**5. Conclusions**

In the present study, we calculated plant phenology information in the TRHR based on the MOD09A1 dataset using the method of HANTS and the relative and absolute rates of change on Google Earth Engine. Meanwhile, the extracted plant phenology results were verified using plant phenology station data. Then, we explored the spatiotemporal patterns of plant phenology based on linear regression and standard deviation analyses. Finally, the potential influence mechanism of climatic and soil factors on phenology was analyzed using Pearson correlation coefficients and an SEM model. The verification of plant phenological results shows that our results were well-correlated with observational

data acquired by phenological stations; the determination coefficients of SOS, EOS, and LOS stages were 0.84, 0.72, and 0.86, respectively. The temporal variation of the SOS and LOS indicated that the SOS advanced while the LOS extended. As for spatial patterns, the SOS was the earliest and the LOS was the longest in the Lancang River Basin, while the EOS was the latest in the Yangtze River Basin. Furthermore, the spatial distributions of SOS, EOS, and LOS have strong spatial heterogeneity at different elevations, slopes, and aspects. The potential influence mechanism of climatic and soil factors on the phenology indicated that plant phenology in the Yangtze River Basin is mainly affected by soil factors, while that in the Yellow and Lancang river basins is mainly impacted by climatic factors. The results of this study revealed the spatiotemporal patterns of plant phenology of the TRHR and emphasize the important role of soil factors, precipitation, and temperature in controlling plant phenological dynamics. These findings might help to reveal the mechanisms of potential impacts on plant phenology in alpine wetland ecosystems and provide a theoretical basis for ecosystem management.

**Supplementary Materials:** The following are available online at https://www.mdpi.com/2072-429 2/13/13/2528/s1, Figure S1: Topographic features of Three-River Headwaters region: (a) elevation; (b) slope; (c) aspect; and (d) topographic relief, Figure S2. The monthly means for (a) soil temperature, (b) soil moisture, (c) relative humidity, (d) temperature, (e) precipitation, (f) shortwave radiation in the Yangtze (A), Yellow (B), and Lancang (C) river basins in different periods. Horizontal lines in box plots denote the 95th, 75th, 50th, 25th, and 5th percentiles from top to bottom; the rectangles represent the average values, Figure S3. Spatial pattern of (a, d, g, j, m, and p), standard deviation (b, e, h, k, n, and q) and temporal trend (c, f, i, l, o, and r) for the monthly mean temperature, precipitation, relative humidity, shortwave radiation, soil temperature, and soil moisture at the start of the growing season, Figure S4. Spatial pattern of (a, d, g, j, m, and p), standard deviation (b, e, h, k, n, and q), and temporal trend (c, f, i, l, o, and r) for the monthly mean temperature, precipitation, relative humidity, shortwave radiation, soil temperature, and soil moisture at the end of the growing season, Figure S5. Spatial pattern (a, d, g, j, m, and p), standard deviation (b, e, h, k, n, and q), and temporal trend (c, f, i, l, o, and r) for the monthly mean temperature, precipitation, relative humidity, shortwave radiation, soil temperature, and soil moisture in length of the growing season.

**Author Contributions:** Conceptualization, J.W. and H.S.; methodology, H.S.; software, H.S.; validation, J.W. and H.S.; formal analysis, H.S.; investigation, H.S.; resources, J.X.; data curation, H.S. and D.H.; writing—original draft preparation, H.S.; writing—review and editing, J.W., J.X., D.H., W.C., C.Y., Z.Y. and X.H.; visualization, H.S.; supervision, J.W.; project administration, J.W.; funding acquisition, J.W. and J.X. All authors have read and agreed to the published version of the manuscript.

**Funding:** The study has been funded by the National Natural Science Foundation of China (41701428), Key R & D project of Sichuan Science and Technology Department (Grant No. 2021YFQ0042), the Strategic Priority Research Program of Chinese Academy of Sciences (XDA20030302), the Science and Technology Project of Xizang Autonomous Region (XZ201901-GA-07), National Key R&D Program of China (2020YFD1100701).

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** The data used to support the findings of this study are included within the article.

**Conflicts of Interest:** The authors declare no conflict of interest.
