Spatial prediction of soil organic carbon stocks in Ghana using legacy data
- Autores
- Owusu, Stephen; Yigini, Yusuf; Olmedo, Guillermo Federico; Omuto, Christian Thine
- Año de publicación
- 2019
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- Soil organic carbon (SOC) is a major driver of the multiple functions of soils in the delivery of ecosystem services. While the spatial prediction and mapping of SOC stocks are of key importance for land managers to understand the synergies between SOC management and soil health, a spatially-explicit map of the distribution of SOC stocks in Ghana is non-existent. Therefore, we quantified the spatial distribution of SOC stocks and associated uncertainties to a target depth of 0–30 cm based on regression-kriging modelling to fill this knowledge gap. The mean error (ME) of the predictions is negligible. The mean absolute error (MAE) shows that the model has prediction errors of about 0.48%. The coefficient of determination (R2) shows that the model explains 34% of the variation in model predictions of SOC stocks. The RMSE is 0.63% of the prediction errors. The predicted SOC stocks show significant variation in their spatial distribution throughout the country. Generally, a trend of decreasing SOC stocks from the southwest to the northeast is clearly recognized. SOC stocks are highest in the Semi-Deciduous agro-ecological zone (43.5 Mg C ha−1) and lowest in the Guinea Savannah agro-ecological zone (0.05 Mg C ha−1). About 5.4 Tg of SOC stocks is stored in the top 0–30 cm of the soils in Ghana. This preliminary work at a spatial resolution of 30 arc-seconds (~1 km) has been accomplished within the framework and guidelines of the Global Soil Partnership (GSP). To our knowledge, this is the first time ever in Ghana that a soil property map has been produced along with its uncertainties. Thus, this study represents a significant first step towards revolutionizing future soil property mapping in Ghana. Even though there remains the need to improve on the quality and spatial resolution, the SOC stocks map presented herein is a satisfactory first step to guide future research on soil organic carbon management at both national and global scales.
EEA Mendoza
Fil: Owusu, Stephen. Council for Scientific and Industrial Research. Soil Research Institute; Ghana
Fil: Yigini, Yusuf. Naciones Unidas. Food and Agriculture Organization (FAO); Italia
Fil: Olmedo, Guillermo Federico. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Mendoza; Argentina
Fil: Omuto, Christian Thine. University of Nairobi. Department of Environmental and Biosystems Engineering; Kenia - Fuente
- Geoderma 360 : 114008 (February 2020)
- Materia
-
Carbono Orgánico del Suelo
Suelo
Estimación de las Existencias de Carbono
Teledetección
Ghana
Soil Organic Carbon
Soil
Carbon Stock Assessments
Remote Sensing - Nivel de accesibilidad
- acceso restringido
- Condiciones de uso
- Repositorio
- Institución
- Instituto Nacional de Tecnología Agropecuaria
- OAI Identificador
- oai:localhost:20.500.12123/6430
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Spatial prediction of soil organic carbon stocks in Ghana using legacy dataOwusu, StephenYigini, YusufOlmedo, Guillermo FedericoOmuto, Christian ThineCarbono Orgánico del SueloSueloEstimación de las Existencias de CarbonoTeledetecciónGhanaSoil Organic CarbonSoilCarbon Stock AssessmentsRemote SensingSoil organic carbon (SOC) is a major driver of the multiple functions of soils in the delivery of ecosystem services. While the spatial prediction and mapping of SOC stocks are of key importance for land managers to understand the synergies between SOC management and soil health, a spatially-explicit map of the distribution of SOC stocks in Ghana is non-existent. Therefore, we quantified the spatial distribution of SOC stocks and associated uncertainties to a target depth of 0–30 cm based on regression-kriging modelling to fill this knowledge gap. The mean error (ME) of the predictions is negligible. The mean absolute error (MAE) shows that the model has prediction errors of about 0.48%. The coefficient of determination (R2) shows that the model explains 34% of the variation in model predictions of SOC stocks. The RMSE is 0.63% of the prediction errors. The predicted SOC stocks show significant variation in their spatial distribution throughout the country. Generally, a trend of decreasing SOC stocks from the southwest to the northeast is clearly recognized. SOC stocks are highest in the Semi-Deciduous agro-ecological zone (43.5 Mg C ha−1) and lowest in the Guinea Savannah agro-ecological zone (0.05 Mg C ha−1). About 5.4 Tg of SOC stocks is stored in the top 0–30 cm of the soils in Ghana. This preliminary work at a spatial resolution of 30 arc-seconds (~1 km) has been accomplished within the framework and guidelines of the Global Soil Partnership (GSP). To our knowledge, this is the first time ever in Ghana that a soil property map has been produced along with its uncertainties. Thus, this study represents a significant first step towards revolutionizing future soil property mapping in Ghana. Even though there remains the need to improve on the quality and spatial resolution, the SOC stocks map presented herein is a satisfactory first step to guide future research on soil organic carbon management at both national and global scales.EEA MendozaFil: Owusu, Stephen. Council for Scientific and Industrial Research. Soil Research Institute; GhanaFil: Yigini, Yusuf. Naciones Unidas. Food and Agriculture Organization (FAO); ItaliaFil: Olmedo, Guillermo Federico. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Mendoza; ArgentinaFil: Omuto, Christian Thine. University of Nairobi. Department of Environmental and Biosystems Engineering; KeniaElsevier2019-11-29T13:45:54Z2019-11-29T13:45:54Z2019-11info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttps://www.sciencedirect.com/science/article/pii/S0016706118319074http://hdl.handle.net/20.500.12123/64300016-70611872-6259https://doi.org/10.1016/j.geoderma.2019.114008Geoderma 360 : 114008 (February 2020)reponame:INTA Digital (INTA)instname:Instituto Nacional de Tecnología Agropecuariaenginfo:eu-repo/semantics/restrictedAccess2025-09-04T09:48:17Zoai:localhost:20.500.12123/6430instacron: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 09:48:18.011INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuariafalse |
dc.title.none.fl_str_mv |
Spatial prediction of soil organic carbon stocks in Ghana using legacy data |
title |
Spatial prediction of soil organic carbon stocks in Ghana using legacy data |
spellingShingle |
Spatial prediction of soil organic carbon stocks in Ghana using legacy data Owusu, Stephen Carbono Orgánico del Suelo Suelo Estimación de las Existencias de Carbono Teledetección Ghana Soil Organic Carbon Soil Carbon Stock Assessments Remote Sensing |
title_short |
Spatial prediction of soil organic carbon stocks in Ghana using legacy data |
title_full |
Spatial prediction of soil organic carbon stocks in Ghana using legacy data |
title_fullStr |
Spatial prediction of soil organic carbon stocks in Ghana using legacy data |
title_full_unstemmed |
Spatial prediction of soil organic carbon stocks in Ghana using legacy data |
title_sort |
Spatial prediction of soil organic carbon stocks in Ghana using legacy data |
dc.creator.none.fl_str_mv |
Owusu, Stephen Yigini, Yusuf Olmedo, Guillermo Federico Omuto, Christian Thine |
author |
Owusu, Stephen |
author_facet |
Owusu, Stephen Yigini, Yusuf Olmedo, Guillermo Federico Omuto, Christian Thine |
author_role |
author |
author2 |
Yigini, Yusuf Olmedo, Guillermo Federico Omuto, Christian Thine |
author2_role |
author author author |
dc.subject.none.fl_str_mv |
Carbono Orgánico del Suelo Suelo Estimación de las Existencias de Carbono Teledetección Ghana Soil Organic Carbon Soil Carbon Stock Assessments Remote Sensing |
topic |
Carbono Orgánico del Suelo Suelo Estimación de las Existencias de Carbono Teledetección Ghana Soil Organic Carbon Soil Carbon Stock Assessments Remote Sensing |
dc.description.none.fl_txt_mv |
Soil organic carbon (SOC) is a major driver of the multiple functions of soils in the delivery of ecosystem services. While the spatial prediction and mapping of SOC stocks are of key importance for land managers to understand the synergies between SOC management and soil health, a spatially-explicit map of the distribution of SOC stocks in Ghana is non-existent. Therefore, we quantified the spatial distribution of SOC stocks and associated uncertainties to a target depth of 0–30 cm based on regression-kriging modelling to fill this knowledge gap. The mean error (ME) of the predictions is negligible. The mean absolute error (MAE) shows that the model has prediction errors of about 0.48%. The coefficient of determination (R2) shows that the model explains 34% of the variation in model predictions of SOC stocks. The RMSE is 0.63% of the prediction errors. The predicted SOC stocks show significant variation in their spatial distribution throughout the country. Generally, a trend of decreasing SOC stocks from the southwest to the northeast is clearly recognized. SOC stocks are highest in the Semi-Deciduous agro-ecological zone (43.5 Mg C ha−1) and lowest in the Guinea Savannah agro-ecological zone (0.05 Mg C ha−1). About 5.4 Tg of SOC stocks is stored in the top 0–30 cm of the soils in Ghana. This preliminary work at a spatial resolution of 30 arc-seconds (~1 km) has been accomplished within the framework and guidelines of the Global Soil Partnership (GSP). To our knowledge, this is the first time ever in Ghana that a soil property map has been produced along with its uncertainties. Thus, this study represents a significant first step towards revolutionizing future soil property mapping in Ghana. Even though there remains the need to improve on the quality and spatial resolution, the SOC stocks map presented herein is a satisfactory first step to guide future research on soil organic carbon management at both national and global scales. EEA Mendoza Fil: Owusu, Stephen. Council for Scientific and Industrial Research. Soil Research Institute; Ghana Fil: Yigini, Yusuf. Naciones Unidas. Food and Agriculture Organization (FAO); Italia Fil: Olmedo, Guillermo Federico. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Mendoza; Argentina Fil: Omuto, Christian Thine. University of Nairobi. Department of Environmental and Biosystems Engineering; Kenia |
description |
Soil organic carbon (SOC) is a major driver of the multiple functions of soils in the delivery of ecosystem services. While the spatial prediction and mapping of SOC stocks are of key importance for land managers to understand the synergies between SOC management and soil health, a spatially-explicit map of the distribution of SOC stocks in Ghana is non-existent. Therefore, we quantified the spatial distribution of SOC stocks and associated uncertainties to a target depth of 0–30 cm based on regression-kriging modelling to fill this knowledge gap. The mean error (ME) of the predictions is negligible. The mean absolute error (MAE) shows that the model has prediction errors of about 0.48%. The coefficient of determination (R2) shows that the model explains 34% of the variation in model predictions of SOC stocks. The RMSE is 0.63% of the prediction errors. The predicted SOC stocks show significant variation in their spatial distribution throughout the country. Generally, a trend of decreasing SOC stocks from the southwest to the northeast is clearly recognized. SOC stocks are highest in the Semi-Deciduous agro-ecological zone (43.5 Mg C ha−1) and lowest in the Guinea Savannah agro-ecological zone (0.05 Mg C ha−1). About 5.4 Tg of SOC stocks is stored in the top 0–30 cm of the soils in Ghana. This preliminary work at a spatial resolution of 30 arc-seconds (~1 km) has been accomplished within the framework and guidelines of the Global Soil Partnership (GSP). To our knowledge, this is the first time ever in Ghana that a soil property map has been produced along with its uncertainties. Thus, this study represents a significant first step towards revolutionizing future soil property mapping in Ghana. Even though there remains the need to improve on the quality and spatial resolution, the SOC stocks map presented herein is a satisfactory first step to guide future research on soil organic carbon management at both national and global scales. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-11-29T13:45:54Z 2019-11-29T13:45:54Z 2019-11 |
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 |
format |
article |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
https://www.sciencedirect.com/science/article/pii/S0016706118319074 http://hdl.handle.net/20.500.12123/6430 0016-7061 1872-6259 https://doi.org/10.1016/j.geoderma.2019.114008 |
url |
https://www.sciencedirect.com/science/article/pii/S0016706118319074 http://hdl.handle.net/20.500.12123/6430 https://doi.org/10.1016/j.geoderma.2019.114008 |
identifier_str_mv |
0016-7061 1872-6259 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/restrictedAccess |
eu_rights_str_mv |
restrictedAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Elsevier |
publisher.none.fl_str_mv |
Elsevier |
dc.source.none.fl_str_mv |
Geoderma 360 : 114008 (February 2020) reponame:INTA Digital (INTA) instname:Instituto Nacional de Tecnología Agropecuaria |
reponame_str |
INTA Digital (INTA) |
collection |
INTA Digital (INTA) |
instname_str |
Instituto Nacional de Tecnología Agropecuaria |
repository.name.fl_str_mv |
INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuaria |
repository.mail.fl_str_mv |
tripaldi.nicolas@inta.gob.ar |
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