Abstract:

The impacts of future global warming of 1.5°C and 2°C on the productivity and carbon (C) storage of grasslands in China are not clear yet, although grasslands in China support ~45 million agricultural populations and more than 238 million livestock populations, and are sensitive to global warming.

This study used a process-based terrestrial ecosystem model named ORCHIDEE to simulate C cycle of alpine meadows and temperate grasslands in China. This model was driven by high-resolution (0.5° × 0.5°) climate of global specific warming levels (SWL) of 1.5°C and 2°C (warmer than pre-industrial level), which is downscaled by EC-EARTH3-HR v3.1 with sea surface temperature and sea-ice concentration as boundary conditions from IPSL-CM5-LR (low spatial resolution, 2.5° × 1.5°) Earth system model (ESM).

Compared with baseline (1971–2005), the mean annual air temperature over Chinese grasslands increased by 2.5°C and 3.7°C under SWL1.5 and SWL2, respectively. The increase in temperature in the alpine meadow was higher than that in the temperate grassland under both SWL1.5 and SWL2. Precipitation was also shown an increasing trend under SWL2 over most of the Chinese grasslands. Strong increases in gross primary productivity (GPP) were simulated in the Chinese grasslands, and the mean annual GPP (GPP_MA) increased by 19.32% and 43.62% under SWL1.5 and SWL2, respectively. The C storage increased by 0.64 Pg C and 1.37 Pg C under SWL1.5 and SWL2 for 50 years simulations. The GPP_MA was 0.670.880.39 (0.82) (model meanmaxmin0.670.390.88 (0.82) (model meanminmax (this study)), 0.851.240.45 (0.97)0.850.451.24 (0.97) and 0.941.300.61 (1.17)0.940.611.30 (1.17) Pg C year−1 under baseline, SWL1.5 and SWL2 modeled by four CMIP5 ESMs (phase 5 of the Coupled Model Inter-comparison Project Earth System Models). In contrast, the mean annual net biome productivity was −18.554.47−40.37 (−3.61),−18.55−40.374.47 (−3.61),18.6564.03−2.03 (10.29)18.65−2.0364.03 (10.29) and 24.1538.778.38 (24.93)24.158.3838.77 (24.93) Tg C year−1 under baseline, SWL1.5 and SWL2 modeled by the four CMIP5 ESMs. Our results indicated that the Chinese grasslands would have higher productivity than the baseline and can mitigate climate change through increased C sequestration under future global warming of 1.5°C and 2°C with the increase of precipitation and the global increase of atmospheric CO₂ concentration.

Key words: productivity, carbon storage, specific warming level, grassland, climate change