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Figure 1.

Image of A) N. nimmoniana plant and chemical structure of B) Camptothecine extracted from wood of N. nimmoniana C) Irinotecan and D) Topotecan, two clinically used drugs synthesized from Camptothecine as a precursor.

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Figure 2.

Map showing the distribution and sampling locations of Nothapodytes nimmoniana in the Western Ghats, India.

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Table 1.

Location, geographical coordinates, sample size (N) and private alleles (AP) in eight populations of Nothapodytes nimmoniana.

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Figure 3.

Demographic parameters of Nothapodytes nimmoniana in four protected and adjacent non-protected areas in the central Western Ghats, India.

A) Western Ghats map showing sampling locations B) Mean density of adults per quadrat C) Mean regenerants per adult D) Mean regeneration per quadrat E) Mean saplings per quadrat F) Harvesting index. Note: Error bars are standard error. For each parameter, dissimilar letters above the bars are significantly different at 0.05 levels (t-test). PA, protected area; NPA, non-protected area; WG, Western Ghats; KEM, Kemmangundi; MUL, Multavara; TALA, Talakaveri; BAN, Bondikadu; DAN, Dandeli; JOID, Joida; AGU, Agumbe; VADE, Vadagere.

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Figure 4.

Map showing genetic diversity parameters at sampling locations of Nothapodytes nimmoniana from Western Ghats, India A) Nei’s gene diversity B) Allelic richness.

Note: Regions represented in dark red indicate areas of high genetic diversity and allelic richness.

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Table 2.

Summary of genetic variation at seven microsatellite loci scored for eight Nothapodytes nimmoniana populations in the Western Ghats, India: expected and observed heterozygosity (HO and HE), and observed number of alleles per polymorphic locus (A), Weir & Cockerham (1984) estimates of FIT, FST, FIS and RST.

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Table 3.

Summary of genetic diversity parameters of Nothapodytes nimmoniana in four protected (PA) and adjacent non-protected areas (NPAs) in the central Western Ghats, India.

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Figure 5.

Results of Bayesian model based clustering method (STRUCTURE) analysis.

a) Posterior probability of the data LnP(D) (±SD) against the number of K clusters, and increase of LnP(D) given K, calculated as (LnP(D)k–LnP(D)k–1) b) Delta K values from the mean log-likelihood probabilities from STRUCTURE runs where inferred clusters (K) ranged from 1 to 14 (c) Estimates of the proportion of ancestry, Q, in each of K = 2 clusters for 198 Nothapodytes nimmoniana individuals using the model-based cluster analysis, STRUCTURE (version 2.1). Note: A single vertical line represents each individual with estimated membership in each cluster denoted by the different colors. The analysis was based on seven SSR loci and used admixture model of ancestry. Individuals are separated based on their population and black vertical lines in the bar chart are population identifiers. Populations are ordered as per their population name.

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Table 4.

Analysis of molecular variance (AMOVA) for 195 individuals of Nothapodytes nimmoniana in protected (PA) and non-protected (NPA) areas.

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Table 5.

Membership of each pre-defined population in each of the two (K = 2) clusters generated by CLUMPP based on the results of STRUCTURE v2.2 analysis of SSR data.

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Table 6.

Analysis of historical and recent genetic bottleneck based on stepwise mutation model (SMM) of microsatellite evolution and Mode shift test for allele frequency distribution.

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Figure 6.

Predicted genetic diversity in eight populations of Nothapodytes nimmoniana sampled from protected (PA) and non-protected (NPA) areas of Western Ghats, India over next 100 years using BOTTLESIM.

The current population size is unable to maintain 90% of current genetic diversity over the next 100 years in almost all sampled populations. A) Agumbe (PA) B)Vadagere (NPA) C)Dandeli (PA) D) Joida (NPA) E) Kemmangundi (PA) F) Multavara (NPA) G) Talakaveri (PA) and H) Bondikadu (NPA). Note: The observed numbers of alleles (OA) were projected to decline (Sex ratio 1∶1 F:M).

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