Baseline map of soil organic matter in China and its associated uncertainty

Accurate digital soil maps of soil organic matter (SOM) are needed to evaluate soil fertility, to estimate stocks, and for ecological and environment modeling. We used 5982 soil profiles collected during the second national soil survey of China, along with 19 environment predictors, to derive a spat...

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Main Authors: Liang, Z., Chen, S., Yang, Y., Zhao, R., Shi, Z., Viscarra Rossel, Raphael
Format: Journal Article
Published: Elsevier Science 2019
Online Access:http://hdl.handle.net/20.500.11937/73642
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author Liang, Z.
Chen, S.
Yang, Y.
Zhao, R.
Shi, Z.
Viscarra Rossel, Raphael
author_facet Liang, Z.
Chen, S.
Yang, Y.
Zhao, R.
Shi, Z.
Viscarra Rossel, Raphael
author_sort Liang, Z.
building Curtin Institutional Repository
collection Online Access
description Accurate digital soil maps of soil organic matter (SOM) are needed to evaluate soil fertility, to estimate stocks, and for ecological and environment modeling. We used 5982 soil profiles collected during the second national soil survey of China, along with 19 environment predictors, to derive a spatial model of SOM concentration in the topsoil (0–20 cm layer). The environmental predictors relate to the soil forming factors, climate, vegetation, relief and parent material. We developed the model using the Cubist machine-learning algorithm combined with a non-parametric bootstrap to derive estimates of model uncertainty. We optimized the Cubist model using a 10-fold cross-validation and the best model used 17 rules. The correlation coefficient between the observed and predicted values was 0.65, and the root mean squared error was 0.28 g/kg. We then applied the model over China and mapped the SOM distribution at a resolution of 90 × 90 m. Our predictions show that there is more SOM in the eastern Tibetan Plateau, northern Heilongjiang province, northeast Mongolia, and a small area of Tianshan Mountain in Xinjiang. There is less SOM in the Loess Plateau and most of the desert areas in northwest China. The average topsoil SOM content is 24.82 g/kg. The study provides a map that can be used for decision-making and contribute towards a baseline assessment for inventory and monitoring. The map could also aid the design of future soil surveys and help with the development of a SOM monitoring network in China.
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institution Curtin University Malaysia
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publishDate 2019
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spelling curtin-20.500.11937-736422019-08-14T06:14:43Z Baseline map of soil organic matter in China and its associated uncertainty Liang, Z. Chen, S. Yang, Y. Zhao, R. Shi, Z. Viscarra Rossel, Raphael Accurate digital soil maps of soil organic matter (SOM) are needed to evaluate soil fertility, to estimate stocks, and for ecological and environment modeling. We used 5982 soil profiles collected during the second national soil survey of China, along with 19 environment predictors, to derive a spatial model of SOM concentration in the topsoil (0–20 cm layer). The environmental predictors relate to the soil forming factors, climate, vegetation, relief and parent material. We developed the model using the Cubist machine-learning algorithm combined with a non-parametric bootstrap to derive estimates of model uncertainty. We optimized the Cubist model using a 10-fold cross-validation and the best model used 17 rules. The correlation coefficient between the observed and predicted values was 0.65, and the root mean squared error was 0.28 g/kg. We then applied the model over China and mapped the SOM distribution at a resolution of 90 × 90 m. Our predictions show that there is more SOM in the eastern Tibetan Plateau, northern Heilongjiang province, northeast Mongolia, and a small area of Tianshan Mountain in Xinjiang. There is less SOM in the Loess Plateau and most of the desert areas in northwest China. The average topsoil SOM content is 24.82 g/kg. The study provides a map that can be used for decision-making and contribute towards a baseline assessment for inventory and monitoring. The map could also aid the design of future soil surveys and help with the development of a SOM monitoring network in China. 2019 Journal Article http://hdl.handle.net/20.500.11937/73642 10.1016/j.geoderma.2018.08.011 Elsevier Science restricted
spellingShingle Liang, Z.
Chen, S.
Yang, Y.
Zhao, R.
Shi, Z.
Viscarra Rossel, Raphael
Baseline map of soil organic matter in China and its associated uncertainty
title Baseline map of soil organic matter in China and its associated uncertainty
title_full Baseline map of soil organic matter in China and its associated uncertainty
title_fullStr Baseline map of soil organic matter in China and its associated uncertainty
title_full_unstemmed Baseline map of soil organic matter in China and its associated uncertainty
title_short Baseline map of soil organic matter in China and its associated uncertainty
title_sort baseline map of soil organic matter in china and its associated uncertainty
url http://hdl.handle.net/20.500.11937/73642