Broad pattern of plant distribution in Western Himalaya

What is it about?

We explore these determinants of species richness in Western Himalayas using high-resolution species data available for the area to energy, water, physiography and anthropogenic disturbance. The floral data involves 1279 species from 1178 spatial locations and 738 sample plots of a national database. The mutual influences of the climatic variables were found to affect the predictions of the model significantly. To our knowledge, the 67.4% deviance found in the species richness pattern is one of the highest values reported in mountain studies. Broadly, climate described by water–energy dynamics provides the best explanation for the species richness pattern. Both modeling approaches supported the same conclusion that energy is the best predictor of species richness. The dry and cold conditions of the region account for the dominant contribution of energy on species richness.

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Why is it important?

Disentangling the effects of abiotic predictors on species richness in understudied Western Himalaya is significant for providing better insights into ecologists and planners dealing with plant distribution patterns vis-à-vis climate change projections.