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Climate change and its cascading impacts are being increasingly recognized as a major challenge across the globe. Climate is one of the most critical factors affecting biomes and their distribution. The present study assessed shifts in biome types of India using the conceptual framework of Holdridge life zone (HLZ) model, minimum distance classifier and climatic datasets to assess the distribution pattern of potential biomes under climate change scenarios in India. Modelling was conducted on the entire region of India using various combinations; (i) current climate scenario, and, (ii) increased temperature and precipitation scenario. The geographical analysis identifies nineteen (19) HLZs in the Indian sub-continent; seven (7) biomes and nineteen (19) sub-biomes. The overall accuracy and kappa coefficient of the biome map prepared for current climate scenario was 82.73% and 0.75, respectively. With the changes in increasing temperature and precipitation scenario, the modelling results predict significant decrease in the area cover for tropical deserts (plains), tropical desert scrubs (lower montane), tropical moist forests (lower montane) and tropical wet forests (lower montane). Along with these changes, there have been substantial increases in the area cover for tropical dry forests (plains) and tropical very dry forests (plains), especially in central and southern India. The results show shifts from very dry tundra (alvar) to dry tundra (alpine) and moist tundra (alpine) and in some places tropical moist forests (sub-alpine) as well. In central India, decrease in tropical moist forests (lower montane) has been observed, while an increase in the area cover of tropical rain forests (plains) in northeastern India has been observed. It is important to understand the impacts and vulnerabilities of projected climate change on forest ecosystems so that better management and conservation strategies can be adopted for biodiversity and forest dependent communities. The knowledge of impact mechanisms will identify adaptation strategies for some conditions which will help in decreasing the susceptibility to anticipated climate change in the forest sector. (c) 2013 Elsevier Ltd. All rights reserved.