关键词: 碳储存, LULC预测, 随机森林, Markov–FLUS模型, InVEST模型

Abstract: The evolution of land use/land cover (LULC) patterns significantly influences the dynamics of carbon storage (CS) in terrestrial ecosystems. In response to future environmental changes, however, most studies fail to synthesize the effects of policy pathways and evolving core driving factors on LULC projections. This article presents a systematic framework to assess the dynamic response of the terrestrial ecosystem CS to future LULC changes. After investigating spatiotemporal characteristics and driving forces, policy effects and future core driving factors are integrated into the improved Markov–future land use simulation model to project LULC across diverse scenarios. Then the Integrated Valuation of Ecosystem Service and Tradeoff model is coupled to explore CS dynamics with LULC changes. This framework was applied to the Weihe River Basin. The finding reveals that the overall proportion of cultivated land, forestland and grassland is above 85% and is significantly influenced by policy effects. Precipitation, temperature, population density and gross domestic product are core driving factors of LULC changes. Equal-interval projection is a viable approach to mitigate policy impacts by avoiding error propagation while coupling future core driving factors to improve LULC projection accuracy. Ecological protection should be emphasized in the future. The rate of increase in CS is 1.25 and 1.63 times higher than the historical trend and economic development scenario, respectively, which alleviates carbon loss from the expansion of built-up land. This research provides a valuable reference for future insight and optimization of ecological conservation strategies.

Key words: carbon storage,  LULC projection, random forest, Markov–FLUS, InVEST model