Ecological Indicators (Sep 2024)
An integrated model chain for diagnosing and predicting conflicts between production-living-ecological space in lake network regions: A case of the Dongting Lake region, China
Abstract
The disorderly expansion of human production-living construction activities into aquatic ecological sensitive areas has triggered severe production-living-ecological space (PLES) conflicts. However, research on the risk-triggering mechanisms of PLES conflicts in lake network regions and multidimensional scenario simulation techniques is relatively lacking. To address these issues, this study constructs an integrated model chain by coupling the Markov-GMOP-PLUS model to achieve a quantified diagnosis and simulated regulation of spatial conflict strength index (SCSI) under sustainable development goals. Applying it to the Dongting Lake region reveals that: (1) The overall PLES exhibited a distribution pattern where “ecological space encompasses production space, with living space interspersed within”. The category conversion mainly reflected the encroachment of agricultural production space on the plain water ecological space, with a conversion area of up to 899.48 km2. (2) The distinctive “high in the north, low in the south” PLES conflict pattern was closely aligned with the land use structure and water system distribution, with conflict hotspots persistently clustering in the core lake network regions amid rapid urbanization. Among these, the growth rate of severe conflicts in the last ten years was 3.86 times that of the previous ten years. (3) The sustainable development scenario showcased the most effective conflict mitigation by curtailing production-living space expansion and ecological space encroachment. This scenario reversed the growth trend in conflict high-value zones and the reduction trend in low-value zones, with change rates of −3.30 % and 7.05 %, respectively, compared to 2020. This study provides a scientific basis for formulating sustainable land-use policies in lake network regions.
