Ecological gradients hosting plant communities in Himalayan subalpine pastures: Application of multivariate approaches to identify indicator species.

The development of vegetation communities is typically influenced by their response to variation in environmental, geographic and as well as physiographic gradients. The current study was planned to evaluate the influence of environmental gradients upon the structure of plant communities and to highlight their respective indicators in subalpine pastures of the Himalaya, Pakistan. In relation to this aim, ecological techniques were used following the Line transect (50 m) method to quantify the vegetation structure of the study area. Soil samples were collected from each sampling site and edaphic gradients were examined using standard protocols. Weather station data (Kestrel 4000) was used to determine the climatic gradients, GPS data was used to record the geographic and physiographic gradients. PCORD software was used to recognize communities through two-way indicator species analysis (TWINSPAN), R and CANOCO software was employed for ordination analysis to find variation directories of different plant species. A total of 56 plant species, recorded from 21 sampling sites, were grouped into four plant communities with the help of environmental gradients. The highest index of similarity was recorded between the Bergenia-Sibbaldia-Rheum and Sibbaldia-Rheum-Bergenia communities and highest dissimilarity between Bergenia-Sibbaldia-Rheum and Juniperus-Sibbaldia-Poa communities. The highest number of plant species (50 species), maximum alpha diversity (H' = 3.38) and beta diversity was reported in Sibbaldia-Rheum-Bergenia community (0.95), but Pielou's evenness was highest (0.89) in Juniperus-Sibbaldia-Poa among all recorded communities. Besides, the edaphic (i.e. organic matter, phosphorous, pH and soil texture) and climatic factors (temperature, humidity) were the strong environmental gradients that were responsible for structuring and hosting the diverse plant communities in subalpine meadows. Techniques adapted in the current study for identification of vegetation indicators could further be used for conservation management.