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Global warming is causing shifts in distribution of plants, leading to alterations in the native flora. In addition, increased intensity and frequency of wildfires is posing threats to Himalayan ecosystems. Modeling a species' ecological niche and its potential distribution under projected impacts of climate change and distribution of wildfires provides an understanding of the behavior of native flora in altered climatic conditions. In this study, we predicted future distribution of four endemic tree species Pinus roxburghii, Quercus semecarpifolia, Rhododendron arboretum, and Cedrus deodara in western Himalaya under A1B scenario of Special Report on Emission Scenarios for 2030, 2050, and 2080, under two conditions: (i) without wildfire and (ii) with wildfire. We included wildfire occurrence as a predictor variable in the Maxent model along with 35 climate variables, to predict the future distribution of four indicator species. As per the predictions, there will be a significant reduction in the geographic distribution of the indicator species under the 'with wildfire' scenario as compared to the 'without wildfire' scenario. The future distribution range was shifted towards the northern and north-eastern regions of our study area owing to higher moisture availability. We predicted reduction in the range of C. deodara during 2030, R. arboreum during 2050, and P. roxburghii during 2080, while the distribution of Q. semecarpifolia remained unchanged. Our modeling predicted that climate change could induce reduction, expansion, and shift in the distributions of endemic plant species, which could lead to alteration in the endemic flora of the Himalayas. [ABSTRACT FROM AUTHOR]

A seamless vegetation type map of India (scale 1: 50,000) prepared using medium-resolution IRS LISS-III images is presented. The map was created using an on-screen visual interpretation technique and has an accuracy of 90%, as assessed using 15,565 ground control points. India has hitherto been using potential vegetation/forest type map prepared by Champion and Seth in 1968. We characterized and mapped further the vegetation type distribution in the country in terms of occurrence and distribution, area occupancy, percentage of protected area (PA) covered by each vegetation type, range of elevation, mean annual temperature and precipitation over the past 100 years. A remote sensing-amenable hierarchical classification scheme that accommodates natural and semi-natural systems was conceptualized, and the natural vegetation was classified into forests, scrub/shrub lands and grasslands on the basis of extent of vegetation cover. We discuss the distribution and potential utility of the vegetation type map in a broad range of ecological, climatic and conservation applications from global, national and local perspectives. We used 15,565 ground control points to assess the accuracy of products available globally ( i.e ., GlobCover, Holdridge’s life zone map and potential natural vegetation (PNV) maps). Hence we recommend that the map prepared herein be used widely. This vegetation type map is the most comprehensive one developed for India so far. It was prepared using 23.5 m seasonal satellite remote sensing data, field samples and information relating to the biogeography, climate and soil. The digital map is now available through a web portal ( http://bis.iirs.gov.in ). [ABSTRACT FROM AUTHOR]

Ecosystem services (ES) are increasingly recognized as a means to facilitate adaption to environmental change. However, the provisions of ES are likely to be impacted by changes in climate and/or changes in land use. In developing countries, where people are typically dependent on these services for their livelihoods, these impacts are of concern; however, very little is known about the changes in provisioning of ES over time. In this study, we assess the perceived changes on ES in the Panchase Mountain Ecological Region of western Nepal. The study area accommodates three distinct ecoregions, ranging from lowland to upland ecosystems and communities. Focus group discussions and key informant interviews were used to collect information on how ES may have changed in the landscape over time. This approach was supported by transect walks, field observations, and secondary sources of information, such as climatic and remote sensing data. Perceived changes on ES in the study region include reduced availability of water, reduced food production, degradation of forest ecosystems, and changes in species compositions. These changes are thought to have impacted other ES, and, in turn, local livelihoods. Management actions that can help local communities foster ES are recommended. [ABSTRACT FROM AUTHOR]