Abstract
Optimizing the spatial pattern of its carbon storage is of great significance for increasing the carbon storage capacity of regional ecosystem and maintaining regional carbon balance. Although the existing research has achieved remarkable results in regional carbon storage assessment and multi-scenario simulation studies, there are still obvious deficiencies in determining specific carbon storage optimization areas for developed regions and formulating targeted low-carbon development strategies. Taking the economically developed Jiangsu section of the Yangtze River Basin (JS-YRB) as an example, combined with InVEST and PLUS models, the carbon storage and its spatial distribution pattern of the study area in 2030 were predicted under three different scenarios: natural development, cropland protection and ecological protection. The pattern of carbon storage in the study area was optimized by a Bayesian belief network (BBN) with decision optimization ability. The results showed that: (1) From 2000 to 2020, the carbon storage in the study area exhibited a decreasing trend, with a total reduction of 47.98 × 10(6) t. The primary reason for these decreases was the conversion of cropland and forest land to built-up land. (2) In 2030, under the ecological protection scenario, the carbon storage in the study area would be 390.58 × 10(6) t, showing an upward trend, while under the other two scenarios, the carbon storage would show a downward trend. (3) Key variables and key state subsets were selected by BBN, and the study area would be divided into four types of optimal zones: ecological protection area, cropland protection area, water conservation area and economic construction area. The findings can provide a reference for the sustainable development of land use within the watershed and contribute to advancing the watershed's efforts toward achieving the carbon neutrality goals.