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Spatial-Temporal Changes of Soil Organic Carbon Content in Wafangdian, China

Author

Listed:
  • Shuai Wang

    (College of Land and Environment, Shenyang Agricultural University, Shenyang 110866, Liaoning Province, China)

  • Qiubing Wang

    (College of Land and Environment, Shenyang Agricultural University, Shenyang 110866, Liaoning Province, China)

  • Kabindra Adhikari

    (Department of Soil Science, University of Wisconsin-Madison, Madison, WI 53706, USA)

  • Shuhai Jia

    (College of Land and Environment, Shenyang Agricultural University, Shenyang 110866, Liaoning Province, China)

  • Xinxin Jin

    (College of Land and Environment, Shenyang Agricultural University, Shenyang 110866, Liaoning Province, China)

  • Hongbin Liu

    (College of Land and Environment, Shenyang Agricultural University, Shenyang 110866, Liaoning Province, China)

Abstract

Soil organic carbon (SOC) plays an important role in soil fertility and the global carbon cycle. A better understanding of spatial-temporal changes of SOC content is essential for soil resource management, emission studies, and carbon accounting. In this study, we used a boosted regression trees (BRT) model to map distributions of SOC content in the topsoil (0–20 cm) and evaluated its temporal dynamics from 1990–2010 in Wafangdian City, northeast of China. A set of 110 (1990) and 127 (2010) soil samples were collected and nine environment variables (including topography and vegetation) were used. A 10-fold cross-validation was used to evaluate model performance as well as predictive uncertainty. Accuracy assessments showed that R 2 of 0.53 and RMSE (Root-mean-square error) of 9.7 g∙kg −1 for 1990, and 0.55, and 5.2 g∙kg −1 for 2010. Elevation and NDVI (Normalized Difference Vegetation Index) were the two important variables affecting SOC distribution. Results showed that mean SOC content decreased from 19 ± 14 to 18 ± 8 g∙kg −1 over a 20 year period. The maps of SOC represented a decreasing trend from south to north across the study area in both periods. Rapid urbanization and land-use changes were accountable for declining SOC levels. We believe predicted maps of SOC can help local land managers and government agencies to evaluate soil quality and assess carbon sequestration potential and carbon credits.

Suggested Citation

  • Shuai Wang & Qiubing Wang & Kabindra Adhikari & Shuhai Jia & Xinxin Jin & Hongbin Liu, 2016. "Spatial-Temporal Changes of Soil Organic Carbon Content in Wafangdian, China," Sustainability, MDPI, vol. 8(11), pages 1-16, November.
  • Handle: RePEc:gam:jsusta:v:8:y:2016:i:11:p:1154-:d:82553
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    References listed on IDEAS

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    1. Kabindra Adhikari & Alfred E Hartemink & Budiman Minasny & Rania Bou Kheir & Mette B Greve & Mogens H Greve, 2014. "Digital Mapping of Soil Organic Carbon Contents and Stocks in Denmark," PLOS ONE, Public Library of Science, vol. 9(8), pages 1-13, August.
    2. Lefeng Qiu & Jinxia Zhu & Ke Wang & Wei Hu, 2015. "Land Use Changes Induced County-Scale Carbon Consequences in Southeast China 1979–2020, Evidence from Fuyang, Zhejiang Province," Sustainability, MDPI, vol. 8(1), pages 1-13, December.
    3. Kai Yin & Dengsheng Lu & Yichen Tian & Qianjun Zhao & Chao Yuan, 2014. "Evaluation of Carbon and Oxygen Balances in Urban Ecosystems Using Land Use/Land Cover and Statistical Data," Sustainability, MDPI, vol. 7(1), pages 1-27, December.
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    Cited by:

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    2. Li Qi & Shuai Wang & Qianlai Zhuang & Zijiao Yang & Shubin Bai & Xinxin Jin & Guangyu Lei, 2019. "Spatial-Temporal Changes in Soil Organic Carbon and pH in the Liaoning Province of China: A Modeling Analysis Based on Observational Data," Sustainability, MDPI, vol. 11(13), pages 1-17, June.
    3. Hongbin Liu & Shunting Li & Yuepeng Zhou, 2019. "Spatial-Temporal Variability of Soil Organic Matter in Urban Fringe over 30 Years: A Case Study in Northeast China," IJERPH, MDPI, vol. 17(1), pages 1-22, December.
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    5. Cuiying Zhou & Xingxing Ge & Wei Huang & Dexian Li & Zhen Liu, 2019. "Effects of Aqua-Dispersing Nano-Binder on Clay Conductivity at Different Temperatures," Sustainability, MDPI, vol. 11(18), pages 1-13, September.
    6. Zefang Zhao & Yanlong Guo & Haiyan Wei & Qiao Ran & Wei Gu, 2017. "Predictions of the Potential Geographical Distribution and Quality of a Gynostemma pentaphyllum Base on the Fuzzy Matter Element Model in China," Sustainability, MDPI, vol. 9(7), pages 1-15, July.

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