 sizes and enhancing connectivity between populations using available demographic, ecological and genetic information for the species –. Integration of such datasets is critical for prioritizing conservation efforts.
The tiger (Panthera tigris) typifies large carnivores severely threatened by historical anthropogenic impacts. Wild tigers historically occurred across 70 degrees of latitude and 100 degrees of longitude, spanning 30 present-day nations ranging from Armenia to Indonesia, the Russian Far East to the Southern tip of India ,. This range encompassed a variety of habitats, including taiga and boreal forests, tropical evergreen, moist and dry deciduous forests, alluvial grasslands and mangroves. Historical times have seen a dramatic range collapse of 93% for wild tigers due to habitat loss, prey depletion and direct hunting . Current global estimates of wild tiger populations range from 3000–3500 individuals ,. The Indian subcontinent is estimated to harbor about 2000 tigers , or about 60% of the global wild population, although it retains only an estimated 8–25% of remaining global habitat ,,. These data emphasize the importance of Indian tigers for future species recovery from a demographic perspective. Ecology and population dynamics of tigers in the Indian subcontinent has been reasonably well studied ,, as has been their spatial distribution and habitat diversity ,. However, the genetic make up and diversity of Indian wild tiger populations have not been examined in a global context.
Limited phylogeographic studies , reveal only moderate levels of variation within Indian tigers, in spite of more than half of the global population and the most varied habitat conditions occurring in this region. In order to adequately assess genetic variability of extant Indian tigers, it is critical to obtain as many genetic samples as possible from the varied, disjunct and fragmented tiger habitats. However, because wild tigers are endangered, elusive and difficult to capture, it is difficult to invasively collect sufficient samples such as blood or tissue. We overcome this problem by using genetic samples non-invasively collected from tiger scats to assess genetic variation, phylogeography and demographic history of tigers in the Indian subcontinent.
In this paper we investigate (1) the proportion of global tiger genetic variation harboured by tigers in the Indian subcontinent and (2) the demographic history of tigers in the Indian subcontinent, with a synthesis based on historical population sizes and recent human impacts. We address these questions using 1.26 kb of mitochondrial DNA and 10 microsatellite loci surveyed in 73 individual tigers from 28 different populations, and compare our results to published data from 68 tigers outside the Indian subcontinent.
Our sampling strategy concentrated on tiger populations living in varied habitats throughout the Indian subcontinent. Using 71 (Table S1) non-invasively collected fecal samples and two tissue samples from across the Indian subcontinent, we investigated genetic variability of Indian tigers using mtDNA and microsatellite loci. Our results reveal that Indian tigers have much higher genetic variation than wild tigers elsewhere. For mitochondrial DNA, 76% of all tiger genetic variability (32 out of 42 haplotypes) is found within the Indian subcontinent (Figure 1A). These results are robust to differences in sample size (67 within India versus 57 outside India). Re-sampling simulations reveal that if only 57 Indian tigers were sampled, we would expect between 18 and 25 haplotypes, much higher than the observed 10 haplotypes. Similarly, five microsatellite loci reveal higher average number of alleles (Table 1), allelic size range (Table 1) and heterozygosity (Table 1) in Indian subcontinent tigers compared to tigers from the rest of the world. Additionally, the program STRUCTURE  (based on five loci) illustrates that Indian tigers retain high allelic richness and varied ancestry (Figure 1B). Thus both markers and several analyses suggest higher genetic variability within th