Novel model for NPP prediction based on temperature and land use changes: A case in Sichuan and Chongqing, China

The net primary productivity (NPP) is a direct reflection of the productivity of vegetation communities; predicting changes in the NPP is important for assessing the sustainability of ecosystems. However, few studies have been conducted on the prediction of the NPP, and it is necessary to develop more prediction models. Therefore, in this study, a model based on temperature and land use/cover changes (LUCCs) was developed and applied to the Sichuan-Chongqing region, and the prediction results were obtained under the development scenarios composed of a shared socioeconomic pathway (SSP) and a representative concentration pathway (RCP). The results show that: (1) the NPP in the Sichuan-Chongqing region in 2020 simulated using the newly developed model to the actual NPP in 2020, and the kappa coefficient was 75.03%, which indicates that this model has a good applicability. (2) The total NPP increased in all five SSP-RCP scenarios (from high to low, SSP5-8.5, SSP4-6.0, SSP1-2.6, SSP2-4.5, and SSP3-7.0), but the SSP3-7.0 and SSP5-8.5 scenarios include uncontrolled urban expansion, leading to destruction of ecological areas. The SSP2-4.5 scenario continues the existing development pattern, with more moderate land use and NPP changes. The urban land use in the SSP1-2.6 and SSP4-6.0 scenarios is more intensive and the level of ecological protection is better. Simulating the LUCCs under different SSP-RCP scenarios and predicting the NPP changes can provide a theoretical basis for coping with future ecological changes and improving ecosystem stability