Distribution modelling and climate change risk assessment strategy for rare Himalayan Galliformes species using archetypal data abundant cohorts for adaptation planning

In a macroecological approach, we have used the data abundant species or archetypal cohorts as proxies for the data deficient species, to model their distributions. Upon successful modelling, we assessed climate change impacts on their distribution in the Himalayan arc extending from the Indian borders in the west to the hills in Myanmar. Out of 34 Galliformes species occurring in the Himalayan arc, 21 species were retained in this study, rest were dropped due to very low occurrences. Best performing variables from the set of environmental variables (n = 36) consisting of topography, vegetation, soil, anthropogenic indices and bioclimatic factors were tested for collinearity. Ordination (PCA and NMDS) and clustering (hierarchical clustering, agnes, partitioning around medoids and k-means clustering) and Species Archetype Modelling (SAM) methods were performed for finding the archetypal cohorts among the species. The clusters were used for two different modelling frameworks- Species Distribution Models (SDMs) with a combination of biophysical and topographical parameters; and Bioclimatic Envelope Models (BEMs) with only bioclimatic variables. Predicted climate-driven changes in species ranges (year 2070, RCP 4.5 and 8.5) were assessed. The 21 species were clustered in four groups. Precipitation emerged as the overall significant driving factor for all the three clusters. Random Forest was the highest performing model across the clusters. Two cluster restricted to the eastern Himalayas were found to be the most affected in a climate change scenario. Cluster belonging to the western Himalayas was predicted to lose about 70% of its bioclimatic habitats in both the scenarios. In a first attempt, this study presents a novel approach towards distribution and climate change modelling for the rare Galliformes, using abundant Galliformes over a pan Himalayan scale.