Scenario Simulation of the Relationship between Land-Use Changes and Ecosystem Carbon Storage: A Case Study in Dongting Lake Basin, China

Wenqiang Zhou; Jinlong Wang; Yu Han; Ling Yang; Huafei Que; Rong Wang

doi:10.3390/ijerph20064835

Scenario Simulation of the Relationship between Land-Use Changes and Ecosystem Carbon Storage: A Case Study in Dongting Lake Basin, China

Int J Environ Res Public Health. 2023 Mar 9;20(6):4835. doi: 10.3390/ijerph20064835.

Authors

Wenqiang Zhou¹, Jinlong Wang², Yu Han³, Ling Yang², Huafei Que⁴, Rong Wang⁵

Affiliations

¹ College of Forestry, Central South University of Forestry and Technology, Changsha 410004, China.
² College of Business, Central South University of Forestry and Technology, Changsha 410004, China.
³ College of Economics and Management, Southwest University, Chongqing 400715, China.
⁴ Hunan Sports Vacational College, Changsha 410019, China.
⁵ College of Fumiture and Art Design, Central South University of Forestry and Technology, Changsha 410004, China.

Abstract

High-frequency land-use changes caused by rapid economic development have become a key factor in the imbalance of carbon sequestration within regions. How to balance economic development and ecological protection is a difficult issue for regional planning. Studying the relationship between future land-use changes and ecosystem carbon storage (CS) is of important significance for the optimization of regional land-use patterns. The research used the gray prediction model and coupled the patch-generating land-use simulation (PLUS) model and the integrated valuation of ecosystem services and trade-offs (InVEST) model. On this basis, the evolution characteristics and spatial coordination between land-use changes and CS in the Dongting Lake Basin (DLB) in different scenarios in 2030 were simulated. The results show that: (1) The spatial distribution of CS remains stable in different scenarios, while land-use types with high carbon density in the periphery of cities are constantly invaded by construction land, which results in the greatest carbon loss in the urban areas. (2) Compared with the natural evolution scenario (NES), only 195.19 km² of land-use types with high carbon density are transformed into construction land in the ecological protection scenario (EPS), generating a carbon sink gain of 182.47 × 10⁴ Mg. Conversely, in the economic development scenario (EDS), a total of over 1400 km² of farmland and ecological land are transformed into construction land, which weakens the carbon sequestration capacity of ecosystems, and more than 147 × 10⁴ Mg of carbon loss occurs in the urban areas. (3) The planned development scenario (PDS) takes ecological protection and economic development both into consideration, which not only generates a carbon sink gain of 121.33 × 10⁴ Mg but also reduces the carbon loss in urban areas by more than 50%. The PDS performs well in both land use and CS growth and can better motivate the effect of land-use changes in increasing the carbon sink, which is also proved by analysis of the coordination between land-use intensity (LUI) and CS. Therefore, the PDS better satisfies the future development demand of DLB and can provide a reference for sustainable land use in the basin.

Keywords: Dongting Lake Basin; PLUS model; carbon storage; gray prediction; land-use change.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Carbon
China
Conservation of Natural Resources
Ecosystem*
Lakes*

Substances

Carbon

Grants and funding

This research was funded by the National Social Science Fund of China, grant numbers 22BJY094 and 22BGL169; the General Project of Humanities and Social Sciences Research of Ministry of Education of China, grant number 19YJC630166; the China Postdoctoral Science Foundation, grant number 2021M693573; the Natural Science Foundation of Hunan Province of China, grant number 2022JJ30080; the Project of Social Science Achievement Review Committee of Hunan Province of China, grant number XSP22YBC221; and the Research Foundation of Educational Commission of Hunan Province of China, grant number 22A0174.