Soil Organic Carbon Stock Estimates with Uncertainty across Latin America
- Autores
- Guevara, Mario; Olmedo, Guillermo Federico; Stell, Emma; Yigini, Yusuf; Hernández Arelano, Carlos; Arevalo, Gloria; Arroyo-Cruz, Carlos Eduardo; Bolivar, Adriana; Bunning, Sally; Bustamante Canas, Nelson; Cruz-Gaistardo, Carlos Omar; Davila, Fabian; Dell Acqua, Martín; Encina, Arnulfa; Fontes, Fernanda; Hernández Herrera, José A.; Pereira, Gonzalo; Schulz, Guillermo; Spence, Adrian; Vazques, Gustavo
- Año de publicación
- 2019
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- This dataset 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. This dataset is representative for the period between 1980 to 2000s corresponding with the highest density of observations available in the WoSIS system and the covariates used as prediction factors for soil organic carbon across Latin America. SOC stocks (kg/m2) were estimated for the SOC and bulk density point measurements and a spatially explicit measure of the SOC estimation error was also calculated. 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. These SOC estimates provide a reproducible example, on country-specific and regional scales, for digital soil mapping across Latin America and contribute to reducing the uncertainty of SOC estimates and improving the parameterization of global models across Latin America. This dataset includes six data files in GeoTIFF (.tif) format at 5 km resolution across Latin America, including: (1) a mosaic of country-specific soil organic carbon estimates, (2) model uncertainty derived for the country-specific estimates, (3) a mosaic of the regional soil organic carbon estimates, (4) model uncertainty derived for the regional estimates, and (5-6) two trend maps of approximate errors associated with the SOC stock calculation method. There is one data file in comma-separated format (.csv) of the point soil characterization data with calculated SOC stock estimates. Four companion files include: a 133-band GeoTiff containing the environmental predictor variables for SOC across Latin America, a .csv file with descriptions of the environmental variables, a shapefile (.shp) of the point soil characterization data with SOC stock estimates and a *.kmz file to display the same.
Fil: Guevara, Mario. University of Delaware. Department of Plant and Soil Sciences; Estados Unidos
Fil: Olmedo. Guillermo Federico. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Mendoza; Argentina. FAO; Italia
Fil: Stell, Emma. University of Delaware. Department of Plant and Soil Sciences; Estados Unidos
Fil: Yigini, Yusuf. FAO; Italia
Fil: Hernández Arellano, Carlos. Instituto Nacional de Estadística y Geografía; México
Fil: Arevalo, Gloria. Zamorano University of Honduras; Honduras. Asociación Hondureña de la Ciencia del Suelo; Honduras
Fil: Arroyo-Cruz, Carlos Eduardo. National Commission for the Knowledge and Use of Biodiversity; México
Fil: Bolivar, Adriana. Instituto Geográfico Agustín Codazzi. Subdirección Agrología; Colombia
Fil: Bunning, Sally. FAO. Oficina Regional de la FAO para América Latina y el Caribe; Chile
Fil: Bustamante Cañas, Nelson. Servicio Agrícola y Ganadero; Chile
Fil: Cruz-Gaistardo, Calos Omar. Instituto Nacional de Estadística y Geografía; México
Fil: Dell Acqua, Martin. Dirección General de Recursos Naturales, Ministerio de Ganadería, Agricultura y Pesca; Uruguay
Fil: Davila, Fabian. Ministerio de Ganadería, Agricultura y Pesca, Dirección General de Recursos Naturales; Uruguay
Fil: Encina, Arnulfo. Universidad Nacional de Asunción. Facultad de Ciencias Agrarias; Paraguay
Fil: Fontes, Fernando. Ministerio de Ganadería, Agricultura y Pesca, Dirección General de Recursos Naturales; Uruguay
Fil: Hernández Herrera, José Antonio. Universidad Autónoma Agraria Antonio Narro Unidad Laguna; México
Fil: Pereira, Gonzalo. Ministerio de Ganadería, Agricultura y Pesca. Dirección General de Recursos Naturales; Uruguay
Fil: Schulz, Guillermo Andrés. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Suelos; Argentina
Fil: Spence, Adrian. University of the West Indies. International Centre for Environmental and Nuclear Sciences; Jamaica
Fil: Vasques, Gustavo M. Embrapa Solos; Brasil - Fuente
- ORNL-DAAC News : 1-6. (03 july 2019)
- Materia
-
Carbono Orgánico del Suelo
América Latina
Soil Organic Carbon
Factores de Predicciones
Error de Estimación
Prediction Factors
Estimation Error - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc-sa/4.0/
- Repositorio
.jpg)
- Institución
- Instituto Nacional de Tecnología Agropecuaria
- OAI Identificador
- oai:localhost:20.500.12123/17694
Ver los metadatos del registro completo
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Soil Organic Carbon Stock Estimates with Uncertainty across Latin AmericaGuevara, MarioOlmedo, Guillermo FedericoStell, EmmaYigini, YusufHernández Arelano, CarlosArevalo, GloriaArroyo-Cruz, Carlos EduardoBolivar, AdrianaBunning, SallyBustamante Canas, NelsonCruz-Gaistardo, Carlos OmarDavila, FabianDell Acqua, MartínEncina, ArnulfaFontes, FernandaHernández Herrera, José A.Pereira, GonzaloSchulz, GuillermoSpence, AdrianVazques, GustavoCarbono Orgánico del SueloAmérica LatinaSoil Organic CarbonFactores de PrediccionesError de EstimaciónPrediction FactorsEstimation ErrorThis dataset 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. This dataset is representative for the period between 1980 to 2000s corresponding with the highest density of observations available in the WoSIS system and the covariates used as prediction factors for soil organic carbon across Latin America. SOC stocks (kg/m2) were estimated for the SOC and bulk density point measurements and a spatially explicit measure of the SOC estimation error was also calculated. 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. These SOC estimates provide a reproducible example, on country-specific and regional scales, for digital soil mapping across Latin America and contribute to reducing the uncertainty of SOC estimates and improving the parameterization of global models across Latin America. This dataset includes six data files in GeoTIFF (.tif) format at 5 km resolution across Latin America, including: (1) a mosaic of country-specific soil organic carbon estimates, (2) model uncertainty derived for the country-specific estimates, (3) a mosaic of the regional soil organic carbon estimates, (4) model uncertainty derived for the regional estimates, and (5-6) two trend maps of approximate errors associated with the SOC stock calculation method. There is one data file in comma-separated format (.csv) of the point soil characterization data with calculated SOC stock estimates. Four companion files include: a 133-band GeoTiff containing the environmental predictor variables for SOC across Latin America, a .csv file with descriptions of the environmental variables, a shapefile (.shp) of the point soil characterization data with SOC stock estimates and a *.kmz file to display the same.Fil: Guevara, Mario. University of Delaware. Department of Plant and Soil Sciences; Estados UnidosFil: Olmedo. Guillermo Federico. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Mendoza; Argentina. FAO; ItaliaFil: Stell, Emma. University of Delaware. Department of Plant and Soil Sciences; Estados UnidosFil: Yigini, Yusuf. FAO; ItaliaFil: Hernández Arellano, Carlos. Instituto Nacional de Estadística y Geografía; MéxicoFil: Arevalo, Gloria. Zamorano University of Honduras; Honduras. Asociación Hondureña de la Ciencia del Suelo; HondurasFil: Arroyo-Cruz, Carlos Eduardo. National Commission for the Knowledge and Use of Biodiversity; MéxicoFil: Bolivar, Adriana. Instituto Geográfico Agustín Codazzi. Subdirección Agrología; ColombiaFil: Bunning, Sally. FAO. Oficina Regional de la FAO para América Latina y el Caribe; ChileFil: Bustamante Cañas, Nelson. Servicio Agrícola y Ganadero; ChileFil: Cruz-Gaistardo, Calos Omar. Instituto Nacional de Estadística y Geografía; MéxicoFil: Dell Acqua, Martin. Dirección General de Recursos Naturales, Ministerio de Ganadería, Agricultura y Pesca; UruguayFil: Davila, Fabian. Ministerio de Ganadería, Agricultura y Pesca, Dirección General de Recursos Naturales; UruguayFil: Encina, Arnulfo. Universidad Nacional de Asunción. Facultad de Ciencias Agrarias; ParaguayFil: Fontes, Fernando. Ministerio de Ganadería, Agricultura y Pesca, Dirección General de Recursos Naturales; UruguayFil: Hernández Herrera, José Antonio. Universidad Autónoma Agraria Antonio Narro Unidad Laguna; MéxicoFil: Pereira, Gonzalo. Ministerio de Ganadería, Agricultura y Pesca. Dirección General de Recursos Naturales; UruguayFil: Schulz, Guillermo Andrés. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Suelos; ArgentinaFil: Spence, Adrian. University of the West Indies. International Centre for Environmental and Nuclear Sciences; JamaicaFil: Vasques, Gustavo M. Embrapa Solos; BrasilORNL-DAAC2024-05-10T14:06:41Z2024-05-10T14:06:41Z2019-07-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://hdl.handle.net/20.500.12123/17694https://daac.ornl.gov/CMS/guides/Country_SOC_Latin_America.htmlhttps://doi.org/10.3334/ORNLDAAC/1615ORNL-DAAC News : 1-6. (03 july 2019)reponame:INTA Digital (INTA)instname:Instituto Nacional de Tecnología Agropecuariaenginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)2025-09-04T09:50:21Zoai:localhost:20.500.12123/17694instacron:INTAInstitucionalhttp://repositorio.inta.gob.ar/Organismo científico-tecnológicoNo correspondehttp://repositorio.inta.gob.ar/oai/requesttripaldi.nicolas@inta.gob.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:l2025-09-04 09:50:22.153INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuariafalse |
| dc.title.none.fl_str_mv |
Soil Organic Carbon Stock Estimates with Uncertainty across Latin America |
| title |
Soil Organic Carbon Stock Estimates with Uncertainty across Latin America |
| spellingShingle |
Soil Organic Carbon Stock Estimates with Uncertainty across Latin America Guevara, Mario Carbono Orgánico del Suelo América Latina Soil Organic Carbon Factores de Predicciones Error de Estimación Prediction Factors Estimation Error |
| title_short |
Soil Organic Carbon Stock Estimates with Uncertainty across Latin America |
| title_full |
Soil Organic Carbon Stock Estimates with Uncertainty across Latin America |
| title_fullStr |
Soil Organic Carbon Stock Estimates with Uncertainty across Latin America |
| title_full_unstemmed |
Soil Organic Carbon Stock Estimates with Uncertainty across Latin America |
| title_sort |
Soil Organic Carbon Stock Estimates with Uncertainty across Latin America |
| dc.creator.none.fl_str_mv |
Guevara, Mario Olmedo, Guillermo Federico Stell, Emma Yigini, Yusuf Hernández Arelano, Carlos Arevalo, Gloria Arroyo-Cruz, Carlos Eduardo Bolivar, Adriana Bunning, Sally Bustamante Canas, Nelson Cruz-Gaistardo, Carlos Omar Davila, Fabian Dell Acqua, Martín Encina, Arnulfa Fontes, Fernanda Hernández Herrera, José A. Pereira, Gonzalo Schulz, Guillermo Spence, Adrian Vazques, Gustavo |
| author |
Guevara, Mario |
| author_facet |
Guevara, Mario Olmedo, Guillermo Federico Stell, Emma Yigini, Yusuf Hernández Arelano, Carlos Arevalo, Gloria Arroyo-Cruz, Carlos Eduardo Bolivar, Adriana Bunning, Sally Bustamante Canas, Nelson Cruz-Gaistardo, Carlos Omar Davila, Fabian Dell Acqua, Martín Encina, Arnulfa Fontes, Fernanda Hernández Herrera, José A. Pereira, Gonzalo Schulz, Guillermo Spence, Adrian Vazques, Gustavo |
| author_role |
author |
| author2 |
Olmedo, Guillermo Federico Stell, Emma Yigini, Yusuf Hernández Arelano, Carlos Arevalo, Gloria Arroyo-Cruz, Carlos Eduardo Bolivar, Adriana Bunning, Sally Bustamante Canas, Nelson Cruz-Gaistardo, Carlos Omar Davila, Fabian Dell Acqua, Martín Encina, Arnulfa Fontes, Fernanda Hernández Herrera, José A. Pereira, Gonzalo Schulz, Guillermo Spence, Adrian Vazques, Gustavo |
| author2_role |
author author author author author author author author author author author author author author author author author author author |
| dc.subject.none.fl_str_mv |
Carbono Orgánico del Suelo América Latina Soil Organic Carbon Factores de Predicciones Error de Estimación Prediction Factors Estimation Error |
| topic |
Carbono Orgánico del Suelo América Latina Soil Organic Carbon Factores de Predicciones Error de Estimación Prediction Factors Estimation Error |
| dc.description.none.fl_txt_mv |
This dataset 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. This dataset is representative for the period between 1980 to 2000s corresponding with the highest density of observations available in the WoSIS system and the covariates used as prediction factors for soil organic carbon across Latin America. SOC stocks (kg/m2) were estimated for the SOC and bulk density point measurements and a spatially explicit measure of the SOC estimation error was also calculated. 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. These SOC estimates provide a reproducible example, on country-specific and regional scales, for digital soil mapping across Latin America and contribute to reducing the uncertainty of SOC estimates and improving the parameterization of global models across Latin America. This dataset includes six data files in GeoTIFF (.tif) format at 5 km resolution across Latin America, including: (1) a mosaic of country-specific soil organic carbon estimates, (2) model uncertainty derived for the country-specific estimates, (3) a mosaic of the regional soil organic carbon estimates, (4) model uncertainty derived for the regional estimates, and (5-6) two trend maps of approximate errors associated with the SOC stock calculation method. There is one data file in comma-separated format (.csv) of the point soil characterization data with calculated SOC stock estimates. Four companion files include: a 133-band GeoTiff containing the environmental predictor variables for SOC across Latin America, a .csv file with descriptions of the environmental variables, a shapefile (.shp) of the point soil characterization data with SOC stock estimates and a *.kmz file to display the same. Fil: Guevara, Mario. University of Delaware. Department of Plant and Soil Sciences; Estados Unidos Fil: Olmedo. Guillermo Federico. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Mendoza; Argentina. FAO; Italia Fil: Stell, Emma. University of Delaware. Department of Plant and Soil Sciences; Estados Unidos Fil: Yigini, Yusuf. FAO; Italia Fil: Hernández Arellano, Carlos. Instituto Nacional de Estadística y Geografía; México Fil: Arevalo, Gloria. Zamorano University of Honduras; Honduras. Asociación Hondureña de la Ciencia del Suelo; Honduras Fil: Arroyo-Cruz, Carlos Eduardo. National Commission for the Knowledge and Use of Biodiversity; México Fil: Bolivar, Adriana. Instituto Geográfico Agustín Codazzi. Subdirección Agrología; Colombia Fil: Bunning, Sally. FAO. Oficina Regional de la FAO para América Latina y el Caribe; Chile Fil: Bustamante Cañas, Nelson. Servicio Agrícola y Ganadero; Chile Fil: Cruz-Gaistardo, Calos Omar. Instituto Nacional de Estadística y Geografía; México Fil: Dell Acqua, Martin. Dirección General de Recursos Naturales, Ministerio de Ganadería, Agricultura y Pesca; Uruguay Fil: Davila, Fabian. Ministerio de Ganadería, Agricultura y Pesca, Dirección General de Recursos Naturales; Uruguay Fil: Encina, Arnulfo. Universidad Nacional de Asunción. Facultad de Ciencias Agrarias; Paraguay Fil: Fontes, Fernando. Ministerio de Ganadería, Agricultura y Pesca, Dirección General de Recursos Naturales; Uruguay Fil: Hernández Herrera, José Antonio. Universidad Autónoma Agraria Antonio Narro Unidad Laguna; México Fil: Pereira, Gonzalo. Ministerio de Ganadería, Agricultura y Pesca. Dirección General de Recursos Naturales; Uruguay Fil: Schulz, Guillermo Andrés. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Suelos; Argentina Fil: Spence, Adrian. University of the West Indies. International Centre for Environmental and Nuclear Sciences; Jamaica Fil: Vasques, Gustavo M. Embrapa Solos; Brasil |
| description |
This dataset 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. This dataset is representative for the period between 1980 to 2000s corresponding with the highest density of observations available in the WoSIS system and the covariates used as prediction factors for soil organic carbon across Latin America. SOC stocks (kg/m2) were estimated for the SOC and bulk density point measurements and a spatially explicit measure of the SOC estimation error was also calculated. 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. These SOC estimates provide a reproducible example, on country-specific and regional scales, for digital soil mapping across Latin America and contribute to reducing the uncertainty of SOC estimates and improving the parameterization of global models across Latin America. This dataset includes six data files in GeoTIFF (.tif) format at 5 km resolution across Latin America, including: (1) a mosaic of country-specific soil organic carbon estimates, (2) model uncertainty derived for the country-specific estimates, (3) a mosaic of the regional soil organic carbon estimates, (4) model uncertainty derived for the regional estimates, and (5-6) two trend maps of approximate errors associated with the SOC stock calculation method. There is one data file in comma-separated format (.csv) of the point soil characterization data with calculated SOC stock estimates. Four companion files include: a 133-band GeoTiff containing the environmental predictor variables for SOC across Latin America, a .csv file with descriptions of the environmental variables, a shapefile (.shp) of the point soil characterization data with SOC stock estimates and a *.kmz file to display the same. |
| publishDate |
2019 |
| dc.date.none.fl_str_mv |
2019-07-03 2024-05-10T14:06:41Z 2024-05-10T14:06:41Z |
| dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
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article |
| status_str |
publishedVersion |
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http://hdl.handle.net/20.500.12123/17694 https://daac.ornl.gov/CMS/guides/Country_SOC_Latin_America.html https://doi.org/10.3334/ORNLDAAC/1615 |
| url |
http://hdl.handle.net/20.500.12123/17694 https://daac.ornl.gov/CMS/guides/Country_SOC_Latin_America.html https://doi.org/10.3334/ORNLDAAC/1615 |
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eng |
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eng |
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info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
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openAccess |
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http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
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application/pdf |
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ORNL-DAAC |
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ORNL-DAAC |
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ORNL-DAAC News : 1-6. (03 july 2019) reponame:INTA Digital (INTA) instname:Instituto Nacional de Tecnología Agropecuaria |
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