Evaluation of the impacts of ozone on the vegetation productivity of woodland and grassland ecosystems in China

In the context of global warming, with the increasing tropospheric ozone concentration and the obvious trend of aridity, terrestrial ecosystems are experiencing multiple pressures. However, there are still many uncertainties in modeling the effects of ozone on ecosystem productivity. In this study, an ozone uptake module was coupled to the BEPS (Boreal Ecosystem Productivity Simulator) model, and the new version, the BEPS-O3 model, was used to simulate the impacts of ozone on the gross primary productivity (GPP) of woodland and grassland ecosystems in China. Observational data from four sites were used to verify and improve the models, namely, DXG (grassland), HBG (shrub), DHS (evergreen broad-leaved) and CBS (coniferous forest). The regional results show that the total GPP of forest, grassland and shrub in China was 3.62 Pg C, 0.75 Pg C 0.33 Pg C in 2016, respectively. The GPP loss of forests, grasslands and shrubs caused by ozone was 2.8% and 1.1% and 1.5% of the GPP in woodland and grassland ecosystems, respectively (excluding farmland). Subtropical regions experienced the worst GPP losses, although ozone concentrations were not high. However, higher stomatal conductance leads to higher ozone absorption. By comparing the parameters of previous studies, we conclude that the ozone uptake function was better than the ozone exposure function in modeling. Furthermore, the selection of the ozone uptake function will have a significant impact on the final simulation results, especially for grassland.

Automated summary

In this study, the BEPS-O3 model was used to simulate the impacts of ozone on the gross primary productivity (GPP) of woodland and grassland ecosystems in China. The results showed that the total GPP of forest, grassland, and shrub in China was 3.62 Pg C, 0.75 Pg C, and 0.33 Pg C in 2016, respectively. The GPP loss caused by ozone in woodland and grassland ecosystems was 2.8%, 1.1%, and 1.5%, respectively.