Soil Organic Carbon Stock Estimates with Uncertainty across Latin America
This new dataset form the Carbon Monitoring System provides 5 x 5 km gridded estimates of soil organic carbon (SOC) across Latin America that were derived from existing point soil characterization data and compiled environmental prediction factors for SOC. The dataset is representative for the period 1980 to 2000s, corresponding with the highest density of observations available in the WoSIS system. A modeling ensemble, using a linear combination of five statistical methods (regression Kriging, random forest, kernel weighted nearest neighbors, partial least squared regression and support vector machines) was applied to the SOC stock data at (1) country-specific and (2) regional scales to develop gridded SOC estimates (kg/m2) for all of Latin America. Uncertainty estimates are provided for the two model predictions based on independent model residuals and their full conditional response to the SOC prediction factors.
The CMS is designed to make significant contributions in characterizing, quantifying, understanding, and predicting the evolution of global carbon sources and sinks through improved monitoring of carbon stocks and fluxes. See all ORNL DAAC datasets from the Carbon Monitoring System.
Data Citation: Guevara, M., G.F. Olmedo, E. Stell, Y. Yigini, C.A. Hernandez, G. Arevalo, C.E. Arroyo-cruz, A. Bolivar, S. Bunning, N.B. Canas, C.O. Cruz-gaistardo, F. Davila, M.D. Acqua, A. Encina, F. Fontes, J.A.H. Herrera, A.R.I. Navarro, V. Loayza, A.M. Manueles, F.M. Jara, C. Olivera, G. Pereira, P. Prieto, I.A. Ramos, J.C.R. Brina, R. Rivera, J. Rodriguez-Rodriguez, R. Roopnarine, A. Rosales, K.A.R. Rivero, G.A. Schulz, A. Spence, G.M. Vasques, R.R. Vargas, and R. Vargas. 2019. Soil Organic Carbon Stock Estimates with Uncertainty across Latin America. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1615
Data Center: ORNL DAAC
Sponsor: EOSDIS
