## 5 Conclusions  
In this study, we compared the timing of SOS and EOS and their response to preceding climate conditions in meadow steppe, typical steppe, and desert steppe in Inner Mongolia. Our findings suggest that desert steppe has a relatively later growing season than meadow steppe and typical steppe. We further found that, on average for all Mongolian grassland, water availability mainly controlled the timing of SOS, while temperature is the key factor for determining the occurrence of EOS.  
Figure 9: Shifts of pre-SOS/EOS temperature (**a**) and precipitation (**b**) from 2000–2014 to 2011–2015 in typical steppe and desert steppe. In the figure, the different letters denote there is a significant change of temperature/precipitation from 2000–2014 to 2011–2015 at the level of 0.05, while the same letter denotes there is no significant variation of temperature/precipitation from 2000–2014 to 2011–2015.  
Regarding differences among grasslands, we conclude that SOS is primarily controlled by pre-SOS precipitation in all the three grasslands showing the largest sensitivity in desert steppe. In comparison, our findings suggest that EOS was closely connected with pre-EOS air temperature in meadow steppe and typical steppe while pre-EOS precipitation determined EOS in desert steppe. Based on our results we conclude that temperature and precipitation both affect the phenological process of grassland plants, but their influencing magnitudes are inconsistent for different phenological events and for different vegetation types. Additionally, we found that SOS in typical steppe and desert steppe has significantly advanced due to the significant increase of pre-SOS precipitation, while EOS in desert steppe has also significantly advanced because of elevated preseason temperature and precipitation. Overall, the findings from this study highlight the diverse timings of spring and autumn phenology and their contrasting responses to pre-season temperature and precipitation in different grassland types which has important implications for adopting grazing systems to future climate change and for developing policy frameworks grassland protection.  
The following are available online at www.mdpi.com/2072-4292/10/1/17/s1. We validated the reliability of gridded climate data with measured climate data in 42 meteorological sites. Table S1. Linear regression of grid climate data and measured climate variables in meteorological stations.  
We would like to thank the Environmental and Ecological Science Data Center for West China, National Natural Science Foundation of China ([[http://westdc.westgis.ac.cn](http://westdc.westgis.ac.cn)]([http://westdc.westgis.ac.cn](http://westdc.westgis.ac.cn))), for providing the 1:1,000,000 Editorial Board of Vegetation Map of China. This work was funded by grants from the National Key R&D Program of China (2017 YFA0604801), the National Natural Science Foundation of China (No. 41601064) and the independent grants from the State Key Laboratory of Cryosphere Sciences (SKLCS-ZZ-2017).  
[PERSON] designed the research and performed phenological metric extraction and spatiotemporal analysis. All authors contributed to the interpretation of the results and the writing of the paper.  
The authors declare no conflict of interest.