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

Viewed

Total article views: 6,985 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
5,042 1,749 194 6,985 411 126 142
  • HTML: 5,042
  • PDF: 1,749
  • XML: 194
  • Total: 6,985
  • Supplement: 411
  • BibTeX: 126
  • EndNote: 142
Views and downloads (calculated since 25 Jan 2018)
Cumulative views and downloads (calculated since 25 Jan 2018)

Viewed (geographical distribution)

Total article views: 6,985 (including HTML, PDF, and XML) Thereof 6,137 with geography defined and 848 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Discussed (final revised paper)

Discussed (preprint)

Latest update: 28 Nov 2023
Download
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.