A Coupled InVEST-PLUS Model for the Spatiotemporal Evolution of Ecosystem Carbon Storage and Multi-Scenario Prediction Analysis

Land(2024)

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摘要
In investigating the spatiotemporal patterns and spatial attributes of carbon storage across terrestrial ecosystems, there is a significant focus on improving regional carbon sequestration capabilities. Such endeavors are crucial for balancing land development with ecological preservation and promoting sustainable, low-carbon urban growth. This study employs the integrated InVEST-PLUS model to assess and predict changes in ecosystem carbon storage under various land use scenarios within the Chengdu urban cluster, a vital region in Central and Western China, by 2050. The results indicate the following. (1) A linkage between land use dynamics and ecosystem carbon storage changes: over two decades, a 7.5% decrease in arable land was observed alongside a 12.3% increase in urban areas, leading to an 8.2% net reduction in ecosystem carbon storage, equating to a loss of 1.6 million tons of carbon. (2) Carbon storage variations under four scenarios—natural development (NDS), urban development (UDS), farmland protection (FPS), and ecological protection (EPS)—highlight the impact of differing developmental and conservation policies on Chengdu’s carbon reserves. Projections until 2050 suggest a further 5% reduction in carbon storage under NDS without intervention, while EPS could potentially decrease carbon storage loss by 3%, emphasizing the importance of strategic land use planning and policy. This research provides a solid theoretical foundation for exploring the relationship between land use and carbon storage dynamics further. In summary, the findings highlight the necessity of incorporating ecological considerations into urban planning strategies. The InVEST-PLUS model not only sheds light on current challenges but also presents a method for forecasting and mitigating urbanization effects on ecosystem services, thus supporting sustainable development goals.
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关键词
land use change,carbon storage,InVEST model,PLUS model,simulation prediction
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