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Journal of Heredity Advance Access originally published online on September 28, 2007
Journal of Heredity 2008 99(1):22-33; doi:10.1093/jhered/esm080
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© The American Genetic Association. 2007. All rights reserved. For permissions, please email: journals.permissions@oxfordjournals.org.

Population Genetic Variation and Structure of the Invasive Weed Mikania micrantha in Southern China: Consequences of Rapid Range Expansion

Ting Wang, Yingjuan Su, and Guopei Chen

From the Wuhan Institute of Botany, the Chinese Academy of Sciences, Wuhan, Hubei 430074, China (Wang and Chen); the School of Life Sciences, Sun Yat-sen University, Guangzhou, Guangdong 510275, China (Su and Chen); and the Department of Biology, Indiana University, Bloomington, IN 47405 (Su)

Address correspondence to Y. Su at the address above, or e-mail: suyj{at}mail.sysu.edu.cn

Invasive plants such as Mikania micrantha provide valuable opportunities for studying population genetic consequences of rapid range expansion. Twenty-eight populations of M. micrantha throughout its introduced range in southern China were examined by using intersimple sequence repeat markers. Population genetic parameters were estimated by Bayesian approaches as well as conventional methods. Bottleneck signature, multilocus linkage disequilibrium, character compatibility, and cluster analyses were conducted to assay the factors that may act to shape population variability. High levels of genetic variation and differentiation were detected in the introduced populations of M. micrantha. All populations experienced severe bottlenecks. Most of them demonstrated significant linkage disequilibrium and matrix compatibility. Populations were mainly clustered into 2 groups, and those from different regions intermingled in the unweighted pair group method with arithmetic mean (UPGMA) dendrogram. No geographical signature was found in the pattern of population genetic variation. This research indicates that during M. micrantha invasion, multiple introductions mitigated the loss of genetic variation associated with bottlenecks. Nonetheless, bottlenecks enhanced the population differentiation. Human-mediated long-distance dispersal events of seeds or propagules explain the lack of geographic structure in genetic variation. Although asexual reproduction is the predominant mating mode in M. micrantha, it has little effect on the population genetic composition.

Biological invasions are recognized as a leading threat to global biodiversity (Sala et al. 2000). Some invasive species cause severe economic loss in agriculture and forestry (Wilcove et al. 1998; Pimentel et al. 2000; Sakai et al. 2001; Bossdorf et al. 2005). However, invasions also provide significant opportunities to study genetic consequences of populations with expanding range (Sakai et al. 2001; Hassel et al. 2005). Generally, colonization of new areas involves considerable founder effects with genetic drift that reduce within-population genetic variation and increase genetic differentiation among populations (Husband and Barrett 1991; Novak and Welfley 1997; Amsellem et al. 2000). This is especially the case for selfing and apomictic weedy plant species (Husband and Barrett 1991; Amsellem et al. 2000; Walker et al. 2003). But exceptions, such as high genetic variation and low genetic differentiation (Jørgensen and Mauricio 2004; Refoufi and Esnault 2006), high genetic variation and high genetic differentiation (Meekins et al. 2001; Walker et al. 2003; Chapman et al. 2004; Durka et al. 2005), as well as low genetic variation and low genetic differentiation (Amsellem et al. 2000), have been recorded. Mechanisms proposed to explain the maintenance of genetic variation or depauperation of diversification in introduced regions include multiple introductions, admixture or hybridization of different source populations, and selection realignment (Carson 1989; Ellstrand and Schierenbeck 2000; Moody and Les 2002; Kolbe et al. 2004; Lindholm et al. 2005; Parisod et al. 2005).

From an applied perspective, the knowledge of population genetic structure of invasive plants is essential for improving the efficacy of biological control programs (Burdon and Marshall 1981; Chapman et al. 2004; Gaskin et al. 2005). Intraspecific genetic variation has been observed in plant defense to biological control agents (Jarosz and Burdon 1990; Bruckart et al. 2004). A mixture of both resistant and nonresistant genotypes within an invasion may hinder biological control efforts because plants resistant to the biological control agent may become predominant (Burdon et al. 1981, 1984). Moreover, analyses of molecular genetic variation can characterize the roles that local and long-distance dispersal events have played in invasions (Walker et al. 2003).

Mikania micrantha H.B.K. (Tribe Eupatorieae, Family Asteraceae), a perennial creeping vine commonly called "mile-a-minute," is one of the top 10 worst weeds in the world (Holm et al. 1977). It originates from tropical Central and South America (Kong et al. 2000) and has become a major pest of crops and forests across Asia and Africa. The earliest record of the species in the eastern hemisphere is from 1884 when it was cultivated at Hong Kong Zoological and Botanical Gardens (voucher number: HK14738) (Wang et al. 2003). Its naturalization in Hong Kong dates to at least 1919, and it is believed to have started to spread during the 1950–1960s (Wang et al. 2003). The earliest collection of M. micrantha in mainland China (voucher number: IBSC545255) is in 1984 at Yinhu, Shenzhen, Guangdong Province (Kong et al. 2000). By the late 1980s and early 1990s, the weed had spread over Guangdong, colonizing agricultural land, orchards, nurseries, lawns, mangroves, secondary forests, scrubland, waste ground, ponds, and seashores (Zan et al. 2000; Zhang et al. 2004). Once established, M. micrantha smothers and displaces native vegetation.

Mikania micrantha reproduces readily through both sexual and vegetative means (Swarmy and Ramakrishnan 1987; Zhang et al. 2004). It produces copious amounts of fine, fluffy seeds with mean seed production ranging from 23 673 to 52 616/0.25 m–2 (Zhang et al. 2003). Seeds are dispersed by wind or water; but the most efficient mechanism is to become attached to clothing, animals, and machinery. When reproducing vegetatively, M. micrantha produces shoots from small stem fragments and rosettes (Swarmy and Ramakrishnan 1987; Wen et al. 2000).

Intersimple sequence repeats (ISSR) have been used to characterize genetic diversity in plants (e.g., Tsumura et al. 1996; Camacho and Liston 2001; Deshpande et al. 2001; Barth et al. 2002; King et al. 2002; Meloni et al. 2006). The technique may provide a higher reproducibility of bands than some polymerase chain reaction (PCR)–generated markers such as randomly amplified polymorphic DNA (RAPD) (Nagaoka and Ogihara 1997; Wolfe et al. 1998). However, for population genetic studies, a major drawback of ISSR markers is their dominance (Zietkiewicz et al. 1994). To mitigate this problem, Holsinger et al. (2002), Holsinger and Wallace (2004) developed a Bayesian approach to partition genetic variation with data derived from dominant markers. Interestingly, it has also been reported that the Shannon diversity index is insensitive to the bias generated by the dominance of molecular markers in the assays of population genetic differentiation of plant species such as Gliricidia sepium (Dawson et al. 1995), Alliaria petiolata (Meekins et al. 2001), and Platanthera leucophaea (Holsinger et al. 2002).

Although some research has been conducted on ecophysiological aspects as well as eradication methods of M. micrantha (Hu and But 1994; Yang et al. 2003; Deng et al. 2004; Yang et al. 2005), comprehensive analyses of molecular genetic composition of introduced populations are lacking. Because all populations of M. micrantha in southern China are derived from recent colonization events, several hypotheses can be formulated that are testable with ISSR markers. First, if expansion of M. micrantha is a result of easily dispersed and sexually produced seeds, little genetic differentiation will occur among populations and the initial bottleneck event may hardly have an effect on population genetic diversity due to effective dispersals. Second, if independent introductions are frequent because of anthropogenic activities (e.g., intensive human-mediated transport), no association between geographical and genetic structure may be detected. Third, if sexually reproduced seeds are the main agent of dispersal, little linkage disequilibrium is expected among loci; alternatively, high linkage disequilibrium is expected if asexual reproduction is dominant.


   Materials and Methods
Top
 Materials and Methods
Results
 Discussion
 Funding
 References
 
Plant Material
Samples were collected from 28 populations of M. micrantha throughout its introduced range in southern China (Figure 1 and Table 1). The physical boundaries of each population were well delineated, and most populations were separated by more than 20 km. A population (Mikania cordata from Xinglong [MCXL]) of another Mikania species, Mikania cordata, was also sampled in Xinglong, Hainan Province, China. This taxon is primarily distributed in tropical Asia and closely related to M. micrantha (Kong et al. 2000; Wang et al. 2001).


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  		Table 1. Mikania micrantha populations evaluated from 6 regions in southern China. The sample size, invasion year, and altitude are listed

 


Figure 1
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  		Figure 1. Map of populations of Mikania micrantha sampled in the introduced range of southern China.

 
Twelve to 19 plants (intervals at ≥ 10 m) were sampled from each population (Table 1). For each plant, approximately 3.0 g of fresh leaf tissue was collected using silica gel to dry and preserve samples (Meekins et al. 2001). Voucher specimens (CGP1–409) have been deposited at the herbarium of Sun Yat-sen University, Guangzhou, China.

DNA Extraction
Total genomic DNA was extracted from ground tissue following the modified CTAB protocol (Su et al. 2005). DNA concentration and purity were determined by measuring Ultraviolet (UV) absorption using a Pharmacia 2000 UV/Visible Spectrophotometer. The quality of DNA was determined by 0.8% agarose gel electrophoresis.

ISSR Amplification and Examination
PCR amplification of ISSR loci was carried out in 20 µl volumes containing 50 mM KCl, 10 mM Tris–HCl (pH 9.0), 0.1% Triton X-100, 2.0 mM MgCl2, 0.2 mM each deoxynucleoside triphosphate, 1 U Taq DNA polymerase, 0.3 µM primer, 30 ng genomic DNA, and DNA-free water. Each reaction mixture was overlaid with 20 µl of PCR grade paraffin oil. PCR was performed in an MJ-Research PTC-100TM Peltier thermal cycler. The thermocycling program was set for 5 min at 94 °C, 40 cycles of 40 s at 94 °C, 35 s at 53 °C, 70 s at 72 °C, and 5 min at 72 °C. Negative controls where all reagents but DNA were added to the reaction mix were included with each experiment in order to verify the absence of contamination. Genotyping was performed with 24 ISSR primers (Table 2) that were selected based on the results of initial screening of 80 ISSR primers (UBC ISSR Primers 802, 805, 807–881, 885, 886, and 888, University of British Columbia, Vancouver, Canada) against a set of representative samples of M. micrantha. When amplifications for the whole set of samples were conducted, one reaction mix per primer was prepared for all samples to reduce possible inconsistencies among different amplification runs. Duplicate reactions were run to determine the reproducibility of banding patterns. In the few cases where the 2 replicates were not identical, PCR reactions were repeated at least 3 times to confirm the banding pattern. Amplification products were separated by electrophoresis in 1.8% agarose gels containing ethidium bromide and then photographed under UV light.


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  		Table 2. Primers used in ISSR analyses of Mikania micrantha (R = A, G; Y = C, T)

 
Data Analysis
Data were scored according to the presence and absence of bands, and only those bands that are clear and reproducible were used to construct data matrices. Percentage of polymorphic loci, Nei's (1973) gene diversity, and coefficient of gene differentiation, GST, were computed with POPGEN32 software (Yeh and Yang 1999). An unweighted pair group method with arithmetic mean (UPGMA) dendrogram based on Nei's (1978) unbiased genetic distances was constructed to illustrate relationships among populations. Shannon's index of phenotypic diversity was calculated as S = –{sum}pi ln pi, where pi is the frequency of a given ISSR band in the population (Lewontin 1973). In line with Allnutt et al. (1999), we here rather denote Shannon's measure as "S" than "H" in order to avoid confusion with other measures of diversity such as heterozygosity. S was calculated for 2 levels: the average diversity within population (Spop) and the diversity within species (Ssp). Its 95% confidence interval was estimated by a sampled randomization test (Sokal and Rohlf 2003).

Holsinger et al. (2002) proposed a Bayesian approach to infer allele frequency and population structure from banding data of dominant markers. Its parameters, f and {theta}B, are analogues to the inbreeding coefficient (FIS) and the fixation index (FST) of F-statistics (Wright 1951), respectively. The posterior distributions of f and {theta}B were approximated numerically through Markov Chain Monte Carlo methods by running HICKORY v1.0 (Holsinger et al. 2002). The "f-free" model option was used due to its lower deviance information criterion and pD (measure of model complexity) values than for other models. Point estimates of {theta}B as well as their 95% credible intervals were achieved with a burn-in of 50 000 iterations and a sampling run of 250 000 iterations from which every 50th sample is retained for posterior calculations. Three runs were conducted to ensure that the results were consistent. In order to report allele frequency at each locus, a "Set reportFrequencies" statement was specified in the hickory block of data files. Alleles were considered rare if their frequencies were ≤0.05 in the sampled populations (Marshall and Brown 1975).

Linkage disequilibrium and character compatibility analysis were carried out to assess whether marker distributions originated from sexual or asexual reproduction in the introduced populations. Multilocus linkage disequilibrium was estimated using the index of association IA (Brown et al. 1980; Maynard Smith et al. 1993; Haubold et al. 1998) and its modified measure Formula d(Agapow and Burt 2001) to remove the dependency of sample size. The program Multilocus v1.2 (http://www.bio.ic.ac.uk/evolve/software/multilocus/) was used to calculate statistics and test their significance by randomization. With compatibility methods, for a pair of biallelic markers, no more than 3 of the 4 possible character combinations should be observed. Once all 4 character combinations are present, this means an incompatibility and will be explained by recombination. Thus, the sum of incompatible counts over all pairwise comparisons can be used as a measure of recombination (Mes 1998; van der Hulst et al. 2000; Wilkinson 2001). In this research, a summary statistic, the incompatibility excess ratio (IER) (Wilkinson 2001) was estimated based on comparison of the observed incompatibility count for the original data and mean incompatibility count for randomly permuted data. Asexual reproduction is expected to cause none or a small fraction of incompatible loci (Chapman et al. 2004; Hassel et al. 2005).

The program BOTTLENECK (Luikart and Cornuet 1999) was used to test whether populations have recently passed through a bottleneck. Both the stepwise mutation model (SMM) and the infinite allele model (IAM) were run to calculate the heterozygosity (Heq) expected at mutation–drift equilibrium because ISSR markers may evolve under a true model intermediate between them (Di Rienzo et al. 1994; Godwin et al. 1997; Hassel et al. 2005). The sign test was conducted to determine the significance of heterozygosity excess (Cornuet and Luikart 1996).

A Euclidean squared distance matrix was calculated in ARLEQUIN 2.0 (Schneider et al. 2000) and used as the input file for an analysis of molecular variance (AMOVA) described by Excoffier et al. (1992). In this analysis, the total variance in the ISSR data set was partitioned into regional, among-population, and within-population components. Using the same software, a Mantel test (Mantel 1967) was conducted to determine the correlation between the matrix of pairwise {theta}B estimates and the matrix of geographic distances.


   Results
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 Materials and Methods
 Results
Discussion
 Funding
 References
 
Population Genetic Variation
A pilot experiment was performed to evaluate primer suitability. From an initial screening of 80 primers, 24 (Table 2) were identified that produce clear and reproducible banding patterns. Only reproducible bands obtained from the selected primers were scored to construct data matrices for subsequent statistical analyses. Figure 2 presented examples of ISSR profiles produced with primer UBC817.


Figure 2
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  		Figure 2. ISSR patterns produced with primer UBC817 for representative individuals from 28 introduced populations of Mikania micrantha and a population of Mikania cordata. M = 100 bp DNA ladder. Population codes as indicated in Table 1.

 
The 24 primers generated 209 bands, and each detected polymorphic loci, with 73.14% of polymorphic loci overall (Table 3). The number of bands per primer ranged from 2 to 15 with an average of 8.71 bands/primer. No identical ISSR pattern was found to be shared among sampled individuals.


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  		Table 3. Summary statistics revealed by using 24 ISSR primers to detect populations of Mikania micrantha

 
At the regional scale, all the genetic diversity statistics consistently indicated that Hong Kong and Neilingding maintained the highest level of variation (Table 3). As for regions of Hong Kong, Shenzhen, Macao, and Neilingding, each contained populations like HK84, HK87, SZ35, SZ64, SZ72, MA105, MA106, and NLD10 that possessed considerably lower amounts of genetic variation than the others in the same region (Table 3).

Allele Frequency Distribution
In total, 22 alleles were identified as rare at the species level. Across regions, 16, 11, and 8 rare alleles were detected in Hong Kong, Neilingding, and Shenzhen, respectively; whereas no rare alleles were found in Zhuhai, Dongguan, and Macao. Populations in Neilingding and Macao tended to possess more rare alleles. Specifically, population NLD10 possessed the highest number of rare alleles (51), NLD30 and MA106 the second (50), NLD1 and NLD31 the third (47), and NLD26 and MA105 the fourth (46). In contrast, population ZH43 possessed the least (Table 4). These results indicated that certain alleles were rare in certain populations, but not in others.


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  		Table 4. Number of rare alleles and parameters derived from linkage disequilibrium and character compatibility analysis for Mikania micrantha

 
Linkage Disequilibrium and Character Compatibility
By testing the index of association (IA and Formula d) and IER, significant linkage disequilibrium and considerable matrix compatibility were observed within each region (Table 4). At the population scale, significant linkage disequilibrium and matrix compatibility were likewise detected in populations NLD1, NLD26, NLD31, SZ34, SZ35, SZ77, ZH43, ZH50, HK81, HK82, HK84, HK85, HK87, MA101, MA106, and DG91; but not in NLD10, SZ75, HK89, and HK90 (Table 4). For the remaining populations, either significant linkage disequilibrium or matrix incompatibility was obtained.

Bottleneck Signature Test
Our data demonstrate that M. micrantha has gone through severe bottlenecks across all the populations and regions. Each data set revealed a heterozygosity excess/deficiency ratio that significantly deviated from the expected ratio (1:1) at mutation–drift equilibrium when either the SMM or the IAM was assumed (P < 0.05, data not shown). Moreover, a significant bottleneck signature was also detected over the whole range (Figure 3).


Figure 3
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  		Figure 3. Heterozygosity excess at each of 179 polymorphic loci in Mikania micrantha. The horizontal dashed line represents the heterozygosity excess expected at equilibrium. Loci with a heterozygosity excess scatter above the dashed line. {diamondsuit}IMM, {square}SMM.

 
Population Genetic Differentiation and Relationship
A run of f-free analysis in Hickory yielded an overall estimate for {theta}B = 0.2797 (95% credible interval: 0.2540–0.3038). For comparisons, the degree of population genetic differentiation was also quantified by other parameters. AMOVA analysis indicated that {Phi}ST = 0.3226; 67.74% of the variation was partitioned within populations, 23.83% was attributed to differences among populations within regions, and only 8.43% of the variation was due to regional differences (all 3 hierarchical levels were significant with P < 0.001) (Table 5). When individual pairs of populations were compared, all pairwise {Phi}ST values derived from AMOVA were significant (P < 0.001) except between populations DG91 and DG92 (P = 0.100), highlighting remarkable differences between populations. Meanwhile, values of GST (Nei 1973) and the component of genetic diversity among populations (1 – Spop/Ssp) based on Shannon's index were 0.4422 and 0.2911, respectively.


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  		Table 5. AMOVA analysis of ISSR variation for 28 Mikania micrantha populations in 6 regions: Hong Kong, Shenzhen, Zhuhai, Macao, Neilingding, and Dongguan

 
Pairwise estimates of {theta}B between populations showed nonsignificant associations with geographical distances (r = 0.139, P = 0.123) for the full data set. Similar results were derived from the data sets of regions. Thus, Mantel tests failed to detect any evidence of "isolation by distance" (Wright 1943) at either the regional or the entire range level.

UPGMA analysis (Figure 4) revealed that 28 populations mainly fell into 2 groups: Group I was composed of HK84, HK87, SZ35, SZ64, SZ72, NLD10, MA105, and MA106, whereas Group II consisted of the remaining populations. Populations from different regions intermingled in the dendrogram, except for Zhuhai and Dongguan, suggesting a lack of geographical pattern.


Figure 4
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  		Figure 4. UPGMA dendrogram, derived from Nei's (1978) unbiased genetic distances, showing the relationships among 28 examined populations of Mikania micrantha. A population of Mikania cordata MCXL was used as the root. Branch lengths are proportional to genetic distances (see scale at the bottom of figure).

 

   Discussion
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 Materials and Methods
 Results
 Discussion
Funding
 References
 
Compared with population genetic estimates based on ISSR analyses of other invasive weed species (Table 6), substantial amounts of intraspecific and within-population variation were revealed across the introduced range of M. micrantha in southern China (Table 3). The findings are striking considering all the populations have passed through severe bottlenecks. Kolbe et al. (2004) suggest that high genetic variation in introduced populations can be created via multiple introductions by transforming among-population variation from different geographical sources into within-population variation. Here, multiple introductions are inferred among populations of M. micrantha. As shown with cluster analysis, closely related populations often are from different geographical locations (Figure 4), whereas individuals from the same location do not group together (data not shown). Therefore, it is reasonable to deduce that multiple introductions have played a role in the spread of M. micrantha. In addition, M. micrantha populations that are genetically more similar appear to maintain equivalent level of genetic variation. For example, populations HK84, HK87, SZ35, SZ64, SZ72, NLD10, MA105, and MA106 are all members of Group I, and they unvaryingly possess less variation than those populations that constitute Group II (Figure 4 and Table 3). The result further indicates that levels of population genetic variation are affected by introduced individuals.


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  		Table 6. Percentage of polymorphic loci (PL), Shannon's diversity within species (Ssp), Nei's (1973) total gene diversity (HT), GST, and {Phi}ST obtained from the introduced populations of different invasive weed species based on ISSR data

 
Holm et al. (1977) suggest that M. micrantha mainly propagates by seeds, but others report that its local spread results mostly from vegetative propagation (Swarmy and Ramakrishnan 1987; Wen et al. 2000). We find that significant linkage disequilibrium and locus compatibility were identified in a majority (16 out of 28) of the M. micrantha populations (Table 4), suggesting that asexual reproduction is the predominant mating system in the populations. This is in accordance with the findings that most invasive plants are selfing or asexual (Price and Jain 1981; Husband and Barrett 1991; Amsellem et al. 2001), and some plants can even switch to higher levels of inbreeding or vegetative reproduction during their invasions (Barrett and Richardson 1986; Barrett and Husband 1990; Pellegrin and Hauber 1999; Amsellem et al. 2001). However, in 4 other populations NLD10, SZ75, HK89, and HK90, M. micrantha indeed reproduces sexually and generates substantial recombinations (Table 4). And contrary to general expectation that sexual reproduction tends to increase population genetic variation (Godt and Hamrick 1991; Hamrick and Godt 1996; Pappert et al. 2000), these 4 populations possess either less or similar degree of genetic variation to those with predominantly asexual reproduction in the same region (Table 3). Reproductive system seems not to have been a determining factor in the level of population genetic variation during the range expansion of M. micrantha.

A relatively high degree of genetic differentiation was detected among introduced populations of M. micrantha in comparison with ISSR inferences from other invasive weeds (Table 6), which was further highlighted by the findings that pairwise {Phi}ST values between populations were all significant (P < 0.001) except between DG91 and DG92. Such a population genetic structure is not unexpected in view of each population having experienced a severe bottleneck. The rationale behind the bottleneck signature test is that a population that has suffered a recent bottleneck will transiently disrupt the mutation–drift equilibrium across loci and generate a heterozygosity excess (Luikart and Cornuet 1999). Our results show that all the sampled populations and regions exhibit a significant bottleneck pattern under both the SMM and the IAM. Generally, bottlenecks can enhance genetic differentiation among newly established populations by causing rapid losses of rare alleles as well as significant changes in allelic frequencies (Hedrick 1999, 2000). Besides M. micrantha, high genetic differentiations have also been recorded in the populations of other invasive weeds such as Heracleum mantegazzianum (Walker et al. 2003), Hieracium lepidulum (Chapman et al. 2004), and A. petiolata (Durka et al. 2005). In those studies, effects of multiple independent introductions are invoked to account for the strong population genetic structure. Similar reasoning may apply to M. micrantha. Additionally, given the results that 16 populations are dominant for asexual reproduction, whereas 4 are prevalent for sexual reproduction, impact of mating systems on population differentiation were further examined. AMOVA analyses, using the data sets established from sexually reproduced and asexually reproduced populations separately, demonstrated that equivalent amounts (28.71% and 29.53%) of among-population variation are partitioned (data not presented).

At either regional or entire range scale, no geographical signature is revealed in the pattern of ISSR variation among introduced populations of M. micrantha. The result may be mainly attributed to long-distance dispersals of seeds or propagules mediated by humans. During the past 2 decades, business trade, transport, and tourism have dramatically increased in the area including the Pearl River Delta, Hong Kong, and Macao. It has been noticed that intensive economic activities do assist the expansion of M. micrantha in the region (Zhang et al. 2004). Nonanthropogenic mechanisms also play a role in generating the nongeographical nature of population divergence. Typhoons, tornadoes, and thunderstorms occur in the spring in the coastal area of Guangdong Province, precisely at the time that fruits of M. micrantha are maturing and seeds are being released (Hu and But 1994). Because M. micrantha seeds are small and light (8.80–10.20 x 10–5 g) (Zhang et al. 2003), the violent winds are potentially able to uplift and transport them several hundred kilometers (Zhou and Huang 2001), facilitating gene flow among distant populations. And finally, repeated or secondary introductions induced by both mechanisms would further complicate the geographical consequences of population genetic variation.

F-statistics developed by Wright (1951, 1965) are widely used for describing population genetic structure. Subsequently, Nei (1973, 1977) has improved Wright's method in 2 respects: making it independent of the number of alleles at a locus and of the pattern of evolutionary forces such as mutation, selection, and migration (Nei 1973). Nevertheless, in the case of only 2 alleles at a locus, Nei's coefficient of gene differentiation GST becomes identical with FST (Nei 1973; Nei and Kumar 2000). Thus, values of GST and FST should not be different when derived from our ISSR data. Another type of F-statistic analogues, {Phi}-statistics, has been established within an AMOVA framework (Excoffier et al. 1992; Stewart and Excoffier 1996). In the present research, calculated from ISSR data of M. micrantha populations, Nei's (1973) method and AMOVA give GST = 0.4422 and {Phi}ST = 0.3226, respectively. Both are substantially larger than Bayesian estimate {theta}B = 0.2797 (95% credible interval: 0.2540–0.3038). However, when the data were analyzed phenetically, Shannon's index partitioned 29.11% of the genetic diversity among populations, which is consistent with {theta}B estimate. This study provides further evidence that Shannon diversity is insensitive to the skewing effects caused by the dominance of molecular markers, such as ISSR and RAPD (Dawson et al. 1995; Meekins et al. 2001; Holsinger et al. 2002).


   Funding
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 Materials and Methods
 Results
 Discussion
 Funding
References
 
Key Pilot Project of Department of Science and Technology of Guangdong Province, China (2004B33301020); the Scientific Foundation for the Returned Overseas Chinese Scholars, State Education Ministry of China ([2005]546); and the "100 Talent Project" of the Chinese Academy of Sciences (05052903).


   Acknowledgments
 
We thank Dr Troy E. Wood at the Department of Biology, Indiana University for advice and revision of English.


   Footnotes
 
Corresponding Editor: Lisa J Rowland

Received May 16, 2007
Accepted August 28, 2007


   References
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 Materials and Methods
 Results
 Discussion
 Funding
 References
 

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