Abstract: 　　
　　The relationship between land use change and carbon stock is of great significance for the scientific planning of regional land space and the enhancement of ecosystem carbon stock.In this study, we take Eryuan County in Dali Prefecture as an example to analyse the land use changes from 2000 to 2020 based on the InVEST and PLUS models, and to predict the land use and carbon stock under four scenarios (Natural Development S1, Ecological Priority S2, Socio-economic Development S3, and Urban and Rural Development S4) in 2035 and 2040.The results showed that the carbon stock in 2010 was the highest, 314.06×105t, mainly because the area of forest land in 2010 was higher than that in 2000 and 2020, which was 26.34km2 and 1.65km2 respectively; by 2035, the carbon stock under the S1 and S2 scenarios increased slightly, 0.28×105t and 0.42×105t, respectively, while the S3 and S4(0.43×105t, 0.17×105t, respectively) under the scenarios, with the main changes originating from changes in carbon stocks in forest land.By 2040, the carbon stocks in the S1, S2 and S4 scenarios increase to 1.26×105t, 0.33×105t and 0.16×105t respectively, which mainly comes from the increase of carbon stocks in forest land and grassland, while the S3 scenario slightly decreases by 0.09×105t due to the increase in the area of construction land and unutilised land, which encroach on the neighbouring cultivated land, forest land and grassland.Combining the results of the two-year simulation, the area and carbon stock of forest land, grassland and arable land increase under the ecological protection scenario, while the expansion of construction land is effectively curbed under the synergistic development of urban and rural areas, which results in little change in the area and carbon stock transferred from arable land.The results of this paper are intended to provide data support for Eryuan County and even counties in Yunnan Province in terms of land spatial planning and development, regional development, and the enhancement of regional ecosystem carbon stocks.
　　The relationship between land use change and carbon stock is of great significance for the scientific planning of regional land space and the enhancement of ecosystem carbon stock.In this study, we take Eryuan County in Dali Prefecture as an example to analyse the land use changes from 2000 to 2020 based on the InVEST and PLUS models, and to predict the land use and carbon stock under four scenarios (Natural Development S1, Ecological Priority S2, Socio-economic Development S3, and Urban and Rural Development S4) in 2035 and 2040.The results showed that the carbon stock in 2010 was the highest, 314.06×105t, mainly because the area of forest land in 2010 was higher than that in 2000 and 2020, which was 26.34km2 and 1.65km2 respectively; by 2035, the carbon stock under the S1 and S2 scenarios increased slightly, 0.28×105t and 0.42×105t, respectively, while the S3 and S4(0.43×105t, 0.17×105t, respectively) under the scenarios, with the main changes originating from changes in carbon stocks in forest land.By 2040, the carbon stocks in the S1, S2 and S4 scenarios increase to 1.26×105t, 0.33×105t and 0.16×105t respectively, which mainly comes from the increase of carbon stocks in forest land and grassland, while the S3 scenario slightly decreases by 0.09×105t due to the increase in the area of construction land and unutilised land, which encroach on the neighbouring cultivated land, forest land and grassland.Combining the results of the two-year simulation, the area and carbon stock of forest land, grassland and arable land increase under the ecological protection scenario, while the expansion of construction land is effectively curbed under the synergistic development of urban and rural areas, which results in little change in the area and carbon stock transferred from arable land.The results of this paper are intended to provide data support for Eryuan County and even counties in Yunnan Province in terms of land spatial planning and development, regional development, and the enhancement of regional ecosystem carbon stocks.