arastra, Karnataka, Tamil Nadu, Andhra Pradesh and Kerala) using coalescent simulations ,. Models including linear and exponential decline (Table S5 and Table S6, Figure S4 and Figure S5) revealed that the current effective size is about one tenth of the historical effective size, indicating that the Indian subcontinent has lost about 90% of its tigers (Figure 2). As these models do not allow us to investigate the absolute historical effective size as well as the timing of decline, we also used the Storz and Beaumont method to explore recent population decline. Results reveal a strong signal of population decline (91.4% decline, Figure 2), which potentially occurred around 200 years before present.
(A) Posterior distributions for population size change based on coalescent simulations for peninsular Indian tigers based on 10 microsatellite loci and the Beaumont method. Red and green curves correspond to the posterior distributions under models of exponential and linear population size change, respectively. The prior distribution is represented by the flat dotted line. Irrespective of various models, there is no support for population increase. For peninsular Indian tigers, the results reveal about 10-fold decrease. (B) Posterior distributions for population size change based on coalescent simulations for peninsular Indian tigers based on 10 microsatellite loci and the Storz and Beaumont method. The posterior distributions for ancestral (red curve) and present (green) effective population size are represented here. The priors are represented by the dotted line (present population) and dashed line (ancestral population). Results confirm that post-decline population size is much smaller than the pre-decline population size. (C) The posterior distribution for the time since the population decline started for Indian tigers (black curve). The priors are shown by the dashed lines. The distribution has a median value at around 200 years. The vertical red and blue lines represent the approximate time since bounty-killing by the British and first written history of tiger hunting by Mughals respectively. (D) The joint posterior distribution of ancestral and present effective population size based on Indian tiger data. The 90%, 50%, and 10% highest probability density (HPD) limits are plotted for the joint distribution of ancestral and current population size on a logarithmic scale. The diagonal line corresponds to stable population size.
We investigated the sensitivity of our results on demographic history to the number of genetic loci. Coalescent simulations that included 5 wild caught tigers (data from 13) genotyped at 30 microsatellite loci also revealed a very similar extent and timing of demographic decline (Figure S3). Further, using genetic data from tigers across the Indian subcontinent resulted in similar extent of population decline (Figure S2). Our sensitivity analyses re-iterate that the extent of demographic decline and its timing are robust to population structure as well as increased genetic data.
An assessment of genetic variation for tigers reveals tigers in the Indian subcontinent retain more than 60% of the genetic variability of the species. In this study, we have taken extreme care to sample Indian tigers in a spatially exhaustive way. However, our results are also conditional on adequate sampling of tiger variation outside the India. Future studies might also include additional sampling of wild tigers outside the Indian subcontinent. Additionally, data from captive tigers of known origin could also be used to investigate discrepancies in genetic variation.
Indian subcontinent tigers could retain higher genetic variation not only because they had high historical population size but also because other tiger subspecies declined more severely in the recent past. Single population models in LAMARC for Indochinese tigers using the microsatellite data also exhibit a signature of recent population decline (MLE of g = −0.881825 (−1.29, −0.560142)), although lower than the estimated decline for Indian tigers. We also qua