Nitrogen (N) deposition has increased globally and has profoundly influenced the structure and function of grasslands. Previous studies have discussed how N addition affects aboveground biomass (AGB), but the effects of N addition on the AGB of different functional groups in grasslands remain unclear. We conducted a meta-analysis to identify the responses of AGB and the AGB of grasses (AGB_grass) and forbs (AGB_forb) to N addition across global grasslands. Our results showed that N addition significantly increased AGB and AGB_grass by 31 and 79%, respectively, but had no significant effect on AGB_forb. The effects of N addition on AGB and AGB_grass increased with increasing N addition rates, but which on AGB_forb decreased. Although study durations did not regulate the response ratio of N addition for AGB, which for AGB_grass increased and for AGB_forb decreased with increasing study durations. Furthermore, the N addition response ratios for AGB and AGB_grass increased more strongly when the mean annual precipitation (MAP) was 300–600 mm but decreased with an increase in the mean annual temperature (MAT). AGB_forb was only slightly affected by MAP and MAT. Our findings suggest that an acceleration of N deposition will increase grassland AGB by altering species composition.

The modeling and partitioning of regional evapotranspiration (ET) are key issues in global hydrological and ecological research. We incorporated a stomatal conductance model and a light-use efficiency-based gross primary productivity (GPP) model into the Shuttleworth–Wallace model to develop a simplified carbon-water coupling model, SWH, for estimating ET using meteorological and remote sensing data. To enable regional application of the SWH model, we optimized key parameters with measurements from global eddy covariance (EC) tower sites. In addition, we estimated soil water content with the principle of the bucket system. The model prediction of ET agreed well with the estimates obtained with the EC measurements, with an average R² of 0.77 and a root mean square error of 0.72 mm·day⁻¹. The model performance was generally better for woody ecosystems than herbaceous ecosystems. Finally, the spatial patterns of ET and relevant model outputs (i.e., GPP, water-use efficiency and the ratio of soil water evaporation to ET) in China with the model simulations were assessed.

Changes in the sizes of precipitation events in the context of global climate change may have profound impacts on ecosystem productivity in arid and semiarid grasslands. However, we still have little knowledge about to what extent grassland productivity will respond to an individual precipitation event. In this study, we quantified the duration, the maximum, and the time-integrated amount of the response of daily gross primary productivity (GPP) to an individual precipitation event and their variations with different sizes of precipitation events in a typical temperate steppe in Inner Mongolia, China. Results showed that the duration of GPP-response (τ _R) and the maximum absolute GPP-response (GPP_max) increased linearly with the sizes of precipitation events (P _es), driving a corresponding increase in time-integrated amount of the GPP-response (GPP_total) because variations of GPPtotal were largely explained by τ _R and GPP_max. The relative contributions of these two parameters to GPP_total were strongly P _es-dependent. The GPP_max contributed more to the variations of GPP_total when P _es was relatively small (<20 mm), whereas τ _R was the main driver to the variations of GPP_total when P _es was relatively large. In addition, a threshold size of at least 5 mm of precipitation was required to induce a GPP-response for the temperate steppe in this study. Our work has important implications for the modeling community to obtain an advanced understanding of productivity-response of grassland ecosystems to altered precipitation regimes.