## 4 Discussion  
### Biotic and Climatic Control over \(Re\)  
Our analysis reveals that among biotic and climatic factors, plant productivity and moisture exert stronger influences than temperature on regulating the spatial pattern of \(RE\). These two factors together can well explain the spatial patterns of \(RE\), accounting for 54% and 58% of the variation in the temperate grasslands and alpine grasslands, respectively (Table 4). The important role of plant productivity and moisture in regulating the spatial pattern of \(RE\) is in good accordance with other studies across the world [20; 46; 59; 60]. Most of the variation in \(RE\) could be attributed to the difference in plant productivity among sites, with a relatively smaller proportion being further explained by moisture, but the moisture effect differs significantly between the two grasslands and plays a more crucial role in the water-deficit temperate grasslands than the alpine grasslands (Figure 3, Table 4). \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Grassland Type**} & \multicolumn{2}{c}{_EV\({}_{mean}\) \& _EV\({}_{mean}\) \& _LSW\({}_{mean}\)_} & _EV\({}_{mean}\) \& _LSW\({}_{mean}\) \& _LSW\({}_{mean}\)_ \& _LST\({}_{mean}\)_ \\ \cline{2-7}  & \(R^{2}\) & **RMSE (g C m\({}^{-2}\) day\({}^{-1}\))** & \(R^{2}\) & **RMSE (g C m\({}^{-2}\) day\({}^{-1}\))** & \(R^{2}\) & **RMSE (g C m\({}^{-2}\) day\({}^{-1}\))** \\ \hline Temperate grasslands & 0.424 & 0.147 & 0.541 & 0.125 & 0.554 & 0.113 \\ Alpine grasslands & 0.539 & 0.714 & 0.577 & 0.653 & 0.588 & 0.617 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Relationship between _Reref_ and the combined effects of _EV\({}_{mean}\)_, _LST\({}_{mean}\)_, and _LSW\({}_{mean}\)_.  
Figure 7: Predicted spatial distribution of the mean annual ecosystem respiration (RE). (**a**) and the reference respiration (_Reref_); (**b**) by our model and mean annual \(RE\) by CLM4 CN; (**c**) in northern China’s grasslands. Although temperature has been noted to be positively correlated with \(RE\) across biomes at a global scale [40; 41] and an important limitation on \(RE\) in alpine ecosystems, the inclusion of \(LST_{mean}\) does not significantly affect the explanation of _Reref_ variation (Table 4). In the alpine grasslands, studies increasingly suggest that plant biomass is the direct determinant of \(RE\) distribution [61; 62; 63], while moisture changes, but not temperature, serve as another indirect determinant via regulating plant growth and distribution in the vast alpine grasslands (4400-4800 m) [64]. The above two explanations describe how temperature is less important to governing the spatial pattern of \(RE\) in the alpine grasslands. However, the dependence of _Reref_ on \(LST_{mean}\) appears to be stronger and negative in the temperate grasslands (Figure 3, Table 2). In fact, the relation of \(RE\) with temperature can be confounded by moisture in arid and semi-arid ecosystems [63; 65]. Specifically, the gradient of precipitation mainly defines the declining gradient of \(RE\) from the northeast to the southwest in the Inner Mongolian Plateau, which is exactly opposite to the gradient of temperature [66], thus leading to the apparently close and negative spatial correlation between temperature and \(RE\). In contrast, temperature becomes the major controlling factor in terms of the temporal pattern of \(RE\) (Figure 4). The significant exponential dependence of seasonal \(RE\) on temperature that was observed in these two regions is consistent with many other grassland ecosystems [67; 68]. However, there are obvious differences in the temperature control over \(RE\) among different climate zones. For the alpine grasslands, temperature explained 75.2% of the seasonal variability of \(RE\) and was the strongest controlling factor. However, the magnitude of the temporal dynamics of \(RE\) due to temperature decreased to 68.7% for the temperate grasslands.