Biodiv Sci ›› 2024, Vol. 32 ›› Issue (5): 23432.  DOI: 10.17520/biods.2023432

• Original Papers: Plant Diversity • Previous Articles     Next Articles

Temporal and spatial trends in NDVI of vegetation in water level fluctuation zone and drivers along an altitude gradient in the Yarlung Zangbo River Basin

Yao Zhang1,2, Junyao Sun2,3(), Wei Li1,4,5,*()()   

  1. 1 School of Ecology and Environment, Tibet University, Lhasa 850000
    2 Aquatic Plant Research Center, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan 430074
    3 Hubei Key Laboratory of Wetland Evolution & Ecological Restoration, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan 430074
    4 Yani Wetland Ecosystem Positioning Observation and Research Station, Tibet, Lhasa 850000
    5 Key Laboratory of Biodiversity and Environment on the Qinghai-Tibetan Plateau, Ministry of Education, Tibet University, Lhasa 850000
  • Received:2023-11-13 Accepted:2024-02-04 Online:2024-05-20 Published:2024-06-03
  • Contact: E-mail: liwei@wbgcas.cn

Abstract:

Aim: The important question of how riparian vegetation adapts to climatic and river hydrological changes is gaining global attention. Yet, the impact of snow and frequency of water level fluctuation on vegetation in the water level fluctuation zones remains underexplored. This study focuses on the response of the normalized difference vegetation index (NDVI) of riparian vegetation to climatic and hydrological changes in the basin of Yarlung Zangbo River, with an emphasis on understanding the impacts of snow and water level fluctuations in alpine fluctuation zones.

Method: This study employed Theil-Sen Median trend analysis and Mann-Kendall test to evaluate spatiotemporal vegetation trends utilizing NDVI as a key indicator from 1990 to 2022 in the Yarlung Zangbo River Basin, focusing on both the water level fluctuation zone and the adjacent 1-5 km buffer zones. A generalized linear model was used to quantify influencing factors including temperature, precipitation, snow water equivalent, and frequency of water level fluctuation.

Results: The spatial distribution of riparian vegetation’s NDVI demonstrated lower values in the northwest and higher in the southeast. Temporally, a notable fluctuating upward trend in NDVI was observed, reaching its peak in 2002 (0.16) and its bottom in 2022 (0.06). The annual NDVI progression revealed a consistent increase at mid-to-high altitudes, contrasting with the downstream areas’ sustained and irregular declines. Altitudinal analysis indicated that the decrease in NDVI varied in both the water level fluctuation and buffer zones, but was especially prominent between 1,500-3,000 m. The frequency of water level fluctuations stood out as the primary determinant for riparian NDVI, while temperature predominantly influenced the buffer zone’s NDVI. Additionally, the role of snow water equivalent in explaining NDVI became increasingly significant with elevation.

Conclusion: Vegetation in the water level fluctuation zone is influenced by various climatic and environmental factors, with water level fluctuations being pivotal. The importance of snow intensifies with increasing altitude, underscoring its significance in the spatial-temporal vegetation distribution.

Key words: water level fluctuation zone, frequency of water level fluctuation, snow water equivalent, elevation, normalized difference vegetation index (NDVI)