Response of grassland net primary productivity to climate change in China

Abstract

To protect the grassland ecosystem’s security, and coordinate the utilisation of grassland resources, explicitly estimating the response of Net Primary Productivity (NPP) of 10 grassland groups to future climate change is necessary. Based on the Comprehensive and Sequential Classification System (CSCS) and modified Carnegie Ames Stanford Approach (CASA) model, in conjunction with four Representative Concentration Pathways (RCP 2.6, RCP 4.5, RCP 6.0, RCP 8.5) of the Intergovernmental Panel on Climate Change (IPCC), the response of China’s grassland NPP to climate change was simulated and estimated. Results showed that: (1) the simulation accuracy of modified CASA model (R2 = 0.65) is 34% higher than that of CASA model, indicating that the modified CASA was suitable for estimating grassland NPP in China; (2) annual mean NPP and total NPP (2001–18) were 138.4 g C m−2 year−1 and 495.7 T g C, respectively; compared with the period 2001–18, NPP during the 2050 under RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5 were predicted with increases of 34.8%, 35.9%, 34.9% and 35.8%, respectively; and (3) from the present-day to the 2050, the NPP of Warm desert exhibited the largest increase (73.2–76.3%), while that of Tundra and alpine grassland the smallest (1.3–1.6%). These differences in NPP increase likely lead to differences in grassland carrying capacity. To respond to the impact of future climate change on grassland, grassland classification management strategies according to different groups should be implemented as grassland NPP changes differently in different grassland groups.