## 5 Conclusions  
In this study, we examined the correlations between changes in snow cover and the NDVI and investigated the response of the NDVI to snow cover changes on the QTP. Our main conclusions can be summarized as follows: The snow depth on the whole plateau exhibited significant small fluctuations, where the multi-year rate of change was \(-\)0.016 mm/a. The NDVI did not increase significantly over a large area, and the multi-year rate of change was 0.0005/a. The changes in snow cover were negatively correlated with the changes in NDVI over time, and other meteorological factors also had correlations, where the Pearson correlations significance followed the order of precipitation > snow depth > temperature > solar radiation. The overall spatial correlations between the snow cover and NDVI had pronounced regional characteristics; the impact of snow cover on vegetation was more significant in high-altitude areas. The maximum snow depth corresponded to the lowest NDVI value with a lag of about 2 months, and abnormally deep snow cover caused by heavy snowfall events had negative impacts on the NDVI for more than 3 years. Compared with the effects of snow in winter on the NDVI in spring, the lagged effect of snow in spring on the NDVI in summer was weaker. The lagging effect was significant inter-annually, but not intra-annually, and extreme weather exacerbated the inter-annual lagging effect. The hysteresis effect was inter-annual but not intra-annual, and extreme weather exacerbated the inter-annual hysteresis effect. These findings have implications for animal husbandry and ecological protection in the QTP region. Future work in this area will contribute to the sustainable development of plateau animal husbandry and ecological protection. Conceptualization, F.L. ; formal analysis, Y.Z. ; investigation, Y.Z. ; resources, Y.Z. and F.L. ; data curation, Y.Z. ; writing--original draft preparation, Y.Z. ; writing--review and editing, F.L., G.Z. and J.W. ; visualization, Y.Z. and J.W. ; supervision, F.L. and J.W. ; project administration, F.L. ; funding acquisition, F.L. All authors have read and agreed to the published version of the manuscript. This research is supported by the National Key Research and Development Program (2019 YFA0606902). **Data Availability Statement:** All observational datasets and model simulations used in this study are publicly available. Snow depth data are available from the TPDC China Snow Depth Long-Time Series Dataset at [[http://data.tpdc.ac.cn/zh-hans/data/df40346a-0202-4](http://data.tpdc.ac.cn/zh-hans/data/df40346a-0202-4) ed2-bb07-b65 dfcda9]([http://data.tpdc.ac.cn/zh-hans/data/df40346a-0202-4](http://data.tpdc.ac.cn/zh-hans/data/df40346a-0202-4) ed2-bb07-b65 dfcda9) 368/ (accessed on 30 August 2022). NDVI data are available from NOAA GIMS NDVI3g at [[https://www.star.nesdis.noaa.gov/pub/corp/scsb/wguo/data/](https://www.star.nesdis.noaa.gov/pub/corp/scsb/wguo/data/)]([https://www.star.nesdis.noaa.gov/pub/corp/scsb/wguo/data/](https://www.star.nesdis.noaa.gov/pub/corp/scsb/wguo/data/)) (accessed on 5 September 2022). Temperatures data are available from TPDC China 1 km resolution monthly average temperature dataset (1901-2020) at [[https://poles.tpdc.ac.cn/zh-hans/data/7](https://poles.tpdc.ac.cn/zh-hans/data/7) lab677-b66c-dfd1-d004-b2a541 cd5 bf/]([https://poles.tpdc.ac.cn/zh-hans/data/7](https://poles.tpdc.ac.cn/zh-hans/data/7) lab677-b66c-dfd1-d004-b2a541 cd5 bf/) (accessed on 10 April 2023). Precipitation data are available from TPDC China 1 km resolution monthly precipitation dataset (1901-2020) at [[http://www.tpdc.ac.cn/zh-hans/data/faae7605-a0f2-4d18-b28f-5](http://www.tpdc.ac.cn/zh-hans/data/faae7605-a0f2-4d18-b28f-5) cee413766a2/]([http://www.tpdc.ac.cn/zh-hans/data/faae7605-a0f2-4d18-b28f-5](http://www.tpdc.ac.cn/zh-hans/data/faae7605-a0f2-4d18-b28f-5) cee413766a2/) (accessed on 10 April 2023).