Extreme climate occurred frequently in subtropical region, which seriously affects carbon and water fluxes such as evapotranspiration (ET) and gross primary productivity (GPP) of terrestrial ecosystems. The process -based biome biogeochemical cycles (Biome-BGC) model is widely used for simulating carbon and water fluxes of forest ecosystems. However, the lack of the interaction information of climate, vegetation and soil, such as the hysteresis effect, canopy stratification on photosynthesis, impedes better simulations of the ecohydrological processes. Here, we tended to improve the simulation accuracy of Biome-BGC model at a subtropical forest on the Xin'an River in Southeastern China by reconstructing the precipitation series, modifying the ET and canopy multilayers modules, and optimizing the parameters. The spatiotemporal patterns of GPP, ET, water use efficiency (WUE) and their response to environmental factors across the Xin'an River Basin from 1982 to 2018 were further explored. The results showed that the improved model performed well, with the determination coefficient, root means square error and mean absolute error being 0.730, 1.522 gC/m2/d and 1.218 gC/m2/d for GPP, 0.857, 1.082 mm/d and 0.838 mm/d for ET, respectively. Basin -averaged GPP, ET and WUE increased during 1982-2018 and these increasing trends were more pronounced during 1999-2018. Significant positive trends of WUE occurred in the northeast corner. The increasing air temperature and precipitation respectively dominated the increase in GPP and ET, the increasing CO2 concentration and NDVI mitigated the negative effect of extreme precipitation on WUE. Given that human activities such as afforestation have effectively reduced the extent of damage to forest ecosystems from extreme precipitation, we highlight an urgent need to formulate adaptation strategies aimed at reducing the risk of extreme climate in humid regions.

Rapid warming in alpine regions exerts important effects on carbon cycling in alpine ecosystem, which are sensitive to environmental changes. So far, little is known about the spatial and temporal variation in carbon budgets and the main influencing factors over different ecosystems. Here, we examined the monthly and annual gross primary production (GPP), net ecosystem CO2 exchange (NEE) and ecosystem respiration (ER) during 2004-2017 in four types of ecosystems (i.e., alpine meadow, steppe, forest and cropland) on the Tibetan Plateau. We explored the relationships between carbon fluxes and environmental factors. The results show that forest, cropland and alpine meadow ecosystems acted as carbon sinks, with NEE values ranging from -21.25 +/- 3.54 to -308.75 +/- 21.65 g C m-2a-1, while alpine steppe and overmature forest ecosystems serve as carbon sources (mean annual NEE: 23.12 +/- 15.88 g C m-2a-1). The temperature sensitivity values (Q10) of ER in the forest (9.39) and alpine steppe (7.47) ecosystems were greater than those in the alpine meadow ecosystems (Q10 = 4.20), indicating that the carbon emissions in the forest and alpine steppe ecosystems were more sensitive to warming. Multiple linear regression analysis indicated that the carbon fluxes (GPP, NEE, ER) of alpine steppe and alpine meadow in the permafrost regions were more sensitive to water forcing (precipitation, soil water content), while in the forest and cropland ecosystems temperature forcing (air and soil temperature) were strong predictors of all the carbon flux indices. Our results showed differential responses of carbon budgets among ecosystems, which could be considered in the future modeling of carbon cycle in alpine regions.