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[Interactions and Driving Factors of Ecosystem Services and Human Well-being: A Case Study of Chengdu-Chongqing Urban
Xiang Liao1,2, Xin Yang1,3, She-Ping Guo2
1College of Geography and Planning, Chengdu University of Technology, Chengdu 610059, China.
Abstract:
Revealing the complex interactions between ecosystem services (ESs) and human well-being (HW) across different spatial scales is a prerequisite for achieving coordinated and sustainable development of ESs and HW. This study assessed five categories of provisioning services-water yield (WY), habitat quality (HQ), food production (FP), ecological recreation (ER), and comprehensive ecosystem services (CES)-as well as the level of human well-being in 2000 and 2020. Based on interannual changes, the trade-offs/synergies and their intensities were quantified at grid and county scales, and the dominant driving factors were identified. The results showed that: ① From 2000 to 2020, FP showed the largest increase, with growth rates of 52.70% (grid scale) and 47.88% (county scale), while HQ showed the largest decrease, with reductions of 32.65% (grid scale) and 43.15% (county scale). Overall, human well-being improved by 5.11 times. ② Among the five ES-HW pairs, WY, FP, and ER exhibited overall synergies with HW, whereas HQ and CES displayed trade-offs with HW. At the county scale, the corresponding ES-HW trade-offs/synergies were enhanced, and across scales, the intensities of these trade-offs/synergies showed significant spatial clustering. ③ The five ES-HW pairs were jointly dominated by multiple factors, with the combined effect of these factors being stronger than any single factor. GDP had a significant influence on all ES-HW relationships across scales, while the influence of land use and vegetation factors was more pronounced at the county scale. ④Compared to ordinary least squares regression (OLS) and geographically weighted regression (GWR), multiscale geographically weighted regression (MGWR) performed better in explaining the influence of driving factors on trade-offs/synergies. As a result, some spatially targeted ecological development measures were proposed and recommended to reduce ES-HW trade-offs and better achieve synergies. This study reveals the trade-offs and synergies between ESs and HW in the Chengdu-Chongqing region, along with the driving factors behind them, providing guidance and insights for the region's coordinated ecological and well-being development.
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