Coupling Coordination Degree of Ecological-Economic and Its Influencing Factors in the Counties of Yangtze River Economic Belt

Abstract

The rapid economic development (ED) of the Yangtze River Economic Belt (YREB) has had a significant negative impact on regional ecosystem services (ES). Accurately understanding and properly handling the relationship between ES and ED is critical to achieving coordinated regional development of the YREB. Restricted by a minimal number of research units, traditional studies have not fully considered the spatial heterogeneity of the influencing factors, leading to results with poor accuracy and applicability. To address these problems, this paper introduces a spatial econometric model to explore the impact of influencing factors on the level of coordinated development in the YREB. For the 1013 counties in the YREB, we used the value equivalent method, the entropy weight method, and the coupling coordination model to quantify the coupling coordination relationship between the ecosystem services value (ESV) and ED from 2010 to 2020. The multi-scale geographically weighted regression model (MGWR) was adopted to analyze the role of influencing factors. The results showed the following: (1) The coupling coordination degree (CCD) of ESV and ED along the YREB demonstrated significant spatial heterogeneity, with Sichuan and Anhui provinces forming a low-value lag. The average CCD from high to low were found in the Triangle of Central China (TOCC), the Yangtze River Delta urban agglomeration (YRDUA), and the Chengdu–Chongqing urban agglomeration (CCUA). (2) There was spatial autocorrelation in the distribution of CCD, with high–high clustering mainly distributed in Hunan, Jiangxi, and Zhejiang provinces. The counties with high–high clustering were expanding, mainly centering on Kunming City in Yunnan Province and expanding outward. (3) There was significant spatial heterogeneity in the impact of each influencing factor on CCD. Per capita fiscal expenditure was sensitive to low–low clustering areas of CCD; per capita, food production was a negative influence, and the rate of urbanization transitioned from negative to positive values from west to east.