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

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

🔬研究者:Useful for spatial analysis methods (bivariate spatial autocorrelation) applied to carbon and ecosystem service interactions.

🏢実務担当者:Land-use planners and regional development agencies can apply the approach to balance ecological conservation and emission reduction.

🏛政策担当者:Highlights the need for spatial targeting in carbon neutrality policies to avoid conflicts between emission hotspots and ecological service areas.

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.

• semanticscholar https://doi.org/10.62381/i265302first seen 2026-07-24 06:56:38