Botanical Studies (2008) 49: 147-153.
*
Corresponding author: E-mail: xjge@yahoo.com; Tel:
+86-20-3725 2551; Fax: +86-20-3725 2831.
POPULATION GENETICS
Population genetic structure of Camellia nitidissima
(Theaceae) and conservation implications
Xiao WEI
1, 2
, Hong-Lin CAO
1
, Yun-Sheng JIANG
2
, Wan-Hui YE
1
, Xue-Jun GE
1,*
, and Feng LI
2
1
South China Botanical Garden, Chinese Academy of Sciences, Guangzhou 510650, P. R. China
2
Guangxi Institute of Botany, Guangxi Zhuangzu Autonomous Region and Chinese Academy of Sciences, Guilin 541006,
P.R. China
(Received January 11, 2007; Accepted October 19, 2007)
ABSTrACT.
Camellia nitidissima Chi (Theaceae), with its golden-yellow flowers, is a famous ornamental
species. Due to deforestation and collection of seedlings, its natural populations have receded greatly in recent
decades. Genetic diversity and genetic differentiation of the twelve extant natural populations and one ex situ
conserved population of C. nitidissima in China were analyzed using inter-simple sequence repeats (ISSR)
markers. We found a low level of genetic diversity at both the species (P = 63.22%, Nei”¦s genetic diversity
H
T
= 0.1561 and Shannon diversity Hsp = 0.2490) and population levels (P = 18.77%, H
E
= 0.0831 and
Hpop = 0.1188) and a relatively high degree of differentiation among populations (AMOVA analysis: 41.85%;
Hickory £c
B
: 0.4056) in naturally occurring populations. In contrast, the ex situ population contained higher
genetic variability compared to each natural population. No significant correlation was found between genetic
diversity and population size. Based on the results, we suggest that all the wild C. nitidissima populations
should be protected in situ. For the ex situ conservation of the species in Guilin Botanical Garden, samples
from Long”¦an County should be added to the existing collections.
Keywords: Camellia nitidissima; China; Endangered species; Ex situ conservation; ISSR fingerprinting; Small
population size.
INTrODUCTION
The section nitidissima Chang of the genus Camellia
(Theaceae) comprises 18 rare and endangered species
occurring in a narrow range 20¢X32”¦-23¢X53”¦ N, 104¢X-108¢X
56”¦ E, and at the altitudes of 50-650 m, in Southwest China
and North Vietnam (Zhang, 1996). The golden-yellow
petals of the flowers have earned them the title "the queen
of the Camellia family" (Liang, 1993). They represent
valuable germplasm resources for cultivar breeding,
especially for producing yellow flowers. With the big size,
golden color, and the transparent waxy appearance of its
flowers, Camellia nitidissima Chi is the most interesting
species of the section. Although first discovered in
Fangcheng County in 1933 and reported to the public in
1948, C. nitidissima received no attention from the public
or horticulturists until the early 1960”¦s when it was found
again in Yongning County (Deng et al., 2000). Camellia
nitidissima is a diploid shrub (2n = 30, Huang and Zhou,
1982), with a restricted distribution in the southwestern
Guangxi Zhuang Autonomous Region in China and in the
neighboring regions of North Vietnam. It grows under
shady and moist evergreen broad-leaf forests dominated
by Canarium album, Dendrobenthamia hongkonensis,
and Canstanopsis cuspidata. Its big and colorful flowers
(diameter: 1.2-2.3 cm) blossom from November to March
and set fruits in the spring.
Due to deforestation of the regions where C. nitidissima
grows and the over collection of its seedlings, its natural
population has declined dramatically in recent decades.
It is now classified as one of the most endangered
plant species in China (Fu, 1992). In order to protect
this valuable genetic resource, one natural reserve was
established in Fangcheng in 1986. In addition to the
in situ habitat preservation for rare and endangered
plant species, ex situ conservation in botanical gardens
plays an important role in conserving these plants. In
the 1980s, Guilin Botanical Garden (GL) started an ex
situ conservation program for this species and planted
more than 1300 seeds and 100 seedlings collected from
Yongning, Fangcheng, Dongxing, and Fusui Counties.
Today, about 800 individuals are settled in the garden, and
most of them blossom and set fruits.
Although the morphology (Ye and Xu, 1992), ecology
(Su, 1994; Huang, 2001), and condition for cultivation
(Zhang and Huang, 1984) have been studied, the popula-
tion genetic structure of this endangered species has never
been examined extensively across the species range (Bin et
al., 2005; Tang et al., 2006). Understanding the levels and
pg_0002
148
Botanical Studies, Vol. 49, 2008
distribution of genetic variation within species/populations
not only aids in recovering the evolutionary history, it
also helps in conservation and management of the species
(Frankham et al., 2002). Several PCR-based fingerprinting
techniques (e.g., RAPD, SSR, ISSR and AFLP) have been
developed to study population genetic structures. Among
them, the sensitivity of the inter-simple sequence repeat
(ISSR) technique (Zietkiewicz et al., 1994) makes it a
powerful tool for investigating genetic variation within
species (Wolfe and Liston, 1998), and it has been success-
fully applied in the conservation genetics of many rare
and endangered plant species. Amplifying ISSR markers
does not require knowledge of the genome sequence. They
are simple to use and generate data quickly, which makes
them highly suitable for population genetics studies.
Therefore, in this work, we estimated the genetic diversity
and differentiation of twelve remaining natural popula-
tions and one ex situ population (GL) of the endangered C.
nitidissima by using ISSR molecular markers, with a view
to achieving more efficient conservation of this rare ge-
netic resource and to ensure that most of its genetic varia-
tions are adequately preserved in the ex situ conservation
projects. As it is governed by random genetic drift, like
many other rare species, low levels of genetic diversity
within populations, but high genetic differentiation among
populations, would be expected.
MATErIALS AND METHODS
Sample collection
In August 2003, a total of 250 individuals were sampled
from twelve geographically isolated natural populations
of C. nitidissima across the entire range of distribution of
the species in Guangxi, China (Figure 1; Table 1). These
populations could be divided into two regions separated
by about 117-148 km. Seven populations (A-G) were dis-
tributed around Fangcheng, and the other five populations
(H-L) surrounded Nanning. Within each region, the popu-
lations were isolated from each other at a distance of 4 to
40 km, and their sizes varied from 32 to 206 plants (Table
1). In order to check the effectiveness of ex situ conserva-
tion of C. nitidissima in Guilin Botanical Garden, sixty
individuals from this conserved population (GL) were also
sampled. Fresh leaves of each selected plant were col-
lected and dried quickly by using silica gels in the field.
Vouchers were collected from each population and depos-
ited at the herbarium of Guangxi Institute of Botany (IBK).
Table 1. Camellia nitidissima populations in China and their genetic variability detected by ISSR analysis.
Code Provenance
Altitude (m) Longitude (E) Latitude (N) Ns
1
N
2
H
E
Ho P (%)
A Fangcheng
165
108
o
9”¦
21
o
52”¦ 22 120 0.0948 0.1345 20.69
B Fangcheng
20
108
o
18”¦
21
o
43”¦ 19 182 0.0804 0.1150 18.39
C Dongxing
130
107
o
58”¦
21
o
39”¦ 20 37 0.0612 0.0874 13.79
D Fangcheng
178
108
o
07”¦
21
o
40”¦ 20 63 0.0889 0.1279 20.69
E Fangcheng
120
108
o
03”¦
21
o
51”¦ 20 206 0.0892 0.1285 20.69
F Fangcheng
170
107
o
56”¦
21
o
50”¦ 22 39 0.0925 0.1319 20.69
G Dongxing
410
107
o
55”¦
21
o
41”¦ 20 32 0.0664 0.0949 14.94
H Yongning
240
107
o
50”¦
22
o
57”¦ 21 190 0.1033 0.1472 22.99
I Yongning
380
107
o
46”¦
22
o
53”¦ 22 160 0.0970 0.1384 21.84
J Long”¦an
230
107
o
48”¦
22
o
58”¦ 20 165 0.0513 0.0731 11.49
K Long”¦an
250
107
o
46”¦
22
o
56”¦ 21 135 0.0677 0.0963 14.94
L Fusui
280
107
o
42”¦
22
o
52”¦ 23 140 0.1048 0.1507 24.14
GL ex situ conserved in Guilin
Botanical Garden
178
11 0
o
12”¦ 25
o
11”¦ 60 800 0.1525 0.2273 41.38
1
sample size;
2
population sizes; H
E
: Nei”¦s genetic diversity; Ho: Shannon”¦s information index; P: percentage of polymorphic loci.
Figure 1. Locations of sampled populations of Camelli a
nitidissima in China.
pg_0003
WEI et al. ”X Genetic structure of
Camellia nitidissima
149
Total DNA extraction and ISSr analysis
Total DNA was extracted following the CTAB
method described by Doyle (1991). One hundred ISSR
primers from the University of British Columbia primer
set nine (the Michael Smith Laboratories, University
of British Columbia, primer set #9, Vancouver, BC,
Canada: http://www.michaelsmith.ubc.ca/services/NAPS/
Primer_Sets/Primers.pdf) were initially screened for PCR
amplifications. Eleven of them (UBC # 808, 834, 835,
836, 840, 841, 848, 855, 857, 866, 880) that consistently
generated clear and reproducible banding patterns were
selected for further analysis. PCR and gel electrophoresis
were carried out as described by Ge et al. (2003). Only
those bands that showed consistent and unambiguous
amplifications were scored. Smeared and weak bands were
excluded.
Data analysis
ISSR profiles were scored for each individual as having
a specific band present (1) or absent (0). POPGENE 1.31
(Yeh et al., 1999) was used to compute the percentage of
polymorphic loci (P), Nei”¦s genetic diversity (H
E
) (Nei,
1973), and Shannon diversity (Ho = -£Up
i
log
2
p
i
), where
pi was the frequency of the fragment recorded. Shannon
diversity was calculated at two levels: the average
diversity within populations (Hpop), and the total diversity
(Hsp). The correlation between population size and genetic
diversity parameters was calculated with the Spearman
rank correlation coefficient.
Components of variance within and between popula-
tions were estimated using an analysis of molecular vari -
ance (AMOVA) that was performed by Arlequin 2.000
(Schneide et al., 2000). Pairwise genetic distances (£X
ST
)
among the twelve populations were obtained from the
AMOVA. For each analysis 1,000 permutations were per-
formed to obtain significance levels. Genetic structure was
also examined using a Bayesian approach (Holsinger et al.,
2002). We estimated £c
B
, a Bayesian derived analogue of
F
ST
, using Hickory”¦s default values, burn-in (50,000), sam -
pling (250,000) and thin (50), to specify the prior distribu -
tions. Gene flow was estimated indirectly using Wright”¦s
(1931) formula: Nm = 0.25(1-F
ST
)/F
ST
, where F
ST
was from
the AMOVA analysis.
In order to test the correlation between genetic (D )
and geographical distances (in km) among populations, a
Mantel test was performed using TFPGA (Miller, 1997)
with 5000 permutations. A neighbor-joining (NJ) dendro-
gram based on pairwise F
ST
(£X
ST
) comparisons between
populations was constructed using the PHYLIP programs
NEIGHBOR and CONSENSE (Felsenstein, 1993). The to-
pology of the dendrogram shown in Figure 2 was assessed
by a bootstrap test with 1000 replicates.
rESULTS
For the twelve natural populations, eleven primers
generated 87 DNA bands with molecular sizes ranging
from 230 to 1600 bp. Of these bands, 55 (63.22%) were
polymorphic at the species level. The percentages of poly-
morphic loci (P) ranged from 11.49% (J) to 24.14% (L)
within the twelve natural populations, with an average of
18.77%. The average genetic diversity was 0.0831 within
populations (H
E
) and 0.1561 at the species level (H
T
) (Ta-
ble 1). Population L had the highest level of variability (P:
24.14%, H
E
: 0.1048) while population J had the lowest (P:
11.49%, H
E
: 0.0513). The Shannon diversity indices also
revealed the lowest estimate (0.0513) in J and the highest
(0.1048) in L (Table 1). The mean value of Shannon diver-
sity was 0.1188 at thepopulation level (Hpop) and 0.2490
at the species level (Hsp) (Table 1). The ex situ conserved
population GL had higher genetic variability than any of
the twelve natural populations, but less than that at the
species level (P: 41.38%, H
E
: 0.1525, Ho: 0.2273) (Table
1). No significant correlation was found between popula-
tion size and genetic diversity (r
s
= 0.31, p = 0.154 for H
E
or Hpop and r
s
= 0.32, p = 0.154 for percentage of poly-
morphic loci).
AMOVA indicated that 11.83% of the molecular varia-
tion was attributable to regional divergences (between
Fangcheng and Nanning), 30.02% to population differen-
tiation within regions, and 58.15% to differences among
individuals within populations (Table 2). According to the
Bayesian analysis of population structure, the best model
was obtained with the free model (DIC = 1309.79, lower
than the f = 0 model with DIC = 1354, the full model with
DIC = 1356, f = 0 model with DIC = 4433). The mean £c
B
in the free model was 0.4056 (SD = 0.0256). The estimat-
ed gene flow among populations was Nm = 0.347.
Two clusters were identified (Figure 2), one consisting
of populations of the Fangcheng region and population L
of the Nanning region and the other including the remain-
ing four populations of the Nanning region (from Yongn-
ing and Long”¦an Counties). Populations H and I (97%)
and J and K (96%) were closely clustered as indicated
by bootstrapping. Mantel tests show a low correlation
Figure 2. The neighbor-joining (NJ) dendrogram constructed
based on population pairwise genetic distances. Branch length
is proportional to genetic distance. Numbers at nodes indicate
bootstrap values in percentage (> 50%).
pg_0004
150
Botanical Studies, Vol. 49, 2008
between genetic and geographical distances among popu-
lations (r = 0.5114, p = 0.002).
DISCUSSION
Genetic variation and genetic structure
As the primary components of evergreen broad-
leaf forest in East Asia, like most Camellia species,
C. nitidissima is rather restricted to a small area in
southwestern Guangxi Province of China and the
neighboring region of Vietnam. Compared to the average
of angiosperms obtained with dominant markers (RAPD,
AFLP, ISSR) (Nei”¦s genetic diversity at population level:
0.22-0.23; Nybom, 2004), a low level of genetic diversity
was detected in C. nitidissima, a result consistent with
Tang et al.”¦s (2006) observations. This can be interpreted
as a consequence of restricted, scattered distributions
of C. nitidissima, as a strong association exists between
geographical range and genetic diversity (Hamrick and
Godt, 1989), although exceptions are also common
(Gitzendanner and Soltis, 2000). Comparing eleven
pairs of endemic and widespread
congeners for genetic
variability, Karron (1991) found that
rare species had
significantly lower levels of genetic variation
than their
widespread congeners.
Population genetic theory predicts that small
populations tend to lose genetic variation because of the
effects of genetic drift. However, in some investigations,
levels of genetic diversity were not correlated with
population size (i.e., Greimler and Dobe., 2000; Lei
and Mutikainen, 2005; Mathiasen et al., 2007). As C.
nitidissima is a rare and endangered species, its natural
populations are generally small, eleven of the twelve
populations have fewer than 200 individuals (Table 1).
Despite the low levels of genetic diversity at the species
level, no significant correlation was found between
population size and genetic diversity in this study. The
population size of C. nitidissima has only fallen in recent
decades due to deforestation and destructive collection
of seedlings; the current fragmented populations are
the remants of a larger former population. According to
our demographic study (Wei et al., unpublished data),
the populations of C. nitidissima, as a long-lived shrub,
are dominated by adults with DBH greater than 2 cm.
Seedlings with DBH shorter than 1 cm were rare. In the
present study, the genetic variation of sampled adult C.
nitidissima trees may reflect a structure established prior to
the destruction that has recently occurred.
The ex situ conserved GL population has a higher level
of genetic diversity than any of the twelve natural popula-
tions, and it contains all the DNA bands that the natural
populations have. According to the sampling record, the
plants cultivated in the garden cover the range of the
species in China except for Long”¦an County. When we
combined the genetic data of J and K populations with GL
together, the genetic diversity as a whole exceeded that of
the natural populations at the species level (H
T
and Hsp:
0.1701 and 0.2571 vs. 0.1561 and 0.2490), demonstrat-
ing that the ex situ conservation in the Guilin Botanical
Garden could be improved through supplemental materials
from Long”¦an County.
The genetic structure of plant populations reflects the
interactions of various long-term evolutionary processes,
such as shifts in distribution, habitat fragmentation, popu-
lation isolation, mutation, genetic drift, mating system,
gene flow, and selection (Schaal et al., 1998). The breeding
system is one of the most powerful explanatory variables
for genetic diversity within and among populations of
plant species (Hamrick and Godt, 1989). Inbreeding spe-
cies are generally characterized by high levels of genetic
differentiation among populations while outbreeding ones
tend to retain considerable variability within populations.
In this study, about 41% of genetic variation was parti-
tioned between populations in C. nitidissima, comparable
with that of species with a mixed breeding system (£X
ST
:
0.40) and gravity seed dispersal (£X
ST
: 0.45) (cf. Nybom,
2004). Significant genetic differentiation was also reported
by Bin et al. (2005) (£X
ST
: 0.5752) and Tang et al. (2006)
(£X
ST
: 0.539).
High genetic divergence among populations suggests
limited gene flow (Nm = 0.347), which in turn increases
the probability of inbreeding. Although no comprehensive
studies on its mating system and seed dispersal have been
done, C. nitidissima was found to be mainly pollinated by
bees of a short flight range (Cheng et al., 1994). Moreover,
long distance seed dispersal is unlikely to be efficient be-
cause it”¦s the species”¦ big, heavy seeds (1.73-2.16 cm long
and 1.94-2.5 cm in diameter, 2.3-3.5 g in weight). In con-
Table 2. AMOVA results for the twelve natural populations of Camellia nitidissima.
Source of variation
d.f. Sum of squares Variance components Percentage of variation P-value
Among regions
1
104.779
0.57989
11.83
< 0.001
Among populations within regions 10
334.607
1.47119
30.02
< 0.001
Within populations
238
678.261
2.84984
58.15
< 0.001
Total
249
1117.648
4.90091
P-values are the probabilities of having a more extreme variance component than the observed values by chance alone. Probabilities
were calculated by 1000 random permutations of individuals across populations.
pg_0005
WEI et al. ”X Genetic structure of
Camellia nitidissima
151
trast to this limited gene flow in C. nitidissima, bird-polli-
nation contributes to a strong gene flow in C. japonica, for
which a low degree of allozyme differentiation between
populations in Japan and Korea was detected (Chung and
Chung, 2000). Apparently, limited gene flow is one factor
contributing to C. nitidissima”¦s high level of population
differentiation.
Conservation consideration
Threatened and endangered species that possess small-
sized populations are more prone to extinction than those
with large, stable populations. According to IUCN criteria,
C. nitidissima populations are mostly endangered. The
goals of conservation are to avert the genetic deterioration
of the species, to preserve the species”¦ potential for adapta-
tion to both short- and long-term environmental variation,
and thereby reduce the chances of extinction. Genetic
impoverishment, coupled with demographic stochastic-
ity, is expected to increase the risk of local extinction in
small populations (Hanski and Gilpin, 1991). Although a
natural reserve for C. nitidissima has been established in
Fangcheng, one of the primary distribution areas of the
species in China, germplasm of the other seven popula-
tions, especially populations H and L with the highest ob-
served and expected genetic diversities (Table 1) has never
been included. Results of the present study indicate that
representation of the species”¦ gene pool could be substan -
tially improved through inclusion of additional popula-
tions.
Conserving the genetic diversity of rare and endangered
species and their evolutionary potential is one of the long-
term goals of ex situ conservation. Appropriate sample
collections are the key to creating ex situ reserves. For C.
nitidissima, Tang et al. (2006) suggested "more individual
plants from each population but fewer populations" as the
ex situ sampling strategy. However, based on the observed
high genetic differentiation in C. nitidissima, we suggest
an ex situ sampling strategy of fewer individual plants
from every population. The high genetic diversity harbored
in the GL population verified the effect of this strategy as
it has a wide source from Yongning, Fangcheng, Dongx -
ing, and Fusui Counties.
Botanical gardens have played important roles in
the ex situ conservation of rare and endangered plants.
Nevertheless, because of limited spatial and financial
resources, most ex situ conservation project in Chinese
botanical gardens ignore the sampling strategy. Generally
only a very few individuals from each species are
cultivated, completely neglecting the need to conserve
the genetic diversity range (Li et al., 2002). Inevitably,
much genetic diversity is lost, subsequently increasing
inbreeding chances in the ex situ population. Fortunately,
about 800 C. nitidissima individuals were conserved in
the Guilin Botanical Garden. The high genetic diversity
in the GL population indicates that the reintroduction of
C. nitidissima from this garden is plausible from a genetic
diversity perspective.
As with most endangered species, habitat loss and
destructive human collection of seedlings are the main
threats to C. nitidissima. Although the plants in the
natural reserves are shielded from destruction, the risk
of extinction cannot be reduced (Hensen and Wesche,
2006). In the long term, the small population size of C.
nitidissima will drive this species to an "extinction vortex."
Reintroduction to increase population size and genetic
diversity is thought to be the most effective method for
population recovery (Falk et al., 1996). For C. nitidissima,
the reintroduction from ex situ conserved populations is
needed in the future.
Genetic diversity and differentiation of neutral
markers often provide useful information on the
demographic events that occurred in natural populations
(such as bottlenecks, rapid expansion, and migration).
Nevertheless, due to the lack of correlation between
genetic variability of neutral markers and variation
of genes coding quantitative traits, molecular-marker
studies have contributed little to our understanding of
natural selection and adaptation in forest-tree populations
(Gonzalez-Martinez et al., 2006). In this study, only
spatial demographic processes was measured using
neutral markers, and whether the ex situ population can
represent the quantitative and adaptive genetic variation
remains unclear. For C. nitidissima, the extant twelve
populations of two regions (Fangcheng and Nanning) may
have evolved into locally adapted ecotypes. Therefore, a
detailed population genomics study by using candidate
gene markers (e.g. SNPs or EST-based markers) is needed
for re-evaluating the ex situ conservation of this valuable
genetic resource.
Acknowledgements. The authors thank Zhang-Ming
Wang, Xiao-Lan Wang, Zhong-Chao Li and Guo-Qing
Chen for their assistance and advice in the experiment and
manuscript writing. Thanks also go to Hui Tang for his
help in collecting the samples. This study was financially
supported by the National Science Foundation of China
(No. 30560015), the National Basic Research Program of
China (973 Program) (2007CB411600), and the Science
Foundation of Guangxi (No. 0575115).
LITErATUrE CITED
Cheng, J.H., J.Y. Chen, and S.W. Zhao. 1994. Interspecific cross
breeding for new yellow camellias. J. Beijing Forest. U. 16:
55-59 (in Chinese with English abstract).
Chung, M.G. and M.Y. Chung. 2000. Levels and partitioning of
genetic diversity of Camellia japonica (Theaceae) in Korea
and Japan. Silvae Genet. 49: 119-124.
Deng, G.Y., Z.D. Yang, and T.L. Lu. 2000. A brief review of
research on yellow camellia in China. J. Guangxi Agr. Biol.
Sci. 19: 126-130 (in Chinese with English abstract).
Doyle, J. 1991. DNA protocols for plants ”V CTAB total DNA
isolation, In G.M. Hewitt and A. Johnston (eds.), Molecular
pg_0006
152
Botanical Studies, Vol. 49, 2008
Techniques in Taxonomy. Springer, Berlin. pp. 283-293.
Falk, D.A., C. I. Millar, and M. Olwell (eds.). 1996. Restoration
diversity. Island Press, Washington, DC
Felsenstein, J. 1993. PHYLIP, Phylogenetic inference package,
Vers ion 3.5.7. A compute r program dis tributed by the
author, http://evolution.genetics.washington.edu/phylip.
html. Department of Genetics, University of Washington,
Seattle.
Frankham, R., J.D. Ballou, and D.A. Briscoe. 2002. Introduction
to Cons ervation Genetics. Cambridge University Press,
New York.
Fu, L.G. 1992. China Plant Red Data Book. S cience Press ,
Beijing.
Gonzalez-Martinez, S.C., K.V.Krutovsky, and D.B. Neale. 2006.
F ores t-tree population genomics and adaptive evolution.
New Phytol. 170: 227-238.
Ge, X.J., Y. Yu, N.X. Zhao, H.S. Chen, and W.Q. Qi.
2003. Ge n e ti c va r ia t i o n in th e e n da n g er e d In n e r
Mongolia endemic s hrub Tet raena mongolica Maxim.
(Zygophyllaceae). Biol. Conserv. 111: 427-434.
Gitzendanner, M.A. and P.S. Soltis. 2000. Patterns of genetic
variation in rare and widespread plant congeners. Am. J.
Bot. 87: 783-792.
Greimler, J. and C. Dobe.. 2000. High genetic differentiation in
relict lowland populations of Gentianella austriaca (A. and
J. Kern.) Holub (Gentianaceae). Plant Biol. 2: 628-637.
Hamrick, J .L. and M.J.W. Godt. 1989. Allozyme diversity in
plant species. In A.H.D. Brown, M.T. Clegg, A.L. Kahler
and B.S. Weir (eds.), Plant Population Genetics, Breeding
and Genetic Resources. Sinauer Associates Inc., Sunderland,
Massachusetts, USA. pp. 43-63.
Hanski, I.A. and M.E. Gilpin. 1991. Metapopulation Biology:
Ecology, Genetics, and Evolution. California: Academic
Press, San Diego.
Hensen, I. and K. Wesche. 2006. Relationships between popula-
tion size, genetic diversity and fitness components in the
rare plant Dictamnus albus in Central Germany. Biodivers.
Conserv. 15: 2249-2261.
Holsinger, K.E., P.O. Lewis, and D.K. Dey. 2002. A Bayesian
approach to inferring population structure from dominant
markers. Mol. Ecol. 11: 1157-1164.
Huang, F.P. 2001. Comm unity type s for the ha bitat ion of
Camellia sect. nitidissima in Fangcheng city. Guangxi
Forest. Sci. 30: 35-38 (in Chinese with English abstract).
Huang, P.J. and Q.L. Zhou. 1982. Karyotype study on Camellia
nitidissima. Guihaia 2: 15-16 (in Chinese with English
abstract).
Karron, J.D. 1991. P atterns of genetic variation and breeding
s ystems in rare plants . In D.A. Falk and K.E. Holsinger
(eds.), Genetics and Conservation of Rare Plants, Oxford
University Press, New York. pp. 87-98.
Lei, M. and P. Mutikainen. 2005. Population his tory, mating
system, and fitness variation in a perennial herb with a frag-
mented distribution. Conserv. Biol. 19: 349-356.
Li, Q., Z. Xu, and T. He. 2002. Ex situ genetic conservation
of endangered Vatica guangxiensis (Dipterocarpaceae) in
China. Biol. Conserv. 106: 151-156.
Liang, S.Y. 1993. Golden Camellia. China Forest Press, Beijing.
Mathiasen, P., A.E. Rovere, and A.C. Premoli. 2007. Genetic
s tructure and early effects of inbreeding in fragm ented
temperate forests of a self-incompatible tree, Embotbrium
coccineum. Conserv. Biol. 21: 232-240.
Mil ler, M.P. 1997. Tool s for Population Genetic Analys is.
Version 1.3. Department of Biological Science, Northern
Arizona University, Arizona, Flagstaff.
Nei, M. 1973. Analysis of gene diversity in subdivided
populations. Proc. Natl. Acad. Sci. USA 70: 3321-3323.
Nybom, H. 2004. Comparison of different nuclear DNA markers
for estimating intraspecific genetic diversity in plants. Mol.
Ecol. 13: 1143-1155.
Schaal, B.A., D.A. Hayworth, K.M. Olsen, J.T. Rauscher, and
W.A. S mith. 1998. P hylogeographic studies in plants:
problems and prospects. Mol. Ecol. 7: 465-474.
Schneide, S., D. Roessli, and L. Excoffier. 2000. Arlequin ver.
2.000, A Software for Population Genetics Data Analysis.
Genetics and Biometry Laboratory, University of Geneva,
Switzerland.
Su, Z.M. 1994. A preliminary study on the population ecology
of Camellia sect. nitidissima. Guangxi S ci. 1: 31-36 (in
Chinese with English abstract).
Tang, S., X. Bin, L. Wang, and Y. Zhong. 2006. Genetic diversity
and population structure of yellow camellia (Camellia
nitidissima) in China as reveale d by RAPD and AFL P
markers. Biochem. Genet. 44: 449-461.
Wolfe, A.D. and A. Liston. 1998. Contributions of PCR-Based
methods to plant systematics and evolutionary biology. In
D.E. Soltis, P.S. Soltis and J.J. Doyle (eds.), Plant Molecular
Systematics II, MA: Kluwer, Boston. pp. 43-86.
Wright, S. 1931. Evolution in Mendelian populations. Genetics
16: 97-159.
Ye, C.X. and Z.Y. Xu. 1992. A taxonomy of Camellia Sect.
Chrysantha Chang. Acta Sci. Nat. U. Sunyatseni. 31: 68-77
(in Chinese with English abstract).
Yeh, F.C., R.C. Yang, and T. Boyle. 1999. POPGENE 1.31,
Microsoft Windows-Based Freeware for Population Genetic
Analysis. University of Alberta, Edmonton, Canada.
Zhang, H.T. 1996. Diagnosis on the systematic development
of Theaceae. Acta Sci. Nat. U. Sunyatseni. 35: 77-83 (in
Chinese with English abstract).
Zhang, Z.X. and Q.B. Huang. 1984. A report on experiment
in graftage and cultivation of Camellia sect. nitidissima.
Guihaia 4: 65-70 (in Chinese with English abstract).
Zietkiewicz, E., A. Rafalski, and D. Labuda. 1994. Genome
fingerprinting by simple sequence repeat (SSR)-anchored
polymerase chain reaction amplification. Genomics 20:
176-183.
pg_0007
WEI et al. ”X Genetic structure of
Camellia nitidissima
153
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