[Analysis on the Trade-off Relationship between Carbon Storage and Non-point Source Pollution Load and Its Influencing Factors in the Dongjiang River Source Basin].

Abstract

Revealing the relationship between carbon storage and pollution load is conducive to understanding the mechanism of regional ecosystem service. The carbon storage and pollution load of Dongjiang River Source Basin were analyzed using the ecosystem service assessment and pollution load assessment model. Land use was obtained using a supervised classification method based on a Landsat 8 image in 2018. The InVEST model and carbon density data from literature survey were used to evaluate the carbon storage of Dongjiang River Source Basin. The non-point source pollution load was estimated by the Johnes coefficient model. Regression analysis and redundancy analysis were used to explore the trade-offs and influencing factors between carbon storage and pollution load. The results showed that forest land, cultivated land, and orchard land were the main land use types in the Dongjiang River Source Basin, accounting for 74.7%, 12.0%, and 9.7%, respectively. The carbon storage of the Dongjiang River Basin was 140-180 t·hm^-2, showing a pattern of a wide distribution of hot spots and mosaic of cold spots in space. The pollution load showed a mosaic distribution pattern with the high value area including Tianjiu, Changpu, Wenfeng, and Zhengang and the low value area including Sanbaishan, Sanbiao, and Guizhumao. The pollution discharge of livestock and poultry breeding was one of the main sources of non-point source pollution. Regressive analysis showed the complex relationship between pollution load and carbon storage of Dongjiang River Source Basin. Redundancy analysis showed that both were affected by natural conditions and socio-economic conditions, in which carbon storage was affected more significantly by land use, NDVI, and population and pollution load was affected more significantly by GDP, temperature, and precipitation. The results emphasize the use of ecosystem services trade-off collaborative analysis to identify priority areas for pollution reduction and carbon sequestration.