Spatio-Temporal Evolution and Multi-Scenario Modeling Based on Terrestrial Carbon Stocks in Xinjiang

Xiaohuang Liu (), Zijing Xue, Jiufen Liu, Xiaofeng Zhao, Yujia Fu, Ran Wang, Xinping Luo, Liyuan Xing, Chao Wang and Honghui Zhao
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Xiaohuang Liu: Key Laboratory of Natural Resource Coupling Process and Effects, Ministry of Natural Resources of the People’s Republic of China, Beijing 100055, China
Zijing Xue: Integrated Natural Resources Survey Center, China Geological Survey, Beijing 100055, China
Jiufen Liu: Key Laboratory of Natural Resource Coupling Process and Effects, Ministry of Natural Resources of the People’s Republic of China, Beijing 100055, China
Xiaofeng Zhao: Key Laboratory of Natural Resource Coupling Process and Effects, Ministry of Natural Resources of the People’s Republic of China, Beijing 100055, China
Yujia Fu: Key Laboratory of Natural Resource Coupling Process and Effects, Ministry of Natural Resources of the People’s Republic of China, Beijing 100055, China
Ran Wang: Key Laboratory of Natural Resource Coupling Process and Effects, Ministry of Natural Resources of the People’s Republic of China, Beijing 100055, China
Xinping Luo: Key Laboratory of Natural Resource Coupling Process and Effects, Ministry of Natural Resources of the People’s Republic of China, Beijing 100055, China
Liyuan Xing: Key Laboratory of Natural Resource Coupling Process and Effects, Ministry of Natural Resources of the People’s Republic of China, Beijing 100055, China
Chao Wang: Integrated Natural Resources Survey Center, China Geological Survey, Beijing 100055, China
Honghui Zhao: Integrated Natural Resources Survey Center, China Geological Survey, Beijing 100055, China

Land, 2024, vol. 13, issue 9, 1-23

Abstract: The increase in atmospheric CO 2 leads to global warming and ecological environment deterioration. Carbon storage modeling and assessment can promote the sustainable development of the ecological environment. This paper took Xinjiang as the study area, analyzed the spatial and temporal evolution of land use in four periods from 1990 to 2020, explored the spatial relationship of carbon stocks using the InVEST model, and coupled the GMOP model with the PLUS model to carry out multiple scenarios for the future simulation of land use in the study area. We found (1) Over time, the types with an increasing area were mainly impervious and cropland, and the types with a decreasing area were grassland, snow/ice, and barren; spatially, the types were predominantly barren and grassland, with the conversion of grassland to cropland being more evident in the south of Northern Xinjiang and north of Southern Xinjiang. (2) The evolutionary pattern of terrestrial carbon stocks is increasing and then decreasing in time, and the carbon sink areas are concentrated in the Tarim River Basin and the vicinity of the Ili River; spatially, there are differences in the aggregation between the northern, southern, and eastern borders. By analyzing the transfer in and out of various categories in Xinjiang over the past 30 years, it was obtained that the transfer out of grassland reduced the carbon stock by 5757.84 × 10 4 t, and the transfer out of Barren increased the carbon stock by 8586.12 × 10 4 t. (3) The land use layout of the sustainable development scenario is optimal under the conditions of satisfying economic and ecological development. The reduction in terrestrial carbon stocks under the 2020–2030 sustainable development scenario is 209.79 × 10 4 t, which is smaller than the reduction of 830.79 × 10 4 t in 2010–2020. Land optimization resulted in a lower loss of carbon stocks and a more rational land-use layout. Future planning in Xinjiang should be based on sustainable development scenarios, integrating land resources, and achieving sustainable economic and ecological development.

Keywords: land use; carbon stock; InVEST model; multi-scenario simulation; Xinjiang (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:gam:jlands:v:13:y:2024:i:9:p:1454-:d:1473516

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