Spatiotemporal Heterogeneity and Driving Forces of Carbon Storage in the Lower Yangtze River Based on Multi-Model Coupling

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

🔬研究者:Provides a robust framework combining PLUS, InVEST, and Geographical Detector models for analyzing carbon storage dynamics and driving factors, useful for further research on land use and carbon cycling.

🏢実務担当者:Land-use planners and sustainability professionals can apply this methodology to evaluate carbon impacts of different development scenarios and guide land management decisions.

🏛政策担当者:The scenario analysis highlights the importance of protecting high carbon storage zones and implementing region-specific land-use policies to achieve carbon neutrality targets.

For advancing carbon peaking and neutrality objectives and regional socio-ecological sustainability, it is critical to examine how land use change and ecosystem carbon storage may evolve under different development scenarios, and to reveal the spatiotemporal patterns and key drivers of carbon sink capacity across the Lower Yangtze River Basin. Such analysis bears both substantial scientific insight and practical relevance. By coupling the PLUS, InVEST, and Geographical Detector models, the present study conducted a comprehensive assessment of land use and carbon storage dynamics in the Lower Yangtze River region from 2000 to 2025. We further explored how different factors drive the spatiotemporal variation in carbon storage, and predicted the potential land use patterns and associated carbon storage values in the research area by 2030 under three hypothetical scenarios. Collectively, our analysis yielded four core conclusions. (1) Between 2000 and 2025, the land use transformation in the research area was dominated by the continuous shrinkage of arable land and the expansion of construction land. (2) The total carbon storage in the study area declined steadily throughout the study period, showing distinct phased characteristics with a steep drop in the early stage and a slower decline thereafter. (3) Implementing the S2 scenario could effectively curb regional carbon storage loss, whereas the S3 Scenario would result in the most severe carbon stock depletion. (4) The spatial configuration of carbon storage is primarily structured by natural environmental factors. In light of these research outcomes, several recommendations are proposed to guide regional sustainable development. Specifically, efforts should be made to improve the intensive use of urban construction land, thereby minimizing carbon storage loss caused by urbanization. Additionally, develop scientific and targeted ecological conservation policies based on the spatial distribution patterns of high carbon storage zones. Finally, implementing regionally tailored management measures will help achieve coordinated and sustainable development across the study area.

• openalex https://doi.org/10.3390/su18136822first seen 2026-07-08 05:23:06