Articles | Volume 4, issue 3
https://doi.org/10.5194/soil-4-173-2018
https://doi.org/10.5194/soil-4-173-2018
Original research article
 | 
01 Aug 2018
Original research article |  | 01 Aug 2018

No silver bullet for digital soil mapping: country-specific soil organic carbon estimates across Latin America

Mario Guevara, Guillermo Federico Olmedo, Emma Stell, Yusuf Yigini, Yameli Aguilar Duarte, Carlos Arellano Hernández, Gloria E. Arévalo, Carlos Eduardo Arroyo-Cruz, Adriana Bolivar, Sally Bunning, Nelson Bustamante Cañas, Carlos Omar Cruz-Gaistardo, Fabian Davila, Martin Dell Acqua, Arnulfo Encina, Hernán Figueredo Tacona, Fernando Fontes, José Antonio Hernández Herrera, Alejandro Roberto Ibelles Navarro, Veronica Loayza, Alexandra M. Manueles, Fernando Mendoza Jara, Carolina Olivera, Rodrigo Osorio Hermosilla, Gonzalo Pereira, Pablo Prieto, Iván Alexis Ramos, Juan Carlos Rey Brina, Rafael Rivera, Javier Rodríguez-Rodríguez, Ronald Roopnarine, Albán Rosales Ibarra, Kenset Amaury Rosales Riveiro, Guillermo Andrés Schulz, Adrian Spence, Gustavo M. Vasques, Ronald R. Vargas, and Rodrigo Vargas

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Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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AR: Author's response | RR: Referee report | ED: Editor decision
ED: Revision (16 Apr 2018) by Peter Finke
AR by Mario Antonio Guevara Santamaría on behalf of the Authors (29 May 2018)  Author's response   Manuscript 
ED: Publish subject to minor revisions (review by editor) (04 Jun 2018) by Peter Finke
AR by Mario Antonio Guevara Santamaría on behalf of the Authors (15 Jun 2018)  Author's response   Manuscript 
ED: Publish as is (18 Jun 2018) by Peter Finke
ED: Publish as is (24 Jun 2018) by Johan Six (Executive editor)
AR by Mario Antonio Guevara Santamaría on behalf of the Authors (03 Jul 2018)
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Short summary
We provide a reproducible multi-modeling approach for SOC mapping across Latin America on a country-specific basis as required by the Global Soil Partnership of the United Nations. We identify key prediction factors for SOC across each country. We compare and test different methods to generate spatially explicit predictions of SOC and conclude that there is no best method on a quantifiable basis.