A Framework Combining CENTURY Modeling and Chronosequences Sampling to Estimate Soil Organic Carbon Stock in an Agricultural Region with Large Land Use Change
Agricultural land use has a remarkable influence on the stock and distribution of soil organic carbon (SOC). However, both regional soil sampling and process-based ecosystem models for SOC estimation at the regional scale have limitations when applied in areas with a large land use change. In the pr...
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| Format: | Article |
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MDPI AG
2023-04-01
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| Series: | Agronomy |
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| Online Access: | https://www.mdpi.com/2073-4395/13/4/1055 |
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| author | Xiaoyu Liu Yin Chen Yang Liu Shihang Wang Jiaming Jin Yongcun Zhao Dongsheng Yu |
| author_facet | Xiaoyu Liu Yin Chen Yang Liu Shihang Wang Jiaming Jin Yongcun Zhao Dongsheng Yu |
| author_sort | Xiaoyu Liu |
| collection | DOAJ |
| description | Agricultural land use has a remarkable influence on the stock and distribution of soil organic carbon (SOC). However, both regional soil sampling and process-based ecosystem models for SOC estimation at the regional scale have limitations when applied in areas with a large land use change. In the present study, a framework (CMCS) combining CENTURY modeling (CM) and chronosequences sampling (CS) was established, and a case study was conducted in Cangshan County, where vegetable cultivation conversion from grain production was significant in recent decades. The SOC stock (SOCS) of the non-vegetable area estimated by CM was comparable to that estimated by regional soil sampling in 2008. This result confirmed that CM was reliable in modeling SOC dynamics in a non-vegetable area without land use change. However, when applied to the overall cropland of Cangshan County, the CM, without considering the land use change, underestimated the SOCS by 0.23 Tg (6%), compared with the observed measurements (3.58 and 3.81 Tg, respectively). Using the CMCS framework of our study, the underestimation of CM was offset by the SOC sequestration estimated by CS. The SOCS estimated by the CMCS framework ranged from 3.72 to 4.02 Tg, demonstrating that this framework is reliable for the regional SOC estimation of large-area land use change. In addition, annual SOCS dynamics were obtained by this framework. The CMCS framework provides a low-cost and practicable method for the estimation of the regional SOC dynamic, which can further support the strategy of carbon peaking and carbon neutrality in China. |
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| institution | Directory Open Access Journal |
| issn | 2073-4395 |
| language | English |
| last_indexed | 2024-03-11T05:20:10Z |
| publishDate | 2023-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Agronomy |
| spelling | doaj.art-ab5b9e7c36e44629b6f744437c8c3e2f2023-11-17T17:56:57ZengMDPI AGAgronomy2073-43952023-04-01134105510.3390/agronomy13041055A Framework Combining CENTURY Modeling and Chronosequences Sampling to Estimate Soil Organic Carbon Stock in an Agricultural Region with Large Land Use ChangeXiaoyu Liu0Yin Chen1Yang Liu2Shihang Wang3Jiaming Jin4Yongcun Zhao5Dongsheng Yu6School of Information Engineering, Jiangsu Vocational College of Agriculture and Forestry, Jurong 212400, ChinaSchool of Information Engineering, Jiangsu Vocational College of Agriculture and Forestry, Jurong 212400, ChinaInstitute of Agricultural Information, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, ChinaSchool of Geomatics, Anhui University of Science and Technology, Huainan 232001, ChinaSchool of Information Engineering, Jiangsu Vocational College of Agriculture and Forestry, Jurong 212400, ChinaState Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, ChinaState Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, ChinaAgricultural land use has a remarkable influence on the stock and distribution of soil organic carbon (SOC). However, both regional soil sampling and process-based ecosystem models for SOC estimation at the regional scale have limitations when applied in areas with a large land use change. In the present study, a framework (CMCS) combining CENTURY modeling (CM) and chronosequences sampling (CS) was established, and a case study was conducted in Cangshan County, where vegetable cultivation conversion from grain production was significant in recent decades. The SOC stock (SOCS) of the non-vegetable area estimated by CM was comparable to that estimated by regional soil sampling in 2008. This result confirmed that CM was reliable in modeling SOC dynamics in a non-vegetable area without land use change. However, when applied to the overall cropland of Cangshan County, the CM, without considering the land use change, underestimated the SOCS by 0.23 Tg (6%), compared with the observed measurements (3.58 and 3.81 Tg, respectively). Using the CMCS framework of our study, the underestimation of CM was offset by the SOC sequestration estimated by CS. The SOCS estimated by the CMCS framework ranged from 3.72 to 4.02 Tg, demonstrating that this framework is reliable for the regional SOC estimation of large-area land use change. In addition, annual SOCS dynamics were obtained by this framework. The CMCS framework provides a low-cost and practicable method for the estimation of the regional SOC dynamic, which can further support the strategy of carbon peaking and carbon neutrality in China.https://www.mdpi.com/2073-4395/13/4/1055soil organic carbon (SOC)CENTURY modeling (CM)land use changechronosequences sampling (CS)vegetable cultivation |
| spellingShingle | Xiaoyu Liu Yin Chen Yang Liu Shihang Wang Jiaming Jin Yongcun Zhao Dongsheng Yu A Framework Combining CENTURY Modeling and Chronosequences Sampling to Estimate Soil Organic Carbon Stock in an Agricultural Region with Large Land Use Change Agronomy soil organic carbon (SOC) CENTURY modeling (CM) land use change chronosequences sampling (CS) vegetable cultivation |
| title | A Framework Combining CENTURY Modeling and Chronosequences Sampling to Estimate Soil Organic Carbon Stock in an Agricultural Region with Large Land Use Change |
| title_full | A Framework Combining CENTURY Modeling and Chronosequences Sampling to Estimate Soil Organic Carbon Stock in an Agricultural Region with Large Land Use Change |
| title_fullStr | A Framework Combining CENTURY Modeling and Chronosequences Sampling to Estimate Soil Organic Carbon Stock in an Agricultural Region with Large Land Use Change |
| title_full_unstemmed | A Framework Combining CENTURY Modeling and Chronosequences Sampling to Estimate Soil Organic Carbon Stock in an Agricultural Region with Large Land Use Change |
| title_short | A Framework Combining CENTURY Modeling and Chronosequences Sampling to Estimate Soil Organic Carbon Stock in an Agricultural Region with Large Land Use Change |
| title_sort | framework combining century modeling and chronosequences sampling to estimate soil organic carbon stock in an agricultural region with large land use change |
| topic | soil organic carbon (SOC) CENTURY modeling (CM) land use change chronosequences sampling (CS) vegetable cultivation |
| url | https://www.mdpi.com/2073-4395/13/4/1055 |
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