Assessment and simulation of ecosystem carbon storage in rapidly urbanizing areas based on land use cover: a case study of the southern Jiangsu urban agglomeration, China

Since China’s reform and opening-up period, the southern Jiangsu urban agglomeration has been one of the fastest urbanizing regions in the country. This rapid urbanization has led to dramatic changes in land use cover that have been the primary drivers of carbon stock changes in the terrestrial ecosystem. In this study, we utilize the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model and a patch-generating land use simulation (PLUS) model to analyze the land use changes and carbon stocks in the southern Jiangsu urban agglomeration over the past 30 years. We then simulate the carbon stock changes in the study area in the year 2050 under natural growth, cultivated land conservation, and ecological conservation scenarios. The results showed that 1) over the past 30 years, the urban area has increased by 2.98 times, reaching 7,408.42 km2 by 2020. In contrast, the area of cultivated and forested land has continued to decrease with rapid urbanization. 2) Between 1990 and 2020, the carbon stock of the urban agglomeration in southern Jiangsu decreased by 5.34%. The changes in the spatial distribution of carbon stocks are consistent with the changes in land use. 3) By 2050, the carbon stock loss was the largest under the natural growth scenario at 10.49 mt, while the carbon stock loss was the smallest under the cultivated land protection scenario at 0.97 mt. Under the ecological protection scenario, the carbon stock loss was 9.9 mt. The results indicate that the adoption of cultivated land and ecological protection measures can effectively control the reduction of carbon stock in rapidly urbanizing areas. 4) The conversion of cultivated land and forest land to urban land was the primary reason for the carbon stock reduction in the study area, which was primarily located in the urban outward expansion area. This study provides a reference- and data-based support for the management, decision-making, and planning in rapidly urbanizing areas.