## 4 Discussion  
### Seasonal Variations in \(R_{s}\)  
The seasonal patterns of \(R_{s}\), \(T_{s}\), LST, and NDVI all showed symmetrical bell type distributions, while \(M_{s}\) fluctuated during the nine-year measuring time. The variation in \(R_{s}\) was consistent with that of the temperature (\(T_{s}\), LST), illustrating that temperature could explain most of the temporal variation of \(R_{s}\). [PERSON] et al. (2018) observed a similar trend in the daily mean soil temperature at 1 cm depth and daily CO\({}_{2}\)-C efflux, and a fluctuating trend of \(M_{s}\) at 15 cm depth among the four surveyed years of 1999-2002 in a cool-temperate deciduous broad-leaved forest in Japan. [PERSON] et al. (2018) found that the seasonal variation of \(R_{s}\) was not completely consistent with the daily mean \(T_{s}\) of the upper 10 cm and that variations in \(R_{s}\) followed GPP during most of the growing seasons in a wheat and maize rotation cropland in the North China Plain. The present study site was a sub-alpine meadow;  
Figure 8: Reference soil respiration (R\({}_{10}\)) and temperature sensitivity of soil respiration (Q\({}_{10}\)) derived from the exponential equations in each year. Figure 7: Temperature sensitivity of soil respiration (Q\({}_{10}\)) with (**a**) soil respiration (\(R_{s}\)) and (**b**) soil temperature (\(T_{s}\)) in different temperature intervals. Error bars indicate the standard errors. accordingly, the amount of biomass was very small. Moreover, obvious vegetation degradation due to anthropogenic activities has occurred in the region in recent years. Therefore, biomass had a relatively smaller effect on \(R_{\rm s}\) in the study site, with the temporal variation of \(R_{\rm s}\) being not completely consistent with that of NDVI. The correlation analysis of all measured data (analysis not shown) revealed that the correlation between \(R_{\rm s}\) and \(T_{\rm s}\) became lower as soil depth increased (T\({}_{\rm 5}\) \(>\) T\({}_{\rm 10}\) \(>\) T\({}_{\rm 15}\)), indicating that the soil respiration rate was more influenced by the soil temperature close to the surface. Since there was no forest cover in the study site, the soil temperature was completely controlled by changes in solar radiation. A lagging phenomenon in which the soil temperature at greater depth showed obvious time hysteresis when compared with the soil temperature near the surface was observed by [PERSON] et al. (2013). The LST\({}_{\rm m}\) (nighttime LST from the Terra satellite) captured the seasonal variation of \(R_{\rm s}\) best among all the MODIS eight-day LST products in the study site during the nine-year period, which was consistent with the results of other studies. [PERSON] et al. (2013) selected the nighttime LST observed by the Terra satellite to estimate \(R_{\rm s}\) at 2 contrasting forest sites, while [PERSON] et al. (2013) chose the average LST of daytime and nighttime data from MOD1A2 as a driver of the \(R_{\rm s}\) fitting model of a deciduous broadleaf forest in the midwestern United States. [PERSON] et al. (2013) reported that the nighttime LST from the Terra satellite was better correlated with the soil respiration than the daytime LST at a Canadian boreal black spruce stand and indicated that the nighttime LST could be a better estimate of the baseline temperature that regulated plant phenology. These results confirmed that the nighttime land surface temperature data from the MODIS eight-day spatial products captured \(R_{\rm s}\) variation reliably. [PERSON] et al. (2014) demonstrated that the \(R_{\rm s}\) of 0 \({}^{\circ}\)C soil temperature at -1 cm was higher during autumn than spring because the active soil layer remained large as the deeper soil layers warmed up in the summer. [PERSON] (2013) also found that the \(R_{\rm s}\) of 0 \({}^{\circ}\)C soil temperature was higher during the highest fine-root production period from July to September.