Aim: Climate change alters the water cycle, potentially affecting the distribution of species. Using an ensemble of species distribution models (SDMs), we predicted changes in distribution of the Asian elephant in South Asia due to increasing climatic variability under warming climate and human pressures.Location: India and Nepal.Methods: We compiled a comprehensive geodatabase of 115 predictor variables, which included climatic, topographic, human pressures and land use, at a resolution of 1 km², and an extensive database on current distribution of elephants. For variable selection, we first developed 14 candidate models based on different hypotheses on elephant habitat selection. For each candidate model, a series of 240 individual models were evaluated using several metrics. Using three climatic and one land use change datasets for two greenhouse gas scenarios, ensemble SDMs were used to predict future projections.Results: Nine predictor variables were selected for ensemble SDMs. Elephant distribution is driven predominantly by changes in climatic water balance (>60%), followed by changes in temperature and human‐induced disturbance. The results suggest that around 41.8% of the 256,518 km² of habitat available at present will be lost by the end of this century due to combined effects of climate change and human pressure. Projected habitat loss will be higher in human‐dominated sites at lower elevations due to intensifying droughts, leading elephants to seek refuge at higher elevations along valleys with greater water availability in the Himalayan Mountains.Main conclusions: Changes in climatic water balance could play a crucial role in driving species distributions in regions with monsoonal climates. In response, species would shift their range upwards along gradients of water availability and seasonal droughts. Conservation and management of elephant populations under global change should include design of movement corridors to enable dispersal of the elephant and other associated species to more conducive environments.

The Asian elephant is mostly confined to mountainous ranges and therefore risks population fragmentation if hard protected area (PA) boundaries near steep slopes prevent movement. We tested whether elephant gene flow is (i) controlled by slope and (ii) affected by the interplay between barriers and slope. We used 176 unique genotypes obtained non-invasively from fresh elephant dung to assess individual-by-individual genetic distance across the Western Ghats of India, a biodiversity hotspot. To assess landscape distance, 36 resistance models were produced by transforming a slope raster. Core areas and corridors were calculated from the raster that provided the best correlation between the genetic and distance matrices. The influence of the closure of PAs on gene flow was examined for one region, the Nilgiri Biosphere Reserve. The best resistance raster obtained by transforming the slope occupancy model was better than Euclidean distance for explaining genetic distance, indicating that slope partially controls gene flow. Fencing elephant PAs on hilly terrain reduces core areas and disrupts corridors. Consequently, hard PA boundaries abutting slopes can fragment elephant populations, but this can be ameliorated by protecting the adjacent flatter terrain.

Genetic analysis is an important tool in understanding population structure, genetic diversity, and phylogenetics of endangered species likely to be affected by microevolution and anthropogenic factors. Western Ghats landscape is one of the identified biodiversity hotspots in India, and micro-evolutionary processes are observed in this landscape due to the presence of the gaps in the mountain ranges. Nilgiri tahr is endemic to and distributed in this landscape while very little is known about genetic characteristics, population structure and impact of these gaps on the species. In the present study, two different populations of Nilgiri tahr from the north (NPG) and south (SPG) of Palghat gap (PG) were studied using the cytochrome b gene (Cyt b; 310 bp) of mtDNA genome in the Western Ghats, India. Two variable sites were observed in the Cyt b fragment while the mean pairwise genetic distance between these two populations was 0.007. All the samples phylogenetically clustered in either north or south of PG. The presence of shallow divergence indicates the presence of suitable habitat in past which may have facilitated movement between NPG and SPG. A subsequent change in Paleo-climatic conditions and gradual formation of PG may have resulted in population diversification during the Pleistocene. Besides, Forensically Informative Nucleotide Sequence (FINS) observed would help in geo-assigning any individual from NPG or SPG to understand the likely influences on population demography due to poaching.

The western Terai Arc Landscape (wTAL) in Uttarakhand, India, marks the range limit for the Asian elephant in north‐western India. This region has been impacted by land‐use changes and infrastructure expansion for the last seven decades. To evaluate the impact of habitat deterioration on the population structure of elephants in the region, we characterized their genetic diversity and local genetic structure using mitochondrial (D loop) and nuclear DNA (microsatellites; n = 15) markers. We used tissue samples of 114 elephants from five different sub‐populations, collected between 2005 and 2014. The genetic variation was moderate ( H _O = 0.49–0.55) compared with other Indian elephant populations. Two mtDNA haplotypes were identified without strong spatial patterns across wTAL. Bayesian individual‐based clustering algorithm identified two genetic clusters ( K = 2) with high admixture (50% at Q < 0.7) and no spatial adherence. Though K = 1 was not supported by the Bayesian algorithm, multivariate analysis and sibship patterns did not indicate genetic differentiation. The lack of spatial genetic structuring suggests high levels of gene flow, indicating that this population is still panmictic. This suggests that the life history traits of elephants as well as the ecological features of this landscape influence genetic connectivity. However, ongoing land use changes necessitate regular genetic monitoring in wTAL to identify incipient structuring caused by anthropogenic barriers to movement.