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
INTA Digital (INTA)
Institución
Instituto Nacional de Tecnología Agropecuaria
OAI Identificador
oai:localhost:20.500.12123/6430

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spelling 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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