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. 2019 Apr 18;9(9):5362–5371. doi: 10.1002/ece3.5127

Genetic diversity and genetic structure of Decalobanthus boisianus in Hainan Island, China

Huan Jiang 1,2, Wenxing Long 1,2,✉, Hui Zhang 1,2,✉, Chengneng Mi 1,2, Tao Zhou 1,2, Zongzhu Chen 3
PMCID: PMC6509374  PMID: 31110685

Abstract

Decalobanthus boisianus is a native plant of Hainan Island, China, which has caused considerable damage to tropical forest ecosystems in recent decades. Understanding the genetic diversity and structure of this species can facilitate uncovering the molecular mechanism of its invasive ability. Here, we collected 77 individuals of D. boisianus spanning 8 distribution areas with a gradient of human disturbance intensity (i.e., low, moderate, and high disturbance intensity groups) to assess patterns of genetic diversity and structure using inter simple sequence repeat (ISSR) markers. We found that a total of 220 loci were scored with 13 primers using ISSR methods, and that 198 loci were polymorphic. The genetic diversity of D. boisianus among these eight forests decreased with increasing human disturbance intensity. Over 70% of the total genetic variation was present within populations, while less than 30% of variation was found among populations. There was a high gene flow (1.27) among them due to a lack of effective geographic barriers. The mean Nei's genetic distance of D. boisianus populations was found to be relatively small (i.e., 0.07), and the average genetic similarity of the eight populations was high (i.e., 0.93). Our findings indicate that the genetic diversity of D. boisianus correlated to human disturbance density, and that D. boisianus populations in Hainan Island have frequent gene exchange. We suggest that reduce deforestation to decrease human disturbance may be a good way to prevent the invasion of D. boisianus.

Keywords: gene flow, genetic diversity and structure, human disturbance intensity, sexual and clonal reproduction

1. INTRODUCTION

Invasive species are a major problem across the globe and pose a multitude of threats to natural ecosystems (Carboneras et al., 2017). Despite massive efforts to understand the factors influencing invasion potential of introduced species, we still lack a predictive framework for determining which species are most likely to become invasive. This may be due to the fact that most research on this topic has focused on life‐history traits and not on genetic diversity. Recently, many studies have demonstrated that genetic diversity of invasive plant species leads to their strong ability to adapt to environmental change and facilitates their capacity to spread to novel habitats (Bozkurt, Muth, Parzies, & Haussmann, 2015; Prentis, Wilson, Dormontt, Richardson, & Lowe, 2008; Templeton, 1994). Therefore, it is essential to investigate the genetic diversity and structures of invasive plants to better understand how these plants successfully invade and cause ecological damages.

Environmental pressure is seen as an important factor accounting for plant reproductive strategies, which can further influence levels of genetic diversity in the species (Cook, 1985; Eriksson, 1997; Philbrick & Les, 1996; Sinclair et al., 2016). For example, sexual reproduction typically increases genetic diversity in a population. In contrast, clonal reproduction allows species to rapidly colonize available habitats, but often leads to a decline in genetic diversity (Ellstrand & Roose, 1987; Hamrick, Linhart, & Mitton, 1979; Schmid, Bazzaz, & Weiner, 1995). Several studies have showed that environmental pressures often have negative consequences for genetic diversity. Rusterholz, Kissling, and Baur (2009) demonstrated that soil disturbance induced by human trampling reduced the frequency of sexual reproduction for Anemone nemorosa populations, resulting in lower levels of genetic diversity for these populations. Likewise, Aveliina et al. (2009) demonstrated that the genetic diversity of Briza media was negatively associated with environmental pressures caused by high population densities of humans.

Decalobanthus boisianus (Gagnep.) A. R. Simões & Staples is a liana that distributed in Hainan Island and Guangzhou City. It also has three varieties including Decalobanthus boisianus var. boisiana, Decalobanthus boisianus var. fulvopilosa, and Decalobanthus boisianus var. sumatrana, which distributed in Yunan and Guangxi Province of China, as well as Laos, Vietnam, Malaysia, Kalimantan Island, and Sumatra Island (Flora of China Editorial board, 1995; Wang et al., 2005; Wang, Peng, Li, & Zhou, 2009; Staples, 2010). This species has recently moved from genus Merremia Hall. f. to Decalobanthus Ooststr since the former now only included polyphyletic species because of the weak support for monophyly and strong support for polyphyly of this genus (Simões & Staples, 2017). Therefore, D. boisianus is more closely related to species such as Decalobanthus peltatus (L.) A. R. Simões & Staples which is also a harmful weeds, Decalobanthus borneensis (Merr.) Simões & Staples, Decalobanthus eberhardtii (Gagnep.) Simões & Staples, and Decalobanthus pacificus (Ooststr.) Simões & Staples, ect. D. boisianus is adapted to a wide range of ecological conditions, due to its ability to undergo both sexual and clonal reproduction (Lian et al., 2007; Liu, 2007; Wang et al., 2009; Wu, Liang, Chen, Li, & Cao, 2007). A number of studies assumed that viable seeds of the species can be transported over streams (Wu et al., 2007; Wang et al., 2009), which helps D. boisianus spread long distance. The species is thus characterized by rapid growth and a strong competitive ability (Huang et al., 2015), which allow it to easily invade plantation areas, shrublands, and secondary forests with low canopy density (Wang et al., 2009; Huang et al., 2015), covering more than 2000 ha areas in Hainan Island. After invasion, it often kills a large number of trees and understory plants with low canopy coverage (Huang et al., 2013). Although researchers suggest that D. boisianus can be taken advantage and used for vegetation recovery in barren mountains, as well as leaves feeding livestocks (Sun, Shen, Wan, & Xie, 2006), it has been listed as a major forest harmful pest in China due to the serious damage to secondary forests that the species causes (State Forestry Administration, China).

In this study, we explored genetic diversity and structures of D. boisianus in eight Nature Reserves in Hainan Island. According to field surveys and interviews with local residents, we found that D. boisianus distributed in areas with relatively high human disturbance intensity. Human disturbance intensity has been proved to affect genetic diversity of plant species (Aveliina et al., 2009; Ledo & Schnitzer, 2014; Rusterholz et al., 2009). Increases in human disturbance intensity across the eight distributed areas of D. boisianus likely led to a decrease in its genetic diversity. We thus hypothesized that genetic diversity of D. boisianus was high in areas with the low human disturbance intensity, and vice versa.

2. MATERIALS AND METHODS

2.1. Sample collection

Samples of D. boisianus were collected from eight forest sites in Hainan Island. A total of 8–10 individuals were randomly selected in each forest site, with at least 100 m intervals between adjacent individuals to reduce possibility of sampling clones. For each individual, three to four fresh leaves were collected and placed in a zip‐lock plastic bag with 20 g of silica gel. In total, 77 individuals from the eight populations were collected.

The eight forests are located in Wuzhishan National Nature Reserve (WZS), Bawangling National Nature Reserve (BWL), Yinggeling National Nature Reserve (YGL), Diaoluoshan National Nature Reserve (DLS), Jianfengling National Nature Reserve (JFL), Limushan Nature Reserve (LMS), Baishiling Nature Reserve (BSL), and Ganshiling Nature Reserve (GSL) (Figure 1). We took the proportion of natural primary forest area occupying the whole land area in each region as a measure of the degree of human disturbance, and assumed that the greater proportion of natural primary forest means the smaller degree of human disturbance, and vice versa (FAO, 2005 2005; Sabatini et al., 2018) (Table 1). In light of the human disturbance intensity, we categorized D. boisianus in these eight forests into three groups, including low disturbance intensity group (WZS), moderate disturbance intensity group (YGL, BWL, JFL, and DLS), and high disturbance intensity group (LMS, BSL, and GSL).

Figure 1.

Figure 1

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Distributions of sampling sites of eight populations of Decalobanthus boisianus in Hainan Island, China. BSL: population sampled from Baishiling Nature Reserve; BWL: population sampled from Bawangling National Nature Reserve; DLS: population sampled from Diaoluoshan National Nature Reserve; GSL: population sampled from Ganshiling Nature Reserve; JFL: population sampled from Jianfengling National Nature Reserve; LMS: population sampled from Limushan Nature Reserve; WZS: population sampled from Wuzhishan National Nature Reserve; YGL: population sampled from Yinggeling National Nature Reserve

Table 1.

Site conditions of the eight Decalobanthus boisianus populations

Group Code Population Sample size Longitude (°E) Latitude (°N) Altitude (m) Proportion of natural primary forests (%)
A WZS Wuzhishan National Nature Reserve, Wuzhishan County 10 109°37′–109°41′ 18°43′–18°54′ 300–800 54.20
YGL Yinggeling National Nature Reserve, Baisha County 10 109°21′–109°24′ 19°01′–19°04′ 300–500 14.10
BWL Bawangling National Nature Reserve, Changjiang County 10 109°02′–109°05′ 19°07′–19°11′ 150–600 13.50
B JFL Jianfengling National Nature Reserve, Ledong County 10 108°47′–108°49′ 18°40′–18°43′ 200–650 18.50
DLS Diaoluoshan National Nature Reserve, Lingshui County 10 109°53′–109°58′ 18°43′–18°52′ 100–600 12.60
LMS Limushan Nature Reserve, Qiongzhong County 8 109°42′–109°43′ 19°09′–19°10′ 500–750 0
C GSL Ganshiling Nature Reserve, Sanya City 9 109°38′–109°40′ 18°22′–18°23′ 100–300 0
BSL Baishiling Nature Reserve, Qionghai County 10 110°22′–110°23′ 19°09′–19°10′ 100–300 0
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2.2. DNA extraction and PCR amplification

DNA was extracted from our 77 samples using the Plant DNA Isolation Kit (Foregene Co., Ltd., Chengdu, China). We followed the manufacturer's protocol using 25–30 mg of dried leaf material. DNA quality and quantity were determined visually by comparisons with the DNA marker DL2000 on 1.0% (W/V) agarose gel electrophoresis. Samples were then stored at −20°C prior to PCR amplification.

A set of 100 ISSR primers was synthesized by SinoGenoMax Co., Ltd. according to the sequences obtained from the University of British Columbia (Biotechnology Laboratory, University of British Columbia, primer set #9: http://www.biotech.ubc.ca/services/naps/primers/Primers.pdf). An initial experiment was performed to determine the suitable primer and reaction conditions. One sample randomly selected from each eight D. boisianus populations to test the preliminary number of polymorphic loci with 100 primers and to optimize the reaction and amplification procedure for PCR. Finally, we obtained optimal reaction and amplification procedures as well as 13 primers that produced a high number of variable and readable loci (Table 2).

Table 2.

Primers selected from the UBC (University of British Columbia) used for ISSR amplification

Primers Sequence Annealing temperature (°C) Fragment size (bp) Loci number Polymorphic loci number Proportion of polymorphic loci (%)
UBC825 (AC)8T 52 200–1,300 15 13 87
UBC826 (AC)8C 52 200–1,500 19 18 95
UBC827 (AC)8G 52 150–1,300 19 19 100
UBC836 (AG)8YA 52 150–1,800 17 13 76
UBC841 (GA)8YC 52 150–1,200 16 12 75
UBC842 (GA)8YG 52 150–1,200 17 15 88
UBC849 (GT)8YA 52 200–1,800 12 12 100
UBC851 (GA)8YG 52 300–1,800 17 15 88
UBC856 (AC)8YA 54 200–1,300 18 14 78
UBC880 (GGAGA)3 54 150–1,300 19 15 79
UBC888 BDB(CA)7 54 150–1,100 17 15 88
UBC891 HVH(TG)7 54 200–1,400 19 15 79
UBC899 CAT(GT)3CATTGTTCCA 54 200–1,100 15 15 100
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The PCR amplification was performed using the GeneAmp PCR System 9700 (Applied Biosystems, Carlsbad, CA, USA) in 20 μl reaction volumes containing 2 μl of DNA (50 ng/μl), 2 μl of primer (10 μM), 6 μl of ddH2O, and 10 μl of 1X Taq‐Plus PCR Forest Mix (included 0.1 U/μl Taq‐Plus DNA Polymerase Forest Reaction Buffer, 1.5 mM MgCl2, 200 μM of each dNTP). Polymerase chain reaction started with an initial activation step at 94°C for 4 min, followed by 45 cycles of denaturation at 94°C for 45 s, annealing at 52–54°C for 50 s (depending on primer, Table 2), extension at 72°C for 60 s, and then a final extension at 72°C for 6 min, followed by cooling at 4°C until recovery of the samples (Table 2).

The amplified products were separated on a 1.5% (W/V) agarose gel in 1× TAE buffer staining by GoldView (Beijing Solarbio Science & Technology Co., Ltd, Beijing, China) with a setup of 100V, 200 mA and 50 min and then visualized and photographed under ultraviolet light. A 2000 bp DNA ladder (Real times Biotechnology Co. Ltd., Beijing, China) was used to estimate the molecular weights in the Alphalmager—2200 UV Transilluminator (NatureGene Corp., Beijing, China).

2.3. Data analysis

Only bands that were clear and reproducible were used to construct data matrices. The amplified bands were scored as presence (1) or absence (0) of a particular band for each primer. These data were then used to assemble the data matrix of ISSR phenotypes.

2.4. The genetic diversity of the eight D. boisianus populations

We calculated the proportion of polymorphic loci (PPL), Shannon's diversity index (I), Nei's gene index (H), the observed number of alleles (Na), and the effective number of alleles (Ne) to assess levels of genetic diversity among our populations using the POPGENE program v. 1.32 (Francis, Rong, & Boyle, 1999). The PPL is an important indicator of genetic diversity and of the adaptability of populations to a particular environment. Shannon's index is based on the band phenotypic frequency and is used to estimate the genetic diversity within and between populations according to King and Schaal's method (King & Schaal, 1989). H is an index to reflect the gene diversity based on Hardy–Weinberg hypothesis (Nei, 1972). Other indices such as Na and Ne indicate the observed and effective numbers of alleles that are maintained in the populations (Johnson, 1974). Here, we compared the differences in genetic diversity of the eight D. boisianus populations across different human disturbance intensity using ANOVA analysis.

2.5. The genetic structure of the eight D. boisianus populations

Genetic differentiation among population (Gst) represents the portion of the total genetic diversity found among populations (Nei, 1972), and the number of migrants (gene flow, Nm) measures the degree of genetic differentiation among populations (Wright, 1950). Here, Gst, Nm, total genetic diversity (Ht), and gene diversity within populations (Hs) were used to determine the genetic differentiation among the eight populations of D. boisianus. A matrix of genetic similarity and Nei's genetic distances were used to depict genetic relationship among the eight D. boisianus populations (Nei, 1972). Populations with high genetic similarity and low Nei's genetic distances value indicate a close genetic relationship. All parameters were calculated using the POPGENE program v. 1.32 (Francis et al., 1999).

We also explored spatial structures of D. boisianus with a Bayesian model‐based cluster analysis, using the STRUCTURE program version 2.3.4 (Pritchard, Stephens, & Donnelly, 2000) and calculated the appropriate number of clusters of populations (K) (Evanno, Rengaut, & Gouget, 2005). Groups were chosen that best fit the genetic variability observed in the dataset, irrespective of the number of populations sampled (Andreakis, Kooistra, & Procaccini, 2009). After initial pilot runs of variable burn‐in and run‐length, 20 independent runs were performed at K = 2–8 with 10,000 MCMC repetitions and a burn‐in period of 10,000 iterations, using no prior information and assuming correlated allele frequencies and admixture model in this study. The STRUCTURE output was further interpreted by STRUCTURE HARVESTE (Earl & VonHoldt, 2012). The CLUMPP version 1.1 (Jakobsson & Rosenberg, 2007) were used with greedy algorithms, with 1,000 random input orders and 1,000 repeats to calculate the average pairwise similarity of runs. The clustered output was visualized using the software Distruct version 1.1 (Rosenberg, 2004). Finally, we conducted cluster analysis for the eight populations with the MEGA v.10.0.1 (Kumar, Stecher, Li, Knyaz, & Tamura, 2018) based on the Nei's genetic distances and bootstrap analysis with 5,000 replications using the unweighted pair‐group method of averages (UPGMA).

Geographic distances (in kilometers) among populations were estimated by using toolbox in ArcGIS 10.3 (Esri: California, CA, USA) according to the coordinate (the longitude and latitude) of each population. A Mantel test was performed to assess isolation‐by‐distance with 1,000 random permutations, to test the significance of the relationship between ɸst and geographic distances. The distribution of whole genetic diversity was estimated using the molecular variance (AMOVA), taking populations and individuals as different levels. The significance of ɸst genetic differentiation was assessed with 1,000 random permutations. The principal coordinate analysis (PCoA) was carried out for the genetic relationships among populations. These analyses above (Mantel test, AMOVA, and PCoA) were carried out using the GenALEx6.5 program (Peakall & Smouse, 2012).

3. RESULTS

3.1. PCR amplification

A total of 220 unique loci ranging in size from 150 to 1800 bp were scored from ISSR marker products. From these, 198 (90.00%) were polymorphic (Table 3). A mean of 18 loci was generated per primer, in which the number of loci varied from 13 to 21. The UBC827, UBC849, and UBC899 primers had the highest proportion of polymorphic loci (100%) per D. boisianus population, whereas UBC841 had the lowest one (75%).

Table 3.

Genetic diversity of eight populations of Decalobanthus boisianus based on 220 ISSR loci

Population Polymorphic loci PPL (%) Na Ne I H
YGL 126 57.27 1.57 1.24 0.24 0.15
BWL 128 58.18 1.58 1.29 0.27 0.17
JFL 94 42.73 1.43 1.24 0.21 0.14
GSL 76 34.55 1.35 1.20 0.17 0.11
LMS 87 39.55 1.40 1.22 0.20 0.13
WZS 146 66.36 1.66 1.33 0.31 0.20
DLS 110 50.00 1.50 1.24 0.22 0.14
BSL 81 36.82 1.37 1.22 0.19 0.13
Mean (with ± SD) 106 48.18 1.48 (±0.11) 1.25 (±0.04) 0.23 (±0.04) 0.15 (±0.03)
Species level (with ± SD) 198 90.00 2.00 (±0.00) 1.33 (±0.33) 0.33 (±0.22) 0.21 (±0.17)
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H: Nei's gene index; I: Shannon's diversity index; Na: the observed number of alleles; Ne: the effective number of alleles; PPL: the proportion of polymorphic loci.

3.2. Genetic diversity

Among the eight D. boisianus populations collecting from the eight forest sites, the mean values of the proportion of polymorphic loci, the observed number of alleles (Na), the effective number of alleles (Ne), Shannon's diversity index (I), and Nei's gene index (H) were 48.18%, 1.48 ± 0.11, 1.25 ± 0.04, 0.23 ± 0.04, and 0.15 ± 0.03, respectively (Table 3). At the species level, PPL, Na, Ne, I, and H were 90.00%, 2.00 ± 0.00, 1.33 ± 0.33, 0.33 ± 0.22, and 0.20 ± 0.17, respectively (Table 3).

We also found the genetic diversity varies significantly with human disturbance intensity, with the high, medium, and low genetic diversity observing in low‐intensity group (D. boisianus population in WZS), moderate intensity group (D. boisianus population in YGL, BWL, JFL, DLS), and high‐intensity group (D. boisianus populatoin in LMS, BSL and GSL), respectively (Polymorphic loci: F (2,8) = 18.89, p = 0.003; PPL: F (2,8) = 18.89, p = 0.003; Na: F (2,8) = 19.08, p = 0.003; Ne: F (2,8) = 23.05, p = 0.002; I: F (2,8) = 21.34, p = 0.002; and H: F (2,8) = 24.54, p = 0.001).

3.3. Genetic structure

Among the eight populations, the total gene diversity index (Ht) and gene diversity within population index (Hs) were 0.21 ± 0.03 and 0.15 ± 0.01, respectively. The genetic differentiation index among the eight populations (Gst) was 0.28. AMOVA analysis showed that a relatively large proportion of genetic variation (75.67%) occurred within the eight D. boisianus populations, whereas only 24.33% of genetic variation was observed among the eight populations (ɸst = 0.24, p < 0.001; Table 4). The historical mean number of migrants (Nm) was 1.27, indicating the effective gene flow among the eight D. boisianus populations.

Table 4.

Analysis of molecular variance (AMOVA) for 8 populations of Decalobanthus boisianus based on 220 ISSR loci

Source of variation df SSD MSD Variance component Total variance (%) p *
Among populations 7 574.09 82.01 6.45 24.33 <0.001
Within populations 69 1382.71 20.04 20.04 75.67 <0.001
Total 76 1956.81 102.05 26.48 100  
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df, the degree of freedom; SSD, the sum of squared deviations; MSD, the mean squared deviations.

*

Indicated significance tests after 1,000 permutations.

The mean value of genetic similarity among the eight D. boisianus populations was high (0.93), while the genetic distances among the eight D. boisianus populations were relative low (0.07), indicating the close relationships among the eight D. boisianus populations (Table S1). The Mantel test's results (r = 0.39, p = 0.10) indicated that there were no significant correlations between Nei's genetic distances and geographic distances.

STRUCTURE analysis showed that delta K displayed two peaks (K = 3 and K = 5) but the maximum one was obtained at K = 3 (Figure 2a), suggesting the eight D. boisianus populations can be clustered into three groups, including group 1 (populations in BWL, WZS, DLS, BSL, and LMS), group 2 (populations in JFL and GSL) and group 3 (population in YGL). These three groups, moreover, were confirmed using UPGMA dendrogram (Figure 3) and PCoA analyses (Figure 4).

Figure 2.

Figure 2

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Cluster of 77 individuals from eight Decalobanthus boisianus populations using made by STRUCTURE for K = 3. Each individual is represented by a vertical, colored line. Same color in different individuals indicates that they are belonging to the same cluster. BSL: population sampled from Baishiling Nature Reserve; BWL: population sampled from Bawangling National Nature Reserve; DLS: population sampled from Diaoluoshan National Nature Reserve; GSL: population sampled from Ganshiling Nature Reserve ; JFL: population sampled from Jianfengling National Nature Reserve; LMS: population sampled from Limushan Nature Reserve; WZS: population sampled from Wuzhishan National Nature Reserve; YGL: population sampled from Yinggeling National Nature Reserve

Figure 3.

Figure 3

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UPGMA dendrogram based on Nei's genetic distances among 8 populations of Decalobanthus boisianus. BSL: population sampled from Baishiling Nature Reserve; BWL: population sampled from Bawangling National Nature Reserve; DLS: population sampled from Diaoluoshan National Nature Reserve; GSL: population sampled from Ganshiling Nature Reserve; JFL: population sampled from Jianfengling National Nature Reserve; LMS: population sampled from Limushan Nature Reserve; WZS: population sampled from Wuzhishan National Nature Reserve; YGL: population sampled from Yinggeling National Nature Reserve

Figure 4.

Figure 4

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Principal coordinate analysis (PCoA) analyses showing the genetic structures of Decalobanthus boisianus populations. BSL: population sampled from Baishiling Nature Reserve; BWL: population sampled from Bawangling National Nature Reserve; DLS: population sampled from Diaoluoshan National Nature Reserve; GSL: population sampled from Ganshiling Nature Reserve; JFL: population sampled from Jianfengling National Nature Reserve; LMS: population sampled from Limushan Nature Reserve; WZS: population sampled from Wuzhishan National Nature Reserve; YGL: population sampled from Yinggeling National Nature Reserve

4. DISCUSSION

4.1. Genetic diversity of D. boisianus varies with human disturbance intensity

Genetic diversity of the eight D. boisianus populations significantly increase with the decrease in human disturbance intensity (Polymorphic loci: F (2,8) = 18.89, p = 0.003; PPL: F (2,8) = 18.89, p = 0.003; Na: F (2,8) = 19.08, p = 0.003; Ne: F (2,8) = 23.05, p = 0.002; I: F (2,8) = 21.34, p = 0.002; H: F (2,8) = 24.54, p = 0.001), which proves our hypotheses. Human disturbance may influence the balance between sexual and clonal reproduction of D. boisianus populations (Hamrick et al., 1979; Loveless & Hamrick, 1984), to alter genetic diversity of D. boisianus populations (Cook, 1985; Eriksson, 1997; Sinclair et al., 2016). For example, D. boisianus in LMS, BSL and GSL with high‐intensity human disturbances may allocate resources to clonal reproduction, which helps it rapidly expand to novel habitats. But the clonal reproduction produces the same offspring gene and leads to low genetic diversity (Ellstrand & Roose, 1987; Philbrick & Les, 1996; Kudoh, 1999). In contrast, low‐intensity human disturbances allow WZS population to allocate more resources to sexual reproduction, thereby maintaining higher level of genetic diversity (Prentis et al., 2008; Silander, 1979). Our results are consistent with Aveliina et al. (2009), which demonstrated that human activity leads to a decrease in genetic diversity for Briza media. Although our study shows the relationships between the genetic diversity of D. Boisiana and human disturbance intensity, the cause of the conversion between sexual and clonal reproduction still need large‐scale manipulative experiments.

4.2. Genetic structure of D. boisianus in Hainan Island

In our study, both Nei's genetic differentiation index (Gst = 0.28) and AMOVA values (24.88%) indicated that there was a large proportion of genetic variation (over 70%) present within the eight D. boisianus populations, while less than 30% of genetic variation was observed among the eight populations. These results are consistent with the previous reports from other invasive species like Carduus acanthoides L. (Bohumil, Petr, Dana, Petr, & Ivana, 2009), Ambrosia artemisiifolia L. (Kočiš et al., 2015), and Spartina densiflora Brongn. (Castillo et al., 2018) but are less than most clonal invasive species, such as Eupatorium catarium Veldkamp (Li, Li, & Liu, 2014), Praxelis clematidea R.M.King & H.Rob. (Wang, Huang, Downie, Chen, & Chen, 2015), Galinsoga quadriradiata Ruiz & Pav. (Li, Qi, Yao, & Liu, 2015), Mikania micrantha H.B.K. (Li, Dong, & Zhong, 2007), and Alternanthera philoxeroides Griseb. (Ye, Li, Cao, & Ge, 2003). These results indicate that a very low genetic differentiation of the eight D. boisianus populations is observed on Hainan Island. One possible reason is that the effective gene flow (1.27) among the eight populations result from the high dispersal ability of D. boisianus to against barriers throughout the expansion of this species (Opedal et al., 2017; Wright, 1950). Indeed, the small mean value of Nei's genetic distance (0.07) and the high mean genetic similarity index (0.93) both indicate the close relationship among D. boisianus populations. Although little is known for the dispersal mode of this species, many studies have assumed that viable seeds of D. boisianus may be transported over streams to achieve long‐distance transmission (Wu et al., 2007; Wang et al., 2009). Moreover, several species that are closely related to D. boisianus, such as D. peltata, Merremia palmeri Hallier f., and Merremia ellenbeckii Pilg, were found that could be transported over streams (Francisco & Clara, 1997; Taylor & Kumar, 2016; Thulin, 2010). Value for ɸst (0.24) of D. boisianus is very close to those of hydrophilous plants (0.25) (Nybom, 2004), too. Hence, this stream dispersal mode may therefore generate the effective gene flow across large distances for D. boisianus. On the other side, intense storms on Hainan Island can also increase opportunities for propagules dispersal of D. boisianus and move them long distances across the landscape, downstream, and across catchments (Diez et al., 2012, Murphy & Metcalfe et al., 2016), and therefore accelerated the movement and gene exchange frequency among D. boisianus populations. Therefore, we should try to limit the spread of seeds and propagules of this weed. Further research is needed to identify the optimal management to control this species, for example, introduction of host‐specific natural enemies and proper disposal of this species.

UPGMA dendrogram, Bayesian analysis and PCoA analysis all show that the eight D. boisianu populations are categorized to three different groups (Figures 2, 3, and 4), which is not match the three groups categorized by the human disturbance intensity (Table 1), suggest that human disturbance cannot affect genetic structure of D. boisianu populations. In spite of geographic distances is nonsignificant (Mantel test, r = 0.34, p = 0.09) with genetic distances of this species, some nearby populations have clustered together, such as WZS with LMS and BSL, JFL with GSL populations. This implied that the horizontal expansion of clones might also lead to gene flow among nearby populations of that species and made their genetic relationships closer.

5. CONCLUSION

Generally, we found that genetic diversity of D. boisianus was correlated to the human disturbance intensity, which has been proved to be a major factor governing plant invasion. High dispersal ability and adaptive potential of D. boisianus may be important factors that were attributed to its large distances expansion and cause serious damage to the ecosystems. So far, artificial removal and chemical controls have been implemented to kill and prevent D. boisianus in the study areas, but were seldom effective. We suggest reducing deforestation to decrease human disturbance to forests for one hand. In addition, effective efforts should be taken to remove D. boisianus, and restore the secondary forests.

AUTHOR CONTRIBUTIONS

Huan Jiang, Wenxing Long, Hui Zhang, Chengneng Mi, Tao Zhou, and Zongzhu Chen conceived and designed the experiments; Huan Jiang and Wenxing Long performed the laboratory work; Hui Zhang and Zongzhu Chen analysed the data; Huan Jiang, Wenxing Long, Hui Zhang, and Zongzhu Chen wrote the paper.

Supporting information

 

Click here for additional data file. (30KB, doc)

ACKNOWLEDGEMENTS

We thank Chao Li, Yikang Chen, and Qing Chen for their assistance in field work. Financial supports came from National Natural Science Foundation of China (Grant 31660163 and 31260109), Science Foundation for Youth Scholars of Hainan University (hdkyxj201704), Postgraduate Scientific Research Innovation Projects of Regular Institution of Higher Education in Hainan Province (Hys201765), and CFERN & GENE Award Funds on Ecological Paper.

Jiang H, Long W, Zhang H, Mi C, Zhou T, Chen Z. Genetic diversity and genetic structure of Decalobanthus boisianus in Hainan Island, China. Ecol Evol. 2019;9:5362–5371. 10.1002/ece3.5127

Contributor Information

Wenxing Long, Email: oklong@hainu.edu.cn.

Hui Zhang, Email: 446056962@qq.com.

DATA ACCESSIBILITY

Inter Simple Sequence Repeat (ISSR) data for Decalobanthus boisianus is available from the Dryad Digital Repository: https://doi.org/10.5061/dryad.7nq1636.

REFERENCES

  1. Andreakis, N. , Kooistra, W. H. C. F. , & Procaccini, G. (2009). High genetic diversity and connectivity in the polyploid invasive seaweed Asparagopsis taxiformis (Bonnemaisoniales) in the Mediterranean, explored with microsatellite alleles and multilocus genotypes. Molecular Ecology, 18, 212–226. [DOI] [PubMed] [Google Scholar]
  2. Aveliina, H. , Tatjana, O. , Liina, S. , Krista, T. , Tiina, T. , & Meelis, P. (2009). Human influence lowers plant genetic diversity in communities with extinction debt. Journal of Ecology, 97, 1329–1336. 10.1111/j.1365-2745.2009.01572.x [DOI] [Google Scholar]
  3. Bohumil, M. , Petr, Z. , Dana, K. , Petr, D. , & Ivana, P. (2009). Low population differentiation and high genetic diversity in the invasive species Carduus acanthoides, l. (asteraceae) within its native range in the czech republic. Biological Journal of the Linnean Society, 98, 596–607. 10.1111/j.1095-8312.2009.01304.x [DOI] [Google Scholar]
  4. Bozkurt, M. L. , Muth, P. , Parzies, H. K. , & Haussmann, B. I. G. (2015). Genetic diversity of east and west african Striga hermonthica populations and virulence effects on a contrasting set of sorghum cultivars. Weed Research, 55, 71–81. 10.1111/wre.12117 [DOI] [Google Scholar]
  5. Carboneras, C. , Genovesi, P. , Vilà, M. , Blackburn, T. M. , Carrete, M. , & Clavero, M. (2017). A prioritised list of invasive alien species to assist the effective implementation of eu legislation. Journal of Applied Ecology, 1, 5362–9. 10.1111/1365-2664.12997 [DOI] [Google Scholar]
  6. Castillo, J. M. , Gallego‐Tévar, B. , Figueroa, E. , Grewell, B. J. , Vallet, D. , Rousseau, H. , … Aïnouche, M. (2018). Low genetic diversity contrasts with high phenotypic variability in heptaploid Spartina densiflora populations invading the pacific coast of north america. Ecology & Evolution, 8, 4992–5007. 10.1002/ece3.4063 [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Cook, R. E. (1985). Growth and development in clonal plant populations In Jackson J. B. C., Buss L. W., & Cook R. E. (Eds.), Population Biology and Evolution of Clonal Organisms (pp. 225–296). New Haven, CT: Yale University Press. [Google Scholar]
  8. Diez, J. M. , D'Antonio, C. M. , Dukes, J. S. , Grosholz, E. D. , Olden, J. D. , Sorte, C. J. B. , … Miller, L. P. (2012). Will extreme climatic events facilitate biological invasions? Frontiers in Ecology and the Environment, 10, 249–257. 10.1890/110137 [DOI] [Google Scholar]
  9. Earl, D. A. , & Vonholdt, B. M. (2012). Structure harvester: A website and program for visualizing structure output and implementing the evanno method. Conservation Genetics Resources, 4, 359–361. 10.1007/s12686-011-9548-7 [DOI] [Google Scholar]
  10. Ellstrand, N. C. , & Roose, M. L. (1987). Patterns of genotypic diversity in clonal plant species. American Journal of Botany, 74, 123–131. 10.1002/j.1537-2197.1987.tb08586.x [DOI] [Google Scholar]
  11. Eriksson, O. (1997). Clonal life histories and the evolution of seed recruitment In de Kroon H., & van Groenendael J. (Eds.), Ecology & Evolution of Clonal Plants (pp. 211–226). Leiden, NL: Backhuys. [Google Scholar]
  12. Evanno, G. , Rengaut, S. , & Gouget, J. (2005). Detecting the number of clusters of individuals using the software STRUCTURE: A simulation study. Molecular Ecology, 14, 2611–2620. 10.1111/j.1365-294x.2005.02553.x [DOI] [PubMed] [Google Scholar]
  13. FAO (2005). Global forest resources assessment update. 2005. Terms and definitions. In: Forest resources Assessment Working Paper 83/E, FAO, Rome, 17
  14. Flora of China Editorial Board (1995). Science Press: Flora of China [M] . 16, 271–325. [Google Scholar]
  15. Francis, C. Y. , Rong, C. Y. , & Boyle, T. (1999). POPGENE, Microsoft Window‐based freeware for population genetic analysis. University of Alberta, Canada. 1‐31
  16. Francisco, M. F. , & Clara, T. O. (1997). Vines of a desert plant community in central sonora, mexico. Biotropica, 29, 46–56. 10.1111/j.1744-7429.1997.tb00005.x [DOI] [Google Scholar]
  17. Hamrick, J. L. , Linhart, Y. , & Mitton, J. (1979). Relationships between life history characteristics and electrophoretically detectable genetic variation in plants. Annual Review of Ecology & Systematics, 10, 173–200. 10.1146/annurev.es.10.110179.001133 [DOI] [Google Scholar]
  18. Huang, Q. Q. , Shen, Y. , Fan, Z. , Li, X. , Song, X. , Cheng, H. , & Hou, Y. (2013). Effects of soil from different forest types in wuzhi mountain on the seedling growth of Merremia boisiana . Ecology & Environmental Sciences, 22, 95–99. [Google Scholar]
  19. Huang, Q. Q., Shen, Y. D. , Li, X. X. , Zhang, G. L. , Huang, D. D. , & Fan, Z. W. (2015). Effects of light and water availability on the morphology and allelopathy of the native outbreak species Merremia boisiana (Gagnep.) Oostr. Chinese Journal of Ecology, 34(2), 438–444. [Google Scholar]
  20. Jakobsson, M. , & Rosenberg, N. A. (2007). Clumpp: A cluster matching and permutation program for dealing with label switching and multimodality in analysis of population structure. Bioinformatics, 23, 1801–1806. 10.1093/bioinformatics/btm233 [DOI] [PubMed] [Google Scholar]
  21. Johnson, G. B. (1974). Estimation of effective number of alleles from electrophoretic data. Genetics, 78, 771–776. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. King, L. M. , & Schaal, B. A. (1989). Ribosomal‐dna variation and distribution in Rudbeckia missouriensis . Evolution, 43, 1117–1119. 10.2307/2409592 [DOI] [PubMed] [Google Scholar]
  23. Kočiš Tubić, N. , Djan, M. , Veličković, N. , Anačkov, G. , & Obreht, D. (2015). Microsatellite dna variation within and among invasive populations of Ambrosia artemisiifolia from the southern pannonian plain. Weed Research, 55, 268–277. 10.1111/wre.12139 [DOI] [Google Scholar]
  24. Kudoh, H. (1999). Genet structure and determinants of clonal structure in a temperate deciduous woodland herb, Uvularia perfoliata . Journal of Ecology, 87(2), 244–257. [Google Scholar]
  25. Kumar, S. , Stecher, G. , Li, M. , Knyaz, C. , & Tamura, K. (2018). MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms. Molecular Biology and Evolution, 35, 1547–1549. 10.1093/molbev/msy096 [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Ledo, A. , & Schnitzer, S. A. (2014). Disturbance and clonal reproduction determine liana distribution and maintain liana diversity in a tropical forest. Ecology, 95, 2169–2178. 10.1890/13-1775.1 [DOI] [PubMed] [Google Scholar]
  27. Li, J. M. , Dong, M. , & Zhong, Z. C. (2007). Population genetic differentiations in the invasive plant Mikania micrantha in china. Journal of Plant Ecology, 31, 680–688. 10.17521/cjpe.2007.0088 [DOI] [Google Scholar]
  28. Li, L. Q. , Li, N. Y. , & Liu, Q. (2014). Genetic diversity of the invasive plant Eupatorium catarium populations in hainan island and guangdong of china based on issr analysis. Chinese Journal of Ecology, 33, 611–617. [Google Scholar]
  29. Li, X. C. , Qi, S. Y. , Yao, J. , & Liu, Y. (2015). Genetic diversity and differentiation of invasive plant Galinsoga quadriradiata populations in china. Chinese Journal of Ecology, 34, 3306–3312. [Google Scholar]
  30. Lian, J. Y. , Cao, H. L. , Wang, Z. G. , Li, J. , Ye, W. H. , & Li, J. (2007). The community characteristics for invading damage of the forest killer Merremia boisiana . Guihaia, 27, 482–486. [Google Scholar]
  31. Liu, H. Y. 2007. The Seeds reproduction and biocontrol of Merremia boisiana. PhD thesis, Sun Yat‐sen University, Guangzhou, China. 1–9.
  32. Loveless, M. , & Hamrick, J. L. (1984). Ecological determinants of genetic structure in plant populations. Annual Review of Ecology & Systematics, 15, 65–95. 10.1146/annurev.ecolsys.15.1.65 [DOI] [Google Scholar]
  33. Murphy, H. T. , & Metcalfe, D. J. (2016). The perfect storm: Weed invasion and intense storms in tropical forests. Austral Ecology, 41, 864–874. 10.1111/aec.12376 [DOI] [Google Scholar]
  34. Nei, M. (1972). Genetic distance between populations. The American Naturalist, 106, 283–292. 10.1086/282771 [DOI] [Google Scholar]
  35. Nybom, H. (2004). Comparison of different nuclear dna markers for estimating intraspecific genetic diversity in plants. Molecular Ecology, 13, 1143–1155. 10.1111/j.1365-294x.2004.02141.x [DOI] [PubMed] [Google Scholar]
  36. Opedal, Ø. H. , Falahati‐Anbaran, M. , Albertsen, E. , Armbruster, W. , Rocio, P.‐B. , Stenøien, H. , & Pélabon, C. (2017). Euglossine bees mediate only limited long‐distance gene flow in a tropical vine. New Phytologist, 213, 1898–1908. 10.1111/nph.14380 [DOI] [PubMed] [Google Scholar]
  37. Peakall, R. , & Smouse, P. E. (2012). Genalex 6.5: Genetic analysis in excel. population genetic software for teaching and research–an update. Bioinformatics, 28, 2537–2539. 10.1093/bioinformatics/bts460 [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Philbrick, C. T. , & Les, D. H. (1996). Evolution of aquatic angiosperm reproductive systems. Bioscience, 46, 813–826. 10.2307/1312967 [DOI] [Google Scholar]
  39. Prentis, P. J. , Wilson, J. R. , Dormontt, E. E. , Richardson, D. M. , & Lowe, A. J. (2008). Adaptive evolution in invasive species. Trends in Plant Science, 13, 288–294. 10.1016/j.tplants.2008.03.004 [DOI] [PubMed] [Google Scholar]
  40. Pritchard, J. K. , Stephens, M. , & Donnelly, P. (2000). Inference of population structure using multilocus genotype data. Genetics, 155, 945–959. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Rosenberg, N. A. (2004). Distruct: A program for the graphical display of population structure: Program note. Molecular Ecology Notes, 4, 137–138. 10.1046/j.1471-8286.2003.00566.x [DOI] [Google Scholar]
  42. Rusterholz, H. , Kissling, M. , & Baur, B. (2009). Disturbances by human trampling alter the performance, sexual reproduction and genetic diversity in a clonal woodland herb. Perspectives in Plant Ecology Evolution & Systematics, 11, 17–29. 10.1016/j.ppees.2008.09.002 [DOI] [Google Scholar]
  43. Sabatini, F. , Burrascano, S. , Keeton, W. , Levers, C. , Lindner, M. , Pötzschner, F. , … Kuemmerle, T. (2018). Where are Europe's last primary forests? Diversity and Distributions, 24, 1426–1439. 10.1111/ddi.12778 [DOI] [Google Scholar]
  44. Schmid, B. , Bazzaz, F. A. , & Weiner, J. (1995). Size dependency of sexual reproduction and of clonal growth in two perennial plants. Canadian Journal of Botany, 73, 1831–1837. 10.1139/b95-194 [DOI] [Google Scholar]
  45. Silander, J. A. (1979). Microevolution and clone structure in spartina patens. Science, 203, 658–660. 10.1126/science.203.4381.658 [DOI] [PubMed] [Google Scholar]
  46. Simões, A. , & Staples, G. (2017). Dissolution of Convolvulaceae tribe Merremieae and a new classification of the constituent genera. Botanical Journal of the Linnean Society, 83, 561–586. 10.1093/botlinnean/box007 [DOI] [Google Scholar]
  47. Sinclair, E. A. , Statton, J. , Hovey, R. , Anthony, J. M. , Dixon, K. W. , & Kendrick, G. A. (2016). Reproduction at the extremes: Pseudovivipary, hybridization and genetic mosaicism in Posidonia australis (posidoniaceae). Annal Botany, 117, 237–247. [DOI] [PMC free article] [PubMed] [Google Scholar]
  48. Staples, G. (2010). A Checklist of Merremia (Convolvulaceae) in Australasia and the Pacific. Gardens' Bulletin Singapore, 61, 483–522. [Google Scholar]
  49. Sun, D. L. , Shen, J. M. , Wan, S. Q. , & Xie, W. H. (2006). Danger and utilization of Merremia boisiana . Chinese Wild Plant Resources, 25, 32–34. [Google Scholar]
  50. Taylor, S. , & Kumar, L. (2016). Will climate change impact the potential distribution of a native vine (merremia peltata) which is behaving invasively in the pacific region? Ecology and Evolution, 6, 742–754. 10.1002/ece3.1915 [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Templeton, A. R. (1994). Biodiversity at the molecular genetic level: Experiences from disparate macroorganisms. Philosophical Transactions of the Royal Society of London, 345, 59–64. 10.1098/rstb.1994.0086 [DOI] [PubMed] [Google Scholar]
  52. Thulin, M. (2010). Notes on convolvulus, astripomoea, ipomoea and merremia (convolvulaceae) from the horn of Africa. Nordic Journal of Botany, 23, 629–640. 10.1111/j.1756-1051.2003.tb00444.x [DOI] [Google Scholar]
  53. Wang, B. S. , Li, M. G. , Liao, W. B. , Su, J. , Qiu, H. X. , Ding, M. Y. , … Peng, S. L. (2005). Geographical distribution of Merremia Boisiana . Ecology and Environment, 14(4), 451–454. [Google Scholar]
  54. Wang, B. S. , Peng, S. L. , Li, D. J. , & Zhou, T. (2009). Research progress on Merremia boisiana . Chinese Journal of Ecology, 28, 2360–2365. [Google Scholar]
  55. Wang, Q. Z. , Huang, M. , Downie, S. R. , Chen, Z. X. , & Chen, Y. T. (2015). Genetic diversity and structure of the noxious alien grass Praxelis clematidea in Southern China. Biochemical Systematics & Ecology, 59, 183–189. 10.1016/j.bse.2015.01.021 [DOI] [Google Scholar]
  56. Wright, S. (1950). The genetical structure of populations. Nature, 166, 247–249. 10.1038/166247a0 [DOI] [PubMed] [Google Scholar]
  57. Wu, L. F. , Liang, Y. Q. , Chen, K. , Li, Z. , & Cao, H. (2007). Damageand Prevention of Merremia boisiana in Hainan Province, China. Forestry and Environmental Science, 23, 83–86. [Google Scholar]
  58. Ye, W. H. , Li, J. , Cao, H. L. , & Ge, X. J. (2003). Genetic uniformity of Alternanthera philoxeroides in South China. Weed Research, 43, 297–302. 10.1046/j.1365-3180.2003.00346.x [DOI] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

 

Click here for additional data file. (30KB, doc)

Data Availability Statement

Inter Simple Sequence Repeat (ISSR) data for Decalobanthus boisianus is available from the Dryad Digital Repository: https://doi.org/10.5061/dryad.7nq1636.

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