Avian altitudinal distribution on the Qinghai-Tibet Plateau is shaped by contemporary environmental heterogeneity, history lineage diversification, and high-altitude adaptation. Understanding this pattern is crucial for explaining biodiversity maintenance in the “Third Pole”. However, in extreme arid boundaries with minimal human impact, how the interplay of historical evolutionary constraints and contemporary ecological filters shapes avian communities remains largely unquantified. This study focused on the avian community of the eastern Kunlun Mountains, a high-altitude, cold-arid region on the Plateau’s northern margin. Using field surveys from 2022–2023, supplemented with multi-year data, we integrated taxonomic, phylogenetic, and functional diversity to examine how evolutionary ‘physiological constraints’ and contemporary ‘resource conditions’ jointly shape avian elevational distribution. We recorded 107 bird species across 14 orders and 33 families. Species richness exhibited an asymmetric unimodal pattern along the 2,800–5,200 m gradient, peaking at 3,800 m with a secondary shoulder at 4,500 m, both shaped by precipitation- driven resources. The Enhanced Vegetation Index (EVI) explained over 70% of the variation in large-ranged species diversity, confirming resource availability as the primary constraint on species richness in this arid system. Community structure showed distinct elevational divergence: below 4,400 m, stochastic, resource-driven assembly prevailed; above 4,400 m, constraints from low temperature and high humidity led to functional clustering and phylogenetic convergence, strongly supporting the physiological tolerance hypothesis. Furthermore, a notable masking effect was identified: large-ranged species were predominantly governed by contemporary environmental filtering, whereas small-ranged species were shaped by historical evolutionary contingencies. In summary, the bird diversity pattern in the eastern Kunlun Mountains reflects a trade-off by species between resource benefits and physiological limits. The high sensitivity of high-elevation communities to temperature and precipitation highlights their vulnerability to climate change.
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Tian et al. (2026) studied this question.
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