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dc.contributor.authorGUEVARA, M.
dc.contributor.authorOLMEDO, G. F.
dc.contributor.authorSTELL, E.
dc.contributor.authorYIGINI, Y.
dc.contributor.authorAGUILAR DUARTE, Y.
dc.contributor.authorARELLANO HERNÁNDEZ, C.
dc.contributor.authorARÉVALO, G. E.
dc.contributor.authorARROYO-CRUZ, C. E.
dc.contributor.authorBOLIVAR, A.
dc.contributor.authorBUNNING, S.
dc.contributor.authorBUSTAMANTE CAÑAS, N.
dc.contributor.authorCRUZ-GAISTARDO, C. O.
dc.contributor.authorDAVILLA, F.pt_BR
dc.contributor.authorDELL ACQUA, M.pt_BR
dc.contributor.authorENCINA, A.pt_BR
dc.contributor.authorFIGUEREDO TACONA, H.pt_BR
dc.contributor.authorFONTES, F.pt_BR
dc.contributor.authorHERNÁNDEZ HERRERA, J. A.pt_BR
dc.contributor.authorIBELLES NAVARRO, A. R.pt_BR
dc.contributor.authorLOAYZA, V.pt_BR
dc.contributor.authorMANUELES, A. M.pt_BR
dc.contributor.authorMENDOZA JARA, F.pt_BR
dc.contributor.authorOLIVERA, C.pt_BR
dc.contributor.authorOSORIO HERMOSILLA, R.pt_BR
dc.contributor.authorPEREIRA, G.pt_BR
dc.contributor.authorPIETRO, P.pt_BR
dc.contributor.authorRAMOS, I. A.pt_BR
dc.contributor.authorREY BRINA, J. C.pt_BR
dc.contributor.authorRIVERA, R.pt_BR
dc.contributor.authorRODRÍGUEZ-RODRÍGUEZ, J.pt_BR
dc.contributor.authorROOPNARINE, R.pt_BR
dc.contributor.authorROSALES IBARRA, A.pt_BR
dc.contributor.authorROSALES RIVEIRO, K. A.pt_BR
dc.contributor.authorSCHULZ, G. A.pt_BR
dc.contributor.authorSPENCE, A.pt_BR
dc.contributor.authorVASQUES, G. de M.pt_BR
dc.contributor.authorVARGAS, R. R.pt_BR
dc.contributor.authorVARGAS, R.pt_BR
dc.date.accessioned2018-09-01T00:46:30Z-
dc.date.available2018-09-01T00:46:30Z-
dc.date.created2018-08-31
dc.date.issued2018
dc.identifier.citationSoil, v. 4, n. 1, p. 173-193, 2018.
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1094880-
dc.descriptionCountry-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 x 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 (n = 11 268 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.
dc.language.isoengeng
dc.rightsopenAccesseng
dc.subjectMapeamento digital do solo
dc.subjectCarbono orgânico do solo
dc.titleNo silver bullet for digital soil mapping: country-specific soil organic carbon estimates across Latin America.
dc.typeArtigo de periódico
dc.date.updated2018-09-20T11:11:11Zpt_BR
dc.subject.thesagroCarbono
dc.subject.nalthesaurusSoil organic carbon
dc.subject.nalthesaurusSoil map
riaa.ainfo.id1094880
riaa.ainfo.lastupdate2018-09-20 -03:00:00
dc.identifier.doihttps://doi.org/10.5194/soil-4-173-2018
dc.contributor.institutionMARIO GUEVARA, University of Delaware
dc.contributor.institutionGUILLERMO FEDERICO OLMEDO, INTA EEA Mendoza/FAOpt_BR
dc.contributor.institutionEMMA STELL, University of Delawarept_BR
dc.contributor.institutionYUSUF YIGINI, FAOpt_BR
dc.contributor.institutionYAMELI AGUILAR DUARTE, Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias, Mérida, Mexicopt_BR
dc.contributor.institutionCARLOS ARELLANO HERNÁNDEZ, Instituto Nacional de Estadísitica y Geografía, Aguascalientes, Mexicopt_BR
dc.contributor.institutionGLORIA E. ARÉVALO, Zamorano University of Honduras and Asociación Hondureña de la Ciencia del Suelo, Tegucigalpa, Honduraspt_BR
dc.contributor.institutionCARLOS EDUARDO ARROYO-CRUZ, National Commission for the Knowledge and Use of Biodiversity, Mexico City, Mexicopt_BR
dc.contributor.institutionADRIANA BOLIVAR, Subdirección Agrología, Instituto Geográfico Agustín Codazzi, Bogotá, Colombiapt_BR
dc.contributor.institutionSALLY BUNNING, Oficina Regional de la FAO para América Latina y el Caribe, Santiago de Chile, Chilept_BR
dc.contributor.institutionNELSON BUSTAMANTE CAÑAS, Servicio Agrícola y Ganadero, Santiago de Chile, Chilept_BR
dc.contributor.institutionCARLOS OMAR CRUZ-GAISTARDO, Instituto Nacional de Estadísitica y Geografía, Aguascalientes, Mexicopt_BR
dc.contributor.institutionFABIAN DAVILLA, Ministerio de Ganaderia, Agricultura y Pesca, Montevideo, Uruguaypt_BR
dc.contributor.institutionMARTIN DELL ACQUA, Ministerio de Ganaderia, Agricultura y Pesca, Montevideo, Uruguaypt_BR
dc.contributor.institutionARNULFO ENCINA, Facultad de Ciencias Agrarias de la Universidad Nacional de Asunción, Asunción, Paraguaypt_BR
dc.contributor.institutionHERNÁN FIGUEREDO TACONA, Land Viceministry, Ministry of Rural Development and Land, La Paz, Boliviapt_BR
dc.contributor.institutionFERNANDO FONTES, Ministerio de Ganaderia, Agricultura y Pesca, Montevideo, Uruguaypt_BR
dc.contributor.institutionJOSÉ ANTONIO HERNÁNDEZ HERRERA, Universidad Autónoma Agraria Antonio Narro Unidad Laguna, Torreón, Mexicopt_BR
dc.contributor.institutionALEJANDRO ROBERTO IBELLES NAVARRO, Instituto Nacional de Estadísitica y Geografía, Aguascalientes, Mexicopt_BR
dc.contributor.institutionVERONICA LOAYZA, Ministerio de Agricultura y Ganaderia, Quito, Ecuadorpt_BR
dc.contributor.institutionALEXANDRA M. MANUELES, Zamorano University of Honduras and Asociación Hondureña de la Ciencia del Suelo, Tegucigalpa, Honduraspt_BR
dc.contributor.institutionFERNANDO MENDOZA JARA, Universidad Nacional Agraria, Managua, Nicaraguapt_BR
dc.contributor.institutionCAROLINA OLIVERA, Oficina Regional de la FAO para América Latina y el Caribe, Bogotá, Colombiapt_BR
dc.contributor.institutionRODRIGO OSORIO HERMOSILLA, Servicio Agrícola y Ganadero, Santiago de Chile, Chilept_BR
dc.contributor.institutionGONZALO PEREIRA, Ministerio de Ganaderia, Agricultura y Pesca, Montevideo, Uruguaypt_BR
dc.contributor.institutionPABLO PIETRO, Ministerio de Ganaderia, Agricultura y Pesca, Montevideo, Uruguaypt_BR
dc.contributor.institutionIVÁN ALEXIS RAMOS, Instituto de Investigación Agropecuaria de Panamá, Panamápt_BR
dc.contributor.institutionJUAN CARLOS REY BRINA, Sociedad Venezolana de la Ciencia del Suelo, Caracas, Venezuelapt_BR
dc.contributor.institutionRAFAEL RIVERA, Ministerio de Medio Ambiente, Santo Domingo, Dominican Republicpt_BR
dc.contributor.institutionJAVIER RODRÍGUEZ-RODRÍGUEZ, National Commission for the Knowledge and Use of Biodiversity, Mexico City, Mexicopt_BR
dc.contributor.institutionRONALD ROOPNARINE, Department of Natural and Life Sciences, COSTAATT, Port of Spain, Trinidad an Tobago/University of the West Indies, St. Augustine Campus, Trinidad and Tobagopt_BR
dc.contributor.institutionALBÁN ROSALES IBARRA, Instituto de Innovación en Transferencia y Tecnología Agropecuaria, San José, Costa Ricapt_BR
dc.contributor.institutionKENSET AMAURY ROSALES RIVEIRO, Ministerio de Ambiente y Recursos Naturales de Guatemala, Ciudad Guatemala, Guatemalapt_BR
dc.contributor.institutionGUILLERMO ANDRÉS SCHULZ, INTA CNIA, Buenos Aires, Argentinapt_BR
dc.contributor.institutionADRIAN SPENCE, International Centre for Environmental and Nuclear Sciences, University of the West Indies, Kingston, Jamaicapt_BR
dc.contributor.institutionGUSTAVO DE MATTOS VASQUES, CNPSpt_BR
dc.contributor.institutionRONALD R. VARGAS, FAO, Vialle de Terme di Caracalla, Rome, Italypt_BR
dc.contributor.institutionRODRIGO VARGAS, University of Delaware, Department of Plant and Soil Sciences, Newark, DE, USA.pt_BR
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