Potential drivers of plant diversity and composition in high-altitude alpine regions of Himalaya

In the present era of accelerating climate change, a comprehensive understanding of the distribution patterns of plant communities and their driving factors is pivotal in ecological studies. In view of this, the present research assessed species diversity and composition patterns in the alpine region of Uttarakhand, west Himalaya and their relation with the environmental conditions (climatic, edaphic and topographic) using the standard protocol of Global Observation Research Initiative in Alpine Environment. A total of 104 vascular plants (71 genera and 35 families) were documented in the study with Asteraceae (16 species in 14 genera) being the dominant family. The diversity indices across the study area exhibited significant variations (p < 0.05) with respect to altitude and aspect, i.e., richness and diversity values were higher in lower altitude summits and in south- and east-facing mountain slopes. β-diversity partitioning indicated that there was higher compositional heterogeneity with respect to altitude than aspects, where variation in composition was observed only in case of habitat heterogeneity. Based on the magnitude and representation of the selected climatic and edaphic factors across all plots, distinct clusters of summit sites were formed by principal component analysis that exhibited significant changes in environmental conditions with respect to altitude rather than aspects. Canonical correspondence analysis revealed a strong relationship of community composition with environmental factors, with soil temperature, moisture, organic carbon and nitrogen content prominent edaphic factors and annual air temperature, temperature seasonality, solar radiation and isothermality prominent climatic factors influencing the community compositions. The present study, therefore, enhances our understanding of the contribution of potential drivers that determine spatial patterns of plant diversity on mountain summits, which help monitor, model and predict how the mountain ecosystems will respond to climate warming in the Himalaya.