Spatiotemporal Evolution and Prediction of Ecosystem Carbon Storage in the Yiluo River Basin Based on the PLUS-InVEST Model

Abstract

Land-use change has a great impact on regional ecosystem balance and carbon storage, so it is of great significance to study future land-use types and carbon storage in a region to optimize the regional land-use structure. Based on the existing land-use data and the different scenarios of the shared socioeconomic pathway and the representative concentration pathway (SSP-RCP) provided by CMIP6, this study used the PLUS model to predict future land use and the InVEST model to predict the carbon storage in the study area in the historical period and under different scenarios in the future. The results show the following: (1) The change in land use will lead to a change in carbon storage. From 2000 to 2020, the conversion of cultivated land to construction land was the main transfer type, which was also an important reason for the decrease in regional carbon storage. (2) Under the three scenarios, the SSP126 scenario has the smallest share of arable land area, while this scenario has the largest share of woodland and grassland land area, and none of the three scenarios shows a significant decrease in woodland area. (3) From 2020 to 2050, the carbon stocks in the study area under the three scenarios, SSP126, SSP245, and SSP585, all show different degrees of decline, decreasing to 36,405.0204 × 104 t, 36,251.4402 × 104 t, and 36,190.4066 × 104 t, respectively. Restricting the conversion of land with a high carbon storage capacity to land with a low carbon storage capacity is conducive to the benign development of regional carbon storage. This study can provide a reference for the adjustment and management of future land-use structures in the region.

Study on the variation of carbon storage in the Chang-Zhu-Tan urban agglomeration in China based on topographic relief

“…They found that the associated model could effectively assess the impact of future urban expansion on the environment (He et al 2016). The studies, as mentioned earlier, have achieved satisfactory results by coupling changes in land use with the InVEST model, which enables a clear reflection of the spatial distribution pattern of carbon storage (Adelisardou et al 2022;Li et al 2023).…”