e Indian subcontinent compared to any other subspecies, as well as all compared to all tiger subspecies outside the Indian subcontinent (Figure 1, Table 1).
(A) A haplotype network based on 1,263 bp of mitochondrial DNA reveals that 76% of global tiger genetic variation (32 haplotypes out of 42) is retained within the Indian subcontinent. Locations of each haplotype within India correspond only approximately to the site of sample collection. 71 samples are included from Myanmar, Nepal, and India. All samples from outside India are from Luo et al., 2004 . (B) The partitioning of microsatellite genetic variation based on 5 common microsatellite loci between different sub-species of tigers, with program STRUCTURE (k = 5). Individuals within the Indian subcontinent are the most variable, indicated by the fact that all 5 colours are present, compared to other subspecies, which retain only one colour (e.g. Siberian tigers). All samples from outside India are from Luo et al., 2004 .
Viewed alone, this higher genetic variability observed within the Indian subcontinent is concordant with India being the geographic source for tigers. However, fossil evidence suggests that the tiger evolved in southern China . Phylogenetic and phylogeographic data  suggest the genetic antiquity of the Indochinese tigers (very limited samples from South China tigers), and that Indian tigers are of relatively recent origin. Coalescent-based two population models (LAMARC ; Indian subcontinent tigers versus Indochinese tigers) based on both mitochondrial DNA and microsatellite data (based on five loci) estimate significantly higher immigration into the Indian subcontinent [MLEmtDNA (maximum likelihood estimate) = 185.8 (44.72, 486.63); MLEmicrosats = 36.82 (31.17, 40.40)] compared to emigration [MLEmtDNA = 0.19 (0.000001, 59.84); MLEmicrosats = 13.77 (11.31, 15.32)] out of the subcontinent. Although not conclusive, these independent lines of evidence suggest that Indian tigers are not ancestral to the species.
The higher genetic diversity of Indian tigers could be explained by higher effective population size, due to (1) high levels of population differentiation between tiger populations within the subcontinent due to habitat variability and past fragmentation and/or (2) high historic abundance of tigers in the Indian subcontinent.
We investigated the impacts of population differentiation on our results. We divided our samples into those roughly from the North, Central and South of the Indian subcontinent. Our results reveal a strong signature of population structure for mitochondrial DNA (Table 2), especially between the North and the Central and Southern region. On the other hand, pairwise Fst values (Table 2) for microsatellite data are low. Although the structure plot (Figure 1B) reveals varied ancestry, there is no clear partition of ancestry between regions.
We estimated historical effective population size for Indian tigers. Our mitochondrial DNA data suggest population expansion within the Indian subcontinent (Fu's F = −26.33 (p = 0.000); LAMARC: MLE of g = 2859.7 (2092.67, 5549.68), indicating growth). In contrast, the microsatellite data from the same populations indicate population decline (M ratio 0.35 (s.d. 0.08), BOTTLENECK : 7 to all of the10 loci with heterozygote excess depending on the mutational model, LAMARC (based on 10 loci): MLE of g = −20.87 (−24.29, −17.09), indicating population decline). Tests for selective neutrality of the tiger mitochondrial genome revealed evidence for negative selection on the cytochrome b gene (dN/dS within species = 1.9, between species = 0.09, p = 0.00002). Because of negative selection, mitochondrial genetic variation may result in underestimates of historical population size.
Given that tigers from Central and Southern India do not reveal strong subdivision (low and non-significant pairwise Fst's for both mitochondrial and microsatellite DNA), we investigate the demographic history of tigers in this region that we refer to as peninsular India (including the states of Madhya Pradesh, Chattisgarh, Mah