Zonal simulations for soil organic carbon mapping in coastal wetlands

Digital soil mapping (DSM) has been developed for decades and aims to accurately simulate the soil factors with low cost. However, it still cost considerably in coastal wetlands because of the high difficulty in field survey. A zonal simulation approach was proposed for decreasing the cost of field...

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Autores principales:	Yuan Chi, Dahai Liu, Zuolun Xie
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Soil organic carbon Zonal simulation Subzone Digital soil mapping Coastal wetland Ecology QH540-549.5
Acceso en línea:	https://doaj.org/article/985bd972b9fe43debd301a8dd10d207c
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id	oai:doaj.org-article:985bd972b9fe43debd301a8dd10d207c
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spelling	oai:doaj.org-article:985bd972b9fe43debd301a8dd10d207c2021-12-01T05:01:57ZZonal simulations for soil organic carbon mapping in coastal wetlands1470-160X10.1016/j.ecolind.2021.108291https://doaj.org/article/985bd972b9fe43debd301a8dd10d207c2021-12-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S1470160X21009560https://doaj.org/toc/1470-160XDigital soil mapping (DSM) has been developed for decades and aims to accurately simulate the soil factors with low cost. However, it still cost considerably in coastal wetlands because of the high difficulty in field survey. A zonal simulation approach was proposed for decreasing the cost of field survey in the premise of high accuracy for soil organic carbon stock mapping in coastal wetlands, and Chongming Island, an important estuarine wetland in China, was used to demonstrate the study. A subzone with an area proportion lower than 20% was identified based on the typicalness of land surface characteristics and soil influencing factors for the whole study area. Entire and zonal simulations were conducted using abundant predictors sourced from remote sensing, partial least square regression, and 10-fold cross validation. The results revealed that root mean squared errors of entire and zonal simulations were 1.70 g/kg and 1.95 g/kg, respectively, which were in a low level compared with those in previous studies and indicated the high simulation accuracy. The zonal simulation exhibited a slightly lower accuracy than the entire simulation, while considerably decreased the cost by more than 50%. The decrease in the cost showed a much more practical significance than the increase in the accuracy in areas with high difficulty in field survey, and the geographical integrity and continuity of the whole study area, the typicalness of the selected subzone, and the spatial extent were the three key points when promoting the zonal simulation in DSM. The soil organic carbon stock in the study area was generally high in areas with good vegetation condition, low soil salinity, complex landscape configuration, and long distances from the sea. Human activities and the resulting landscape fragmentation have been the dominant factor that drives the spatial pattern of soil organic carbon stock.Yuan ChiDahai LiuZuolun XieElsevierarticleSoil organic carbonZonal simulationSubzoneDigital soil mappingCoastal wetlandEcologyQH540-549.5ENEcological Indicators, Vol 132, Iss , Pp 108291- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Soil organic carbon Zonal simulation Subzone Digital soil mapping Coastal wetland Ecology QH540-549.5
spellingShingle	Soil organic carbon Zonal simulation Subzone Digital soil mapping Coastal wetland Ecology QH540-549.5 Yuan Chi Dahai Liu Zuolun Xie Zonal simulations for soil organic carbon mapping in coastal wetlands
description	Digital soil mapping (DSM) has been developed for decades and aims to accurately simulate the soil factors with low cost. However, it still cost considerably in coastal wetlands because of the high difficulty in field survey. A zonal simulation approach was proposed for decreasing the cost of field survey in the premise of high accuracy for soil organic carbon stock mapping in coastal wetlands, and Chongming Island, an important estuarine wetland in China, was used to demonstrate the study. A subzone with an area proportion lower than 20% was identified based on the typicalness of land surface characteristics and soil influencing factors for the whole study area. Entire and zonal simulations were conducted using abundant predictors sourced from remote sensing, partial least square regression, and 10-fold cross validation. The results revealed that root mean squared errors of entire and zonal simulations were 1.70 g/kg and 1.95 g/kg, respectively, which were in a low level compared with those in previous studies and indicated the high simulation accuracy. The zonal simulation exhibited a slightly lower accuracy than the entire simulation, while considerably decreased the cost by more than 50%. The decrease in the cost showed a much more practical significance than the increase in the accuracy in areas with high difficulty in field survey, and the geographical integrity and continuity of the whole study area, the typicalness of the selected subzone, and the spatial extent were the three key points when promoting the zonal simulation in DSM. The soil organic carbon stock in the study area was generally high in areas with good vegetation condition, low soil salinity, complex landscape configuration, and long distances from the sea. Human activities and the resulting landscape fragmentation have been the dominant factor that drives the spatial pattern of soil organic carbon stock.
format	article
author	Yuan Chi Dahai Liu Zuolun Xie
author_facet	Yuan Chi Dahai Liu Zuolun Xie
author_sort	Yuan Chi
title	Zonal simulations for soil organic carbon mapping in coastal wetlands
title_short	Zonal simulations for soil organic carbon mapping in coastal wetlands
title_full	Zonal simulations for soil organic carbon mapping in coastal wetlands
title_fullStr	Zonal simulations for soil organic carbon mapping in coastal wetlands
title_full_unstemmed	Zonal simulations for soil organic carbon mapping in coastal wetlands
title_sort	zonal simulations for soil organic carbon mapping in coastal wetlands
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/985bd972b9fe43debd301a8dd10d207c
work_keys_str_mv	AT yuanchi zonalsimulationsforsoilorganiccarbonmappingincoastalwetlands AT dahailiu zonalsimulationsforsoilorganiccarbonmappingincoastalwetlands AT zuolunxie zonalsimulationsforsoilorganiccarbonmappingincoastalwetlands
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Zonal simulations for soil organic carbon mapping in coastal wetlands

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