全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

Effects of Snowpack on Vegetation Phenology in the Hulunbuir Grassland Region of China

DOI: 10.4236/oalib.1112205, PP. 1-11

Keywords: Snowpack, Vegetation, Partial Correlation Analysis, Hulunbuir Grassland

Full-Text   Cite this paper   Add to My Lib

Abstract:

Currently, global warming has a significant impact on snow and vegetation in mid to high latitude regions. This paper primarily utilizes Fractional Vegetation Cover (FVC), snow phenological parameters, including the Start of Snow Cover Days (SCS), Melt of Snow Cover Days (SCM), and Snow Cover Days (SCD), complemented by soil temperature and moisture data. Employing partial correlation analysis, it was found that in this region, SCD is most closely associated with FVC. FVC was most strongly correlated with SCD and SCM. Additionally, the impact of snow cover on FVC is primarily reflected in temperature and moisture. The study’s findings offer new insights into snow phenology and the growth of grasslands. 

References

[1]  Avtar, R., Yunus, A.P., Saito, O., Kharrazi, A., Kumar, P. and Takeuchi, K. (2020) Multi-Temporal Remote Sensing Data to Monitor Terrestrial Ecosystem Responses to Climate Variations in Ghana. Geocarto International, 37, 396-412. https://doi.org/10.1080/10106049.2020.1723716
[2]  Guo, J. and Hu, Y. (2022) Spatiotemporal Variations in Satellite-Derived Vege-tation Phenological Parameters in Northeast China. Remote Sensing, 14, Article 705. https://doi.org/10.3390/rs14030705
[3]  Buus-Hinkler, J., Hansen, B.U., Tamstorf, M.P. and Pedersen, S.B. (2006) Snow-Vegetation Relations in a High Arctic Ecosystem: Inter-Annual Variability Inferred from New Monitoring and Modeling Concepts. Remote Sens-ing of Environment, 105, 237-247. https://doi.org/10.1016/j.rse.2006.06.016
[4]  Desai, A.R., Wohlfahrt, G., Zeeman, M.J., Katata, G., Eugster, W., Montagnani, L., et al. (2016) Montane Ecosystem Productivity Responds More to Global Circulation Patterns than Climatic Trends. Environmental Research Letters, 11, Article ID: 024013. https://doi.org/10.1088/1748-9326/11/2/024013
[5]  Dorji, T., Totland, Ø., Moe, S.R., Hopping, K.A., Pan, J. and Klein, J.A. (2012) Plant Functional Traits Mediate Reproductive Phenology and Success in Response to Experimental Warming and Snow Addition in Tibet. Global Change Biology, 19, 459-472. https://doi.org/10.1111/gcb.12059
[6]  Huang, K., Xu, W., Wang, H., Li, H., Li, L., Li, Z., et al. (2024) Dynamic Snow Melting Pro-cess and Its Driving Factors in Northern Grasslands. Atmosphere, 15, Article 462. https://doi.org/10.3390/atmos15040462
[7]  Verrall, B. and Pickering, C.M. (2020) Alpine Vegetation in the Context of Climate Change: A Global Review of Past Research and Future Directions. Science of the Total Environment, 748, Article ID: 141344. https://doi.org/10.1016/j.scitotenv.2020.141344
[8]  Zhu, Y., Shan, D., Wang, B., Shi, Z., Yang, X. and Liu, Y. (2019) Floristic Fea-tures and Vegetation Classification of the Hulun Buir Steppe in North China: Geography and Climate-Driven Steppe Diversification. Global Ecology and Conservation, 20, e00741. https://doi.org/10.1016/j.gecco.2019.e00741
[9]  Ying, H., Shan, Y., Zhang, H., Yu-an, T., Rihan, W. and Deng, G. (2019) The Effect of Snow Depth on Spring Wildfires on the Hulunbuir from 2001-2018 Based on Modis. Remote Sensing, 11, Article 321. https://doi.org/10.3390/rs11030321
[10]  Sa, C., Meng, F., Luo, M., Li, C., Wang, M., Adiya, S., et al. (2021) Spatiotemporal Variation in Snow Cover and Its Effects on Grassland Phenology on the Mongolian Plateau. Journal of Arid Land, 13, 332-349. https://doi.org/10.1007/s40333-021-0056-7
[11]  Freppaz, M., Celi, L., Marchelli, M. and Zanini, E. (2008) Snow Removal and Its Influence on Temperature and N Dynamics in Alpine Soils (vallée D’aoste, Northwest Italy). Journal of Plant Nutrition and Soil Science, 171, 672-680. https://doi.org/10.1002/jpln.200700278
[12]  Zhang, X., Zhou, J., Liang, S. and Wang, D. (2021) A Practical Reanalysis Data and Thermal Infrared Remote Sensing Data Merging (RTM) Method for Reconstruction of a 1-Km All-Weather Land Surface Temperature. Remote Sensing of Environment, 260, Article ID: 112437. https://doi.org/10.1016/j.rse.2021.112437

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133