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.

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Biodiversity loss is a critical challenge globally, and protected areas (PAs) has been established as an important policy tool for conservation. However, doubts exist regarding their effectiveness, and their policy effects and spatial spillover effects on surrounding areas are poorly understood. To address this, this study evaluated the effectiveness of Heilongjiang Nanwenghe National Nature Reserve (HNNNR) in China by using a combination of the InVEST model and the improved SDID model. The study covers a time span of approximately 31 years (1990–2020) and is divided into two periods (1990–1999 and 1999–2020), which allows for the assessment of the effects of nature reserves in the region. Our results showed that: (1) The establishment of HNNNR has improved the habitat quality in the reserve and Non-reserve area, with a greater impact on habitat quality in non-reserve areas than in the reserve; (2) The core zone within HNNNR showed the most significant improvement in habitat quality, while the buffer zone showed the least improvement; (3) The improvement of habitat quality in non-reserve area was mainly contributed by the policy spatial spillover effects, where the buffer zone has the strongest spillover benefits to the non-reserve, but the core zone has the weakest spillover effects to the non-reserve. Our results show the beneficial impact of a nature reserve for improving habitat quality in and around the reserve. This study provides a quantitative paradigm for assessing the conservation effectiveness of PAs across temporal and spatial scales.