Dual-scale Spatiotemporal Correlation Analysis of Ecosystem Service Value and Land Use Carbon Emissions in the Yangtze River Basin

The spatiotemporal correlation between ecosystem service value (ESV) and land use carbon emissions is of great significance for coordinating regional ecological protection with socio-economic development and promoting the implementation of the "dual carbon" goals. Taking the Yangtze River Basin as the case study area, based on multi-source data from 2002 to 2022, this study employs the equivalent factor method, carbon emission coefficient method, and bivariate spatial autocorrelation analysis. From both grid (20 km) and county-level scales, we systematically analyze the spatiotemporal evolution characteristics and spatial correlation patterns of ESV and land use carbon emissions in the Yangtze River Basin. The results show that: (1) During the study period, the ESV of the Yangtze River Basin remained stable with a slight increase, exhibiting a spatial distribution pattern of "high in the west and low in the east, high in mountainous areas and low in plains"; forestland was the primary contributor to ESV, with its contribution rate increasing from 65.17% to 68.22%, while the negative impact of construction land continued to intensify. (2) The total land use carbon emissions increased from 261 million tons to 738 million tons, with construction land as the dominant carbon source and forestland as the largest carbon sink; high carbon emission areas were concentrated in the Yangtze River Delta in the lower reaches, urban agglomerations in the middle reaches, and the Chengdu-Chongqing region, while high carbon sink areas were located in the upstream mountainous regions and mid-reach forest areas, showing a significant pattern of "carbon sources in the east and carbon sinks in the west". (3) The bivariate spatial autocorrelation analysis reveals a significant negative correlation between ESV and land use carbon emissions, and the degree of negative correlation continuously strengthened during the study period; the negative correlation at the county scale was significantly stronger than that at the grid scale; the Low-High concentration areas were stably distributed in the upstream ecological functional areas, while the High-Low concentration areas were concentrated in the downstream urban agglomerations and agricultural core areas, reflecting the high spatial separation between ecological service supply areas and carbon emission hotspots.