INFERRING INVASION PATTERNS OF LONICERA MAACKII IN SOUTHWESTERN OHIO FROM THE GENETIC STRUCTURE OF ESTABLISHED POPULATIONS

A thesis submitted to Kent State University in partial fulfillment of the requirements for the degree of Master of Science

By Erin J. McNutt December 2010

Thesis written by Erin J. McNutt B.S., Kent State University, 2008 M.S., Kent State University, 2010

Approved by

Advisor Oscar J. Rocha Accepted by

Chair, Department of Biology James L. Blank Dean, College of Arts and Sciences Timothy Moreland

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TABLE OF CONTENTS

LIST OF FIGURES iv

LIST OF TABLES v

ACKNOWLEDGEMENTS vi

CHAPTER 1: General Introduction 1

CHAPTER 2: Inferring invasion patterns of Lonicera maackii in southwestern Ohio from the genetic structure of established populations 13 Introduction 13 Methods 17 Study area 17 Leaf tissue collection 18 Genetic data analysis 19 Spatial analysis of genetic diversity 19 Results 20 Allelic diversity 20 Heterozygosity 21 Population differentiation 21 Spatial analysis of genetic diversity 21 Population structure 22 Discussion 23 Genetic diversity 23 Genetic structure 25 Patterns of colonization 28 Acknowledgements 31

CHAPTER 3: General Conclusions 40

LITERATURE CITED 44

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LIST OF FIGURES

Figure 1: Locations of the 17 sample sites of Lonicera maackii in southwestern Ohio

included in this study.

Figure 2: Relationship between Nei‘s unbiased genetic estimates between pairs of

sample sites and their corresponding geographic distances.

Figure 3: Dendrogram showing the degree of relatedness between woodlots based

on Nei‘s unbiased genetic distances.

Figure 4: Mean log likelihood values for each value of K, where K indicates the

number of distinct Structure clusters

Figure 5: Estimated population structure for Lonicera maackii woodlots from

southwestern Ohio.

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LIST OF TABLES

Table 1: Oligonucleotide primer sequences, repeat motifs, number of alleles, product

sizes, and annealing temperatures for each of the five microsatellite loci

used in this study

Table 2: Mean number of alleles (Na), mean effective number of alleles per locus (Ne),

mean observed heterozygosity (Ho), and Nei‘s mean expected

heterozygosity (He) for the 17 sample sites of Lonicera maackii from

southwestern Ohio, USA included in this study.

Table 3: Summary of F-statistics and gene flow for all five loci.

Table 4: Nei‘s unbiased genetic distance between all woodlot pairs.

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ACKNOWLEDGEMENTS

Deepest gratitude is extended to my advisor, Dr. Oscar Rocha. Your classes during my undergraduate years helped me grow as a person and as a scientist. Thank you for continuing to push me to grow at the graduate level and for offering endless opportunities, encouragement and inspiration. This gratitude also extends to committee members Dr. Andrea Case and Dr. Ferenc de Szalay. Your guidance, comments, and critiques helped shape this document and the writer.

With love and gratitude, I thank my family. You exposed me to nature at a young age and supported me when I wanted to turn those backyard adventures into a career.

Thank you for starting me down this path, trusting in me, believing in my dreams, and providing unwavering encouragement and love.

This work was a collaboration with Miami University; as such, I also wish to recognize Dr. David Gorchov for leading fieldwork, Dr. Mary Henry, and Steve

Castellano for mapping Lonicera maackii populations in southwestern Ohio and helping with collection. Thank you to the landowners who granted us access to their properties

Finally, thank you to all of those that I have no current ability to name individually-those that have offered encouragement, spent time in the lab, shared laughter, and brought out the best in me as a person, student, and researcher. To each of you, I dedicate my work and this thesis.

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CHAPTER 1:

General Introduction

It is well known that human societies have radically changed the distribution of plant species by transporting them throughout the world (Drake et al. 1989, Primack 1993,

Williamson 1996, Ewel et al. 1999). Because the new environment is not always suitable to their needs, the great majority of these exotic species do not become established in places where they are introduced (Ellstrand and Schierenbeck 2000, Reichard and White 2001).

Therefore, only a small percentage of species do establish themselves in their new habitat and even a smaller fraction of these species increase in abundance at expense of native plant populations, communities and ecosystems (Pattison et al. 1998, Ellstrand and Schierenbeck

2000, Reichard and White 2001). Those exotic species that are capable of producing environmental or economic damage, or that represent a threat to human health are considered to be invasive (Rossman 2001).

The invasion and spread of unwanted species imposes a major threat to human and animal health, agricultural production, and biological diversity (Sandlund, Schei and Viken

1999, Pimentel et al. 2000). Alien species introductions affecting human health are abundant and have played an important role in the emergence of infectious diseases. The spread of disease causing organisms and their vector animals are examples of the potential negative effects of invasive species on human health. Another good example of such invasions is the chestnut blight disease that nearly eliminated the chestnut tree (Castanea dentata), the most

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economically important hardwood species in the eastern American forests. The death of nearly one billion trees drastically altered the ecosystem and allowed oak trees to dominate

the landscape (Primack 1993, McNeely 1999, Sandlund, Schei and Viken 1999).

Overall, it is estimated that the economic impact of invasive species on US agriculture, forestry, fisheries and human health, is at least $134 billion annually (US Congress, Office of

Technology Assessment 1993, Pimentel et al. 2000).

There is overwhelming evidence indicating that the introductions of alien species have negative effects on biological diversity at the local level (Vitousek 1990, Primack

1993). For example, many bottomlands of the southeastern United States are completely dominated by the perennial Japanese Honeysuckle (Lonicera japonica). Similarly, fire ants and African honeybees have built up huge populations in the southern United States, and zebra mussels have recently invaded fresh water ecosystems in North America and threaten urban water systems and freshwater fisheries (Johnson and Padilla 1996, Moller 1996). Even though exotic species may be better suited to take advantage of disturbed conditions caused by human activities, they are also capable of invading natural habitats. The invasion of these aggressive species is thought to be responsible for the decline in the number and the abundance of native species.

These detrimental effects have been well documented in the State of Ohio

(Hutchinson and Vankat 1997, 1998, Deering and Vankat 1998, Collier, Gould and Gorchov

2000, Collier, Vankat and Hughes 2002, Gorchov and Trisel 2003). Invasive algae, plants, invertebrates, and fish have negatively impacted aquatic systems; in all, 130 species have been recognized as causing serious problems. In terrestrial ecosystems, the emerald ash

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borer, has killed millions of trees in Michigan and Ontario and is known to be present in at least five Ohio counties. In addition, there is a long list of plant species known to be a threat in terrestrial ecosystems. This list includes species such as Amur, Japanese, morrow andtartarian honeysuckle; common and glossy buckthorn; garlic mustard; purple loosestrife; common reed grass; reed canary grass; and multiflora rose (Ohio Department of Natural

Resources, Division of Natural Resources 2003).

Among exotic plants, honeysuckle species are considered the most aggressive invaders. Collier, Vankat and Hughes (2002) reported that, in southwestern Ohio, the number of plant species in areas dominated by Amur honeysuckle was significantly lower than the number of plant species in places where this species was not present. However, Gorchov and

Trisel (2003) argued that these correlations do not determine causality, and conducted experimental research to determine the direct ecological effects of specific invasive plants.

They demonstrated the negative effects of Amur Honeysuckle on seedling mortality of native species (Gorchov and Trisel 2003, Miller and Gorchov 2004).

While it is not currently clear what traits or combinations of traits make a species invasive (Mack 1996, Rejmánek 1999, 2000, Pysek et al. 2004), considerable effort has been spent trying to solve this (Carroll and Dingle 1996, Mack 1996, Williamson and Fitter 1996,

Daehler 1998, Daehler et al. 2004, Lloret et al. 2004). However, Ellstrand and Schierenbeck

(2000) question wether invasive species are ―born‖ or are ―made.‖ That is, whether species are invasive because they have those characters that are responsible for more aggressive behavior, or if they evolve their invasiveness after they colonize a new site. They propose

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that genetic change experienced during the establishment of exotic species might be an important stimulus for the evolution of invasiveness in plants.

Some species have exhibited their invasive behavior quickly after arriving to their new habitat, but many species appeared to have had long lag periods between their initial introduction and the subsequent population explosion (Crooks and Soulé 1999). These lag periods may be related to genetic changes that are necessary for the adaptation of the alien species to the new environment. For example, Spartina alterniflora was introduced in the

United Kingdom in the early 1800s, but it did not start spreading out of Southampton until after hybridizing with the native S. maritima. These hybrids resulted in a new fertile species,

S. townsendii, through chromosome doubling (Thompson 1991).

Very little is known about the levels of genetic variation in invasive species in relation to their native congeners. Schierenbeck et al. (1995) compared the levels of genetic variability in a native to those of an exotic species of honeysuckle and found them to be similar. They suggested that genetic variation may be less important to the invasiveness of the exotic Japanese honeysuckle than the species‘ life history traits. Pappert et al. (2000) reported high levels of genetic variation among twenty populations of kudzu in southeastern

United States. They claim that such levels are consistent with its history of multiple introductions over an extended period of time. These works suggest that invasive species may build up their genetic variation during their establishment, and this might explain why some species turn invasive only after a long lag time and/or after multiple introductions

(Ellstrand and Schierenbeck 2000).

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Gene flow is an important factor determining the genetic structure at the landscape level. Since plants are relatively immobile, present strong spatial structure, and exhibit restricted dispersal, they become more susceptible to habitat fragmentation and isolation

(Giles and Goudet 1997a, Gillman 1997, Ouborg et al. 1999). Thus, isolation by distance may result in a disruption of the genetic exchange among subpopulations (Giles and Goudet

1997a, Gillman 1997). Bartuszevige and Gorchov (in press) pointed out that seed dispersers distribute seeds of the Amur honeysuckle (Lonicera maackii) in a nonrandom manner, as they tend to forage in sites where they are more likely to find other fruiting honeysuckle. The authors argue that this is especially true in late fall and early winter when fruit sources are scarce. This pattern of seed dispersal and colonization can bring together plant genotypes of different origins, as dispersers move from patch to patch. The establishment of novel genetic combinations is thus favored.

Ellstrand and Schierenbeck (2000) proposed that a cross between species of the same genus or between disparate populations may serve as a stimulus for the evolution of invasiveness. Schierenbeck, Hamrick, and Mack (1995) compared the levels of isozyme variability between Lonicera japonica and L. semperviren. They reported the occurrence of hybridization between these two species and suggested that it may favor the acquisition of the aggressive attributes that characterize invasive species. Similarly, Gaskin and Schaal

(2002) studied the population genetics of invasive Tamarix species in the United States. They found that the largest Tamarix invasion in the USA consists of T. chinensis and T. ramosissima, two morphologically similar species. They also found that the most common plant in this U.S. invasion is a hybrid combination between two species-specific genotypes

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that were geographically isolated in their native Eurasian range. Less extensive hybrids exist in the invasion, involving combinations of T. ramosissima and T. chinensis with T. parviflora and T. gallica. The presence of potentially novel hybrids in the U.S. illustrates how importation of exotics can alter population structures of species and contribute to invasions.

Extensive gene flow, and escape from cultivation can facilitate hybridization between genotypes. There are numerous registered cultivars of honeysuckle in the United States.

These cultivars have been bred for special traits. For example, among Japanese honeysuckles the 'Halliana' (Hall's Japanese honeysuckle), the most widely grown cultivar, has white flowers that change to yellow, and the upper lip is split in half; 'Aureo-reticulata' has yellow veins in the leaves; 'Superba' with scarlet red flowers; the 'Purpurea' with purplish leaves and flowers that are purple on the outside. For Amur honeysuckle, the Rem Red variety, bred by the USDA is still widely promoted in the ornamental plant trade. Some of the cultivars are already the product of hybridization between different varieties of a single species.

Moreover, some cultivars are the product of hybridization between different species of the same genus. For example, Lonicera mandarin, is an intentional garden hybrid between L. tragophylla and L. × brownii. In the case of the Lonicera x bella, (L. morrowii x L. tartarica) there are multiple cultivars within this interspecific hybrid. However, it is not known if changes in genetic composition following introduction could give rise to progeny that are more vigorous and weedy than cultivated honeysuckle, and thereby enhancing their invasiveness.

While some have used genetics to create cultivars, other authors have employed genetic techniques to determine the potential source populations of new invasive plant

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ranges. One method such researchers use is to compare the genetic structures of individuals in a new range with those found in the species‘ native range. Kang et al. (2007) used nuclear and chloroplast microsatellites to trace the source of Scotch broom (Cytisus scoparius) populations in Australia, New Zealand, and the United States. The New Zealand population seemed to arise from a single source while exotic populations established in Australia and the

US showed evidence of being introduced from multiple sources, even though the two continents showed low levels of differentiation between them. Stands of C. scoparius that were isolated by extreme distances still showed some degree of relatedness. One explanation for this result is the spread of plants through horticulture. As cultivars are developed and spread over large regions, related individuals become scattered throughout the landscape.

Okada et al. (2007) identified seven distinct pampas grass (Cortaderia selloana) cultivars.

However, two of these clusters accounted for 78% of genetic material in the invasive range, suggesting that certain cultivars may be more likely to be propagated or become more aggressive than others. Even though some invasions can be traced back to few genetic sources, invasive plants are able to achieve high levels of genetic differentiation and allelic diversity in introduced ranges (Novak and Mack 2001; Durka et al. 2005; Williams et al.

2005; Wang et al. 2008). This evidence has been used as justification for the possibility of multiple introductions.

Genetic data have also been used to infer demographic processes (DeWoody et al.

2004; Hu et al. 2009). Sakai et al. (2001) suggested using genetic variation and differentiation between populations to infer possible sources of founding individuals (see also Wade and McCauley 1988). Moreover, the use of molecular markers may also help

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determine the most likely source population for newly established individuals (Cain et al.

2000; DeWoody et al. 2004; Hu et al. 2009). In turn, this information can be used to estimate dispersal distance and ultimately, patterns of dispersal and colonization. The patterns of dispersal (gene flow) and the number and source of individuals establishing the new population will determine the level of genetic differentiation between populations at the landscape (or metapopulation) level (Whitlockand and McCauley

1990; Hanski 1998).

Once an invasive population becomes established, the question is whether invasions proceed along expanding fronts or through long-distance dispersal events followed by local expansion (Auld and Coote 1980). Long distance (1-10 km) dispersal of only a very small proportion of seeds can lead to an order of magnitude increase in spread rate according to a mathematical model created by Higgins and Richardson

(1999), leading these authors to highlight the need for more data on long-distance dispersal. Increased understanding in the method of invasive plant species will have important implications in their management and control. Knowing where to focus the time, energy, and resources that such measures require should make them more effective and thus slow the spread or inhibit establishment of harmful non-natives.

Increasingly vigilant property owners and effective control measures would greatly aid in controlling the spread of the invasive shrub Lonicera maackii (Rupr.)

Maxim. (Caprifoliaceae), otherwise known as the Amur honeysuckle. Although native to the Russian Far East, China, Korea, and Japan, this self-incompatible shrub was introduced to the United States in 1898 (Luken and Theiret 1995). Its popularity as an

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ornamental and its ability to reduce soil erosion and create wind breaks led to 14 additional introductions from native stock and the species being planted across the country (Sharp and Belcher 1991; Lorenz et al. 1991; Luken and Theiret 1995).

Naturalized populations now occur throughout the eastern United States and were first described in Ohio in the late 1950s (Braun 1961). Lonicera maackii has become a dominant feature throughout the wooded landscape with no native herbivory and extended leaf phenology (Hutchinson and Vankat 1997; Trisel 1997; McEwan et al.

2009)

In addition to being partially self-compatible and having multiple introductions in the area, the mode of seed dispersal may contribute to maintain a low level of differentiation among populations. It has been well documented that L. maackii produces a copious number of fruits and retains them well into winter. Ingold and Craycraft (1983) reported that birds eat these fruits at the time when other food sources have been exhausted (also see Bartuszevige and Gorchov 2006). Nine bird species have been shown to consume honeysuckle fruits (Ingold and Craycraft 1983) in the study area; however, the most important dispersers seem to be American robins (Turdus migratorius) and

European starlings (Sturnus vulgaris) (Bartuszevige and Gorchov 2006). Because these birds are capable of traveling long distances, genetically diverse seeds from multiple neighboring woodlots are likely to arrive in a given location, resulting in the establishment of new populations with high levels of genetic diversity and showing little divergence from other nearby populations.

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Previous studies have suggested that L. maackii has a natural migration rate of 0.5 km/year (Hutchinson and Vankat 1998; Deering and Vankat 1999), possibly indicating an advancement along a single front. However, once a population is established, avian dispersal may facilitate its spread to other woodlots. Seed dispersal is facilitated by the massive production of fruits per shrub and the number of seeds per fruit (between 3 and

11) (Ingold and Craycraft 1983). Moreover, Bartuszevige and Gorchov (2006) documented that American robins need about 70 minutes for the passage of honeysuckle seeds through their system, allowing both short and long distance seed dispersal. The

American robins and European starlings that disperse most of the honeysuckle seeds in the study region prefer to travel along corridors. Only 11% of recorded robin movements occurred between unconnected sites, and across all studied species, a bird was 15 times more likely to travel between connected sites than unconnected (Haas 1995). However, the birds that spread the seeds travel between edge habitats and the forest interior

(Bartuszevige et al. 2006), so both areas are at risk for invasion.

Major policy recommendations to counter invasions include monitoring and controlling early invasions, and ―slow-the-spread‖ programs for established invasions

(Lodge et al. 2006). All of these efforts will be improved by applying scientific research to determine the sites most likely to be invaded by target species (Lodge et al. 2006).

Understanding how landscape structure shapes biological invasions will have direct benefits to management. If invasion is promoted by landscape connectivity, then reducing connectivity (creating barriers) could be effective to slow down the rate of invasion (With

2002, 2004). If advancing fronts shape invasion, then appropriate tactics would include

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searching for recruits in susceptible areas near such fronts, and eradication at the front and working back. If however long-distance dispersal is more important, detection and removal of such ‗nascent foci‘ (Moody and Mack 1988) is more important than control of well-established populations, and control of the vectors of long-distance dispersal (e.g., non-native birds (Bartuszevige and Gorchov 2006), roads (Gelbard and Belnap 2003), vehicles) should be considered. In the case of invasive species that are used in horticulture (Reichard and White 2001; Mack and Erneberg 2002), isolated horticultural plantings might act as nascent foci; if they do, then their removal would be more effective at halting invasion than control of naturalized populations.

It is my hypothesis that this invasive shrub spreads through the establishment of focal populations through long-distance dispersal followed by outward expansion. This idea is supported by other studies. For example, Bartuszegive et al. (2006) found that the only factor that significantly explained the presence of L. maackii populations surrounding Oxford, Ohio was distance from the nearest town. They suggested that seeds produced by cultivated trees are the primary source of seeds beginning new colonization events. A similar result was found by Hutchinson and Vankat (1997) where shrub cover was inversely related to distance from the invasion focus (the city of Oxford, Ohio)

(r2=0.133, p<0.0006). We can expand these findings to the invasion of woodlots by seeds produced in other nearby lots, where escaped L. maackii shrubs have been established and have reached reproductive age. Under this scenario, long distance seed dispersal may result in colonization of new woodlots and short distance dispersal could explain its

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spread to nearby stands. The research presented here attempts to provide support for this hypothesized method of L. maackii invasion in southwestern Ohio.

CHAPTER 2:

Inferring invasion patterns of Lonicera maackii in southwestern Ohio from the

genetic structure of established populations

Introduction

Invasive plants are widely recognized as having major impacts on biological diversity, ecosystem function, and economic value of forests, grasslands, and other ecosystems (Vitousek et al. 1996, Mack et al. 2000, Pimental et al. 2005). Extensive research has been done on the factors that cause certain exotic species to become invasive

(Mack 1996, Williamson and Fitter 1996, Daehler 1998, Daehler et al. 2004, Lloret et al.

2004), and certain sites to be susceptible to invasion (Hobbs and Huenneke 1992, Davis et al. 2000, Levine 2000, Dietz 2002, Foster et al. 2002, Kennedy et al. 2002). Fewer studies have investigated the temporal-spatial patterns of plant invasions and the processes that shape those patterns (Auld and Coote 1980, Moody and Mack 1988,

Andow et al. 1990, Hastings 1996, Radosevich et al. 2003). Genetic analyses are currently the approaches most frequently used to address the latter questions.

Genetic data should be useful in inferring whether an invasion proceeded along expanding fronts(i.e. leading edge dispersal) or through long-distance dispersal events

(i.e. jump dispersal) followed by local expansion (Auld and Coote 1980, Moody and

Mack 1988, Radosevich et al. 2003; Wilson et al. 2008). Molecular markers could be used to test putative sink-source relationships among populations to determine the pattern of invasions. It has been proposed that a strong correlation between genetic distance and

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physical distance between potential source populations and satellite populations is indicative of colonizing fronts (Cousens and Mortimer 1995, Radosevich et al. 2003). In contrast, lack of correlation is considered indicative of high dispersal (Radosevich et al.

2003). In addition, high levels of intrapopulation variation would suggest long distance dispersal due to seed flow arising from different source areas.

The relative importance of long-distance dispersal has major implications for invasion rate, as well as management and control. Long distance (1-10 km) dispersal of only a very small proportion of seeds can lead to an order of magnitude increase in spread rate, according to a mathematical model of Higgins and Richardson (1999), leading these authors to highlight the need for more data on long-distance dispersal. Prediction of the sites most likely to be invaded by target species will improve the monitoring and control of early invasions, as well as ―slow-the-spread‖ programs for established invasions

(Lodge et al. 2006). If advancing fronts shape invasion, then appropriate tactics would include searching for recruits in susceptible areas near such fronts, as well as eradication efforts starting at the fronts and working back. As long as individuals are persistently removed from the perimeter, there need be no further worry about continued advancement from that population (Moody and Mack 1988). If, however, long-distance dispersal is more important for the establishment of new populations, detection and removal of such ‗nascent foci‘ before maturation and the ability to act as seed sources for future generations is more important than control of well-established populations and a larger area must be monitored (Moody and Mack 1988).

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I investigated the genetic structure of woodlots invaded by Amur Honeysuckle,

Lonicera maackii (Rupr.) Maxim. (Caprifoliaceae), one of the most problematic invasive shrubs in forests of eastern USA (Luken and Thieret 1995). Lonicera maackii is a large, upright, partially self-compatible shrub native to the Russian Far East, China, Korea, and

Japan, that was first introduced into the United States in 1898 (Luken and Thieret 1995;

Goodell and Iler 2007). Additional introductions from Asian populations and accessions from European botanical gardens were made by the USDA at least 14 times over the following 86 years (Luken and Thieret 1995). The Soil Conservation Service developed and promoted cultivars for wildlife habitat and food, screens and wind barriers (Sharp and Belcher 1981; Lorenz et al. 1991; Luken and Theiret 1995), and these cultivars have been widely used in horticulture. Naturalized populations were first described in the late

1950s (Braun 1961) and now occur in Ontario and nearly every U.S. state east of the

Mississippi (Pringle 1973; Dirr 1977; Trisel and Gorchov 1994). Naturalized populations of L. maackii have thrived in these regions, growing to become the dominant shrub species in the secondary forest understory (Hutchinson and Vankat 1997). The success of this shrub is likely related to its: ability to grow in a variety of light environments (Luken

1988), limited herbivory (Trisel 1997); extended leaf phenology (Trisel 1997; McEwan et al. 2009); and avian dispersal (Bartuszevige and Gorchov 2006).

Several studies indicate negative effects of L. maackii on native forest plants.

Stands where L. maackii has invaded have lower herb and tree seedling and sapling density and species richness (Hutchinson and Vankat 1997, Hartman and McCarthy

2008) and lower tree basal area growth (Hartman and McCarthy 2007). Within stands,

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herb and tree seedling abundance and richness were lower under L. maackii (Collier et al.

2002). Experimental studies showed that L. maackii reduced survival and seed production of forest annuals (Gould and Gorchov 2000), growth and reproduction of perennials

(Miller and Gorchov 2004), and survival of tree seedlings (Gorchov and Trisel 2003,

Hartman and McCarthy 2004). Dorning and Cipollini (2006) found that L. maackii leaves and rootsystems inhibit the germination and growth of native herb species and determined that allelopathic effects persist in soil after roots and leaves are removed.

The invasion history of L. maackii in southwestern Ohio (Figure 1) is known primarily from herbarium specimens of naturalized shrubs, as reported by Trisel (1997).

The earliest record is from 1952 in Hamilton County, one of the earliest records in the

U.S., and the only county in Ohio where it was described as naturalized by Braun (1961).

For Butler County the earliest record is from Oxford in 1962; Hutchinson and Vankat

(1998) report it was planted in Oxford around 1960 and subsequently naturalized and spread to the north. In Montgomery and Miami Counties, the earliest specimens are from

1977; the earliest naturalized population known was established near Dayton around

1970 (D. Geiger, pers. comm.). The earliest specimens for Warren and Preble Counties are 1988 and 1993, respectively. The earliest specimen from Darke County was collected in 1995 (M. Vincent, pers. comm.), and by 2002 several woodlots in southern Darke

County had been invaded by L. maackii (Bartuszevige et al. 2006). In Indiana the earliest record is from Wayne County, in 1964.

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Three likely potential paths of L. maackii invasion in Darke County are: 1) from the south from Hamilton and/or Butler County via Preble County (proposed by

Hutchinson and Vankat 1998), 2) from the southeast from Dayton, and 3) from the southwest from Richmond (Wayne County) Indiana, where large established shrubs were found in the Hayes Arboretum (HA in this study). To investigate the plausibility of these invasion paths, and the importance of expansion vs. long-distance dispersal, I investigated the genetic structure of L. maackii among different woodlots in and around

Darke County. Specifically, I quantified the relatedness of these stands and whether these results support any of the proposed invasion paths through the region.

Methods

Study area. This study was conducted primarily in southwestern Ohio in 3 of the 35 counties where Lonicera maackii has been documented (Figure 1; Darke, Preble, and

Butler; Trisel 1997). Seventeen (17) well established woodlots were selected for sampling along a south to north transect in the vicinity of the supposed convergence of the three suggested invasion pathways. Samples included one potential source population from southwest Ohio (Butler County) and one from Indiana located just a few miles west from the Ohio line (Wayne County). The other 15 locations represent a sample of more recently established woodlots in Preble and Darke Counties. Leaf samples were collected from seven well-established sites. Maximum distance between study locations was just over 57 kilometers, while the minimum distance between them was 2 kilometers.

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Leaf tissue collection. In plots with lower L. maackii density, leaves were collected from all available plants with the aim of acquiring samples from 30 individuals. In plots where

L. maackii was more abundant, collection efforts were focused on larger, and thus older, individuals. To reduce the likelihood of sampling related individuals, leaf tissue was taken from plants located at least 5 meters apart. Overall, between eight and 37 plants from each sampling sties were collected for a grand total of 376 plants.

Leaf material was collected during the autumns of 2007 and 2008 from each individual and placed in a resealable zip-lock plastic bag. These bags were then kept in a cooler with dry ice to preserve the integrity of the DNA. On return to the laboratory, all leaf material was stored in a -40°C freezer until DNA extraction. Total genomic DNA was extracted from leaves of each honeysuckle plant, using a modification of the CTAB protocol described by Cullings (1992) and Doyle and Doyle (1987).

Patterns of genetic variation were inferred using five microsatellite marker loci specifically developed for Lonicera maackii (ATG Genetics, Table 1). All forward primers were labeled with WellRED fluorescent dyes (D4 or D3, Integrated DNA

Technologies). PCR reactions were performed using a PTC-200 (MJ Research,

Watertown, MA, USA) in 20 l solution containing 5 μl of genomic DNA, 10mM Tris buffer, pH 8.0, 10 mM MgCl2, 0.2 mM dNTPs, 0.4 μM primer of each primer, and 1 unit of Taq polymerase (Fermentas). The PCR program used included an initial step of 1 minute of denaturation at 94°C, 35 cycles of 30 s at 94°C, 30 s at 55°C and 1 minute at

72°C, and a final extension cycle of 5 minutes at 72°C. Genotyping was conducted using capillary electrophoresis on an automated genetic DNA analysis system (CEQ 8800,

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Beckman Coulter, Fullerton, CA, USA). Four microliters of PCR product were mixed with 28 μl of formamide and 0.4 μl of 400 bp DNA size standard (Genolab) for capillary electrophoresis. Fragments were identified on basis of their size and according to their mobility in relation to the size standard using a cubic function.

Genetic Data Analysis. Genetic diversity was quantified by the mean number of alleles per locus (Na), the effective number of alleles per locus (Ne), observed heterozygosity

(HO), and Nei‘s expected heterozygosity (HE, Nei 1973) for each locus and averaged across all loci for all analyzed woodlots using the program POPGENE 1.31 (Yeh et al.

1999). Genetic differentiation was determined using the infinite allele model FST (Weir and Cockerham, 1984), and the degree of relatedness between sampling sites, based on

Nei‘s genetic distances, was represented in a dendrogram. Analysis of molecular variance

(AMOVA) was conducted to determine the level of differentiation between woodlots using genetic analysis software GENALEX 6 (Peakall and Smouse 2006).

Spatial analysis of genetic diversity. To test whether genetic differentiation was caused by dispersal limitation, a Mantel test was conducted to determine the relationship between geographical distance and genetic differentiation between sample sites (Fst/(1-

Fst)) as proposed by Rousset (1997). Pairwise values of Fst were calculated of using

GENALEX 6 (Peakall and Smouse 2006). Correlation between pairwise values of the geographic distance and genetic differentiation was examined using Mantel correlation analysis (Mantel version 2; Leidloff 1999). I also examined the correlation between

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pairwise values of the geographic distance and Nei‘s genetic distance using Mantel correlation analysis.

I used the program Structure (version 2.3.1; Hubisz et al. 2009) to infer the existence of distinct clusters based on a Baysian clustering method. For this analysis, a series of runs were used to estimate Pr(X|K), where X represents the data, for K between

1 (the expected value if all populations represent a single panmictic unit) and 17 (the maximum number of populations). Using the options to ignore population affiliation when defining genetic clusters, assuming independence among loci, and allowing admixture, independent runs were conducted following a burn-in period of 10,000, for each value of K (Pritchard et al. 2000). Once the number of genetic clusters was established, each individual was assigned to the genetic group for which its inferred ancestry was the highest. At the same time, all individuals were grouped according to their location of origin to determine the contribution of each of the K clusters to the genetic make-up.

Results

Allelic diversity. There were high levels of allelic diversity in the L. maackii stands I studied. All five loci examined were polymorphic across all 17 sampling locations, and allele frequencies were variable across woodlots, with many alleles present at low frequencies. A total of 123 different alleles were found across all five loci, with an average of 12.3 alleles per locus. The average number of alleles per locus (Na) in each L. maackii study site averaged 7.6 (Table 1). However, average effective number of alleles per locus (Ne) was lower than Na, having an overall average of 4.4 across all locations.

21

Heterozygosity. Levels of heterozygosity were high across all woodlots. Observed heterozygosity (Ho) in each location averaged 0.7105, while the overall average expected heterozygosity (HE) was 0.7649 (Table 2). High expected and observed heterozygosity and number of alleles (Na) found in these locations suggest high levels of genetic diversity and a low level of inbreeding.

Population differentiation. The low levels of inbreeding were further supported by the

F-statistics calculated for each locus (Table 3). The mean fixation index (FIS), synonymous with the inbreeding coefficient, was found to be 0.0350 when calculated across all loci. Mean FST was also low: 0.1042. Such a low occurrence of inbreeding suggests that most of the genetic diversity in L. maackii is present within each woodlot.

The analysis of molecular variance (AMOVA) supports this result, showing that 92% of the observed variation arises from differences within woodlots.

Spatial analysis of genetic diversity. A Mantel test revealed significant isolation by distance (IBD), based on a positive correlation between genetic differentiation (FST/(1-

FST; as proposed by Rousset 1997)) and geographical distance (correlation coefficient =

0.5547, p<0.05). Similarly, the analysis also showed a positive correlation between Nei‘s genetic distance (Table 2) and geographic distance (correlation coefficient = 0.3566, p<0.05; Figure 2).

22

Population structure. Analyses of the genetic structure using two different approaches were consistent, and indicate multiple well-defined clusters among the individuals sampled. In general, individuals from sample sites at the two geographic extremes remain distinct from other analyzed collection locations; OHR to the south and JM and NEWJ to the north comprise their own distinct clusters. Between these two extremes, individuals from the additional 14 sampling locations have a higher likely to fall within five additional clusters. Moving northward from OHR, individuals from the woodlots referred to as CX, HA, and NP are significantly related. Although located between woodlots dominated by members of the latter cluster, individuals from 379 and WHIN belong to their own distinct cluster with a unique genetic identity. Individuals from SOLL, NMILL,

SELL, EE, and BOW have a high likelihood of belonging to the same cluster and are all grouped together within a fifth cluster. Similarly, individuals from MILL, FORE, and

ROY are significantly related among themselves and form the sixth cluster. Located in close proximity to both cluster five and cluster six, samples from WOLV remain genetically separated from each and form the seventh Structure cluster. The remaining two of the nine clusters are not well represented in any of the 17 sampling locations.

However, individuals with a high likelihood of belonging to these clusters are found in

FORE and MILL (eighth cluster) and NEWJ (ninth cluster). Overall, Structure results reveal that there is high level of admixture among individuals found in any given location, as evidenced by the differences in differ in their highest likelihood of belonging to different clusters (i.e. the proportion of each color in the vertical bars in Figure 5).

The log likelihood values for each proposed number of groups (K) are illustrated

23

in Figure 4, while Figure 5 shows the model‘s predictions for K=9. Structure also provided a graphic depiction of the estimated membership coefficient in each cluster for each individual examined (Figure 5).

Discussion

This study is a first attempt to characterize the genetic diversity and population structure of L. maackii in southwestern Ohio. This information is used to make preliminary inferences about the colonization patterns and range expansion of this invasive shrub. My findings indicate that there are high levels of genetic diversity among analyzed woodlots in southwestern Ohio, and that genetic differentiation among locations is positively correlated with geographical distance. Furthermore, an examination of the relatedness between sampling sites strongly suggests the presence of multiple cultivars or invasion pathways. However, once a new cultivar becomes established or L. maackii invades a new region, the species appears to spread outward from that focal point through a local expansion process known as diffusion.

Genetic diversity. Lonicera maackii shows high levels of heterozygosity and low levels of inbreeding. These results are similar to those observed in Carduus acanthoides

(Mandák et al. 2009) and Centurea diffusa (Marrs et al. 2008) in their invasive ranges.

Both species are reported as being predominant or obligate outcrossers, which could contribute to explaining the high proportion of genetic variation found within each sampling location and the low levels of differentiation between locations. Another factor proposed to contribute to the high genetic diversity of invasive populations of C.

24

acanthoides and C. diffusa, as well as Ambrosia artemissifolia, is multiple introductions

(Genton et al. 2005; Marrs et al. 2008; Mandák et al. 2009). The patterns of genetic diversity of L. maackii reported here may be attributable to these same factors. The high levels of heterozygosity and low inbreeding (FIS) values in these L. maackii individuals both indicate there is little inbreeding, supporting the hypothesis that this species is partly self-compatible but predominantly an outcrosser (Goodell and Iler 2007).

A significant proportion of the genetic diversity (8%) was found among woodlots; a level of genetic differentiation within the range reported by Hamrick and Godt (1990) for short-lived perennials. While this percentage is not large, my finding that the overall average of Nei‘s genetic distance between sampling sites is high (0.50; range 0.34 to

1.37) reveals that the genetic differences among locations are significant. Moreover, the strong correlation between genetic distance and physical distance also support the existence of a well-defined structure across the landscape and not merely the effect of random sampling of genes in each woodlot. In order to test this hypothesis, the sample size must be expanded. Additional woodlots are currently being sampled and analyzed.

When added to the results presented here, we may be able to more fully understand the population structure of L. maackii stands in southwestern Ohio.

The argument that high within-population variation of certain invasive plants in their introduced ranges is a consequence of multiple introductions (Genton et al. 2005;

Marrs et al. 2008) can be applied to L. maackii. At least seven independent introductions of L. maackii were made to the United States between 1898 and 1927 (Luken and Theiret

1996). The United States Soil Conservation Service then promoted planting of the shrub

25

for soil erosion control and wildlife habitat between 1960 and 1984, and seeds of the cultivars that they developed were widely distributed in many states. Five additional introductions from Asia occurred during these years (Sharp and Belcher 1981; Lorenz et al. 1991; Luken and Theiret 1996). Many different cultivars were, and continue to be, present throughout the country, and may continue to increase the genetic diversity present in the study area.

Genetic structure. The genetic differentiation among L. maackii study sites in southwestern Ohio was typical of short-lived perennials, Other invasive plants that exhibit similar levels of genetic differentiation and high genetic diversity include

Carduus acanthoides (Fst = 0.085) (Mandák et al. 2009), Ambrosia artemissifolia (Fst =

0.052) (Genton et al. 2005), and Senecio gallicus (Fst = 0.15) (Comes and Abbott 2000).

In contrast, high levels of genetic variation among locations across the introduced range have been reported for Alliaria petiolata (FST = 0.789), Cirsium arvense (Fst = 0.64 (Solé et al. 2004), Fst = 0.28 (Slotta et al. 2006)), and Ulex spp. (FST = 0.64 to 0.84) (Cubas et al. 2005). Such high levels of genetic differentiation in these latter species may have arisen from independent naturalization of populations from genetically distinct sources.

The clusters proposed by the program Structure appear to be the result of genetic differences alone. No field observations were collected during onsite sampling events that would explain differences between L. maackii individuals collected from various woodlots. Across all sampling locations, the landscape remained a consistent land use; fragmented forested woodlots scattered throughout an agricultural matrix. While the level

26

of land management effort varied with the ownership of the property, no observable differences in the local plant community were identified. At the scale currently analyzed, the pollinators or dispersers responsible for the transmittance of genetic material between shrubs is not likely to dramatically change. Soils at the north and south extremes of the study area remain similar. The two most prevalent soil types near New Madison, Darke

County (i.e., in the vicinity of the JM, NEWJ, EE, WOLV< ROY, SELL, FORE, SOLL,

NMILSS, NOW, and MILL woodlots) were Crosby silt loam and Miamian silt loam.

Each of these are derived from loamy till parent materials, have a moderately high capacity to transmit water, have moderate available water capacities, and have a calcium carbonate content of between 40-45%. The differences between these lie in their drainage capabilities (Crosby silt loams are somewhat poorly drained while Miamian silt loams are well drained), and Miamian silt loams have a much deeper water table. At the southern extent (i.e., near Oxford and the OHR woodlot), the most prevalent soil type is Russell-

Miamian silt loams. Like the more northern soils, this complex is derived from loamy till, is well drained, has a moderately high ability to transmit water, a deep water table, and a similar calcium carbonate content (i.e. 35%). The difference lies in the high available water capacity of the Russell-Miamian silt loams.

With similar soil, landscape, and ecological communities across the extent of the study area, the genetic basis for the differences in Structure clusters is supported. The only observable difference between sampled woodlots was in the abundance and size of the present L. maackii individuals. With no other discernable morphological differences between locations, the variations in number and size were attributed to the length of time

27

since invasion. Woodlots with larger, more abundant shrubs were assumed to contain older individuals and have been invaded for a longer period of time than woodlots with small or few individuals.

The distinctiveness of the proposed clusters may be attributed to independent invasions involving different sets of L. maackii cultivars. These invasions, likely spreading from escaped ornamental specimens in the populous areas of Oxford or

Richmond may be advancing the species northward or eastward from these points. An additional invasion pathway spreading from the north to the south may also exist, potentially arising from individuals planted by the Soil Conservation Service.

Alternatively, the nine clusters may correspond to different subpopulations derived from the same initial invasion (naturalization event). If this is the case, L. maackii subpopulations colonizing Darke County from different directions must represent distinct sampling of the gene pool of the original invasion. These two alternative explanations each potentially explain the observed genetic structure of L. maackii in this region.

However, the number of distinct clusters and the stark distinctions of some woodlotsfrom others within close geographic proximity provide support for the presence of multiple introductions or cultivars within the study area.

In addition to outcrossing and multiple introductions, the extensive seed dispersal of L. maackii may contribute to maintenance of high levels of genetic variation within woodlots. Lonicera maackii produces copious fruits, and seeds are dispersed by five bird species in the study area; the most important are likely American robins (Turdus migratorius) and European starlings (Sturnus vulgaris) (Bartuszevige and Gorchov

28

2006). White-tailed deer also disperse viable seeds (S. Castellano, unpubl. data). Because these animals are capable of traveling long distances, new populations might be founded by seeds from multiple sources, resulting in the establishment of stands with high levels of genetic diversity and showing relatively low divergence from other nearby woodlots.

The results of the Structure analysis indicated that my sampling sites consist of individuals with genotypes that resemble more than one of the identified genetic clusters.

Once new woodlots are invaded, they may serve as propagule sources, facilitating gene dispersal and reducing genetic differences with other nearby woodlots.

Another possible cause for the movement of genetic material from one site to another is through insect pollinators. Lonicera maackii is a mostly self-incompatible species; as such, it relies upon bees and insects for pollinations (Goodell et al. 2010).

During a 2006-2007 study, Goodell et al. (2010) observed 155 flower visits by 62 individual insects. These visitors belonged to eight bee genera and two fly families. Such pollination visits are likely responsible for much of the localized spread of L. maackii.

These insects likely transmit large amounts of pollen (i.e. genetic material) across short distances, which maintains the genetic diversity of invaded woodlots and introduces genes from one woodland into another. The fact that some L. maackii individuals appear to be more closely related to individuals found in a different woodlot than the one in which they were found could be attributed to insect pollination (Figure 5).

Patterns of colonization. The distribution pattern of genetic variation and level of differentiation among locations can be used to infer whether new patches of L. maackii

29

were founded by diffusion from nearby locations or through long-distance dispersal

(Sakai et al. 2001). Genetic structure, using isozyme markers, at the landscape level was used to infer that long distance dispersal (associated with flooding events) occurred in

Boltonia decurrens and that colonization events involved seeds from three to five source populations (DeWoody et al. 2004). Genetic structure was similarly used by Hu et al.

(2009) to argue that seed dispersal in Fraxinus mandshurica was affected by landscape features and that seed dispersal during regular flooding impedes the development of spatial genetic structuring among populations. Each of these studies found no relationship between geographical distance and the level of genetic differentiation among populations, and concluded there was no evidence of isolation by distance.

I hypothesize that this invasive shrub spreads through the establishment of focal sites through long-distance dispersal followed by diffusion. Short-distance diffusion is supported by studies by Bartuszegive et al. (2006) and Hutchinson and Vankat (1997).

Bartuszegive et al. (2006) found that proximity to the nearest town was the only factor that significantly explained the presence v. absence of L. maackii in woodlots in southern

Darke County, with woodlots < 4 km from a town much more likely to be invaded than those > 4 km, and they suggested that cultivated or feral shrubs in these towns were the primary source of seeds that initiated woodlot invasion. Hutchinson and Vankat (1997) found that L. maackii cover in forest stands within 12 km of Oxford, Ohio, was inversely related to distance from that city, suggesting gradual diffusion. My findings that genetic distance is correlated with geographic distance suggest that woodlots are often colonized by seeds produced in nearby woodlots, where naturalized L. maackii shrubs have been

30

established and have reached reproductive age. Evidence for long-distance dispersal comes from my finding that some sampling sites were distinct from nearby locations; colonization from distant seed sources could result in plots with a genetic makeup that is very different from other nearby woodlots (i.e., JM was distinct from the nearby SOLL and NMILLS sample sites).

The results presented here also provide insight on the importance of the three potential invasion paths. The great diversity observed among the individuals of the 17 sample locations included in this study suggests that more than one of these paths may be influencing the genetics of L. maackii in southwestern Ohio. The likely presence of ornamental shrubs in the nearby towns and metropolitan areas, including Richmond, IN and Oxford and Dayton, OH possibly led to the incorporation of alleles from various horticultural strains of the species. The most northerly of the 17 study locations, JM, is genetically the most distinct of the included woodlots, but based on the large size of individuals, is not the youngest (Steve Castellano and David Gorchov, personal observations). This suggests the distinctiveness of the JM woodlot is more likely due to an independent invasion involving a different L. maackii cultivar than divergence from a larger invasive wave from any one direction. The hypothesis that certain varieties of an introduced species are more aggressive or have adaptations that enable them to better exploit the new range is supported by findings for species such as Cortaderia selloana, where two of seven identified cultivars accounted for over three quarters of the invasive populations (Okada et al. 2007) . The next step is to investigate the genotypes of L. maackii cultivars and the history of their planting in Ohio, as well as sample additional

31

naturalized individuals from invaded woodlots, to elucidate the roles of different cultivars in this invasion.

Acknowledgements

I would like to thank the landowners in southwestern Ohio who graciously allowed us to collect samples on their property. S. Krock, M. Monfredi, and M. Ross assisted with lab work. B. Wilfong and S. Castellano provided maps used to locate

Lonicera maackii study sites and contact property owners in the region. S. Castellano and

M. Rocha assisted with field work. This study was funded by grant # 2007-02924 from the U.S. Department of Agriculture National Research Initiative to DLG, OJR, and Mary

Henry.

32

Table 1: Oligonucleotide primer sequences, repeat motifs, number of alleles, product sizes, and annealing temperatures for each of the five microsatellite loci used in this study

Allele

# Size

Locus Repeated Sequence Alleles Range Annealing

Motiff Temperature

Di3 F CA9 AAAAGGCAAAGAAGCTCTTGGCA 7 216-228 55

Di3 R AGAAAAGAAGTCAGACTCTGCA

Di4 F CT19 CTCATTCAGTCAAGTCCAAGT 11 125-147 55

Di4 R CGATGCTACATCATAATTAACAG

Di19 F CT12 CGTGTTCCCCTTCTCTCACT 16 236-272 60

Di19 R CGGGGCTGCTTATCTTCTTC

Tri8 F GAA15 TCAAACGAGCTCCTAGATTGTAAA 13 141-177 55

Tri8 R GTTAGCGTGTTGCGTTCACT

GTAT6.

Tet21F GTAT7 GCCTCCACCGATCTACTTCA 11 157-197 55

Tet21R TCGGACGGTCGTTATGTGTA

33

Table 2. Mean number of alleles (Na), mean effective number of alleles per locus (Ne), mean observed heterozygosity (Ho), and Nei‘s mean expected heterozygosity (He) for the

17 study sites of Lonicera maackii from southwestern Ohio, USA, included in this study.

Standard deviations are shown in parentheses.

Effective Sample Sample Observed number of H H Site Size number of Alleles O E Alleles CX 18 6.60 3.78 0.76 0.73 (2.30) (1.32) (0.23) (0.10) OHR 29 9.00 5.14 0.66 0.80 (3.24) (1.32) (0.31) (0.08) SOLL 27 7.20 3.98 0.65 0.76 (1.48) (0.72) (0.18) (0.05) HA 31 6.80 4.45 0.75 0.72 (3.90) (2.57) (0.20) (0.16) JM 27 7.80 3.96 0.73 0.72 (2.59) (1.53) (0.25) (0.14) NMILLS 8 5.20 3.59 0.76 0.76 (0.84) (0.80) (0.23) (0.09) NP 18 6.40 3.74 0.66 0.70 (2.07) (1.77) (0.22) (0.14) ROY 23 10.40 5.28 0.69 0.81 (1.52) (1.89) (0.09) (0.09) MILL 14 7.20 4.79 0.80 0.79 (2.49) (1.93) (0.12) (0.12) EE 8 4.60 3.46 0.78 0.69 (1.34) (1.02) (0.30) (0.08) 379 37 9.20 4.37 0.78 0.78 (1.48) (0.69) (0.14) (0.04) WHIN 22 9.20 5.05 0.72 0.80 (3.27) (1.47) (0.17) (0.08) FORE 12 6.60 4.19 0.60 0.78 1.52 (1.15) (0.04) (0.08) SELL 26 7.20 4.93 0.70 0.80 (1.30) (1.29) (0.07) (0.05) NEWJ 19 7.80 4.35 0.66 0.77 (1.30) (1.55) (0.17) (0.08) BOW 36 9.00 5.14 0.69 0.79 (2.45) (2.39) (0.13) (0.08) WOLV 21 8.60 5.31 0.72 0.81 (2.07) (2.14) (0.10) (0.09) Overall 376 7.58 4.44 0.7105 0.7649

34

Table 3: Nei‘s unbiased genetic distance between all pairs of sampling locations.

35

Figure 1: Location of the seventeen sample sites of Lonicera maackii in southwestern

Ohio included in this study. Distances between sites range from 2-57 km.

36

0.35

0.3

0.25

0.2

0.15

0.1

Nei's Genetic Distance Genetic Nei's 0.05

0 0 10 20 30 40 50 60 Geographic Distance (km)

Figure 2: Relationship between Nei‘s unbiased genetic estimates between pairs of woodlots and their corresponding geographic distances.

37

.

SELL BOW WOLV ROY FORE SOLL NMILLS MILL EE JM NEWJ HA NP CX 379 WHIN OHR

Figure 3: Dendrogram showing the degree of relatedness between sampling sites based on Nei‘s unbiased genetic distances. JM is worth noting due its apparently distinct genetic background, yet close geographic proximity to the NMILLS and SOLL sites.

38

K 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 0

-1000

-2000

-3000

-4000

-5000

-6000

-7000 Estimated ln Probability Data of Probability ln Estimated

-8000

-9000

Figure 4: Mean log likelihood values for each value of K, where K indicates the number

of distinct cluster. Mean log likelihood values ranged from -7501.3 when K=1 to -6804.7

when K=9.

39

Figure 5: Estimated population structure for Lonicera maackii study sites in southwestern

Ohio. Each individual is represented by a thin vertical line, which is partitioned into K colored segments that represent the individual‘s estimated membership fractions in K inferred clusters. In this case, K = 9. Black lines separate individuals of different sampling locations. These locations are organized from south to north.

1=OHR 7-MILL 13=BOW 2=CX 8-SOLL 14=ROY 3=379 9-FORE 15=WOLV 4=WHIN 10=NMILLS 16=JM 5=HA 11=SELL 17=NEWJ 6-NP 12=EE

Chapter 3

General Conclusions

The Amur honeysuckle, Lonicera maackii, is an aggressive shrub species native to the Russian Far East, China, Korea, and Japan that has become well established throughout much of the eastern United States (Pringle 1973; Dirr 1977; Trisel and

Gorchov 1994; Luken and Thieret 1995). Though naturalized populations in Ohio were first described in 1952, this species has achieved rapid spread due to the introduction of multiple accessions, limited competition and herbivory, extended leaf phenology and its natural ability to grow in a variety of light environments (Luken 1988; Luken and Thieret

1995; Trisel 1997; McEwan et al. 2009). Observations of the spread of L. maackii and the currently limited existence of effective control methods indicate that this invasive is likely to persist in and continually expand its current range.

Prior research has focused on understanding the general traits of L. maackii and the effect this species has on the native plant community. The work presented in the preceding chapters represents a first attempt at looking beyond the present status of the shrub toward the future concerns this species may pose as it continues to spread.

Characterizing the method and direction of range expansion will help predict where this species is likely to next appear and better prepare residents and land managers in their preparation of control methods.

40 41

This work analyzed 17 naturalized L. maackii subpopulations in four counties along the Ohio-Indiana border. Through the utilization of the methods described in

Chapter 2, these 17 woodlots were found to exhibit low levels of inbreeding and high levels of heterozygosity. Such results are typical indicators of high population diversity, possibly caused by gene flow between different woodlots, the presence of multiple known cultivars, and the ardent promotion of the shrub by the United States Soil Conservation Service throughout the region.

Understanding that this species is mostly self-incompatible and maintaining its diversity through cross-pollination with individuals from different locations or of diverse accessions, it follows that some sample sites will be more closely related than others.

The 17 sampling sites were plotted on a dendrogram based upon Nei‘s genetic distances. This exercise supported the fact theory of closely related species; a Structure test verified these results and placed the 17 locations into nine distinct clusters. These clusters were composed as follows: 1) OHR; 2) CX, HA, NP; 3) 379, WHIN; 4) SOLL,

NMILL, SELL, EE, BOW; 5) MILL, FORE, ROY; 6) WOLV; and 7) JM, NEWJ. No entire sampling location fell within either of the final two Structure clusters; however, certain individuals from the MILL and FORE woodlots appear to be more closely related to an eighth cluster than their cohorts in cluster 5. Likewise, individuals from NEWJ appear to tend toward the ninth cluster, but the majority of individuals in that woodlot appear more closely related those analyzed from the JM site.

While the sample sites in each of the Structure clusters lie in close proximity to each other, other sites that are very geographically near to each other are placed in

42

separate clusters. This indicates that while IBD does occur, there remains a high level of genetic diversity among woodlots. Even though genetic material is being shared by these nearby subpopulations and bees have the ability to cross-pollinate the woodlots, they remain distinct.

Together, these data suggest the presence of multiple L. maackii introductions and the likely influence of more than one cultivar in the region of southwest Ohio. A second possible explanation is that the species spreads through long-distance dispersal events facilitated by avian frugivores. After an initial founder population becomes established, the shrub spreads outward through the process of diffusion. This process explains the clustering together, or high relatedness, of the most proximate sites. Overall, the above results led to the following conclusions:

 High levels of heterozygosity (HO=0.7105

 Low levels of inbreeding (FST=0.1042);

 The presence of nine distinct clusters of related sample sites, as indicated by the

program Structure and described above

The relatedness of woodlots in close proximity to each other suggests that L. maackii spreads through outward expansion after local introduction or long-distance dispersal events.

The identification of multiple possible invasion pathway indicates there is still much to learn about the dispersal methods of L. maackii before the locations of new populations may be accurately predicted.

43

Overall, the results of the work presented in this study indicate that the methodology proposed and employed wherein is effective in helping to characterize the invasion of L. maackii in this region. However, additional sample sites and ongoing analyses are required to fully illustrate the existing patterns of spread. The next step in this process is to collect samples between existing clusters, (i.e., ―fill in the gaps‖ on the map) as well as to the north and south of the existing study area. Through more research and a better understanding of the number, direction, and strength of invasion pathways, we can hope to better comprehend the characteristics of the species and to develop increasingly effective control methods.

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