseline for the Global SOC Map of the Global Soil Partnership (GSOCmap-GSP). This endeavor is key to explaining the uncertainty of global SOC estimates but requires harmonizing heterogeneous datasets and building country-specific capacities for digital soil mapping (DSM).We identified country-specific predictors for SOC and tested the performance of five predictive algorithms for mapping SOC across Latin America. The algorithms included support vector machines (SVMs), random forest (RF), kernel-weighted nearest neighbors (KK), partial least squares regression (PL), and regression kriging based on stepwise multiple linear models (RK). Country-specific training data and SOC predictors (5 5 km pixel resolution) were obtained from ISRIC – World Soil Information. Temperature, soil type, vegetation indices, and topographic constraints were the best predictors for SOC, but country-specific predictors and their respective weights varied across Latin America. We compared a large diversity of country-specific datasets and models, and were able to explain SOC variability in a range between 1 and 60 %, with no universal predictive algorithm among countries. A regional (nD11 268 SOC estimates) ensemble of these five algorithms was able to explain 39% of SOC variability from repeated 5-fold cross-validation.We report a combined SOC stock of 77.8 43.6 Pg (uncertainty represented by the full conditional response of independent model residuals) across Latin America. SOC stocks were higher in tropical forests (30 16.5 Pg) and croplands (13 8.1 Pg). Country-specific and regional ensembles revealed spatial discrepancies across geopolitical borders, higher elevations, and coastal plains, but provided similar regional stocks (77.8 42.2 and 76.8 45.1 Pg, respectively). These results are conservative compared to global estimates (e.g., SoilGrids250m 185.8 Pg, the Harmonized World Soil Database 138.4 Pg, or the GSOCmap-GSP 99.7 Pg). Countries with large area (i.e., Brazil, Bolivia, Mexico, Peru) and large spatial SOC heterogeneity had lower SOC stocks per unit area and larger uncertainty in their predictions. We highlight that expert opinion is needed to set boundary prediction limits to avoid unrealistically high modeling estimates. For maximizing explained variance while minimizing prediction bias, the selection of predictive algorithms for SOC mapping should consider density of available data and variability of country-specific environmental gradients. This study highlights the large degree of spatial uncertainty in SOC estimates across Latin America. We provide a framework for improving country-specific mapping efforts and reducing current discrepancy of global, regional, and country-specific SOC estimates.eng
dc.formatapplication/pdfes_AR
dc.language.isoenges_AR
dc.relationinfo:eu-repograntAgreement/INTA/PNSUELO/1134032/AR./Bases conceptuales y nuevas herramientas para la cartografía de suelos.es_AR
dc.rightsinfo:eu-repo/semantics/openAccesses_AR
dc.sourceSoil 4 (3) : 173-193 (Agosto 2018)es_AR
dc.subjectCartografía del Uso de la Tierraes_AR
dc.subjectLand Use Mappingeng
dc.subjectCarbono Orgánico del Sueloes_AR
dc.subjectSoil Organic Carboneng
dc.subjectAmérica Latinaes_AR
dc.subjectLatin Americaeng
dc.titleNo silver bullet for digital soil mapping: country-specific soil organic carbon estimates across Latin Americaes_AR
dc.typeinfo:ar-repo/semantics/artículoes_AR
dc.typeinfo:eu-repo/semantics/articlees_AR
dc.typeinfo:eu-repo/semantics/publishedVersiones_AR
dc.description.filFil: Guevara, Mario. Universidad de Delaware. Department of Plant and Soil Sciences; Estados Unidoses_AR
dc.description.filFil: Olmedo, Guillermo Federico. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Mendoza; Argentina. FAO; Italiaes_AR
dc.description.filFil: Stell; Emma. University of Delaware, Department of Plant and Soil Sciences; Estados Unidoses_AR
dc.description.filFil: Yigini, Yusuf. FAO; Italiaes_AR
dc.description.filFil: Aguilar Duarte, Yameli. Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias; Méxicoes_AR
dc.description.filFil: Arellano Hernández, Carlos. Instituto Nacional de Estadísitica y Geografía; Méxicoes_AR
dc.description.filFil: Arévalo, Gloria E. Zamorano. University of Honduras and Asociación Hondureña de la Ciencia del Suelo; Hondurases_AR
dc.description.filFil: Arroyo-Cruz, Carlos Eduardo. National Commission for the Knowledge and Use of Biodiversity; Méxicoes_AR
dc.description.filFil: Bolivar, Adriana. Instituto Geográfico Agustín Codazzi. Subdirección Agrología; Colombiaes_AR
dc.description.filFil: Bunning, Sally. FAO. Oficina Regional para América Latina y el Caribe; Chilees_AR
dc.description.filFil: Bustamante Cañas, Nelson. Servicio Agrícola y Ganadero; Chilees_AR
dc.description.filFil: Cruz-Gaistardo, Carlos Omar. Instituto Nacional de Estadísitica y Geografía; Méxicoes_AR
dc.description.filDell Acqua, Martín. Ministerio de Ganadería, Agricultura y Pesca. Dirección General de Recursos Naturales; Uruguayes_AR
dc.description.filFil: Encina, Arnulfo. Universidad Nacional de Asunción. Facultad de Ciencias Agrarias; Paraguayes_AR
dc.description.filFil: Figueredo Tacona, Hernán. Ministry of Rural Development and Land. Land Viceministry; Boliviaes_AR
dc.description.filFil: Fontes, Fernando. Ministerio de Ganadería, Agricultura y Pesca. Dirección General de Recursos Naturales; Uruguayes_AR
dc.description.filFil: Hernández Herrera, José Antonio. Universidad Autónoma Agraria Antonio Narro. Unidad Laguna; Méxicoes_AR
dc.description.filFil: Ibelles Navarro, Alejandro Roberto. Instituto Nacional de Estadísitica y Geografía; Méxicoes_AR
dc.description.filFil: Loayza, Verónica. Ministerio de Agricultura y Ganaderia; Ecuadores_AR
dc.description.filFil: Manueles, Alexandra M.. Zamorano University of Honduras and Asociación Hondureña de la Ciencia del Suelo; Hondurases_AR
dc.description.filFil: Mendoza Jara, Fernando . Universidad Nacional Agraria; Nicaraguaes_AR
dc.description.filFil: Olivera, Carolina. FAO. Oficina Regional para América Latina y el Caribe; Colombiaes_AR
dc.description.filFil: Osorio Hermosilla, Rodrigo. Servicio Agrícola y Ganadero; Chilees_AR
dc.description.filFil: Pereira, Gonzalo. Ministerio de Ganadería, Agricultura y Pesca. Dirección General de Recursos Naturales; Uruguayes_AR
dc.description.filFil: Prieto, Pablo. Ministerio de Ganadería, Agricultura y Pesca. Dirección General de Recursos Naturales; Uruguayes_AR
dc.description.filFil: Ramos, Iván Alexis . Instituto de Investigación Agropecuaria de Panamá; Panamáes_AR
dc.description.filFil: Rey Brina, Juan Carlos. Sociedad Venezolana de la Ciencia del Suelo; Venezuelaes_AR
dc.description.filFil: Rivera, Rafael. Ministerio de Medio Ambiente; República Dominicanaes_AR
dc.description.filFil: Rodríguez-Rodríguez, Javier. National Commission for the Knowledge and Use of Biodiversity; Méxicoes_AR
dc.description.filFil: Roopnarine, Ronald. Department of Natural and Life Sciences. COSTAATT; Trinidad y Tobagoes_AR
dc.description.filFil: Rosales Ibarra, Albán. Instituto de Innovación en Transferencia y Tecnología Agropecuaria; Costa Ricaes_AR
dc.description.filFil: Rosales Riveiro, Kenset Amaury. Ministerio de Ambiente y Recursos Naturales de Guatemala; Guatemalaes_AR
dc.description.filFil: Schulz, Guillermo Andrés. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Suelos; Argentinaes_AR
dc.description.filFil: Spence, Adrián. University of the West Indies. International Centre for Environmental and Nuclear Sciences; Jamaicaes_AR
dc.description.filFil: Vasques, Gustavo M. EMBRAPA Solos; Brasiles_AR
dc.description.filFil: Vargas, Ronald R. FAO; Italiaes_AR
dc.description.filFil: Vargas, Rodrigo. University of Delaware. Department of Plant and Soil Sciences; Estados Unidoses_AR
dc.subtypecientifico
dc.subtypeSuelo
dc.subtypeSoileng


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