2 3 Genetic diversity of nine natural Tectona grandis L.f. populations of the Western Ghats in...

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Conservation Genetics ISSN 1566-0621Volume 13Number 5 Conserv Genet (2012) 13:1409-1419DOI 10.1007/s10592-012-0383-5

Genetic diversity of nine natural Tectonagrandis L.f. populations of the WesternGhats in Southern India

P. M. Sreekanth, M. Balasundaran,P. A. Nazeem & T. B. Suma

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ORIGINAL RESEARCH

Genetic diversity of nine natural Tectona grandis L.f. populationsof the Western Ghats in Southern India

P. M. Sreekanth • M. Balasundaran •

P. A. Nazeem • T. B. Suma

Received: 2 December 2011 / Accepted: 2 July 2012 / Published online: 18 July 2012

� Springer Science+Business Media B.V. 2012

Abstract Teak (Tectona grandis L.f.) is one of the most

durable timbers in the world that is used for all conceivable

purposes. Its widespread use has constrained the distribution

of species to small and isolated populations. The genetic

structure within and between nine natural teak growing

forests of the Western Ghats of India belonging to the states

of Kerala, Karnataka and Tamil Nadu was investigated using

amplified fragment length polymorphism markers to provide

reasoned scientific management practices and conservation

measures. The use of ten selective primer combinations on

180 samples (9 populations X 20 trees) resulted in a total of

665 bands of which 99.4 % were polymorphic. Gene

diversity index (H) varied from 0.1387 (Barchi) to 0.2449

(Wayanad). The mean gene diversity (HS) was 0.1995 and

the total gene diversity (HT) was 0.264. The Southern

Western Ghats populations showed higher within population

gene diversity. The relative magnitude of genetic differen-

tiation among populations (GST) was 0.244. Positive cor-

relation between genetic and geographical distances was

observed. PCoA, UPGMA and STRUCTURE analyses

revealed the tendency of the individual trees within a pop-

ulation to align together indicating specific identity of each

population. In the UPGMA dendrogram, Nilambur popula-

tion joined separately with a large cluster in which the other

Kerala populations and Tamil Nadu population formed sub

clusters indicating a separate identity for Nilambur popula-

tion among Southern Western Ghats populations.

Keywords Tectona � Genetic diversity � AFLP � UPGMA

dendrogram � PCoA � STRUCTURE

Introduction

To maintain natural populations as evolutionarily viable

units capable of adapting to changing conditions of the

environment in the long term, genetic variation must exist.

For selectively exploited tropical tree species, genetic

erosion has been considered as a serious matter. Sustain-

able production can be threatened if genetically determined

wood quality or pest resistance capability is undermined

(Newton et al. 1996). A genetic resource management

strategy for such species needs to be based on research data

examining the extent of genetic differentiation within and

between populations, and on understanding the processes

of maintaining these variations.

Teak (Tectona grandis L.f.; Verbenaceae) is known as

an aristocratic hardwood, being one of the most durable

timbers in the world that is used for all conceivable pur-

poses. Timber is used for construction of houses, ships,

furniture, paneling, joinery, plywood and many other uses.

P. M. Sreekanth (&)

Biotechnology and Applied Genetics, Bangalore City College

(New Campus), Kalyan Nagar, Banaswadi Outer Ring Road,

Bangalore, 560043, India

e-mail: [email protected]

M. Balasundaran

Environmental Biotechnology, Tropical Institute of Ecological

Sciences, Velloor P.O., Kottayam 686501, Kerala, India


P. A. Nazeem

Centre for Plant Biotechnology and Molecular Biology, Kerala

Agricultural University, KAU Campus P.O., Thrissur 680656,

Kerala, India


T. B. Suma

Kerala Forest Research Institute, Peechi P.O., Thrissur 680653,

Kerala, India


123

Conserv Genet (2012) 13:1409–1419

DOI 10.1007/s10592-012-0383-5

Author's personal copy

Teak has a wide, but discontinuous distribution in South

and Southeast Asia. It occurs in natural forests, below

1,000 m elevation between 9�–26� north latitude and 73�–

104� east longitude, which includes Southern and Central

India, Myanmar, Laos Peoples’ Democratic Republic and

Northern Thailand (White 1991). In India, there are 8.9

million hectares of teak bearing forests within the annual

precipitation range of 800–2,500 mm (Tewari 1992). Teak

grows in dry and moist deciduous forests below 24� N

latitude in the Indian states of Kerala, Tamil Nadu, Kar-

nataka, Maharashtra, Gujarat, Andhra Pradesh, Chattisgarh,

Madhya Pradesh, Rajasthan, Uttar Pradesh, Manipur and

Orissa.

The Western Ghats is one among the globally identified

Biodiversity Hot Spots (Myres 1998) having an average

annual precipitation of 2,500 mm. The Western Ghats

comprises a 1,600 km (approx.) long mountain range along

the Western side of the Indian Peninsula extending from

the state of Gujarat in the North to Kanyakumari of Tamil

Nadu state in the South. Majority of the natural teak forests

of the states of Karnataka, Kerala and Tamil Nadu are

situated on the Western Ghats.

During the nineteenth century, teakwood from the

Western Ghats was largely exploited for ship building,

and for expanding the Navy of Britain and other Euro-

pean countries. The earliest reported plan of natural teak

forest management and tree felling was through a selec-

tion system in which a pre-determined number of trees

having a minimum diameter were felled from a specific

area during a stipulated period (Pandey and Brown 2000).

But, with the increasing demand of teakwood, felling

cycle and harvestable minimum diameter were further

reduced. The resultant higher harvesting intensity coupled

with other causes of forest degradation undermined the

sustainability of natural timber production (Nair and

Souvannavong 2000; FAO 2009). When the availability

of teakwood from the natural forests decreased, teak

plantations were raised first in Nilambur during 1840s

using seeds from natural forest. As part of checking the

genetic resources for adaptability and tree improvement

programme, provenance testing was initiated in India as

early as 1930s and International Provenance Trials during

1970s under the coordination of FAO and DANIDA

Forest Seed Centre. Establishment of clonal seed orchards

in 1960s and 1970s using phenotypic plus trees selected

from natural forests and older plantations did not provide

quality seeds in expected quantity hindering tree

improvement programmes (Nair and Souvannavong

2000). With the acceptance of conservation of biological

diversity and environmental protection underpinning all

land uses, maintenance of genetic diversity emerged as a

key factor not only as a pre-requisite for ecological sus-

tainability but also for genetic improvement. Protection

of natural teak populations was accepted as most critical

to the long term sustainability of genetic improvement

and development of a vigorous plantation programme

(Enters 2000).

A couple of studies have been carried out for estimating

the genetic diversity of Indian teak through DNA marker

studies (Shrestha et al. 2005; Fofana et al. 2009). But the

DNA required for these studies were extracted from

International Provenance Trails set up by DANIDA Forest

Seed Centre outside India (Keiding et al. 1986; Kjaer et al.

1995). Shrestha et al. (2005) did AFLP marker study col-

lecting leaf samples from field trial No.038 maintained at

Pha Nok Khao in Thailand. DNA was extracted from four

Indian populations with three samples from each popula-

tion. Of these populations, two were from the Southern

Western Ghats namely Konni and Mount Stuart. The study

showed that these two populations were distinct from the

Allapally population of Central India origin. But the

Eastern Indian Berbera population showed association with

both Indian and Thai-Indonesian populations. Fofana et al.

(2009) collected samples from the International Prove-

nance Trials maintained in Cote d’ Ivoire and Ghana for

their study on genetic structure of teak using microsatellite

markers. Forty-eight samples were from Nilambur valley

seed origin (Kerala state), while nine samples were from

Masale Valley and seven samples from Virnoli populations

both belonging to the Karnataka state. Of the other two

Indian teak populations, one originated from the Eastern

Ghats of South India (State of Andhra Pradesh) and the

other from Orissa state located north of Andhra Pradesh.

The study showed grouping of Indian teak into two clusters

that were genetically very distinct from Thailand and Laos

teak which formed the third cluster. All the Western Ghats

and the Andhra Pradesh origin teak populations (South

Indian populations) clustered together while the Orissa

population was grouped in a separate cluster. The highest

genetic variability was reported from Indian populations

and the least from Central Laos teak. They concluded that

India is the center of genetic diversity of teak. Nicodemus

et al. (2005) analysed the genetic diversity of North and

South Indian teak samples from natural populations and

plantations together using RAPD markers and found that

the UPGMA dendrogram grouped the Western Ghats and

Central Indian populations into two distinct clusters. State-

wise grouping into separate sub clusters was observed by

Parthiban et al. (2005) when genetic diversity of 28 Indian

teak seed samples were analysed using RAPD markers.

Even though, teak provenances of the Western Ghats origin

is reported superior in growth and productivity (Keiding

et al. 1986; Kjaer et al. 1995) and genetically superior

(Fofana et al. 2009), information about the diversity and

genetic structure along the Western Ghats mountain range

remain incomplete.

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As a consequence of depletion of natural forests of the

Western Ghats, teak populations also have been depleted

and fragmented to a great extent (Katwal 2005). Such

isolated populations may face considerable risk from the

effects of altered environment such as climate change and

global warming because of loss of genetic diversity. In

order to adopt conservation measures and undertake

genetic improvement of teak plantations, precise informa-

tion of the genetic diversity and population structure are

important. Through the present study using AFLP markers,

we have investigated the genetic structure of nine natural

teak populations of the Western Ghats. The information

available from the studies is expected to contribute to the

development of an integrated strategy for the sustainable

resource management of teak in the Western Ghats.

Materials and methods

Sample collection from natural forest

Leaf samples were collected from nine natural teak growing

forests of the Western Ghats belonging to the states of Ker-

ala, Karnataka and Tamil Nadu (Table 1; Fig. 1). These

geographical areas were selected because they were the

locations of origin of important provenances from the very

moist to moist teak forests of the Western Ghats identified for

raising teak plantations. Historically, Konni, Parambikulam,

Nilambur,Wayanad and Thrissur forests were the sources of

huge teak logs, and currently, majority of the teak plantations

(70,000 ha approx.) and almost the entire seed production

plantations of Kerala are located in the first four areas (Pra-

bhu 2005). Teak from Nilambur Valley had been acclaimed

as the most famous teak source for shipbuilding and struc-

tural purposes during nineteenth century itself and the

first teak plantation was established at Nilambur in 1842

(Kadambi 1972). Teak population sampled from Tamil Nadu

state was from the Anamalai reserve forests; currently within

Indira Gandhi Wildlife Sanctuary located at the Eastern

slope of the Western Ghats (Kala et al. 2005). Teak from

Barchi (Haliyal Forest Division, Karnataka state) was

famous as Dandeli teak because of the unique golden colour

and fine grain (Dilip Kumar 2005). The natural teak forests

are currently protected under the Dandeli Wildlife Sanctu-

ary. Virnoli, which was also part of Haliyal Forest Division

was supposed to be the locality of origin of the famous Teli

variety of teak which showed fast growth, and shiny and

smooth leaves that escape teak defoliator, Hyblaea puera

attack (Katwal 2005). All these populations were from moist

to very moist teak forests. Moreover, except for Virnoli and

Shimoga, these locations had very large, mature trees as well

as smaller girth trees available for sampling. The samples

were collected randomly from a minimum of 2.5 km2 area,

sufficiently interior from reserve forest boundaries. From

each location, we collected expanding leaves from 20 ran-

domly selected trees for DNA extraction.

DNA isolation and AFLP analysis

Total DNA was extracted from 0.5 to 1 g of fresh leaf

tissues using the modified CTAB protocol of (Doyle and

Doyle 1990). AFLP method was carried out following the

standard procedure described by Vos et al. (1995). The

reactions were carried out according to the manufacturer’s

protocol (AFLP� Analysis System 1 and Starter Primer

Kit; Invitrogen Life Technologies, Inc., USA). The amount

of DNA was adjusted to 250 ng for the EcoRI and MseI

digestion at 37 �C for 2 h. Ligation of EcoRI and MseI

adapters was done at 20 �C for 2 h. 5 ll of the template

DNA from a 1:10 diluted ligation mixture in TE (10 mM

Tris–HCl, 1 mM EDTA) buffer was used for preamplifi-

cation with the preamplification primer mix. Twenty cycles

of amplification were carried out at 94 �C for 30 s dena-

turation, 56 �C for 60 s annealing and 72 �C for 60 s pri-

mer extension in PTC-100 Peltier Thermal Cycler (MJ

Research, USA). 5 ll of the preamplification product was

used for selective amplification with ten primer combina-

tions: E-AGG/M-CTT, E-AAC/M-CTG, E-AAC/M-CTT,

Table 1 Particulars of the site of teak populations sample collection from Western Ghats used for AFLP analysis

Population Forest division State Latitude (N) Longitude (E) Aerial distance from

Konni (km)

Konni (Konn) Konni Division Kerala 09�100 76�570 –

Thrissur (Thri) Peechi-Vazhani Wildlife Sanctuary Kerala 10�260 76�580 141

Parambikulam (Para) Parambikulam Wildlife Sanctuary Kerala 10�250 76�450 141

Nilambur (Nila) Nilambur South Division Kerala 11�180 76�100 252

Wayanad (Waya) Wayanad Wildlife Sanctuary Kerala 11�020 76�410 277

Pollachi (Poll) Indira Gandhi Wildlife Sanctuary Tamil Nadu 10�350 76�520 158

Shimoga (Shim) Shimoga Division Karnataka 13�810 75�580 539

Barchi (Barc) Haliyal Division Karnataka 15�170 74�380 725

Virnoli (Virn) Haliyal Division Karnataka 15�060 74�360 707

Conserv Genet (2012) 13:1409–1419 1411

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E-ACT/M-CAG, E-ACC/M-CTT, E-ACA/M-CTT, E-ACC

/M-CTA, E-AGG/M-CAG, E-AGG/M-CTG and E-AGG/

M-CAT selected out of 64 tested combinations. Primer

labeling was performed by phosphorylating the 50 end of

the EcoRI primer with c-p32ATP and T4 kinase. Mix 1 and

Mix 2 components were used for selective AFLP amplifi-

cation in which, Mix 1 was composed of 5 ll of the labeled

selected EcoRI primer and 45 ll of MseI primer. Mix 2

was made according to the protocol supplied by Life

Technologies with the AFLP kit. Selective amplification

was carried out using 5 ll of the preamplification product

as the template DNA, 5 ll of Mix 1 and 10 ll of Mix 2. A

touch down phase of 13 amplification cycles was carried

out initially, with first cycle at 94 �C for 30 s denaturation,

65 �C for 30 s annealing and 72 �C for 60 s primer

extension. The annealing temperature was decreased by

0.7 �C each cycle during the following 12 cycles. The final

23 cycles were run at 94 �C for 30 s, 56 �C for 30 s and

72 �C for 60 s. Samples were denatured by adding an equal

volume of formamide buffer (98 % formamide, 10 mM

EDTA pH 8, 0.05 % bromophenol blue and 0.05 % xylene

cyanol) and heated at 94 �C for 3 min. 5 ll of each sample

was run in a denaturing 6 %, 0.4 mm polyacrylamide gel

(1X TBE buffer) in a sequencing gel electrophoretic

apparatus (Biorad, USA) at 40 A, 900 V for 2 h. The gel

was then transferred onto Whatman No.1 chromatographic

paper, dried at 80 �C for 2 h on a gel drier (Biorad, USA)

and exposed the gel to X-ray film (Kodak�) overnight.

Two replicates of the PCR reactions from independent

DNA extractions were performed to confirm the accuracy

of the AFLP analysis. Pre-amplified tomato DNA provided

with the Invitrogen AFLP Starter Primer Kit as control for

selective amplification was also utilized for checking the

accuracy of the protocol. 30–330 bp AFLP� DNA ladder

(Invitrogen Life Technologies, Inc., USA) was run on

either side of the denaturing gel as the standard marker.

The ladder was labeled with c-p32ATP using T4 polynu-

cleotide kinase according to the manufacturer’s protocol.

Data analysis

The autoradiogram developed was scanned using HP

Scanjet 3770 digital flatbed scanner and transferred each

scanned autoradiogram to Kodak Digital Science 1D Image

Analysis Software. Once the lanes have been marked and

labeled, the bands observed on the image were compared

with standard marker and this determined the molecular

weight and mass of each amplicon developed. These bands

were scored manually as ‘1’ for the presence of a band and

‘0’ for the absence of a band. Both polymorphic and

monomorphic bands were included in the final data sets

forming a binary matrix.

The data matrices were grouped into nine populations

and analyzed using POPGENE, Version 1.32 package for

dominant markers and a pair wise comparison of popula-

tions was made (Yeh et al. 1999). The genetic diversity

parameters within population viz. gene diversity (H), and

per cent of polymorphic loci (PPL), were analysed. F sta-

tistics were used to examine genetic variation among and

within populations and regions. Gene diversity in the spe-

cies (HT) is the sum of average gene diversity among

populations (DST) and average gene diversity within

populations (HS), where HT = HS ? DST. The relative

amount of gene differentiation among populations was

measured by the coefficient of gene differentiation, GST,

where GST = DST/HT. The rate of gene flow (Nm) for

each locus was calculated using the formula Nm =

0.5(1 - GST)/GST and mean value across loci (McDer-

mott and Mcdonald 1993) were determined. The pair wise

genetic distances (Nei 1978) obtained were subjected to

clustering using Unweighted Pair Group Method with

Arithmetic means (UPGMA).

AFLP binary matrix of 180 individual trees was sub-

jected to population structuring using PHYLIP Version

3.66 (Felsenstein 2005). A matrix of genetic distances

between individual genotypes of each population based on

shared amplification products was calculated using the

metric of Nei and Li (1979). This was also used to con-

struct a UPGMA dendrogram using the NEIGHBOUR and

DRAWTREE options in the PHYLIP package. Principal

co-ordinate analysis (PCoA) was performed using the

Fig. 1 Map showing the location of natural populations of teak in the

Western Ghats region selected for AFLP analysis. WLS Wildlife

Sanctuary, IGWLS Indira Gandhi Wildlife Sanctuary, P-V WLSPeechi-Vazhani Wildlife Sanctuary

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modules STAND, SIMINT, DCENTER and EIGEN of

NTSYSpc 2.02 (Rolf 2000) to identify the number of

groups based on eigen vectors. The goodness of fit of the

clustering of the data matrix was determined by calculating

the cophenetic correlation coefficient between the dissim-

ilarity matrix and the cophenetic matrix. Its significance

was evaluated by a Mantel test using 1,000 permutations

(Mantel 1967). A mantel test was also carried out to

investigate the correlation between genetic distance and

geographic distance.

The AFLP data was analyzed using STRUCTURE

software 2.0 (Pritchard and Wen 2003), which helps to

evaluate the level of genetic admixture between the 180

teak genotypes. The genotypes were clustered applying a

minimum of five parametric genetic mixture analysis

implemented in the Structure 2.0 software and the genetic

clusters (K) ranging from 2 to 10 were tested using the

admixture model with a burn-in period of 10,000 followed

by 100,000 Markov Chain Monte Carlo (MCMC) repeats,

considering the presence and absence of bands across the

populations. True number of populations (K) is often

identified using the maximal value of L(K) returned by the

software. However, for the admixture model we observed,

once the real K is reached, L(K) at larger Ks plateaus or

continues increasing slightly. For this model and in order to

detect the uppermost hierarchical level of structure, the

statistic DK was calculated based on the rate of change in

the log probability of data between successive K values

(Evanno et al. 2005). The graphical output display of the

STRUCTURE results was taken as input data using DI-

STRUCT software (Rosenberg 2002; http://www.cmb.usc.

edu/noahr/distruct.html) for better exhibition of graphical

representation.

Results

Genetic diversity

The 10 primer pair combinations generated 665 putative

genetic loci, with an average 66.5 ± 7.36 loci per primer

pair (range 55–76). Out of these, 661 were polymorphic

and the percentage of polymorphism was 99.4 %. At the

population level, the percentage polymorphism varied from

56.84 % (Virn) to 87.97 % (Konn). Similarly Nei’s (1973)

gene diversity index (H) varied from 0.1387 (Barc) to

0.2449 (Konn). The gene diversity and percentage of

polymorphic loci for Konn and Waya were almost similar

and these two Kerala populations showed the highest

genetic diversity. Karnataka populations showed the lowest

genetic diversity index varying from 0.1387 (Barc) to

0.1605 (Shim) and per cent of polymorphic loci ranging

from 56.84 (Virn) to 68.42 (Shim) Table 2.

Genetic differentiation

The mean gene diversity (HS) was 0.1995; the mean total

gene diversity (HT) was 0.264. GST was calculated from

allele frequencies estimated according to the square root

method assuming Hardy–Weinberg equilibrium in POP-

GENE. The relative magnitude of genetic differentiation

among population (GST) was 0.24 indicating that 24 % of

total gene diversity was among the natural population while

the remaining 76 % of total variation occurred within the

population. The gene flow (Nm) estimated from the GST

value was found to be 1.5. The test of correlation between

genetic and geographic distance matrices also revealed a

significant positive correlation (r = 0.4748; p = 0.0090).

Cluster analysis and PCoA of individual genotypes

The standard genetic distance (D) unbiased for the sample

size (Nei 1978) varied from 0.0554 (between Barc and

Virn) to 0.1166 (Poll and Barc). The UPGMA dendrogram

showed two main clusters with clear separation. The larger

cluster comprised of all the Kerala populations (viz. Konn,

Thri, Para, and Waya) along with the Poll population and

the Nila population joined with it separately. The second

cluster consisted of Karnataka populations viz. Shim, Barc

and Virn natural forests (Fig. 2).

The cluster analysis based on AFLP data from 180

genotypes using PHYLIP 3.66 software generated a unique

dendrogram. The dendrogram divided 180 genotypes into

two main clusters of six populations from Kerala and Tamil

Nadu, and three populations from Karnataka. The first

cluster comprised of three sub clusters to which the Nila

population is joined as it stood out separately. Thri and

Para constituted one sub cluster while Poll and Waya

formed the other sub cluster. Konn population remained as

Table 2 Comparison of nine natural populations of teak for various

genetic diversity measures

Pop H NPL PPL

Konn 0.2443 585 87.97

Thri 0.2334 542 81.50

Para 0.2336 541 81.35

Nila 0.1980 502 75.49

Waya 0.2449 577 86.77

Poll 0.1980 492 73.98

Shim 0.1605 455 68.42

Barc 0.1387 426 64.06

Virn 0.1428 378 56.84

Mean 0.1995

±0.04

499.77

±69.86

75.15

±10.51

Pop population, H gene diversity, NPL number of polymorphic loci,

PPL per cent of polymorphic loci

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http://www.cmb.usc.edu/noahr/distruct.html

http://www.cmb.usc.edu/noahr/distruct.html

a separate entity. The observations of the genetic structure

inside each cluster clearly revealed tight grouping of 20

genotypes from each population justifying the different

geographic origin of the populations (Fig. 3). Cophenetic

correlation coefficient between the dendrogram and origi-

nal distance matrix indicated good fitness with r = 0.89

(p \ 1.0000).

The PCoA revealed three distinct clusters of genetic

relationships between the nine populations used in this

study. The populations from Kerala (viz. Konn, Thri, Para

and Waya) and Poll were grouped in cluster II, whereas the

genotypes from Nila population grouped separately in

cluster I. The Karnataka populations (viz. Shim, Barc and

Virn) clustered along cluster III (Fig. 4). Genetic relation-

ships revealed by clustering (Fig. 3) and PCoA are very

concordant. Mantel’s test of significance also proved a

significant and positive correlation between geographic and

genetic distance (r = 0.4748; p = 0.0090).

Population structure analysis (Fig. 5) showed the

graphical output obtained for different K values and the

results were consistent with the tree based clustering

obtained for the same data. The results obtained showed a

genetic structure (a = 0.1868 for K = 3) showing that the

sampled populations are in real structure.

Discussion

Teak trees in the Western Ghats forests have been depleted

considerably from nineteenth century onwards due to over

exploitation, illicit felling, repeated fires, enormous soil

erosion, torrential rain and mortality caused by teak defo-

liator, Hyblea puera (Prabhu 2005). Moreover, most of the

natural teak forests have been gradually converted to

monoculture plantations (Katwal 2005). However, there are

islands of natural teak forests surrounded by plantations,

and large moist deciduous tracts with teak trees of varying

girth class remaining protected deep inside Wildlife

Sanctuaries, National Parks and reserve forests. They are

the teak gene pool reserves and the resources for the future

tree improvement programme. A comparative evaluation of

the genetic diversity of natural teak populations from dif-

ferent geographic areas of the Western Ghats and the

genetic structure of these populations have not been studied

so far. The present study using AFLP analysis provided

considerable information on the magnitude and pattern of

genetic variation existing in nine natural teak populations

from the Western Ghats forests covering three South Indian

states viz. Kerala, Karnataka and Tamil Nadu.

The study showed that the total diversity (HT) of the

nine teak populations was 0.264 ± 0.1672. This estimate is

slightly lower than the value (0.3) reported from earlier

studies using RAPD markers for ten populations of natural

forest and plantation teak from the Western Ghats and

Central India (Nicodemus et al. 2005). Overall levels of

teak genetic diversity was marginally higher than values

obtained using AFLP markers for Cedrela odorata (0.22),

one of the important neotropical timber species (De la

Torre et al. 2008).

Among the nine teak populations considered in the

present study, the gene diversity indices (H) within indi-

vidual populations and percentage of polymorphic loci

were higher for the populations from Southern Western

Ghats than those for Northern populations from Karnataka

state (Table 2). The four Kerala populations (Konn, Thri,

Para and Waya) showed gene diversity above 0.23. Of

these, the locations of sample collection for Thri, Para and

Waya populations were inside Wildlife Sanctuaries (Fig. 1)

where human disturbances were negligible and no major

forestry activity was carried out for the last few decades.

The gene diversity value for Konn was also high (0.2443)

probably because the samples originated from deep inside

the Reserve Forest area of Konni Forest Division where

human disturbances were very less. Though, Poll samples

were also from Wildlife Sanctuary located on the eastern

Fig. 2 Dendrogram constructed based on Nei’s (1978) genetic

distance coefficients of nine natural population of teak. Virn Virnoli,

Barc Barchi, Shim Shimoga, Waya Wayanad WLS, Nila Nilambur,

Poll Pollachi IGWLS, Thri Thrissur P-V WLS, Para Parambikulam

WLS, Konn Konni

1414 Conserv Genet (2012) 13:1409–1419

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slope of the Western Ghats, the diversity was lesser than

those of the Kerala samples except for Nila which showed

the same diversity as that of Poll (0.1980). All the

Karnataka populations showed lesser diversity than the

Kerala and Tamil Nadu populations (0.1387–0.1605).

Though documentary evidences were unavailable, there

Fig. 3 UPGMA dendrogram of

genetic relationships of 180

natural teak trees. Virn Virnoli,

Barc Barchi, Shim Shimoga,

Waya Wayanad WLS, NilaNilambur, Poll Pollachi

IGWLS, Thri Thrissur P-V

WLS, Para Parambikulam

WLS, Konn Konni

Fig. 4 Principal coordinate

analysis (PCoA) of 180

genotypes of natural teak. Filledsquare box indicates Nila (I),unfilled triangle indicates Konn,

Thri, Waya, Poll, Para (II) and

filled triangle indicates Shim,

Barc, Virn (III)

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were indications of wide spread logging, augmentation

planting and fragmentation of the natural teak forest in

these places during the past. In the state of Karnataka, the

demand for timber being quite high due to the continued

growth of urban centers, the natural forests were progres-

sively transformed into teak plantations (Dilip Kumar

2005). Such disturbances in the natural stand and forest

fragmentation could lead to genetic isolation of small

populations that can cause inbreeding and genetic drift

(Bawa 1990). The observations from the present study

were similar to the diversity existing in natural populations

of Uapaca kirkiana, a fruit tree species of Southern Africa

(Mwase et al. 2006).

Tropical trees tend to possess higher levels of genetic

diversity within populations, and species reproducing both

sexually and asexually showed less differentiation than

species reproducing only sexually (Hamrick and Godt

1989). Teak is a perennial, woody, cross pollinated species

and in such species the majority of the genetic variation is

expected within populations. The present study also

showed a large genetic differentiation of GST = 0.244

implying that 24 % of total genetic variation was among

populations and rest 75.6 % of variation residing within the

populations. Yeh (2000) considered a range of GST

between 0.151 and 0.25 as representative of large genetic

differentiation. If so, the teak populations of the natural

forests of the Western Ghats showed large differentiation

among the populations along the mountain tract.

The assessment of genetic diversity among teak popu-

lations of India, Thailand and Indonesia using AFLP

markers showed 43 % (0.43) among populations diversity

(Shrestha et al. 2005). But, this high value was supposed to

be caused by low sample size of their study. The study by

Fofana et al. (2009) using SSR markers showed an overall

FST value of 0.22 indicating large genetic differentiation

among the populations from India, Thailand and Laos

suggests a long period of genetic isolation. The genetic

differentiation obtained in the present study was higher

than the differentiation reported (21 %) for 16 natural teak

populations from Thailand (Changtragoon and Szmidt

2000) and the differentiation (22 %) observed using RAPD

markers for ten teak populations (natural forest and plan-

tations) from the Western Ghats and Central India (Ni-

codemus et al. 2005). Studies on Pines (Hamrick and Godt

1989) and Santalum album populations from India (Suma

and Balasundaran 2003) showed a reverse trend in which

most of the genetic diversity was found to be resided

among populations.

The existence of about 75 % of genetic variation within

teak populations has serious implications on tree

improvement of teak though selection process. Generally,

teak plus trees are marked in plantations or natural forests

based on high intensity phenotypic selection for developing

clonal seed orchards (CSOs). This strategy of selecting

very few trees from individual populations may not be

helpful for exploiting the large intra-population variation

available within populations. Hence, selection intensity has

to be reduced and several good quality genotypes have to

be selected within populations in order to increase the

genetic base of CSOs to a satisfactory level. CSOs with

broad genetic base are expected to enhance the outcrossing

rate resulting in improved seed set.

The difference in genetic distance between the North–

South populations is also evident from the pattern of

grouping in the UPGMA dendrogram. The Karnataka pop-

ulations viz. Shim, Barc and Virn which are geographically

closely located are also genetically closer. These northern

populations nested within one cluster, and the Kerala and

Tamil Nadu populations in a large separate cluster (Figs. 2,

3). The individual tree samples also nested strictly within the

respective populations. PCoA revealed genetic relatedness

of 180 genotypes and confirmed the tendency of individuals

to group according to geographical localities (Fig. 3).

In the present study, samples were collected from pop-

ulations of different latitudes and geographical distances

between them. The test of correlations between genetic

Fig. 5 Summary plot estimates

the population structure of 180

individuals from nine natural

teak populations for K = 2,

K = 3 and K = 4. Each

individual is represented by a

single vertical line broken into

K colored segments, with

lengths proportional to each of

the K inferred clusters. Each

colour represents the proportion

of membership of each

individual, represented by a

vertical line. *See Table 1 for

population information. (Color

figure online)

1416 Conserv Genet (2012) 13:1409–1419

123


distance and geographic distance matrices using mantel test

revealed significant positive correlation. This significant

correlation indicated that long distance dispersal of seeds

had been rare. The correlation between the genetic data and

geographical data were further supported by the genetic

distance coefficients and the UPGMA dendrogram drawn

using PHYLIP package.

It can be found from the UPGMA dendrogram and

PcOA that the Kerala populations viz. Konn, Thri, Para,

Waya and the Tamil Nadu population, Poll formed a large

cluster with its own sub clusters; but Nila population joined

separately to this cluster indicating its separate identity as

revealed by the increased genetic distances from the other

Kerala and the Tamil Nadu populations. A similar sepa-

ration of Nilambur stand was observed using co-dominant

markers (microsatellites) in a study on genetic diversity

and contemporary gene flow in teak (Indira et al. 2008).

The Nilambur population might have the influence of

locality factor, the principal factor governing the distribu-

tion and evolution of teak trees. In their analysis on allelic

richness among the provenances planted in International

Provenance Trial, Fofana et al. (2009) found the highest

mean number of alleles per population in Nilambur prov-

enance. The Nellicutha ‘Provenances’ (Harvest No.15 and

16) and Nilambur Provenance (Harvest No. 3021) (appar-

ently from Nellicutha itself) showed superiority in gene

diversity. The highest mean number of alleles was shown

by the Nellicutha 16 (7.67) and Nellicutha 15 (6.87) har-

vest numbers while the mean number of alleles from all the

21 populations studied was 4.17 only. Actually, all the

three ‘provenances’ originated from Nilambur Valley

because ‘Nellicutha’/’Nellikutha’ was one of the reserve

forests of the former Nilambur Forest Division. The

Nilambur teak, historically known as ‘Malabar teak’ which

showed good log dimensions having golden yellowish-

brown color and highest per cent of heartwood among

Indian teak provenances had excellent reputation in world

trade (Bhat et al. 2008). Nilambur teak has got a separate

identity by virtue of its wood quality, growth, genetic

distance from other populations from the Western Ghats

and the SSR study-reported allelic richness. In spite of all

these facts AFLP diversity for Nilambur teak (0.1980) was

lesser than that of other Kerala populations. The lowest

gene diversity showed by Nilambur teak was not unex-

pected considering the centuries of natural teak extraction

and fragmentation of teak forests of Nilambur Valley

(Kunhikrishnan 1997). If the quality of the provenance is to

be retained and genetic purity maintained, mixing seeds

from other sources with Nilambur seeds has to be avoided

while raising plantations.

The application of population structure analysis to 180

individuals based on structure showed considerable

admixtures or overlap among markers. For example, the

model based clustering showed that teak provenances were

grouped in two clusters among Kerala, Tamil Nadu and

Karnataka populations. When the number of populations

was set at three (K = 3), the values were matching with

number of clusters. Daniel Falush also suggested aiming

for the smallest value of K which captures major structure

in the data (Pritchard and Wen 2003). The likelihood

reaches a maximum around K = 3–4 and decreases from

K [ 4. The results obtained showed a genetic structure

(a = 0.1868 for K = 3) the sampled populations are rela-

ted to geographic distribution. With the admixture model,

the software gave similar estimations for K after K = 3;

the methodology of Evanno et al. (2005) strongly sup-

ported K = 3 as the correct number of clusters and most of

the genotypes were classified into one of the two groups.

The admixture model required the use of DK to find the

same number of clusters. The sampled individuals are

strongly assigned to one population or another, and the

proportions assigned to each group are asymmetric. For the

nine natural teak forests of Western Ghats, the genetic

structure found with the AFLP markers is very strong.

The present study estimated the amount of gene flow

(Nm = 1.5) to be moderate. Hamrick and Nason (2000)

suggested four migrants per generation (Nm = 3.54) as the

minimum to prevent differentiation due to drift. According

to Wright (1969), the critical value for Nm is 0.5. When

Nm value is below 1, it means that populations began to

differentiate due to genetic drift. Nm value below 0.5

indicates that populations will diverge extensively as a

result of drift (Mcdermott and Mcdonald 1993). Overall,

the calculated gene flow (Nm) indicated that the natural

stands of teak are in the process of differentiation.

A few of the best quality teak provenances such as

Nilambur (Nila) and Dandeli (Barc and Virn) have lost

genetic diversity quicker than other provenances of the

Western Ghats as found in our study. These facts invite

attention towards the necessity of adopting more efficient

and scientific methods of in situ and ex situ conservation of

whatever natural teak resources are remaining in the Western

Ghats. Recently, the crisis in natural teak forests of India has

come to a sharp focus. It has been commented that much of

India’s natural teak forests have been reduced to bush land

(FAO, 2009). But, things are not as bad as it is projected.

There are natural teak forests showing large genetic diversity

such as reserve forests of Konni, Wayanad, Parambikulam

and Thrissur as revealed in the present study. The need of the

hour is protection of not only these patches of natural teak

forests but also the entire teak forests of the Western Ghats so

as to conserve their genetic diversity for sustainable use in

the future. Establishment of more protected forests such as

National Parks, Wildlife Sanctuaries and Tiger Reserves

incorporating natural teak forests within their boundaries

would be a promising step towards conservation.

Conserv Genet (2012) 13:1409–1419 1417

123


Acknowledgments The authors acknowledge the financial support

provided by the Department of Biotechnology, Government of India

(S.O.No. BT/PR/2302/AGR/08/161/2000). We are thankful to the

Forest Departments of Kerala, Karnataka and Tamil Nadu for giving

permission for the collection of leaf materials.

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