ZHANG Linhao, TANG Haiping, SHI Peijun. Factors influencing near-surface oxygen in the Three Parallel Rivers Region of the Tibetan Plateau[J]. Journal of Beijing Normal University(Natural Science). DOI: 10.12202/j.0476-0301.2024066
Citation: ZHANG Linhao, TANG Haiping, SHI Peijun. Factors influencing near-surface oxygen in the Three Parallel Rivers Region of the Tibetan Plateau[J]. Journal of Beijing Normal University(Natural Science). DOI: 10.12202/j.0476-0301.2024066

Factors influencing near-surface oxygen in the Three Parallel Rivers Region of the Tibetan Plateau

  • Hypoxia threatens the health of populations at high altitudes (≥2500 meters above sea level). Recent studies have shown that altitude is not the only factor affecting near-surface atmospheric oxygen content on the Tibetan Plateau, but is also influenced by a combination of temperature and vegetation factors that have not been documented in typical areas of the Tibetan Plateau. In this study, we made field route survey measurements along the Sichuan-Xizang and Yunnan-Xizang routes in the summer of 2019-2022, and obtained data from 90 sampling points to explore the relationships between near-surface oxygen content and elevation, vegetation (net primary productivity, leaf area index, vegetation cover, length of the growing season), and climatic variables (air temperature, mean monthly precipitation) in the dry valleys of the Three Parallel Rivers Region. The results showed that: (1) temperature, elevation, LAI, precipitation, NPP and FVC were important variables in predicting near-surface oxygen content in the Three Parallel Rivers Region; (2) Elevation was the main factor influencing the spatial variability of near-surface oxygen content in the Three Parallel Rivers Region; (3) The standardized direct effect of vegetation factors on the near-surface oxygen content in the present study area was significantly reduced compared with that of the entire Tibetan Plateau. Different drivers of near-surface oxygen content should be incorporated into Earth system models to reduce uncertainty in predicting oxygen dynamics and its potential feedback to global warming.
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