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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: sreekanthpm@gmail.com
M. Balasundaran
Environmental Biotechnology, Tropical Institute of Ecological
Sciences, Velloor P.O., Kottayam 686501, Kerala, India
e-mail: bsundaran@rediffmail.com
P. A. Nazeem
Centre for Plant Biotechnology and Molecular Biology, Kerala
Agricultural University, KAU Campus P.O., Thrissur 680656,
Kerala, India
e-mail: cpbmb@rediffmail.com
T. B. Suma
Kerala Forest Research Institute, Peechi P.O., Thrissur 680653,
Kerala, India
e-mail: sumadev@rediffmail.com
123
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DOI 10.1007/s10592-012-0383-5
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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
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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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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
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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
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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
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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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