巢湖流域生态系统服务时空演变及其社会-生态驱动因子研究

Research on spatiotemporal evolution of ecosystem services and their socio-ecological driving factors in Chaohu Lake Basin

摘要

【目的】在快速城市化和区域经济增长背景下，研究生态系统服务(Ecosystem Services, ESs)的时空演变及其驱动机制对区域的可持续发展至关重要。巢湖流域作为长江中下游的重要区域，其生态系统服务具有显著价值。【方法】利用InVEST模型和空间自相关分析方法，分析2000年、2010年和2020年五类关键ESs(碳储存、产水量、生境质量、土壤保持、水质净化)的时空变化格局，通过自组织映射(Self-Organizing Map, SOM)方法将ESs簇划分为森林碳汇簇、水资源簇、综合生态簇和低服务簇，并结合地理加权回归(Geographically Weighted Regression, GWR)探究社会-生态驱动因子的影响。【结果】结果表明，碳储存和土壤保持功能在林地和草地显著增强，水质净化功能在工业区周边提升明显。2000年碳储存与生境质量协同指数在北部林地为0.87,而2020年城市区域产水量与水质净化协同指数为0.77。驱动因子由自然因子(NDVI贡献为98.12%)逐渐转向社会因子，2020年GDP和POP对水质净化和生境质量的贡献分别达10.42%和45.45%。【结论】城市化显著影响巢湖流域ESs的时空格局，应结合驱动因子特征优化生态环境规划与保护策略，平衡ESs的权衡与协同，实现巢湖流域的可持续发展。

Abstract

[Objective] In the context of rapid urbanization and regional economic growth, studying the spatiotemporal evolution of ecosystem services(ESs) and their driving mechanisms is vital for regional sustainable development. The Chaohu Lake Basin, as an important area in the middle and lower reaches of the Yangtze River, has significant value in its ecosystem services. [Methods] Using the InVEST model and spatial autocorrelation analysis, the spatiotemporal variation patterns of five key ESs—carbon storage, water yield, habitat quality, soil conservation, and water purification—in 2000, 2010, and 2020 were analyzed. The self-organizing map(SOM) method was used to classify the ESs into four clusters: forest carbon sink cluster, water resource cluster, integrated ecology cluster, and low service cluster. The effect of socio-ecological driving factors was explored using geographically weighted regression(GWR). [Results] The result showed that carbon storage and soil conservation functions significantly increased in forests and grasslands, while water purification function notably improved around industrial areas. In 2000, the synergy index of carbon storage and habitat quality in northern forests was 0.87, whereas in 2020, the synergy index of water yield and water purification in urban areas was 0.77. Driving factors gradually shifted from natural factors(with normalized difference vegetation index(NDVI) contributing 98.12%) to social factors, with GDP and population(POP) contributing 10.42% and 45.45% to water purification and habitat quality, respectively, in 2020. [Conclusion] Urbanization significantly influences the spatiotemporal patterns of ESs in the Chaohu Lake Basin. It is essential to optimize ecological environment planning and conservation strategies based on the characteristics of driving factors, balance the trade-offs and synergies of ESs, and achieve sustainable development in the Chaohu Lake Basin.

关键词

生态系统服务(ESs) / 社会-生态驱动因子 / 权衡-协同关系 / 空间格局 / 巢湖流域

Key words

ecosystem services(ESs) / socio-ecological driving factors / trade-off and synergy relationship / spatial pattern / Chaohu Lake Basin

基金资助

国家自然科学基金青年科学基金项目(32170183)

安徽省发展和改革委员会资助项目(W2023JSFW0526)