Population Genetics and Breeding Ecology of the Rare Clonal Shrub, Spiraea Virginiana (Rosaceae)

Population Genetics and Breeding Ecology of the Rare Clonal Shrub, Spiraea virginiana (Rosaceae)

A dissertation submitted to the

Graduate School

of the University of Cincinnati

in partial fulfillment of the

requirements for the degree of

Doctor of Philosophy

In the Department of Biological Sciences

of the College of Arts and Sciences

Jessica R. Brzyski

M.S. Biology

Georgia Southern University, December 2006

Committee Chair: T. M. Culley, Ph.D.

ABSTRACT

Two of the most prevalent reasons cited for the decrease in species abundance are the loss and modification of habitat and the impact from invasive species. Riparian species face both of these challenges, being in a habitat that experiences abundant water flow modifications and experiencing a degree of disturbance which is often desired by invasive species. As a result, riparian habitat contains high levels of biodiversity, and also a high frequency of rare species.

Therefore, the goal of my research was to identify genetic and reproductive factors that may be hindering population growth of rare riparian species. Spiraea virginiana can be classified as a characteristic riparian shrub, is considered rare throughout its natural range, and it is suggested to be negatively impacted by competition with the invasive S. japonica. Using this study species, I examined the extent of both clonal growth and sexual reproduction, and seed germination potential using field and laboratory methods. Genetic analyses show that S. virginiana is highly clonal and populations are isolated from one another. Genetic data also indicate that S. virginiana is likely to have been rare for an extended time period rather than recently so.

Possibly as a consequence of long-term isolation, sexual reproduction is minimal and there is evidence to suggest that the self-incompatibility system is breaking down. When sexual reproduction does occur and seeds are produced, their viability and germination rates are low, being significantly lower than those of S. japonica. I conclude that the prolonged survival of S. virginiana has been the result of prolific clonal propagation. Although clonality allows the species to persist and expand, it greatly diminishes the adaptive potential of the species. The lack of mates in a self-incompatible system, or the ability to self, combined with low germination rate also contributes to the rarity of this species. Since many riparian species are both clonal and self-incompatible, the information and management recommendations provided through this research could also be applied to these species of similar life history to benefit restoration efforts. ii

Jessica R. Brzyski

iii

ACKNOWLEDGMENTS

Thank you to my graduate advisor, Dr. Theresa Culley, for all of her advice and guidance. I really appreciate the freedom she gave me to develop my own project. Thank you for accepting a person with virtually no genetic knowledge, and teaching me the genetic techniques and appreciation I needed to accomplish this research. Anyone who can take a field ecologist and turn her into a geneticist must be a great advisor. In addition, my Research

Advisory Committee: Dr. Eric Maurer, Dr. Stephen Matter, Dr. Steve Rogstad, and Sarena Selbo of the U.S. Fish and Wildlife Service, were all instrumental to the project and all provided valuable assistance in the construction and implementation of this research. Thank you all for your knowledge and experience, edits and comments, and general assistance throughout this research which has furthered my professional and personal development.

Due to the rarity of my study organism, I needed many permits to collect the samples necessary for this project and for that I thank U.S. Fish and Wildlife Service, National Park

Service, Daniel Boone National Forest, OH Department of Natural Resources, TN Department of

Environment and Conservation, and the Great Smoky Mountain National Park. The people in charge of permits were all extremely helpful and without them I would not have been able to do this research at all.

The assistance I received in the field was indispensable. I could not have done field sampling without the help of Martin McAllister (OH Department of Natural Resources), Andrea

Bishop (TN Natural Heritage Program), Deb White and Tara Littlefield (KY Natural Heritage

Program), Marie Kerr (Big South Fork NRRA), and Janet Rock (Great Smoky Mountains

National Park), who all took time out of their busy schedules to show me where my shrub lived.

They are some of the most knowledgeable and friendly people I have ever met who were not only helpful, but good company as well. iv

Thank you to The Arnold Arboretum at Harvard University for allowing me to conduct breeding experiments on their S. virginiana collection, while also providing me with funds to do it through the Deland Award. I particularly want to thank Michael Dosmann for his assistance in setting up this relationship, and Abby Hird, who was indispensable for the pollination study, from putting on pollination bags, to assisting in hand pollinations in the rain, to getting me to the airport on time.

I am very grateful for additional funding sources, which came from the Catherine H.

Beatty Fellowship by the Garden Club of America, the University Research Council, and

Wendel, Weiman, Benedict Award from the University of Cincinnati.

Lastly, thank you to the people that are my support system. I am infinitely grateful to

Dan Wetzel, my best friend and soon-to-be husband, who provided me with advice, guidance, and stress relief along the way. My parents, Madeline and Ronald Brzyski, and my brother

Michael, have supported me endlessly in everything I do. My family made me who I am today and I hope I make you proud.

TABLE OF CONTENTS

Abstract...... ii

Acknowledgments...... iv

List of Tables ...... vii

List of Figures...... viii

Chapter 1: General Introduction ...... 1

Chapter 2: Isolation and characterization of microsatellite markers in the rare clonal plant, Spiraea virginiana (Rosaceae)...... 10

Chapter 3: Genetic variation and clonal structure of the rare, riparian shrub Spiraea virginiana (Rosaceae)...... 20

Chapter 4: Capacity for sexual reproduction in the rare, riparian shrub Spiraea virginiana (Rosaceae)...... 55

Chapter 5: The effect of substrate and stratification in germination rate of a native rare shrub compared to a non-native congener ...... 79

Chapter 6: Managing rare plant species: how identifying when rarity occurred can inform management strategies...... 100

Chapter 7: General Conclusion...... 132

Appendix 1: Diagrams of Spiraea virginiana populations and their genotypes...... 140

LIST OF TABLES

Chapter 2

Table 1. Characterization of 11 microsatellite primer pairs developed in Spiraea virginiana. Table 2. Results from analyzing primers in three populations of Spiraea virginiana. Chapter 3

Table 1. Descriptive statistics averaged across loci for populations of Spiraea virginiana.

Table 2. Genetic description of clonal structure within populations for Spiraea virginiana.

Table 3. Average Pgen and Psex values for each genotype within each population of Spiraea virginiana taking into account FIS and number of ramets for each multilocus genotype (MLG) within each population. Table 4. Population assignment results, with confidence intervals (CI) as calculated from BayesAss+. Chapter 4

Table 1. Descriptive statistics of Spiraea virginiana at the self-incompatibility locus.

Table 2. Allele frequencies for the self-incompatibility alleles identified within eight populations of Spiraea virginiana. Table 3. Pollination treatments of Spiraea virginiana that produced fruits with viable seed.

Chapter 5

Table 1. Main effects of time to germination and germination success were analyzed separately between Spiraea virginiana and S. japonica using Kruskal-Wallis nonparametric test. Chapter 6

Table 1. Results from previous research conducted on Spiraea virginiana.

Table 2. List of populations of Spiraea virginiana that were collected, including the state where the population is located, population name, the number of subpopulations that were present within each population, and the number of subpopulations that contained unique alleles. Table 3. Pair-wise comparisons of population differentiation (θ) for Spiraea virginiana. Table 4. Pair-wise migration rates of sampled populations, with clones removed, of Spiraea virginiana.

vii

LIST OF FIGURES Chapter 3

Figure 1. Map of approximate locations of sample sites, represented by the dots, of Spiraea virginiana throughout Ohio, Kentucky, and Tennessee.

Figure 2. UPGMA phenogram of Spiraea virginiana populations constructed using genetic distances (θ).

Figure 3. Principal coordinates analysis of genetic distances among populations of Spiraea virginiana. Axis 1 explained 41.50% of the variation and axis 2 explained 19.15%. Chapter 5

Figure 1. Frequency distribution of the proportion of seeds for Spiraea virginiana and S. japonica by time to germination. Figure 2. Total percent germination of seeds in different growth substrate for Spiraea virginiana and Spiraea japonica. Chapter 6

Figure 1. Map of sampling distribution of populations of Spiraea virginiana. Figure 2. Sample genotype distribution within one population of Spiraea virginiana (OH1). Figure 3. Mantel test showing no correlation (r = 0.162, p = 0.264) between the two matrices of geographic distance and genetic distance (θ) among populations of Spiraea virginiana.

viii

CHAPTER 1

General Introduction

Jessica R. Brzyski

Department of Biological Sciences

University of Cincinnati

614 Rieveschl Hall

Cincinnati, Ohio, 45221, USA

Many plant species are declining in numbers worldwide because of detrimental human impacts on the environment such as urbanization and deforestation. Most rare species face the same general threats with the most frequent cause of plant species decline being habitat loss

(Wilcove et al. 1998). One specific habitat type that has been reduced dramatically is the riparian zone. By 1981, 70% of riparian communities in the United States had been lost (Brinson et al. 1981). One reason for this is the modification and fragmentation of streams and rivers, mostly from dam construction; only 2% of the rivers in the United States run unimpeded

(Abramovitz 1996). Riparian habitat tends to contain high levels of biodiversity, particularly of rare species, which are adapted to the frequent disturbance resulting from periods of flooding

(Naiman and Décamps 1997). Therefore, the impacts of riparian habitat loss on native species that are adapted to this unique environment are imperative to identify.

One such characteristic riparian species is Spiraea virginiana Britton, which requires a flooding regime for the removal of competitors, as well as for propagule dispersal (USFWS

1992). As a native shrub in the Rose family, this species is federally threatened and is in peril in every state it resides (USFWS 1990). To understand the components of species rarity, and to aid in the management and protection of S. virginiana, as well for similar species in riparian habitats,

I explored how genetic diversity and reproductive biology might contribute to rarity (described below). I also investigated the length of rarity (historical or recent) experienced by this species.

The first and most vital piece of information for rare species is population number and size (Schemske et al. 1994), which is also classified as a factor influencing rarity (Rabinowitz

1981). However, factors such as asexual reproduction, can greatly affect demographic information by inflating population estimates. As a result, each individual needs to be genotyped in order to determine if it is a clone, or a unique individual. A plant species capable of asexual

reproduction, as is characteristic of many riparian species, can lead to two different population genetic structures. Only a few, localized genotypes may comprise the population if clonal reproduction is the dominant method of reproduction (Janzen 1977). Alternatively, if sexual reproduction and gene flow is present, populations may be composed of many different genotypes (Price and Waser 1982).

Therefore, to examine the genetic composition of S. virginiana, I designed species specific microsatellite primers (Chapter 2). Using these primers, a genetic approach is utilized in

Chapter 3 to determine not only the number of individuals in a population but also to examine the amount of genetic variation that exists within the species. Rare species with small population sizes generally exhibit lower levels of genetic variation than common congeners (Hamrick and

Godt 1989, Ellstrand & Elam 1993). In addition, species that reproduce clonally also exhibit lower levels of genetic variation (Hamrick and Godt 1989, 1996). Therefore, both traits of rarity and clonality may work together to reduce overall levels of variation, but they might do so in difference capacities (Karron 1991, Balloux et al. 2003). In addition, if there are reduced levels of genetic variation, this could severely limit their ability to adapt to a changing environment

(Frankham 1995; Futuyma 2010), thus making conservation of the species even more imperative.

If individuals of a population are genetically identical as a result of frequent clonal reproduction and also exhibit self-incompatibility, then reproduction may be greatly inhibited.

Theory suggests clonality and sexual reproduction often occurs concurrently to provide reproductive assurance, and prevent the potential negative effects of inbreeding (Richards 1986;

Vallejo-Marin and O’Brien 2006). Therefore, if populations are predominantly clonal then the number of available mates would be limited, resulting in reduced seed production and long-term adverse effects on future breeding (Byers and Meagher 1992). Anecdotal information states that

S. virginiana is self-incompatible (SI) (USFWS 1992). To determine if this is true, in Chapter 4,

I investigated the breeding ecology of this shrub by performing controlled hand pollinations, while also identifying SI allelic richness within and among natural populations.

Habitat loss, especially of riparian habitat, is particularly disconcerting because it is a vital ecosystem; it consists of an interface between aquatic and terrestrial environments and thus creates a mosaic of landforms, communities, and environments (Naiman and Décamps 1997).

As a result of the diversity of the landscape, riparian habitat contains high species richness, particularly those species that are adapted to frequent disturbance by flooding (Naiman and

Décamps 1997). Riparian adapted plant species require a certain level of flooding not only as a mechanism for dispersal but also for the removal of competitors, opening the canopy to allow full sun exposure, and the creation of riverwash deposits for colonization.

Habitat specificity, which is another factor of rarity (Rabinowitz 1981), can directly impact germination and establishment potential. The habitat, including soil quality, flooding regime, and competitors, can greatly influence if and where a propagule colonizes. Water flow is important for dispersing seeds of riparian species and any water stabilization is detrimental to population migration (USFWS 1992). Species spatial distributions are limited by their ability to disperse and establish in additional areas (Gaston 1994), particularly when streams are often impeded (Abramovitz 1996). In regards to S. virginiana specifically, seedlings have never been recorded in nature (USFWS 1992). Therefore, in Chapter 5, I examined if the habitat, specifically soil, is negatively impacting dispersal and seedling establishment by comparing germination success in different growth media. In addition, cold stratification was also manipulated to determine the optimal germination protocol for this species.

Although habitat and species biology can have a major impact on the persistence of rare species, the second most frequent cause of species decline is the effects of invasive species

(Wilcove et al. 1998). Spiraea japonica, a non-native of concern because of its potential for invasiveness, may directly compete for resources, such as sunlight, space, and pollinators, and may also cross-pollinate with S. virginiana, resulting in hybrid plants and dilution of the native gene pool. Spiraea japonica was brought to the northeastern United States in 1870 for cultivation and is commonly used as a horticultural shrub (Remaley 2005). However, this species often escapes cultivation, becoming established and self-sustaining in natural environments (Remaley 1998). Non-native species may be better competitors than native species, which is often observed in measures of plant performance, such as growth and reproduction (Blossey and Nötzold 1995; Dahler 2003, Blair and Wolfe 2004). Negative effects by non-native species on those that are native, particularly species that are rare due to additional factors, could dramatically reduce their future survival and reproduction. Naturalized S. japonica shrubs have been observed growing next to S. virginiana (R. Gardner, pers. comm., J.

Brzyski, pers. observation) and therefore, the chance of competition exists. In Chapter 5, I conducted germination experiments to compare the time of germination and germination success between the native and non-native Spiraeas.

Lastly, before any management decisions can be made, the type of rarity exhibited by the species in question is important to identify (Barrett and Kohn 1991). Although rarity is often considered to be the result of rapid population reduction by human activities, species can also be classified as historically rare and thus, adapted to small population sizes (Barrett and Kohn

1991). One method of distinguishing between the two options of recent or historical rarity is to analyze population genetic structure, and the relationship between genetic and geographic

distance among populations. Higher levels of genetic structuring between populations are expected if they were isolated for an extended period of time (Barrett and Kohn 1991). In addition, a lack of a correlation between genetics and geography is also suggestive that populations have been isolated for many generations and genetic drift is the dominant evolutionary force (Young et al. 1996, Hutchison and Templeton 1999). Although historical information is not available for all species, it can be inferred from these genetic analyses. In the case of S. virginiana, data on historical population range and abundance does not exist so the length of time this species has been rare was investigated and that information was then applied to management suggestions in Chapter 6.

Of the three generally accepted factors that contribute to rarity in a species (restricted geographic range, narrow habitat specificity, and small local population abundance; Rabinowitz

1981), this research addressed the latter two. Generally, species with restricted habitat specificity are particularly vulnerable to habitat loss and degradation (Groom et al. 2006) but to clearly determine the causes behind the rarity of a species, the biology of the taxon in question also needs to be studied in detail (Gaston 1994). This study aimed to bring to light potential biologic, genetic, and habitat factors that are contributing to rarity of plants in riparian habitat using S. virginiana as a model system. With the knowledge gained through this study, possible solutions to prevent plant extinctions and to increase the range and abundance of rare riparian species may be possible.

Literature cited

Abramovitz JN. 1996. Imperiled waters, impoverished future: the decline of freshwater

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and status. FWS/OBS-81/17, US Fish and Wildlife Service. Washington, DC.

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CHAPTER 2

Isolation and characterization of microsatellite markers in the rare clonal plant, Spiraea

virginiana (Rosaceae)1

Jessica R. Brzyski

Department of Biological Sciences

University of Cincinnati

614 Rieveschl Hall

Cincinnati, Ohio, 45221, USA

1 Published in American Journal of Botany Primer Notes & Protocols in the Plant Sciences 97: e20-e22 (2010).

Abstract

Premise of the study: Microsatellite markers were developed in Spiraea virginiana, a

federally threatened native shrub found along stream banks, to specifically identify clonal

genotypes and measure population genetic variability.

Methods and Results: Eleven primer sets were developed using a non-radioactive

protocol. These revealed a moderate level of genetic variation, as indicated by the

number of alleles per locus (range=1-4) and an average observed heterozygosity of 0.595.

Select loci also amplified successfully in the related species Spiraea japonica.

Conclusion: Development of the markers described here is critical for the genetic

identification of clonal plants as a first step in demographic analyses, and is necessary for

the future conservation of this rare species. Amplification of the markers in S. japonica

suggests their potential utility in research regarding this species.

Key words: clonal; microsatellite; Rosaceae; Spiraea virginiana

Introduction

The amount of genetic diversity present in clonal species lacks any general pattern, often exhibiting high, intermediate, or low levels (reviewed in Ellstrand and Roose, 1987). Patterns of genetic diversity in clonal plants can further be complicated by processes such as hybridization and polyploidy (Eckert, 2002). In addition, lower levels of genetic variation are generally expected in rare species through such effects as genetic drift (Hamrick and Godt, 1989) though there have been many exceptions (reviewed in Gitzendanner and Soltis, 2000). This lack of consistency suggests the importance of investigating additional clonal and rare species to detect any discernible patterns in genetic diversity. One rare species of concern is Spiraea virginiana, a rhizomatous shrub in the Rosaceae, which is federally threatened under the United States

Endangered Species Act (USFWS, 1990). It is endemic to the Southern Blue Ridge and

Appalachian Plateau, occurring in seven states: Georgia, Kentucky, North Carolina, Ohio,

Tennessee, Virginia, and West Virginia. Although this is a wide distribution, the species is threatened by small population size as well as the threat of habitat modification (USFWS, 1990).

Spiraea virginiana is found along rocky, flood-scoured riverbanks and is negatively affected by any river manipulation. Depending on the major mode of reproduction (sexual or asexual), these populations may be composed of polymorphic genotypes or of a few, localized genotypes.

Although anecdotal information states that this species requires outcross pollen for successful sexual reproduction, the level of clonal spread is thought to be high (USFWS, 1992). As a result, it has been postulated that each population of S. virginiana could be a single individual genotype

(i.e. clone). Presently, no studies have specifically analyzed whether individual plants within a population are of the same genotype. To measure population structure within multiple

watersheds for the further protection and management of this species, I designed 11 microsatellite markers for S. virginiana.

Methods and Results

Genomic DNA was extracted from leaf tissue from an individual in an Ohio population using a modified cetyltrimethyl ammonium bromide (CTAB) method (Doyle and Doyle, 1987).

A DNA library was created using hybridization capture for enrichment of microsatellites according to the protocol by Glenn and Schable (2002). Genomic DNA was digested with

BstUI, and linkers were ligated to each end of the DNA fragments, and then hybridized to biotinylated oligo probes. Enriched fragments were recovered using PCR, then amplified using the TOPO TA Cloning kit (Invitrogen, Carlsbad, California). Transformed bacterial colonies containing nucleotide repeats were selected and used to construct a primary library. Of the hundreds of positive colonies identified, 71 were randomly selected and then amplified by PCR, and 51 of these (72%) contained fragments within the range of 250-1000 bp and were sequenced.

Eleven sequenced fragments (16%) yielded suitable primers, which were designed from the flanking regions of the microsatellite repeat (Table 1) using Primer3 software (Rozen and

Skaletsky, 2000).

Analysis of individual DNA samples was conducted by performing multiplex reactions that incorporated fluorescent labeling of the forward primers during PCR (adapted from

Schuelke, 2000; see Culley et al., 2008). All 11 microsatellite regions were amplified using an unlabeled reverse primer, a forward primer with a unique sequence attached to the 5’ end, and a third primer composed of the same unique sequence as the forward primer but with a fluorescent label (6-FAM, NED, VIC, or PET) attached to the 5’ end. PCR was conducted in 10-μl reaction

volumes using the Qiagen Multiplex kit with 5 μl Multiplex PCR Master Mix, 1 μl 10X primer mix, 0.2 μl DNA, and 3.8 μl dH2O. Primers were multiplexed in three different reactions: the

first one contained primers VS2, VS5, VS8, and VS10, the second group was composed of VS3,

VS4, and VS6, and the third group consisted of VS11, VS12, VS14, and VS17. Multiplex PCR conditions consisted of the following: 95°C for 15 min, then 30 cycles each of 94°C for 30 s,

57°C for 45 s, and 72°C for 45 s, followed by 8 cycles each of 94°C for 30 s, 53°C for 45s, and

72°C for 45 s. A final extension occurred at 72°C for 10 min. Samples were run at the Cornell

University BioResource Center on a 3730xl sequencer (Applied Biosystems, Fortune City,

California) using LIZ 500 internal size standard. Fragment analysis was performed with

GeneMarker version 1.75 (SoftGenetics, State College, Pennsylvania).

Individual loci were assessed in 91 plant samples collected throughout three populations,

(voucher barcode 00227408, A) located in southern Ohio (N=31), northern Tennessee (N=34), and southern Tennessee (N=26). These populations were chosen to maximize the possible genetic variation found within the species because they inhabit different watersheds that are geographically widespread. Most loci were polymorphic, except VS6, VS12, and VS17 in the

Ohio population, VS4 in the northern Tennessee population, and VS2 and VS12 in the southern

Tennessee population. This lack of polymorphism resulted in a low number of genotypes, of which there were 3, 6, and 3, in the three populations respectively. Total allele number per locus ranged from 1-4, and observed heterozygosity varied widely, ranging from 0-1 but averaging

0.595 across populations (Table 2). To determine if these loci would amplify in another species within the genus, multiplex reactions were conducted on seven samples of Spiraea japonica, a species commonly used in horticulture yet also capable of naturalization. This resulted in

successful amplification of all of the 11 loci except VS2. Four loci (VS6, VS8, VS11, and

VS17) exhibited polymorphism in S. japonica.

Conclusions

The 11 microsatellite markers developed for Spiraea virginiana are effective in identifying clonal genotypes. In such a highly clonal species, markers that are capable of discriminating between genotypes are required to identify individuals and quantify population genetics. These markers are now providing necessary information on the genetic status of this rare species, and can be utilized in conservation decisions. In addition, successful amplification of these markers in S. japonica will now allow investigation into any potential for hybridization of this species with native congeners and may also prove useful for horticultural breeding programs.

Acknowledgments

The author thanks T. Culley for lab equipment and assistance in primer development, T. Glenn for his protocol, and U.S. Fish and Wildlife Service, National Park Service, and state agencies for collecting permits. Field collections were assisted by M. McAllister (Ohio Department of

Natural Resources) and A. Bishop (Tennessee Natural Heritage Program). Funding was provided by the Catherine H. Beattie Fellowship from the Garden Club of America and the

Deland Award from Harvard University.

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plan. Newton Corner, Massachusetts, USA

Table 1. Characterization of 11 microsatellite primer pairs developed in Spiraea virginiana.

For each primer pair the following are reported: forward and reverse sequence, the repeat motif, fluorescent label, size range of the original fragment (bp), annealing temperature (Ta), and

GenBank accession number.

Size Fluorescent range Primer Sequence Repeat Label (bp) Ta (C) GenBank

VS2 F: AGCTCGTTGTGTAGCCGATT (TC)14 VIC 100-112 56 GU194460 R: ACCCTAAATCAACGGGCAAG

VS3 F: TCTTCGTGAGTGCAATCGTC (GT)6 6-FAM 206-208 56 GU194461 R: GTTCAAGCCCGTAGAAGTGC

VS4 F: TCTAGGCCGCACCTGACTAT (CTG)6 PET 248-260 56 GU194462 R: TGGCCTTAAATTACGGGATG

VS5 F: AAGCTAGGAAATGGGCTGTG (TAG)6 PET 185-199 56 GU194463 R: GAGCCACCACGAACAAGAA

VS6 F: TTCGCACTTGGTTTGTGATG (TG)8 6-FAM 161-182 56 GU194464 R: ATCAGATGTAGCACGCAACC

VS8 F: CGGAGAGATGCGAACTGG (GAGGA)4 VIC 118-139 57 GU194465 R: CAGTACCGAGGGAGCACAGT

VS10 F: CGAGTTATTACTTCTGTCTT (GT)6 6-FAM 267-312 54 GU194466 R: CATACCATGTGCCAACTGC

VS11 F: GCACAGAGTAGCCAGCAACA (CAG)4 PET 149-160 57 GU194467 R: AAGTGGTGGTGATTGGCATT

VS12 F: TTGCTGATGTAGATTGCTCGAT (TGG)4 6-FAM 164-169 56 GU194468 R: ACAGCCCCAAAGTGTAAACG

VS14 F: CGGTAATTGGTTGTGGATCA (TCT)10 VIC 226-240 57 GU194469 R: ACAGACCTTCGTGCTCCAGT

VS17 F: ATTCCTTCATTCCACCTCTT (TG)11 6-FAM 207-227 55 GU194470 R: ATGAGATGAGCGGTTTCCTG

Table 2. Results from analyzing primers in three populations of Spiraea virginiana. For each primer pair, the number of alleles (A) and average observed heterozygosity (Ho) are reported.

Sample size within each population (N) is indicated within parentheses.

Number of Observed alleles heterozygosity Ohio (N = 31) VS2 3 0.032 VS3 2 0.871 VS4 3 1.000 VS5 3 0.968 VS6 1 0.000 VS8 2 0.161 VS10 2 0.129 VS11 2 1.000 VS12 1 0.000 VS14 2 0.161 VS17 1 0.000 N. Tennessee (N = 34) VS2 3 0.463 VS3 2 0.500 VS4 1 0.000 VS5 4 0.765 VS6 4 0.742 VS8 2 0.500 VS10 4 1.000 VS11 4 1.000 VS12 2 0.000 VS14 4 0.500 VS17 4 1.000 S. Tennessee (N = 26) VS2 1 0.000 VS3 2 0.962 VS4 2 0.923 VS5 2 1.000 VS6 2 0.962 VS8 2 1.000 VS10 2 1.000 VS11 2 1.000 VS12 1 0.000 VS14 2 1.000 VS17 2 1.000

CHAPTER 3

Genetic variation and clonal structure of the rare, riparian shrub Spiraea virginiana

(Rosaceae)

Jessica R. Brzyski and Theresa M. Culley

Department of Biological Sciences

University of Cincinnati

614 Rieveschl Hall

Cincinnati, Ohio, 45221, USA

Abstract

Genetic diversity is often considered important for species that inhabit highly disturbed environments to allow for adaptation. Many variables affect levels of genetic variation; however, the two most influential variables are population size and type of reproduction. When analyzed separately, both small population size and asexual reproduction can lead to reductions in genetic variation, although the exact nature of which can be contrasting. Genetic variables such as allelic richness, heterozygosity, inbreeding coefficient, and population differentiation have opposite predictions depending upon the trait (rarity or clonality) examined. The goal of this study was to quantify genetic variation and population differentiation in a species that resides in a highly stochastic environment and is both rare and highly clonal, Spiraea virginiana, and to determine if one trait is more influential genetically than the other. From populations sampled throughout the natural range of S. virginiana, we used microsatellite loci to estimate overall genetic variation. We also calculated clonal structure within populations, which included genotypic richness, evenness, and diversity. Gene flow was investigated by quantifying the relationship between genetic and geographic distances, and population differentiation (θ) among populations. Observed heterozygosity, genotypic richness, and inbreeding coefficients were found to be representative of high clonal reproduction (averaging 0.505, 0.1, and –0.356, respectively) and the number of alleles within populations was low (range = 2.0-3.6), being more indicative of rarity. Population differentiation (θ) among populations was high (average = 0.302) and there was no relationship between genetic and geographic distances. By examining a species that exhibits two traits that both can lead to reduced genetic variation, we may find an enhanced urgency for conservation. Accurate demographic counts of clonal species are rarely, if ever, possible and genetic exploration for every species is not feasible. Therefore, the conclusions in

this study can be potentially extrapolated to other riparian, clonal shrubs that share similar biology as S. virginiana.

Keywords: conservation, disturbance, microsatellite, multilocus genotypes

Introduction

Many plant species of conservation importance are found in a variety of highly disturbed environments, including riparian areas in which their very existence along streams is subject to natural processes. In these areas, flooding can pose a significant challenge to plants, whose establishment on banks is threatened by unpredictable surges of water scouring the waterway following substantial rainfall events. To survive, plant species must be able to adapt to this highly stochastic environment in which suitable niches may be transitory and ephemeral

(Naiman et al. 1997). In addition, the resulting low density of individuals may further compound reproductive output if suitable mates cannot be found for sexual reproduction (Byers and

Meagher 1992). Dispersal of propagules and establishment of new plant populations is also highly dependent upon these stream flow events, which ironically not only destroy existing populations but also opens up suitable habitat for colonization (Naiman et al. 1997, Wintle and

Kirkpatrick 2007). Given the stochastic success of sexual reproduction in such an environment, dispersal and gene flow of these plants can be limited to movement of vegetative propagules

(rhizomes) and occasional seeds downstream within watersheds, as opposed to other non-riparian species in which both seed and pollen may be dispersed more broadly across the landscape

(Johansson et al. 1996, Merritt et al. 2010). However, water dispersal also potentially allows for long-distance gene flow between geographically connected, yet widespread populations

(Johansson and Nilsson 1993). Consequently, some riparian species may be naturally rare in terms of limited population sizes and numbers, but may experience unpredictable, long-term dispersal.

In addition to these natural challenges, riparian species today are further being threatened by anthropogenic alterations of the watershed itself. For example, streams throughout the world

are being dammed or modified (Brinson et al. 1981; Abramovitz 1996), often to enhance the water supply to urban and agricultural areas, facilitate construction of roads and buildings, or to provide hydroelectric power. Consequently, the environment to which riparian species have become adapted to over time, is now changing. Many of these species that were already naturally rare must now adapt to these new conditions, a procedure which requires suitable levels of genetic variation as the raw material for evolutionary change (Frankham 1995; Futuyma

2010).

Not surprisingly, conservation of genetic variation in rare species is considered a vital factor for the long-term survival of the species (Hamrick et al. 1991; Falk 1992). Although high levels of genetic variation are associated with evolutionary potential (Frankham 1995; Futuyma

2010), theory suggests that genetic variation in rare species is generally low due to the effects of genetic drift (Wright 1931) or directional natural selection (Van Valen 1965). Small isolated populations of rare species may exhibit reduced gene flow, leading to low rates of gene exchange as well as increased inbreeding, resulting in lower genetic variation (Ellstrand & Elam 1993).

Comparisons of genetic variation between rare and abundant species have shown that rare species generally exhibit lower percent polymorphism, number of alleles, and observed and expected heterozygosity among populations (Karron 1987; Cole 2003, Gustafsson & Sjogren-

Gulve 2002). Gitzendanner and Soltis (2000) also found that rare species generally exhibited a lower number of polymorphic loci, number of alleles, and observed heterozygosity. These effects could be further amplified in riparian areas in which scattered populations may be small in number with gene flow restricted to within waterways.

For those riparian species which have adapted to their unpredictable environment through asexual reproduction (clonality), an additional concern is present. Asexual reproduction, when

examined alone, can result in unaltered or increased genetic variation due to random or preferred elimination of genotypes, respectively. However, asexual reproduction is most commonly associated with lower genetic variation in comparison with species that are obligate outcrossers.

Hamrick and Godt (1989, 1996) found that asexually reproducing species had significantly lower percentages of polymorphic loci and number of alleles per locus than those species that reproduce sexually. Genotypic richness will also decrease as the rate of asexual reproduction increases (Balloux et al. 2003).

Although both rarity and asexual reproduction may lead to reduced overall genetic variation, the exact nature of the variation may differ and one trait may have a stronger effect than the other. In particular, heterozygosity is expected to decrease in rare species as a result of inbreeding (Karron 1991) but it may increase in clonal species due to divergence of alleles within loci (Birky 1996). This high level of heterozygosity is correlated with strong negative FIS

values; whereas FIS is positive in populations of low abundance due to inbreeding (Wright 1965,

Halkett at al. 2005). Population differentiation should be higher in rare species due to the lack of

gene flow among populations with an associated decrease in variation within populations

(Ellstrand & Elam 1993). Conversely, simulations suggest population differentiation is expected

to decrease with clonal reproduction, with the majority of genetic variation occurring within

populations as opposed to among populations (Balloux et al. 2003).

In this study, we examined genetic variation within the rare, clonal shrub Spiraea

virginiana which inhabits streambanks in eastern North America. We measured the level of

genetic variation within and among populations while also identifying the clonal structure of S.

virginiana. Given that the riparian habitat provides an opportunity for long distance dispersal by

both seed and rhizome, we also measured levels of local and long distance gene flow. The

resulting genetic variation of S. virginiana was then compared to patterns documented for other rare or clonal plant species. By examining genetic variation in the context of the natural and anthropogenic challenges imposed on the riparian environment, we gain further insight into the complex patterns of genetic variation that exist in a highly clonal, rare species from the riparian zone.

Materials and methods

Study Organism

Spiraea virginiana Britton is a perennial rhizomatous shrub in the Rosaceae family. It is endemic to Southern Appalachia and occurs in small populations in seven states in the United

States: Georgia, Kentucky, North Carolina, Ohio, Tennessee, Virginia, and West Virginia

(USFWS 1992). It is a characteristic riparian shrub: it is sun loving, capable of vegetative spread, has wind and water dispersed seeds, and requires a flooding regime (Naiman & Décamps

1997) for dispersal as well as for the removal of overstory competitors (USFWS 1992).

Reproduction is thought to be primarily through asexual means, specifically rhizome growth by both phalanx and guerilla strategies (USFWS 1992), although sexual reproduction has also been documented (J. Brzyski, personal observation). This flood-adapted shrub is imperiled globally, with a G2 ranking (Center for Plant Conservation 2010), and was federally listed as threatened in

1990 under the U.S. Endangered Species Act of 1973. This species is in peril in every state it resides, being listed as either threatened (KY and GA) or endangered (OH, NC, TN, and VA), and in WV, due to the lack of threatened and endangered legislation, is classified as critically imperiled (USFWS 1990).

Field Collection

Sampling took place throughout 2008-2009 and was conducted in three states within the natural range: Ohio, Kentucky, and Tennessee (Fig. 1). Within those states, eight different locations within watersheds (called “populations” hence forth) were visited with varying numbers of subpopulations within each. Subpopulations were defined as a grouping of plants, regardless of the number of genets (which were determined later). Five subpopulations were sampled in population OH1, two subpopulations were sampled in KY1, seven subpopulations within KY2, five subpopulations within TN1, 15 subpopulations in TN2, three subpopulations in

TN3, four subpopulations in TN4, and two subpopulations in TN5. Due to the rare nature of the species, leaf samples were collected from every plant clump (a cluster of stems originating from one central area) that did not have a visual connection with another. Every plant clump was sampled within the area except for five subpopulations in TN2, which were substantially large, covering ~ 50 m2 area; thus a random sample of leaves were collected from both the exterior and

interior of the plant cluster. A total of 406 samples, representing in most cases all genotypes

present in each population, were collected for DNA extraction.

DNA extraction

DNA from leaf tissue was extracted using a modified CTAB method (adapted from

Doyle & Doyle 1987). DNA was amplified using 11 DNA microsatellite markers that were

designed for S. virginiana (Brzyski 2010; see also Chapter 2). Analysis of individual DNA

samples was conducted by performing multiplex reactions that incorporated fluorescent labeling

of the forward primers during PCR (adapted from Schuelke 2000; see Culley et al. 2008).

Multiplex PCR conditions were conducted at the following conditions: 95°C for 15 min, then 30

cycles each of 94°C for 30 s, 57°C for 45 s, and 72°C for 45 s, followed by 8 cycles each of

94°C for 30 s, 53°C for 45s, and 72°C for 45 s. A final extension occurred at 72°C for 10 min.

Amplified samples were run at the Cornell University BioResource Center on a 3730xl sequencer (Applied Biosystems, Fortune City, California) using the LIZ 500 internal size standard. Fragment analysis was performed with GeneMarker version 1.75 (SoftGenetics, State

College, Pennsylvania).

Data analysis

For all genetic analyses, except where otherwise stated, repeated multilocus genotypes

(MLG) within a subpopulation were designated as clones, and therefore, removed from analysis.

Descriptive statistics of overall genetic variation were calculated using GDA 1.1 (Lewis &

Zaykin 2001). These statistics included observed heterozygosity (Ho), expected heterozygosity

(He), mean number of alleles per polymorphic loci (Ap), percent of polymorphic loci (P), and

inbreeding coefficient (f). The inbreeding coefficient, analogous to Wright’s FIS (Wright 1965), was calculated, as well as deviations from Hardy-Weinberg equilibrium and linkage disequilibrium (Lewis & Zaykin 2001).

To determine if the number of polymorphic markers used was sufficient in discriminating clonal diversity, a resampling jackknife procedure was performed in GENCLONE 2.0 (Arnaud-

Haond & Belkhir 2007) using 1000 permutations. All clones were included but individuals with

missing data (23 individuals) were excluded from GENCLONE analyses. All MLGs were

identified and additional statistics calculated include genotypic richness, which was calculated as

G/N where G is the number of genotypes and N is the number of sampled ramets (Ellstrand &

Roose 1987), Simpson evenness, and Pareto distribution (Arnaud-Haond et al. 2007a). The

Pareto distribution is influenced by both genotypic richness and evenness and has been shown to more accurately represent genotypic diversity than other more commonly used indices, such as

Simpson and Shannon-Weiner (Arnaud-Haond et al. 2007a). This distribution provides information about the frequency distribution of clonal lineages and their replicates.

Analyzing genetic variation of clonal species presents the problem of deciding what level of genetic identity is acceptable, given potential scoring error, when determining if two ramets represent the same clone instead of being very genetically similar. We used both Pgen(f) and

Psex(f), calculated using GENCLONE 2.0, to determine the resolving power of the developed microsatellites. These values are based on the Parks and Werth (1993) round robin method while also incorporating the estimated FIS for populations (Young et al. 2002), and thus takes into

account departures from Hardy-Weinberg equilibrium. Pgen is the probability that identical

genotypes would arise from sexual reproduction under random mating. Psex measures the

probability that the observed number of identical genotypes encountered in a sample originated from sexual reproduction. When Psex values fall below 0.01, it can be concluded that those

identical genotypes originated from the same genet (Arnaud-Haond et al. 2007a, b).

To analyze the level of genetic differentiation among populations, we used GDA 1.1 to

calculate θ, an analog to Wright’s FST (Weir & Cockerham 1984). Weir and Cockerham’s

(1984) θ indicates the degree of genetic differentiation among populations, particularly when

determining differences among populations with small and unequal sample sizes. Significance

of θ estimates for both individual populations and pairwise comparisons was tested by

bootstrapping across loci with 1000 replicates and a 95% confidence interval. Genetic distances

(θ) between subpopulations were clustered using the Unweighted Pair Group Method using

Arithmetic averaging (UPGMA). Principal coordinates analysis (PCA) was also conducted

using GenAlex 6.1 (Peakall & Smouse 2006) to further visualize clustering among individuals and populations by genetic distance.

Analysis of molecular variance (AMOVA) was performed to quantify hierarchical genetic differentiation within and among populations using GenAlex 6.1 (Peakall & Smouse

2006). Genetic distances (θ) were calculated using the 11 microsatellite loci, and geographic distances were determined from GPS coordinates taken in the field. A Mantel test was used to examine correlations between genetic and geographic distance among populations as an indication of long distance dispersal and among subpopulations within population as an estimate of short distance dispersal. An overall rate of migration (Nm) was calculated as [(1/FST)-1]/4

using GenAlex 6.1 (Peakall & Smouse 2006). Less than one migrant per generation is generally

assumed to be insufficient to counterbalance the effects of genetic drift, and migration is thus considered negligible (Wright 1931; Maruyama 1970).

The program GENECLASS2 2.0 (Piry et al. 2004) was used to determine reference

populations for each individual based on their genotype. It can be inferred that any individual

with a reference population other than where they were sampled might be an immigrant. For

each subpopulation, the likelihood of those individual genotypes originating within its original

sampling site was calculated using the Bayesian criterion of Rannala and Mountain (1997) for

1000 simulations using a Monte Carlo algorithm (Paetkau et al. 2004). BayesAss+ 1.3 (Wilson

& Rannala 2003) was used to estimate overall migration rates among populations occurring

within the last several generations. The number of iterations performed was 3 x 106 with samples

being collected every 2000 iterations and a burn-in of 106 generations.

Results

After Bonferroni correction, all of the 11 microsatellite loci in three populations (OH,

TN3, TN5) were found to be in Hardy-Weinberg equilibrium. All other populations had at least two loci out of Hardy-Weinberg equilibrium with variable linkage disequilibrium. All loci except for VS12 were polymorphic. Populations had an average number of 2.71 (range = 2.0-

3.6) alleles per polymorphic locus (Table 1). Considering each locus separately with all populations grouped together, the average number of polymorphic alleles was 6.4 (range: 4.0-

8.0). Sixty-two percent of all alleles occurred in at least two populations, with 14% occurring in all eight populations. All watersheds had private alleles, ranging from one in OH1 and KY1 to

11 alleles in TN2, comprising 38% of the total alleles.

The observed heterozygosity for all populations was higher than the expected heterozygosity, averaging 0.503 and 0.391, respectively (Table 1). Average inbreeding coefficient values among populations were –0.238 and three of the populations (TN2, TN3, TN5) were significantly different from zero after bootstrapping across loci with a 95% confidence interval.

Permutations from GENCLONE 2.0 indicated that 11 loci were more than adequate for

identifying distinct multilocus genotypes (MLGs), determined when the number of discriminated

MLGs asymptotes with the number of loci analyzed (Arnaud-Haond & Belkhir 2007). Out of

406 total samples collected throughout the entire sampling range, 38 MLGs were identified. No

multilocus genotypes were shared among populations. Twelve genotypes differed by a single

locus, thus potentially indicating either scoring error or somatic mutation. Of these, four differed

by two base pairs, but the others differed by many more with the highest being 28 base pairs.

This result may indicate that somatic mutations are more likely the cause of these single allele

differences. For subsequent analyses, these genotypes were treated as unique. When examining subpopulations, 25 of 43 were composed of only a single genotype.

Genotypic richness was low for all populations, with a mean ± SE of 0.127 ± 0.017

(range: 0.067-0.191). Mean evenness was calculated as 0.530 ± 0.11 but was highly variable, ranging from 0.130 to 0.954 across populations (Table 2). The slope of the Pareto distribution for the entire sampling area was 0.315 ± 0.04 (r2 = 0.833, p < 0.0001). This low slope is

indicative of skewed distribution with populations of S. virginiana mostly consisting of a few

prevalent genotypes and many low frequency genotypes. When examining the number of ramets

within each genotype, this pattern holds true with the exception of KY1, in which the two

genotypes were of relatively equal abundance. However, both of these two genotypes

completely dominated the subpopulation in which they occurred.

The probability of identical genotypes arising from random mating (Pgen) was low, less

than 0.01, in all populations (Table 3). The probability of the observed number of repeated

identical genotypes (Psex) was similarly low for all populations (Table 3).

Average genetic differentiation among populations (θ) was 0.302 (θ range = 0.038-

0.547), and all pair-wise θ values were significantly different from zero, indicating that there is substantial genetic differentiation between populations. A phenogram constructed with these genetic distance measures (Fig. 2) revealed that there was no clustering by geographic proximity.

When examining the Tennessee populations specifically in more detail, two populations that are the closest genetically (θ = 0.183) are separated by ~110 kilometers, and those that are closest geographically, separated by ~ 44 kilometers, are the furthest apart genetically (θ = 0.546). The

PCA performed using genetic distances also indicated a lack of clustering among populations with axis 1 explaining 41.50% of the variation and axis 2 explaining 19.15% (Fig. 3).

Values of differentiation among subpopulations also indicated a lack of local dispersal within some populations. Average genetic distance (θ) was 0.141, which increased to 0.238 when repeat genotypes were left in the analysis. However, values were highly variable, ranging from

0.025 to 0.581.

The results of the AMOVA indicated that 68% of the existing genetic variation was found within populations as opposed to among populations (32%), and was highly significant (p

= 0.001). The Mantel test indicated that there was no significant correlation between geographic distance and genetic distance among populations (Rxy = 0.114, p = 0.168). In addition, Mantel

tests performed among subpopulations within the same population also indicated there was also

no correlation.

Population assignment calculated by GENECLASS2 showed that 94.9% of individuals

were correctly assigned to their geographic population based on their genotype. There were four

individuals that were not assigned to their sampling location (p < 0.01). One individual from

KY1 was assigned to KY2, one from KY2 was assigned to KY1, one from TN1 was assigned to

KY1, and one from TN4 was assigned to TN5.

Overall migration rate per generation (Nm) was calculated as 0.528 using GenAlex 6.1.

Further analysis of migration patterns using BayesAss+ indicated that five populations (OH1,

KY2, TN1, TN2, TN3) showed evidence of migration from other populations (Table 4).

Although migration values were very low for most populations, KY2 and TN2 had a large

proportion of migrants, 0.21 and 0.30 respectively. KY2 received migrants from population

TN5, and TN2 have migrants from population OH1. It was also indicated that populations OH1

and TN3 had migration from the TN5 population. In all of these five populations, migration

rates from all other populations fell below 0.023.

Discussion

Species in highly stochastic environments experience many challenges to long-term survival. Adaptability to a changing environment, such as a riparian habitat, requires a suitable amount of genetic variation (Frankham 1995, Lande and Shannon 1996). However, many riparian plant species have small population sizes and reproduce clonally, which together can have a compounding effect in reducing genetic variation, although the exact nature of that variation can differ. In addition, one of these traits, either rarity or clonality, may have a stronger genetic effect over the other. The genetic differences between traits can be observed by examining specific variables, such as heterozygosity, allelic and genotypic richness, and population differentiation. After exploring the genetic variation exhibited by small populations of S. virginiana, we find that a species exhibiting both traits of rarity and clonality will exhibit an overall pattern of genetic variation that is a combination of those expected for each trait in isolation.

Populations of S. virginiana had low genotypic richness values near 0.10 (average =

0.127), providing evidence that observed genotypic diversity in this species follow that predicted for a highly clonal organism. However, this value might also be inflated because it included those genotypes that differed by only one locus (which may in part result from scoring error). If these genotypes are removed, the average richness value decreased to 0.087. Much higher values have been previously reported in other clonal plants. In a review of richness values,

Honnay and Jacquemyn (2008) listed an average value of 0.44 for other studies using SSR markers. Allelic richness for S. virginiana, however, was more comparable to those reported for rare species (i.e. England et al. 2002; Kikuchi & Isagi 2002; Van Geert et al. 2008) than when

compared to other outcrossing clonal plants (i.e. Reusch et al. 2000; Stoeckel et al. 2006;

Meerow et al. 2007).

Considering the low numbers of allelic and genotypic richness observed in S. virginiana, the heterozygosity levels are high and follow the predictions by Balloux et al. (2003), who found that, after analytical and stochastic simulations, asexual reproduction increases heterozygosity.

Conversely, levels of heterozygosity for rare species should decrease with genetic drift (Ellstrand

& Elam 1993). It is likely that the highly clonal nature of this species has allowed it to retain high levels heterozygosity, despite the rarity of the species in general.

In addition to high heterozygosity, levels of clonality can also be detected by negative inbreeding coefficient values (Halkett et al. 2005). The inbreeding coefficient, analogous to

Wright’s FIS, ranges from –1 to +1, with –1 representing strictly clonal reproduction (Wright

1965). All S. virginiana populations had negative inbreeding coefficient values but only four

exhibited highly negative values (> -0.40), indicating that clonal reproduction maybe the

predominant form of reproduction in those locations. Four populations (KY1, KY2, TN1, TN4) had inbreeding coefficient values closer to 0, suggesting that they may not be as strictly clonal.

In addition, the standard errors of FIS were relatively high at 0.24-0.74, which further suggests that the rate of clonal reproduction is high but not complete (Balloux et al. 2003). Therefore,

some level of sexual reproduction is likely occurring within or among some of the sampled

populations. While long distance dispersal within a river by either seed or rhizome is possible,

generally the majority of river dispersal is local (Johansson and Nilsson 1993). Subpopulations

within each of these four populations are highly differentiated from one another, with each subpopulation mostly consisting of a unique genotype, indicating that rhizome dispersal is insufficient in contributing to existing populations (although its role in establishing as of yet

unidentified populations remains unknown). Whether subpopulations are being established by seed or are differentiating through the accumulation of mutations is unknown.

In general, all populations sampled in this study had high levels of genetic differentiation among populations, which more closely follow the predictions of that for small population sizes as opposed to asexual reproducers (Ellstrand and Elam 1993, Balloux et al. 2003). When analyzing all pairwise comparisons between populations, the lowest θ value was 0.159.

Although four individuals were identified as having a different source population other than that of their sampling location (according to simulations from GENECLASS2), the overall migration

rate calculated for S. virginiana was below 1.0, suggesting little to no gene flow among any populations (Wright 1931; Maruyama 1970). Furthermore, there are no known unsampled populations of this rare species within the sampling region that could act as stepping-stones for

dispersal.

Analyzing genetic variation of clonal organisms can potentially produce confounding

results, as can be seen in those of the AMOVA because the reduction in sample size from the

removal of repeat genotypes may produce different results. Highly structured populations that have no gene flow among them should contain higher genetic variation among populations as

opposed to within (Young et al. 1996). While S. virginiana populations exhibited high levels of

genetic structuring, the majority of genetic variation existed within populations (68%).

However, of the 43 subpopulations sampled, over half of them were composed of a single

genotype. When clones of all genotypes are left in the analysis, the majority of the variation

shifts to being among populations (51%). These results are consistent with those of the Pareto

distribution, which indicates that S. virginiana populations are dominated by a few, large clonal

lineages. Whether the dominance of a single genotype is a product of random disturbance effects or related to genotypic differences in fitness is currently unknown.

The highly disturbed nature of the riparian zone may be causing populations to experience frequent turnover due to major flooding events. Recurrent population turnover will reduce genotypic richness within the population due to the smaller number of individuals re- colonizing the area, either by re-sprouting or by dispersal from another subpopulation while increasing population differentiation (Wright 1940). The genetic pattern exhibited by S. virginiana, particularly the high differentiation among populations, yet also sharing 14% of the total alleles, suggests that populations historically had a more continuous distribution and then became fragmented from one another, a process which may have led to clonal reproduction becoming more influential in the genetic pattern.

The isolation of populations could have a consequent negative effect on the sexual reproductive potential of S. virginiana. Although currently being investigated (J.R.B. & T.M.C, unpublished data), S. virginiana is generally assumed to be self-incompatible (USFWS 1992) as is often found in the Rosaceae. The lack of seedling recruitment that has been observed in S. virginiana (USFWS 1992) and the low levels of gene flow calculated in this study will further perpetuate populations being dominated by a limited number of genotypes and, as a result, limit the number of potential mates. This pattern may have been occurring for some time, explaining the very low values of genotypic diversity seen in this study and initial reports of a lack of sexual reproduction (USFWS 1992). If seedling recruitment does take place, it is more likely to happen at initial establishment as opposed to later in time when dense clumps may make the habitat potentially unsuitable for seedling establishment (Eriksson 1989).

The resulting genetic pattern we observed in this study, specifically high heterozygosity, and low genotypic and allelic variation, are indicative of clonal reproduction. Although this clonality has allowed the persistence of this species in highly disturbed habitats, it has resulted in low genotypic richness within populations, which may have detrimental impacts to sexual reproduction due to self-incompatibility, and on the ability of populations to evolve in response to changing evolutionary pressures in the riparian habitat. The genetic data from this study also indicates that the species has been fragmented for a long time, and yet it has been persisting, so perhaps levels of genetic variation have been enough to enable it to survive over time. However, that may change now that streams are being anthropogenically altered (instead of being natural altered in the past). Future research should aim to identify natural populations that are successfully producing seed and those that are not, and quantify levels of fitness between them.

This research shows the importance of examining population structure in species with multiple traits, clonality and rarity, to further understand how they influence genetic patterns in plant species. Knowledge of the biology of the species is vital in the recovery planning process

(Schemske et al. 1994). In the case of S. virginiana, the biology indicates high levels of clonal reproduction. This high rate of clonality affects not only the demographic information, since one genotype may visually appear to be many different individuals, but also the pattern of genetic variation within and among populations. Although an individual approach to conservation management is still desired for maximum benefit, knowledge of the patterns of genetic variation that exist in a rare, clonal species such as S. virginiana can potentially be applied to other species exhibiting these same traits.

Acknowledgments

The authors thank S. Matter, E. Maurer, S. Rogstad, S. Selbo, D. Wetzel, and two anonymous reviewers for editorial comments. Thanks to U.S. Fish and Wildlife Service,

National Park Service, Ohio Department of Natural Resources, and Tennessee Department of

Environment and Conservation for collection permits. We also thank A. Bishop, M. Kerr, T.

Littlefield, M. McAllister, J. Rock, and D. White for field assistance. Funding was provided by the Catherine H. Beatty Fellowship from the Garden Club of America and the University

Research Council Fellowship and Wendel, Weiman, Benedict Award from the University of

Cincinnati to J. Brzyski.

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Table 1. Descriptive statistics averaged across loci for populations of Spiraea virginiana. Listed are average sample size across loci with repeat genotypes within subpopulations excluded (N), percent polymorphism (P), number of alleles (A), number of alleles per polymorphic loci (Ap), expected (He) and observed (Ho) heterozygosity, and the inbreeding coefficient (f) with an *

indicating significantly different from 0 with a 95% confidence interval.

Population N P A Ap He Ho f OH1 6.91 0.727 2.00 2.38 0.306 0.416 -0.401 KY1 3.00 0.636 1.91 2.43 0.382 0.394 -0.040 KY2 9.54 0.909 3.36 3.60 0.530 0.582 -0.096 TN1 8.00 0.909 3.09 3.30 0.543 0.591 -0.095 TN2 31.73 0.727 3.00 3.50 0.376 0.573 -0.539* TN3 5.00 0.455 1.55 2.20 0.264 0.418 -0.704* TN4 6.00 0.727 1.91 2.25 0.280 0.303 -0.093 TN5 5.00 0.818 1.82 2.00 0.442 0.745 -0.843* Average 9.27 0.739 2.33 2.71 0.391 0.503 -0.238

Table 2. Genetic description of clonal structure within populations for Spiraea virginiana.

Number of Population Genotypes Evenness Richness OH1 3 0.391 0.100 KY1 2 0.954 0.067 KY2 9 0.886 0.191 TN1 6 0.851 0.194 TN2 9 0.301 0.074 TN3 3 0.306 0.143 TN4 4 0.424 0.129 TN5 3 0.130 0.120 Average 4.88 0.530 0.127 St. Dev 2.80 0.317 0.048

Table 3. Average Pgen and Psex values for each genotype within each population of Spiraea

virginiana taking into account FIS and number of ramets for each multilocus genotype (MLG)

within each population.

Population No. MLG ramets Pgen (FIS) Psex (FIS) OH1 A 2 -5.99E-10 -1.95E-07 B 4 2.52E-09 9.16E-20 C 24 1.34E-07 9.35E-124 KY1 A 12 2.50E-07 2.20E-53 B 18 2.09E-07 2.77E-86 KY2 A 1 1.05E-09 B 1 1.71E-10 C 3 9.22E-07 4.50E-08 D 4 1.68E-08 2.73E-17 E 5 3.73E-08 2.96E-16 F 6 7.31E-12 6.21E-46 G 10 2.44E-10 3.10E-70 H 15 1.94E-07 1.45E-70 TN1 A 1 -5.55E-21 B 2 -1.92E-12 -6.25E-10 C 2 -8.59E-14 -2.80E-11 D 6 -2.73E-12 -4.50E-48 E 8 4.46E-08 2.57E-38 F 12 4.29E-10 8.50E-84 TN2 A 1 4.81E-07 B 1 5.88E-09 C 1 -2.60E-12 D 1 1.22E-07 E 1 1.15E-09 F 7 2.41E-05 3.06E-16 G 11 1.65E-06 4.93E-40

H 86 7.09E-06 0.000 TN3 A 2 5.79E-06 0.002 B 2 -1.70E-07 5.40E-17 C 17 8.61E-07 4.88E-71 TN4 A 1 -7.27E-11 B 3 3.19E-11 5.40E-17 C 4 2.73E-10 1.17E-22 D 23 1.63E-08 3.73E-138 TN5 A 1 2.94E-09 3.30E-06 B 2 1.01E-08 3.30E-06 C 22 3.57E-09 2.41E-145

Table 4. Population assignment results, with confidence intervals (CI) as calculated from

BayesAss+.

Source Population Non-migrant rate (CI) Migration rate (CI) population OH1 0.708 (0.668, 0.803) 0.181 (0.063, 0.297) TN5 KY1 0.749 (0.670, 0.904) <0.085 - KY2 0.701 (0.667, 0.778) 0.205 (0.068, 0.307) TN5 TN1 0.724 (0.668, 0.849) 0.128 (0.034, 0.255) TN5 TN2 0.677 (0.667, 0.702) 0.300 (0.253, 0.327) OH1 TN3 0.724 (0.669, 0.842) 0.137 (0.035, 0.268) TN5 TN4 0.959 (0.863, 0.999) <0.007 - TN5 0.746 (0.670, 0.952) <0.09 -

Figure 1. Map of approximate locations of sample sites, represented by the dots, of Spiraea virginiana throughout Ohio, Kentucky, and Tennessee.

Figure 2. UPGMA phenogram of Spiraea virginiana populations constructed using genetic distances (θ).

KY1

KY2

TN1

TN5

TN3

TN2

OH1

TN4

Figure 3. Principal coordinates analysis of genetic distances among populations of Spiraea virginiana. Axis 1 explained 41.50% of the variation and axis 2 explained 19.15%.

CHAPTER 4

Capacity for sexual reproduction in the rare, clonal shrub Spiraea virginiana (Rosaceae)

Jessica R. Brzyski1, Theresa M. Culley1, and Abby Hird2

1 Department of Biological Sciences

University of Cincinnati

614 Rieveschl Hall

Cincinnati, Ohio, 45221, USA

2 The Arnold Arboretum of Harvard University,

125 Arborway,

Boston, Massachusetts 02130

Abstract

Reproductive and evolutionary success is often dependent upon levels of genetic variation, which in plants can be influenced by the self-incompatibility (SI) complex. Although self-incompatibility can provide assurance against inbreeding, it may result in reproductive constraints when species are at low abundance or are clonal reproducers. We studied the SI complex of a rare, clonal shrub, Spiraea virginiana, to determine its capacity for selfing. We did this by quantifying allelic richness and population differentiation at the S-locus, and by performing controlled hand pollinations among different genotypes. Results indicated that allelic richness was low; averaging only three alleles per population, and average genetic differentiation

(θ) among populations was moderate at 0.102. Hand pollinations resulted in very low viable seed production for both outcross and self pollinations. These results suggest low sexual reproduction opportunities, possibly as a consequence of low population sizes and prolific rhizomatous growth. Evidence also suggests the possible breakdown of self-incompatibility and the evolution towards selfing capabilities. These results provide an aid to conservation biology and restoration ecology by being applicable to other similar species of clonal riparian plants at low population abundance.

Keywords: clonality, gametophytic self-incompatibility, microsatellite, rarity, Spiraea virginiana

Introduction

In plants, self-incompatibility is highly associated with clonal reproduction (Richards

1986, Vallejo-Marín and O’Brien 2007). Self-incompatibility, determined by the S-locus, is comprised of tightly linked but distinct genes that control the alleles in the pollen and the pistil

(de Nettancourt 2001). Self-incompatibility prevents self-fertilization by recognizing and rejecting pollen that are expressing identical allele specificities as that of the pistils (de

Nettancourt 2001). The association of self-incompatibility and clonality has been postulated to allow for population growth and prevent inbreeding during times of pollen limitation (Baker

1955, Holsinger 2000, Charpentier 2002). However, it poses a potential danger to clonal species in fragmented habitats, namely leading to lack of compatible mates (Byers and Meagher 1992).

This is especially true in highly disturbed riparian habitat in which flooding provides a mechanism of dispersal by transporting seeds as well as clonal propagules such as rhizomes.

Although this promotes long distance dispersal, the dispersal of rhizomes followed by clonal growth can homogenize genotypic diversity within a river system, thereby reducing the number of compatible mates in a given area. Therefore, a self-incompatibility system can be a hindrance to sexual reproduction in populations of clonal plants in riparian habitat (Anderson and Stebbins

1984).

Rare species with a self-incompatibility system are also at a disadvantage because of their small populations, which can experience reduced genetic variation, including variation present at the S-locus. This reduction in variation could result in individuals being too genetically similar to allow sexual reproduction within a population. The number of available mates is then limited, possibly resulting in greatly reduced seed set (Byers and Meagher 1992) or even complete failure

of sexual reproduction (DeMauro 1993), and ultimately limiting evolutionary potential of a species (Frankham 1996).

Furthermore, small populations can exhibit high levels of population differentiation at neutral loci (Ellstrand & Elam 1993). Subdivision of populations can increase allelic richness for a species when compared to a panmictic population because each subdivided population could have their own set of unique alleles (Nagylaki 1985). In addition, Wright (1939) proposed that alleles at the S-locus could have high allelic richness as a result of negative frequency dependent selection. Conversely, theory also suggests that subdivided populations may have fewer S-alleles than a panmictic population due to the imbalance of selection and genetic drift

(Schierup 1998; Schierup et al. 2000). Empirical studies testing these two contrasting hypotheses by comparing neutral allele richness to S-allele richness in subdivided populations have been minimal (Castric and Vekemans 2004) but simulations have shown that subdivision reduces the number of S-alleles when compared to panmixia (Schierup 1998).

Gametophytic self-incompatibility, common in the Rosaceae, prevents sexual reproduction when the S-allele of a haploid pollen grain matches with an S-allele of a diploid pistil (de Nettancourt 1977, 2001). Spiraea virginiana Britton, a native rosaceous riparian shrub is categorized as self-incompatible (USFWS 1992) although there has been no empirical evidence to support this assumption. In addition, this species is rare throughout its natural range and is highly clonal. Populations of S. virginiana exhibit high levels of population differentiation at neutral microsatellite loci (Brzyski and Culley, Chapter 3). Whether this subdivision reduces S-allele richness has yet to be investigated but the effect of population differentiation is imperative for conservation and management decisions. The goals of this study are to first confirm the sexual reproductive potential in this species, and to then identify and

quantify S-alleles in S. virginiana throughout its natural range to determine the capacity for sexual reproduction. Due to the population structuring observed for neutral loci, we hypothesize that there will be low allelic richness at the S-locus. If this prediction is true, it may lead to dire consequences for the prolonged existence of the species.

Methods

Study Organism - Spiraea virginiana is a perennial rhizomatous shrub. It is endemic to

Southern Appalachia in the United States and occurs in seven states: Georgia, Kentucky, North

Carolina, Ohio, Tennessee, Virginia, and West Virginia (USFWS 1992). The species is federally threatened and locally endangered throughout its range (USFWS 1992), existing in mostly small, isolated populations. This species has been shown to be highly clonal (Brzyski and Culley,

Chapter 3) and although prolific seed production has been observed in natural populations

(Brzyski, personal observation), germination rates are relatively low (approximately 10%;

Brzyski & Culley, Chapter 5). Flowers are white compound corymbs and bloom between late

May and late July. The small seeds (2-3 mm in length) are dispersed by water and gravity

(USFWS 1992). Follicles begin to dehisce between late August and September.

For the current study, sampling of S. virginiana took place throughout Ohio, Kentucky, and Tennessee. Eight populations were visited and each population had a varying number of subpopulations. Subpopulations were defined as a cluster of plants, regardless of the number of genets, which were separated by at least 40 meters from the next cluster of plants or subpopulation. One population in southern Ohio (OH1) had five subpopulations; two populations in Kentucky (KY1, KY2) consisted of two and seven subpopulations, respectively; and five populations in Tennessee (TN1, TN2, TN3, TN4, TN5) consisted of five, 15, three, four, and two subpopulations, respectively. Leaf samples for genetic analysis were collected from

every plant clump (a cluster of stems originating from one common area) that did not have a visual connection with another. Every plant clump was sampled within the area except for four subpopulations in TN2, which were substantially large, covering an estimated 50 m2 area; so a

random sample of leaves was collected from both the exterior and interior of the plant cluster.

S-allele genotyping

To determine S-allele diversity in S. virginiana, we genotyped field collected samples at

the S-locus. Primers developed for amplifying the C1 and C3 conserved regions in the European

pear (Pyrus communis L.) (Zuccherelli et al. 2002) successfully amplified alleles in S.

virginiana. These primers were used for analysis at the S-locus, consisting of reactions that

incorporated fluorescent labeling of the forward primers during PCR (adapted from Schuelke

2000; Culley et al. 2008). Reactions included an unlabeled reverse primer, a forward primer

with a unique sequence attached to the 5’ end, and a third primer composed of the same unique

sequence as the forward primer but with a 6-FAM fluorescent label attached to the 5’ end. PCR

was conducted in 10-μl reaction volumes using the Qiagen Multiplex kit with 5 μl Multiplex

PCR Master Mix, 1 μl 10X primer mix, 0.2 μl DNA, and 3.8 μl dH2O. PCR conditions consisted

of the following: 95°C for 15 min, then 35 cycles each of 94°C for 30 s, 57°C for 45 s, and 72°C

for 45 s, followed by 8 cycles each of 94°C for 30 s, 53°C for 45 s, and 72°C for 45 s. A final

extension occurred at 72°C for 10 min. PCR samples were run at the Cornell University

BioResource Center on a 3730xl sequencer (Applied Biosystems, Fortune City, California) using

the LIZ 500 internal size standard. Fragment analysis of the PCR product was performed with

GeneMarker version 1.75 (SoftGenetics, State College, Pennsylvania).

Pollination Experiment

To determine if plants are capable of reproducing with their own pollen (self fertilization) or if they are dependent upon insect pollinators, controlled hand pollinations were performed at the Arnold Arboretum of Harvard University in summer 2009 and 2010. The Arnold Arboretum contains a collection from across the entire range of the species. Each S. virginiana clump within the arboretum was first genotyped at eleven neutral microsatellite loci (Brzyski 2010,

Chapter 2) to ensure the identification of the crosses. In 2009, seven inflorescences consisting of young buds were randomly selected from each of 12 different ramet clusters for each treatment.

Upon flowering, inflorescences were bagged with Delnet® fabric pollination bags with a mesh size of 200 microns to prevent insect visitation and subjected to three different treatments: 1) no manipulation (spontaneous self-pollination), 2) flowers pollinated from a different flower on the same plant (geitonogamy), and 3) flowers pollinated from a plant of a different genotype

(outcross-pollination). A control group that was unbagged with no manipulation to evaluate pollination under natural conditions was also included. For the arboretum pollinations, 26 accessions originally collected from seven different states (OH, KY, VA, WV, NC, GA, TN) were subjected to the above treatments. Only the outcross treatment had inflorescences emasculated before anthesis because the process was extremely time-consuming and it was difficult to ensure that all anthers were removed without the release of pollen due to asynchrony of anther anthesis. Pollinations in 2009 were performed before SI alleles were identified, so outcross pollen was supplied from a mixture of plants from different state localities. Based upon previous research (Brzyski & Culley, Chapter 3), there is no evidence of widespread genotypes, so a plant from a different locality is likely to be a different genotype. Because of the asynchrony of flowering time within an individual, sample sizes varied when the treatments were

applied. Fruits were collected in September 2009 and the number of inflorescences that set fruit was counted at that time. During the summer of 2010, outcross and self pollinations were repeated with a subset of plants of nine individuals at the arboretum. SI alleles had been identified by this time, and outcross pollinations were only conducted between individuals with different known SI alleles.

Of the inflorescences that set seed, the embryo of ten seeds from each inflorescence were dissected and placed in 1% tetrazolium solution to determine seed viability (Cottrell 1947). If there were additional seeds that were potentially viable by visual inspection, they were tested for germination as well. There were two incidences where this occurred: five seeds were tested from the bagged, no manipulation treatment and ten seeds were tested from the unbagged treatment.

These seeds were placed on moist filter paper and monitored until either germination occurred or after two weeks had passed. All seeds that did not germinate were dissected and tested for viability as described previously.

Statistical Analysis

Descriptive genetic statistics were calculated using the program GDA 1.1 (Lewis and

Zaykin 2001), and include allelic richness, percent polymorphic loci, observed and expected heterozygosity. To detect population structure at this locus, we also used GDA 1.1 to estimate θ, an analog to Wright’s FST (Weir and Cockerham 1984), which is a better measurement for small

and uneven population sizes. Due to the analysis being for a single locus, significance of θ was

determined by calculating a jackknife estimated standard error. In addition, S-allele frequencies

were calculated using GenAlEx ver. 6.4 (Peakall and Smouse 2006), and tested for isoplethy,

which is predicted under negative frequency-dependent selection (Wright 1939), using Mantel’s

(1974) statistic,

2 2 2 χ n-1 = (n-1)(∑Cj 4r /n)/(2r-4r/n) where n is the number of alleles observed, Cj is the number of times an allele occurs, and r is the number of individuals examined (Campbell and Lawrence 1981a).

The estimated total number of S-alleles in a population when all individuals were not sampled was determined using the equation,

a = n[1-(1-2/n)m] where a is the number of total S alleles in the population, n is the number of total effective S alleles identified, and m is the number of plants sampled in each population (Paxman 1963).

This equation was calculated for the entire sampling region combined, as well as for each separate population.

Repeatability was also performed with the following equation (Campbell and Lawrence

1981a), R = (m-n)/(m-3)

where m is the total number of alleles in the sample, and n is the number of different alleles identified. This equation provides an estimate of the thoroughness of allele sampling. On a scale from 0-1, 0 indicates that there are no repeats of alleles while 1 indicates that alleles are highly repeated and thus suggests all alleles in the population were sampled.

A G-test of independence was used to determine if there was a significant difference in seed viability among the different pollination treatments. This analysis was performed separately for the 2009 and 2010 experiments.

Results S-allele genotyping

Repeated multilocus genotypes, determined by nuclear microsatellite markers, within a subpopulation were designated as clones, and therefore, removed from analysis. As a result, 61 individuals were successfully characterized at the S-locus. Of these genotypes, 10 unique SI alleles were identified with an average of 3.125 alleles per population (range: 2-7 alleles; Table

1). Population differentiation was significant (average θ = 0.102) based on 95% confidence intervals using jackknife estimated standard error (0.054 ± 0.034). There were two private S- alleles in the OH1 population, one in KY2, and four in TN2.

S-allele frequencies for each population were calculated (Table 2) to test for equal allele frequencies. In five of the eight populations, we rejected the equal allele hypothesis. However, the three populations in which the equal allele hypothesis was accepted were those with the smallest sample sizes, consisting of seven or fewer individuals. When all individuals were tested

2 together, the allele frequencies were significantly not equal (χ 98 = 2761.7, p < 0.001). The total number of alleles, calculated with the Paxman (1963) equation, changed only slightly after the

correction for possible incomplete sampling, with the largest difference being 0.04, suggesting

adequately thorough sampling. Repeatability was high (0.941), again indicating that sampling

was thorough enough to capture the majority of the alleles present within populations. The high

level of repeatability increases the power of the Mantel statistic used to calculate allele

frequencies, therefore indicating that the inequalities were substantial to allow for rejection of

hypothesis (Campbell and Lawrence 1981b).

Pollination experiment

In the 2009 season, a majority of hand pollinations (91%) produced no fruit at all. The only treatments that produced viable seed were those control inflorescences that were unbagged and not manipulated, and those that were bagged but not manipulated in any manner (Table 3).

The unbagged treatment produced significantly more viable seed (G = 42.96, df = 1, p < 0.001) with all seeds tested being viable compared to the 29% seed viability rate from the bagged treatment. Of those treatments that produced viable seed, a subset not destroyed to test for viability was tested for germination. Due to the limited number of total seeds produced, five seeds were tested from the bagged, no manipulation treatment and all five successfully germinated. Of the ten seeds tested from the unbagged treatment, one successfully germinated.

Results from 2010 showed the same low fruit production; 85% of the hand pollinations yielded no fruit. Because the S-alleles had been identified by 2010, crosses were categorized as having received pollen from a different S-allele, the same S-allele, or with same flower pollen.

Of the 15% of inflorescences that did form fruit, viable seeds were produced in all three categories (Table 3). There was 30% fruit production when inflorescences were pollinated with different S-allele pollen resulting in 12% viable seed production. Inflorescences that received pollen from the same S-allele produced fruit 40% of the time, and 40% of those seeds produced were vaible. Lastly, 3% of the self-pollinations produced fruits and only 10% of the seeds were viable. This difference among the three treatments was statistically significant (G = 39.66, df =

2, p < 0.001).

Discussion

Self-incompatibility is a genetic mechanism used to prevent self-pollinations, thereby reducing the negative effects that can result from inbreeding depression. However, in species with low population abundance, there may be low allelic richness at the S-locus resulting in reduced chances for successful sexual reproduction (Byers and Meagher 1992). Those species that experience prolific clonal reproduction may also experience reductions in sexual reproduction as a result of mate limitation (Anderson and Stebbins 1984). In species that are at low abundance and are clonal, it is therefore important to determine reproductive capacity by identifying and quantifying S-alleles within and among populations. Using S. virginiana as a model, we found that a rare and clonal species exhibits low allelic richness at the S-locus, thus providing it with minimal sexual reproductive opportunities which may explain its low seedling recruitment in natural populations.

We identified a total of 10 S-alleles in eight populations of S. virginiana spanning from southern Ohio to Kentucky and Tennessee, with an average of only three alleles per population.

This number of alleles is smaller than the range reported by Lawrence (2000), who found that reports of allelic richness for gametophytic self-incompatible species generally range from 13 to

45 S-alleles. Only one population of S. virginiana had more than three S-alleles, and three of the eight populations had only two, which is below the minimum of the three alleles necessary for compatible crosses. This low S-allele diversity is detrimental to the future of those populations because theoretically a population cannot persist in the long-term with less than three S-alleles

(Wright 1939, Campbell and Lawrence 1981a). Castric and Vekemans (2004) state that such a low number of S-alleles is only possible in the event of extreme isolation among populations, which can be represented by the level of genetic differentiation among populations.

Population differentiation at the SI locus for this study was moderate, averaging 0.102, which is lower than the population differentiation values calculated for S. virginiana at neutral microsatellite loci, which was 0.302 (Brzyski & Culley, Chapter 3). This value corresponds with predictions of the S-locus, which state that population differentiation is expected to be less at the

S-locus than at neutral loci as a result of the balancing selection that occurs at this locus

(Muirhead 2001; Castric and Vekemans 2004). Only three of the ten S-alleles identified were shared among all populations, further indicating structure among populations.

In gametophytic systems, allele frequencies generally conform to the hypothesis of equal allele frequencies (Lawrence 2000). However, we rejected this hypothesis in the majority of populations we tested. Unequal allele frequencies in other organisms have been attributed to demographic perturbations (Kato and Mukai 2004) but it may also be due to genetic drift and population structure (Stoeckel et al. 2008). Population structure and its resulting unequal allele frequencies may also be the product of occasional habitat disturbance (Campbell and Lawrence

1981a). Disturbance, specifically by flooding, is common in riparian habitats and may, therefore, have a negative effect on population structure and allele frequency for self- incompatible species such as S. virginiana. Therefore, population structure at both the S-locus and neutral loci may be one reason for the observed unequal S-locus allele frequencies in this species, but an additional explanation may that the SI system in S. virginiana is leaky, or possibly in the early stages of breakdown.

The maintenance of sexual reproduction in clonal plants has generally been attributed to either the need for seeds as a long distance dispersal mechanism, or for the evolutionary benefits of the resulting increase in genetic variation (Eriksson 1997). For clonal riparian species, the need for seeds to serve as long distance dispersal propagules is of lesser importance for short-

term survival. Rhizomes can disperse just as far as seeds via a river system (Johansson and

Nilsson 1993), and may actually be better adapted for establishment in such an environment due the larger size of fragmented rhizomes. For a species that clonally reproduces as prolifically as

S. virginiana, any additional genetic variation that may arise from sexual reproduction would likely benefit the species. However, the small population size that this species exhibits may lead to the breakdown of this system. The self-incompatibility system is more likely to be lost in small populations as a result of inbreeding and the accumulation of mutations (Barrett et al.

1989). Bottlenecks produce a loss of alleles not only at neutral loci, but also at the self- incompatibility locus (Reinartz and Les 1994). Reinartz and Les (1994) predict that when a reduction in S-alleles leads to a reduction in mates and therefore the frequency of sexual reproduction, this could consequently lead to the breakdown of the self-incompatibility system.

No historical demographic information exists for S. virginiana to determine if any bottleneck events have occurred in the past, but of the populations we sampled, they consist of few genotypes (ranging from 3 to 9). In a strictly self-incompatible system, all individuals should be heterozygous at the S-locus (Richards1986). However, only two populations of S. virginiana showed full heterozygosity and two others had observed heterozygosity levels of 0.25.

In addition, positive FIS values indicate biparental reproduction and are expected in a self- incompatibility system (Holderegger et al. 2008), but the values calculated for this study are highly variable, ranging from -1.0 to 0.50. These data show that the self-incompatibility system in S. virginiana is either breaking down, or is leaky (de Nettancourt 2001). Self-incompatibility breakdown could explain why the majority of hand pollinations that set seed were from those that shared S-alleles. When studying a clonal self-compatible perennial, Decodon verticillatus

(Lythraceae), Eckert (2000) found that the majority of the selfed matings were from

geitonogamous crosses as opposed to within-flower selfing. In this study, the majority of seeds were produced from crosses with other plants with the same S-alleles (40%) whereas only 3% resulted from same-flower crosses. Seedlings that grew to a sufficient size for DNA extraction in this study (N = 3) and seedling from a previous germination experiment (N = 5) were genotyped at neutral loci to correctly identify the method of reproduction: outcrossing, selfing, or agamospermy. Genotyped seedlings were, in general, consistent with outcross sexual reproduction, but this needs to be examined further with a greater number of samples and possibly more markers.

Seed production was low in this study, occurring in only 13% of the hand pollinations.

Low total seed production has been seen in other rosaceous clonal shrubs (Weekely and Race

2001). The low fruit production observed in this study could be the result of the species biology, such as pollen sterility, but it could also be the result of interference of the pollinator bags.

Although pollinator exclusion bags are a common method to explore pollination ecology, the microclimate within the bags may have resulted in an inhospitable environment for fruit production. Temperature and humidity can be higher inside pollinator exclusion bags when compared to the ambient environment. The microclimate differences between the two environments were not examined in this study and therefore, it cannot be conclusively stated that bagging did not have an effect.

The genetic results of this study show low S-allele richness throughout all populations sampled, which could hinder sexual reproduction in natural environments as a result. High levels of habitat fragmentation (Wagenius et al. 2007) and disturbance (Campbell and Lawrence

1981a) have significant negative effects on S-allele diversity. Therefore, habitat perturbations combined with low diversity at the S-locus could accelerate population decline and potentially

lead to extinction of populations. Although clonal growth can prolong population extinction

(Les et al. 1991), it can also restrict the number of potential mates for sexual reproduction

(Reinartz and Les 1994; Anderson and Stebbins 1984). This situation, particularly in small populations, can result in the breakdown of the self-incompatibility system. The highly variable levels of observed heterozygosity and seeds produced in hand pollinations with self pollen suggest that this breakdown may currently be taking place.

Acknowledgments

The authors thank S. Matter, E. Maurer, S. Rogstad, and S. Selbo for editorial comments.

Thanks to U.S. Fish and Wildlife Service, and the Ohio Department of Natural Resources for

collection permits and M. McAllister for field assistance. We thank the Arnold Arboretum of

Harvard University for permission to conduct field work within the living collection, and for

providing funding through the Deland Award to J. Brzyski. Funding was also provided by the

Catherine H. Beatty Fellowship from the Garden Club of America and the University Research

Council Fellowship from the University of Cincinnati to J. Brzyski.

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Table 1. Descriptive statistics of Spiraea virginiana at the self-incompatibility locus. Listed is population, number of ramets within each population (n), number of S-alleles (A), expected and observed heterozygosity (He and Ho, respectively), and the inbreeding coefficient (FIS).

Population n A He Ho FIS OH1 4 3.0 0.464 0.250 0.500 KY1 3 2.0 0.600 1.000 -1.000 KY2 9 3.0 0.627 0.667 -0.067 TN1 4 2.0 0.250 0.250 0.000 TN2 26 7.0 0.701 0.577 0.179 TN3 4 3.0 0.679 1.000 -0.600 TN4 7 2.0 0.527 0.857 -0.714 TN5 4 3.0 0.714 0.500 0.333 Average 8.14 3.14 0.585 0.693 -0.267

Table 2. Allele frequencies for the self-incompatibility alleles identified within eight populations of Spiraea virginiana.

Population Allele/n OH1 KY1 KY2 TN1 TN2 TN3 TN4 TN5 Total 4 3 9 4 26 4 7 4 61 S1 0.750 - - - 0.154 0.125 - 0.500 0.191 S2 0.125 ------0.016 S3 - 0.500 0.444 0.125 0.269 0.375 0.429 0.250 0.299 S4 - 0.500 0.444 0.875 0.462 0.500 0.571 0.250 0.450 S5 - - - - 0.038 - - - 0.005 S6 - - 0.111 - - - - - 0.014 S7 0.125 ------0.016 S8 - - - - 0.019 - - - 0.002 S9 - - - - 0.019 - - - 0.002 S10 - - - - 0.038 - - - 0.005

Table 3. Pollination treatments of Spiraea virginiana that produced fruits with viable seed. The number of seeds tested was variable due to the number of inflorescences within each treatment.

Sample sizes varied due to flowering asynchrony.

Percentage of Percentage pollinations that of seeds Year Treatment produced fruits viable 2009 Unbagged/no manipulation 100 100 Bagged/no manipulation 29 7 2010 Bagged/outcrossed with different S-allele 30 12 Bagged/outcrossed with same S-allele 40 40 Bagged/self pollinated 3 10

CHAPTER 5

The effect of substrate and stratification on the germination of a native rare shrub

compared to a non-native congener

Jessica R. Brzyski and Theresa M. Culley

Department of Biological Sciences

University of Cincinnati

614 Rieveschl Hall

Cincinnati, Ohio, 45221, USA

Abstract

Non-native species are often considered to have a competitive advantage over native species in one or more life history traits. Although only a few non-native individuals may colonize a novel habitat, some introduced species are capable of quickly achieving high levels of abundance.

Contrary to this, native species that have experienced population reductions, often remain at low levels of abundance. To address this difference, we compared plant performance (time to germination and percent germination) between two congeners similar in biology: one native species of low abundance (S. virginiana) and one non-native species that is expanding its range, but is still in low abundance (S. japonica). Plant performance was tested separately with different growth substrate and cold stratification treatments. There was no difference in time to germination between the two species, but percent germination for the native S. virginiana was low when compared to S. japonica, 10% and 35% respectively. Neither cold stratification nor growth substrate had a significant effect on percent germination, but both species germinated faster with cold moist stratification. These results suggest future negative repercussions for the native S. virginiana and may also indicate the further range expansion of the non-native S. japonica.

Keywords: invasive; rare; Rosaceae; Spiraea; stratification, viability

Introduction

Rare species generally exhibit small population sizes and, as a result, may experience detrimental effects, such as genetic drift (Wright 1931). During their initial introduction, invasive species may also exhibit small population sizes resulting from founder events when few individuals are introduced to a new area (Elam et al. 2007). However, the effect of this bottleneck can be highly variable; in one species, the situation can become dire, leading to its potential extinction while the other species, soon after establishing, may experience rapid growth and spread. There has been much research comparing performance at the seedling stage of non- native, invasive species to native, abundant species (i.e. Martin and Canham 2010; Dahler 2003;

Sher et al. 2000), but the comparison involving natives of low abundance has been relatively less well studied (Powell at el. 2010). In addition, native and non-native species that share a phylogenetic relationship (i.e., Mandák 2003; Muth and Pigliucci 2006) or habitat (i.e.,

Bartomeus et al. 2010; Bhattacharjee et al. 2009) are often compared. However, comparisons between non-native and rare species, both of relatively low abundance and which share both phylogenetics and habitat are, to our knowledge, non-existent.

To determine if there is a competitive advantage of one species over another, fitness related traits are often compared, and these traits can be referred to as a plant’s performance

(Dahler 2003). Plant performance can be measured in a variety of different ways, varying from traits associated with plant growth and those related to plant spread and range expansion (Dahler

2003). Seed germination success in particular is an important component of plant fitness, and has also been identified as a key factor in determining invasion success (Van Kleunen and

Johnson 2007), including being listed by Baker (1974) as an ideal weedy trait. However, there is limited empirical research comparing germination success between a rare native and a non-native

congener pair (Powell at al. 2010). Here we use a comparative approach to determine if a non- native shrub has a reproductive advantage over its native, rare congener. The two species used in this study were the threatened and native Spiraea virginiana Britton, and the non-native congener S. japonica L.f, both in the Rosaceae. We examined plant performance by measuring the time to germination and germination success over varying levels of cold stratification when using different growth substrate, including soil collected from field sites. By examining the effect of growth substrate, we hoped to determine if the natural soil environment facilitates, inhibits, or has no effect on germination. Since studies have indicated that some non-native, invasive species experience a level of advantage (either through growth or reproduction) in their introduced range when compared to their native range (i.e., Blossey and Nötzold 1995; Blair and

Wolfe 2004), it was our hypothesis that S. virginiana would be slower to germinate and would experience lower germination success when compared to its non-native congener.

Both S. virginiana and S. japonica occur in riparian habitat, which further compounds the importance of their relative germination abilities. This particular habitat type tends to contain high levels of biodiversity, particularly of rare species, which are adapted to frequent disturbance resulting from periods of flooding (Naiman and Décamps 1997). This habitat type is generally highly modified through human activities, such as stream modification (Brinson et al. 1981;

Abramovitz 1996). For restoration purposes, it is important to identify life history strategies for the natural flora inhabiting the area (Richardson et al. 2007). Therefore, this research will also contribute to the development of a germination protocol that provides the optimum germination conditions for a characteristic riparian shrub, S. virginiana. The information gathered by this research contributes evidence as to how biologically similar species may show dramatic

differences in demography, while also facilitating future propagation efforts involving S. virginiana, and will be applicable to the recovery of this threatened species in the wild.

Methods

Study Species

Both Spiraea virginiana, a rare native species, and S. japonica, a non-native, introduced species are perennial rhizomatous shrubs. In addition to being congeners, these species are also morphologically similar, capable of clonal growth, and exist in riparian habitat. Spiraea japonica and S. virginiana have been observed growing along the same stream, and occasionally right next to each other (R. Gardner, pers. comm., J. Brzyski, pers. observation).

Spiraea virginiana is endemic to Southern Appalachia and occurs in seven states including Georgia, Kentucky, North Carolina, Ohio, Tennessee, Virginia, and West Virginia

(USFWS 1992). It grows 0.6-3 meters tall with arching, upright stems and the leaf shape is mostly oval with a serrate margin (USFWS 1992). Flowers are compound corymbs, white in color, and bloom between late May and late July. The seed size is small (2-3 mm in length) and contains no endosperm, they provide no obvious food source, and dispersal is by gravity and water (USFWS 1992). Seeds begin to dehisce from their follicle between late August and

September. It has been suggested that they do not form a long-lived seed bank (USFWS 1992).

Spiraea japonica is native to Japan, China, and Korea (Remaley 1998), and the introduced range is throughout most of the eastern United States and portions of Canada. It is considered invasive in Kentucky, Tennessee, Pennsylvania, Virginia, and North Carolina (USDA

2010) although it is found in low abundance in other areas. Spiraea japonica was brought to the northeastern United States in 1870 for cultivation and is commonly used as a horticultural shrub

today (Remaley 2005). This species often escapes cultivation, becoming established and self- sustaining in natural environments (Remaley 1998). This shrub grows approximately 1-2 meters tall and has ovate leaves with a toothed margin (USDA 2005). Flowers are also a compound corymb but are of pink color, which is the main distinguishing feature from S. virginiana. Seeds are approximately 2-3 mm in length with endosperm either scarce or absent (Robertson 1974), and also dehisce from an enclosed follicle. Contrary to S. virginiana, seeds of S. japonica have been suggested to survive many years in the soil (USDA 2005). Dispersal of seeds in this species is also by gravity or by water (USFWS 2004).

Germination Experiment

Pollen viability was first tested to ensure that inviable pollen was not the reason for any lack of germination. Pollen viability was tested on five flowers from each of nine plants of S. virginiana, and five flowers from each of three wild plants of S. japonica. Anthers, and subsequent pollen, were stained with Alexander’s stain (Alexander 1980) and 200 pollen grains per flower were counted and categorized as viable or inviable. This stain colors abortive and nonabortive pollen by differentially staining the protoplasm and the cellulose in the cell walls

(Alexander 1980). Statistical difference in pollen viability between species was analyzed using a

G-test of independence.

Before germination tests were conducted, seeds were tested to determine if they imbibe water or if they are impermeable to water (Baskin and Baskin 1998). A random sample of ten seeds of each of the two species (collected as described below) were placed on distilled water soaked filter paper in a petri dish, observed for 24-48 hours and monitored for water absorption,

which did occur in all seeds for both species, thus indicating that scarification was not needed

(Bansal et al. 1980).

Mature fruiting corymbs from naturally pollinated inflorescences of S. virginiana were collected throughout a robust population located in Scioto County, Ohio, between August and

September 2008. Naturally pollinated corymbs of Spiraea japonica were collected from naturalized plants in Lewis County, Kentucky that same season. For each species, entire corymbs were carefully removed from the plant and each placed into a plastic bag. Seeds were stored in a cool, dry place for four months until germination tests could be performed. Seeds were removed from their enclosed capsule and randomly placed into one of 20 treatments. Cold stratification treatments included three cold, moist stratifications at 5°C for differing lengths of time (30 day, 60 day, 90 day), one cold, dry stratification at 5°C (90 day), and the control which received no cold stratification. Seeds were also sown in four different growth substrates: field soil, autoclaved field soil (120° C for 20 min), sterile vermiculite, and filter paper. Field soil was collected from sites where S. virginiana naturally occurs in Ohio and Kentucky. Field soil without any seeds sown acted as a control to ensure that germinations were not from a potential seed bank. Each treatment consisted of one of the four growth substrates combined with one of the four cold stratification treatments in a factorial design. Five replicates of ten seeds were sown into each treatment and all treatments were performed with both S. virginiana and S. japonica separately, for a total of 1000 seeds per species. Planted seeds were randomly positioned in a plastic bag mesocosm to prevent dessication and placed under a timed grow light with a 12 hour light/dark cycle. Moisture levels (well-watered) and temperature (approx. 22° C) were held constant during the germination phase of two weeks.

Due to low germination success, the data did not meet statistical assumptions of normality and variance. Consequently, the non-parametric Kruskal-Wallis test was used to test the main effects of stratification and growth substrate on time to germination and overall percent germination after two weeks using JMP 8.0 (SAS Institute, Cary, NC). To analyze interactions between the three variables of species, cold stratification treatment, and growth substrate, a G- test of independence was calculated with the Williams correction, which is recommended for a more conservative result (Sokal and Rolff 1995).

Results

Pollen viability was high for both species, ranging from 89% (178.7 mean ± 2.58 SE) to

90% (179.5 ± 1.47) in S. japonica and S. virginiana, respectively. There was no statistical difference (p > 0.05) in pollen viability between the two species.

Out of the total of 1000 seeds per species sown, 103 (10.3%) of S. virginiana seeds germinated and 348 (34.8%) of S. japonica seeds germinated. This difference in number of germination between the two species was significantly different (Kruskal-Wallis; H = 64.94, df =

1, p < 0.0001).

Germination occurred in all treatments and the greatest proportion of seeds that germinated did so early on in the experiment; 37% of all S. virginiana seeds and 26% of S. japonica seeds emerged on their first day of observed germination (Figure 1). Species did not differ in the time to germination (Kruskal-Wallis; H = 2.67, df = 1, p = 0.10; summarized in

Table 1), but there was an effect of both cold stratification and growth substrate. The initial start of germination, regardless of species, was on average 5.8 days quicker when moist, cold stratification occurred (Kruskal-Wallis; H = 99.42, df = 4, p < 0.001), but there was no difference

in germination success among the three moist, cold stratifications (30-, 60-, 90-days). Although there was a statistically significant effect of growth media on the time to germination (Kruskal-

Wallis; H = 8.09, df = 3, p = 0.044), a Tukey-Kramer test indicated that this difference was only between filter paper and autoclaved field soil, and therefore, not biologically meaningful.

Cold treatment did not affect the number of seeds germinated for either species. Growth substrate was also not significant, although trends can be seen in the data (Figure 2). When species were analyzed separately, there was a significant interaction between growth substrate and cold stratification with both S. virginiana and S. japonica (Gadj = 26.31, df = 12, p < 0.01;

Gadj = 82.25, df = 12, p < 0.0001, respectively). Spiraea virginiana exhibited higher percent

germination in the dry, cold stratification while on the vermiculite (11%) and autoclaved soil

(10%), and in the 30-day moist stratification treatment while on vermiculite (15%) and field soil

(7%). Spiraea japonica exhibited higher percent germination in the dry, cold stratification

treatment while on filter paper (13%) and vermiculite (5%), and in the 30-day moist treatment on

autoclaved soil (8%) and vermiculite (7%).

Discussion

Despite initial low abundances, some introduced non-native species quickly reproduce

and expand their range, contrary to native species with low abundances that may never recover.

Although there are many criteria that may make one species more likely to invade than others,

fast germination time and high germination success are often inferred to increase the ability of a

plant to become a successful invader (Van Kleunen and Johnson 2007; Baker 1974). However,

the influence of germination success on invasion ability has received relatively little empirical

work (O’Donnell and Pigliucci 2010; Tylkowski 2007). Therefore, we compared measurements

of plant performance to gain further insight as to how two species that appear so similar biologically and ecologically have such different demographic trajectories.

In the current study, one aspect of plant performance measured (time to germination) did not exhibit any difference between the native and non-native Spiraea; furthermore, the variable of cold stratification affected both species in the same manner. Both species experienced faster germination by almost six days with cold, moist stratification regardless of the amount of time spent in stratification. The dry cold stratification treatment had no difference in time to germination when compared to the control, indicating that some level of moisture during stratification is important to germination time. It is generally predicted that species that mature fruit in autumn, as both of these species do, should require some level of cold stratification

(Baskin and Baskin 1998). Although cold moist stratification is not necessary for overall germination success, it may provide a signal to start germination. This signal may be beneficial in the natural environment when quick germination after a disturbance event, such as a major flood, would prevent competition at initial establishment (Eriksson 1989; Gerard et al. 2008). A major flooding event, such as those often experienced by S. virginiana, changes the plant community by removing some plants and thereby increasing the amount of bare soil and sunlight

(Richardson et al., 2007). This potentially produces a more hospitable environment for seed germination, particularly if the seed can germinate quickly to capitalize on the reduction of other plant competitors.

Habitat specificity, including soil quality, can also directly impact germination and establishment potential (Jusaitis et al. 2004, Lesica 1992). Although both species had better germination success in the autoclaved field soil, there was no clear preference for the other growth substrate. Field soil produced one of the lowest germination rates for both S. virginiana

and S. japonica suggesting that habitat may be a limiting factor in seed germination for either species. However, this cannot be stated with certainty until more rigorous soil tests are performed.

Anecdotal information suggests that no S. virginiana seedlings have been found in nature

(USFWS 1992). This is consistent with recent demonstrations that rare species experience a reduced level of recruitment when compared to more common species (Young et al. 2007). In a threatened native scrub plum, low germination success was deemed a likely reason for a lack of seedling recruitment (Weekley et al. 2010). Although germination rates for S. virginiana are rather low (10%), this study suggests that this species is not sexually sterile and germination is possible. This result is particularly interesting because the seeds were collected from naturally pollinated flowers in the field. Previous research has indicated that populations are not genetically diverse, with there being only three genotypes identified at this specific population

(Brzyski and Culley, Chapter 3). It is, therefore, hopeful for this species that successful pollination and fruit production occurred in a natural setting. Even a minimal amount of recruitment by sexually reproduced seed can sustain genetic variability over generations (Soane and Watkinson 1979). However, caution must be used since germination success does not provide information on survival to reproductive maturity. It is also possible that the small population sizes of S. virginiana could result in Allee effects (Courchamp et al. 2008), which would lead to further low sexual recruitment.

We hypothesize that either seed recruitment, although rare (as indicated in this study), is occurring in S. virginiana and just has not been observed, or that seedlings are experiencing competition for available space. Competition with any clonal species may be dominating seedling growth because clonal shoots grow faster than seedlings and would be able to compete

more readily (Bond and Midgley 2001). Future research should examine the growth rate and competition abilities between clonal offspring and sexually produced seeds in S. virginiana, and among likely competitors.

Although the time to germination is equal for both species, S. virginiana seeds experienced significantly lower germination success. Previous studies have had mixed results in determining if non-native species have an advantage over native species. Although non-native congeners had an advantage in seed production, germination success, and time to germination

(O’Donnell and Pigliucci 2010; Colautti et al. 2006; Callaway and Josselyn 1992, Honig et al

1992), a meta-analysis by Dahler (2003) found only 45% of the time the non-native invader had an advantage in either fecundity or germination, or both. When compared to these cited studies, which did not take abundance into account, our results agree with the inference that invaders have relatively high germination success, particularly when compared to a native congener.

Spiraea japonica has approximately three-fold higher germination success than that of S. virginiana.

Based on the data collected from these field sites, we can conclude that the non-native species is producing many more propagules than the native, and thus higher germination success may be one possible component leading to invasiveness in S. japonica in select states, and possibly leading to the species spreading in other localities. Higher propagule pressure and a high intrinsic rate of growth greatly increase the probability of naturalization (Warren et al.

2006) and those species that are capable of becoming naturalized often have faster and higher germination rates (Van Kleunen and Johnson 2007). Our results show that a species can become naturalized without being the faster germinator if overall germination rates are still substantial.

However, clonal reproduction may be a probable contributor in Spiraea, although the rate of

clonal growth has yet to be investigated in S. japonica. Spiraea virginiana, however, is highly clonal. Genetic analyses of both species reveal low genetic diversity in natural populations

(Brzyski and Culley, Chapter 3; J. Brzyski, unpubl. data). If S. japonica is capable of establishing by sexually reproduced seed, the resulting recombination from sexual reproduction may increase its genetic diversity (Soane and Watkinson 1979), potentially allowing more vigorous genotypes to emerge as well as providing the species with more ecological flexibility.

Lastly, to promote further propagation of the rare S. virginiana in an artificial environment, we recommend using sterile substrate and applying a cold (5°C), moist stratification treatment of 30 days. Restoration would benefit best by germinating seeds first in a greenhouse and then transplanting them into the natural environment to minimize detrimental effects from biotic factors, such as competition or abiotic factors, such as flooding and dessication.

Acknowledgments

The authors thank S. Matter, E. Maurer, S. Rogstad, and S. Selbo for research guidance and editorial assistance. We also thank U.S. Fish and Wildlife Service and the Ohio Department of

Natural Resources for scientific permits. Funding was provided by the Catherine H. Beatty

Fellowship by the Garden Club of America and the Wendel, Weiman, and Benedict Grant by the

University of Cincinnati to J. Brzyski.

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Table 1. Main effects of time to germination and germination success were analyzed separately between Spiraea virginiana and S. japonica using the Kruskal-Wallis nonparametric test.

Treatment df Statistic (H) p Time to germination Species 1 2.67 0.10 Cold stratification 4 99.42 <0.0001 Substrate 3 8.09 0.044 Germination success Species 1 64.94 <0.0001 Cold stratification 4 3.96 0.06 Substrate 3 3.93 0.269 Substrate*species 3 15.47 <0.01

Figure 1. Frequency distribution of the proportion of seeds for Spiraea virginiana and S. japonica by time to germination.

Figure 2. Total percent germination of seeds in different growth substrate for Spiraea virginiana and Spiraea japonica.

CHAPTER 6

Managing rare plant species: How identifying when rarity occurred can inform

management strategies

Jessica R. Brzyski and Theresa M. Culley

Department of Biological Sciences

University of Cincinnati

614 Rieveschl Hall

Cincinnati, Ohio, 45221, USA

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Abstract

Definitions of rarity can vary depending on different factors, most commonly with the variables of population abundance, geographic range, and habitat specificity. Rarity can also be classified by time, either of historical or recent rarity. Historically rare species are thought to be adapted to low population abundance and may not benefit from certain management practices, such as large-scale introduction of novel genotypes. Therefore, knowing the temporal pattern of rarity will allow for better management strategies for recovery. However, information on the history of a species with respect to population abundances and range extent is often unknown. Spiraea virginiana is one such species which is considered rare but historical information on abundance is undocumented. Using genetic methods, we infer whether this species has experienced a recent bottleneck within the past few generations or has been historically rare over a much longer time period. Specifically, we examined genetic population differentiation, correlated genetic distance with geographic distance, and calculated the migration rate. We found that, although variable, population differentiation was high indicating that enough time has passed for genetic structuring to occur among populations. In addition, migration rate was low, and there was wide variation in the relationship between genetic and geographic distance, indicating that genetic drift may be the driving force. From this evidence, we conclude that S. virginiana has been historically rare, and we then use this information, in addition to other reproductive traits known to occur in this species, to formulate management recommendations for future preservation and propagation of this federally threatened species.

Keywords: conservation; genetic drift; historical; rarity; Spiraea virginiana

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Introduction

Many plant species are declining in numbers worldwide because of detrimental human impacts on the environment. As of early 2011, there were 758 flowering plants species listed in the United States as either endangered or threatened under the U.S. Endangered Species Act of

1973 and most of these species (84%) have active recovery plans (USFWS 2011). For those species that have documented historical information on population abundance and range as well as information about how quickly any declines took place, these recovery plans may be adequately designed. However, for many species in need of recovery, historical demographic information is unknown, making strategies to recovery more difficult to construct.

This difficulty is due in part to the fact that there may not be one factor that applies to all rare species and it is important to recognize that rarity can arise in different ways (Rabinowitz

1981, Barrett and Kohn 1991, Brigham 2003). Specifically in regards to time of rarity, species are generally either historically rare or they may have become rare due to a recent population decline of a once more common species. Although research is limited, historically rare species are suggested to have become adapted to low population abundance. For example, historically rare species may have mechanisms that allow retention of genetic diversity, maintenance of fitness at low genetic diversity levels, or maintenance of pollinator levels at low abundance

(Brigham 2003). It is suggested that, at least genetically, historically rare species experience negative consequences to fitness less frequently than those species that have recently declined but were formerly common (Brigham 2003), due in part to purging of the gene pool through inbreeding. However, no significant pattern between fitness and genetic diversity has emerged for either historical or recent rarity, suggesting that the time since a species became rare, and how that species responds to being rare, is often specific to the taxon and can, therefore, have an

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effect on the conservation methods enacted (Barrett and Kohn 1991). This is especially important when deciding to intervene with population supplementation because those populations that are naturally rare may have evolved local adaptations that would be disrupted with the addition of outside genotypes. In addition, if populations are small but stable, then efforts can be put towards those that are unstable and in urgent need for conservation.

There are many methods that can be used to determine if populations have experienced a decline such as a bottleneck in the absence of observational documentation. Genetic diversity can be compared within the same population over different time intervals, but this method requires sampling spaced over time which is often not feasible (Williamson and Slatkin 1999).

Genetic diversity has also been compared between populations suspected of a decline and those that are assumed to be stable (Soule 1976). However, a stable population for comparison may not exist, and if so, the assumption of stability can be difficult to verify. One commonly used method of distinguishing if a species has experienced a recent decline is to examine the level of heterozygosity present within the species in question. Recent bottleneck events within the last few generations generate an excess of heterozygotes as rare alleles are quickly lost from the population (Luikart and Cornuet 1998). However, this method cannot be used for species that exhibit any degree of clonality because this form of reproduction maintains allelic variation and increases levels of heterozygosity (Balloux et al. 2003). Therefore, other methods must be utilized to infer recent decline for clonal species. One example is to examine the relationship between genetic variation and population structure (Barrett and Kohn 1991). Higher levels of genetic structuring between populations are expected if they were isolated for an extended period of time due to increased genetic drift, increased inbreeding, lack of gene flow, and/or extinction of local demes (Young et al. 1996). In addition, by comparing geographic distance with genetic

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distance, one can infer which dominating force, genetic drift or gene flow, is most influential

(Hutchison and Templeton 1999). If a population has been historically rare, then genetic drift will be the major force, and if more recently rare, then there could be evidence of recent gene flow (Young et al. 1996).

Areas of high disturbance, such as in riparian habitat, tend to contain a prevalence of rare species, as well as species that reproduce clonally (Fahrig et al. 1994, Stöcklin and Bäumier

1996, Naiman and Décamps 1997). Spiraea virginiana Britton (Rosaceae), native to the eastern

United States, is a characteristic riparian shrub capable of clonal reproduction. This flood- adapted shrub is federally threatened and is considered rare at some level within every state it resides (USFWS 1990). However, information on historical population range and abundance does not exist and it is unknown whether this species is historically rare or has only recently become so, possibly as a result of habitat loss or degradation. Although small populations have a greater chance of experiencing genetic drift (Ellstrand and Elam 1993), dispersal by river offers a unique opportunity for migration, and therefore greater potential connectedness among populations. In addition, the effect of migrants on genetic variation is much higher in small populations than in more abundant populations (Lacy 1987). For example, simulations have shown that very minimal migration, as few as one migrant every two generations will reduce the effects of genetic drift, and even bring levels of genetic variation back to those when under panmixia (Lacy 1987).

In this study, we determined length of rarity of S. virginiana by examining both population structure and associations between geographic distance and genetic diversity.

Migration rate was also calculated as an additional measurement of gene flow which could determine if the rarity experience by this species is historical or recent. We also looked at rare

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alleles within subpopulations, which will remain present in only one or a few subpopulations if migration is minimal (Hartl and Clark 2007). After estimating how long S. virginiana has been rare, we apply this information to recommendations concerning the management and protection of this species, which may also be used for biologically and demographically similar species in riparian habitats.

Methods

Spiraea virginiana is a flood-adapted, perennial shrub endemic to Southern Appalachia and occurs in seven states in the United States: Georgia, Kentucky, North Carolina, Ohio,

Tennessee, Virginia, and West Virginia (USFWS 1992). Spiraea virginiana is an outcrossing species that is self-incompatible and also capable of asexual reproduction, specifically through rhizome growth and fragmentation (USFWS 1992). Spiraea virginiana was federally listed as threatened in 1990 under the U.S. Endangered Species Act of 1973 and is also globally imperiled with a G2 ranking (Center for Plant Conservation 2010). This shrub also has state designations throughout its range being listed as threatened (KY and GA), endangered (OH, NC, TN, and

VA), and in WV, due to the lack of threatened and endangered legislation, is classified as critically imperiled (USFWS 1990). Previous research on this species has shown that this species is highly clonal, has low probability for sexual reproduction, and when outcrossing does take place, the seeds have low germination rates (Table 1).

Sampling for genetic analysis took place throughout a portion of the natural range (Ohio,

Kentucky, and Tennessee) during 2008-2009. A number of populations were sampled within each state, with varying numbers of subpopulations sampled within each population (Figure 1;

Table 2). Subpopulations were along the same river and classified as an area with at least one

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cluster of plants and physically separated by the next subpopulation. Two leaf samples were collected from every plant cluster that did not have a visual connection with another, and genotypes were determined using 11 nuclear microsatellite markers, as described in Brzyski

(2010) and Brzyski and Culley (Chapter 3).

Any repeated genotypes obtained within a subpopulation were designated as clones, and therefore not included in analyses. Estimates of population differentiation were quantified using the program GDA 1.1 (Lewis and Zaykin, 2001), which calculated θ, an analog to Wright’s FST

(Weir and Cockerham 1984). Significance of θ was determined by bootstrapping across loci with 1000 replicates and a 95% confidence interval. These θ values were used to construct a genetic distance matrix.

A geographic distance matrix was constructed among populations using GenAlex 6.1

(Peakall and Smouse 2006). Euclidean geographic distances were calculated using decimal latitudes and longitudes taken in the field. A Mantel test (Mantel 1967) was then performed on the genetic and geographic matrices using Tools for Population Genetic Analyses (TFPGA) 3.1

(Miller 1997). The Mantel test examines the relationship between geographic distance matrix and pairwise genetic differentiation, thereby testing isolation-by-distance. A Mantel test was also used to analyze the genetic and geographic relationship among subpopulations within each population, except for populations KY1 and TN5 which contained only two subpopulations within each. Subpopulations are located within the same watershed, and geographic distances more closely resemble actual river distances.

Migration rate averages across all populations was calculated using Wright’s infinite island model, [(1/Fst)-1]/4, using GenAlex 6.1 (Peakall and Smouse 2006). Additionally, rare

alleles within subpopulations were identified in all sites.

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Results

Throughout the sampling range, nuclear microsatellite markers indicated that clonal reproduction was prevalent with only 38 multi-locus genotypes identified from 406 plants sampled and with low average numbers of alleles per locus (2.33 alleles) and high observed heterozygosity among populations (0.503) (Brzyski and Culley, Chapter 3). Many populations are dominated by a single clone (Figure 2; see also Appendix 1). Average genetic differentiation among populations (θ) ranged from low (0.038) to high (0.547), with an average of 0.300. All but one pair-wise θ values were significantly different from zero (Table 3).

The Mantel test indicated that there was no correlation between genetic and geographic distance among populations when analyzed without clones (r = 0.162, p = 0.264; Figure 3), and similar results were produced even when clones were left in the analysis. There was also a high degree of variation among populations, indicating that genetic drift is influencing population structure (Hutchinson and Templeton 1999). There was also no evidence of local dispersal within each population. Mantel tests for within populations also indicated no relationship between genetic and geographic distance among subpopulations, resulting in p values ranging from 0.113 to 0.565.

Overall migration rate (Nm) was low, calculated at an average of 0.528. When pairwise comparisons of migration rate between populations were analyzed, four pairs had values equal to or above 1.00 (Table 4). All but one population (TN5) had subpopulations that contained private alleles (Table 2).

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Discussion

Genetic drift is a prevalent force in rare species with small populations experiencing the effects of drift to a greater extent than more abundant populations. Fragmentation of populations is common in rare species and this produces isolation among populations, which also results in genetic drift. So although genetic drift may be common in small, fragmented populations, it is important to identify the extent of genetic drift that populations have experienced. If drift is the predominant force acting upon populations and there is little to no evidence of gene flow, then it suggests that the species has been rare for some time. For maximum effectiveness, management decisions for a threatened species should be constructed based upon whether the species is historically or recently rare. For example, when managing species that are historically rare, enlarging already existing populations with introduced individuals could disrupt locally adapted genotypes and result in negative outbreeding effects (Templeton 1986, Barrett and Kohn 1991).

When no historical data exists, as in the case of S. virginiana, this information can be inferred through genetic analyses, specifically by examining levels of population genetic structuring, the relationship with genetic and geographic distance, and migration rate.

A high degree of genetic spatial structuring among populations is consistent with populations being separated for an extended period of time and experiencing little gene flow, thus allowing populations to diverge from one another due to genetic drift (Young et al. 1996).

Historically isolated populations exhibit high levels of population differentiation, as demonstrated in clonal plants (Stehlik and Holdregger 2000), butterflies (Williams et al. 2003), and birds (Hille et al. 2003). In this study, values of genetic structuring among populations of S. virginiana were high (average θ = 0.300), suggesting that S. virginiana has not gone through a recent bottleneck and that populations have been isolated from one another for some time.

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The relationship between genetic and geographic distance can also provide information on whether gene flow or genetic drift is more influential in shaping populations (Hutchison and

Templeton 1999). This study found that there was no relationship between genetic and geographic distance, the correlation coefficient was low (r = 0.162) and there was wide variation among the populations. This can be interpreted as extreme isolation of populations with drift being more influential than gene flow (Hutchison and Templeton 1999) in this species, which is consistent with historical rarity. Using this same method of comparing the two matrices of geography and genetics, drift was also determined to be the dominant force in other rare clonal plants (Eckstein et al. 2006, Fischer et al. 2000, Stehlik and Holdregger 2000).

In small populations, a migration rate of 0.5 immigrants per generation can be enough to sufficiently reduce the loss to genetic variation as result of genetic drift (Lacy 1987, Slatkin

1987). However, this migration rate of 0.5 is determined by simulations, and it is generally assumed that a migration rate of less than 1 migrant per generation is adequate. There were fifteen pair-wise comparisons where migration rate was above 0.5, and four pair-wise comparisons above 1.0. The higher values of those four populations (KY1, KY2, TN1, TN2) could suggest gene flow. However, these populations are located in different watersheds so it is suggestive that perhaps these specific populations were once part of a more abundant and widespread distribution that were connected and gene flow existed before the current fragmentation. If clonal reproduction predominated after populations became fragmented and isolated from one another, then those individuals would share alleles and would falsely affect the data by indicating gene flow. It is important to note, however, that although there are shared alleles, there are no widespread genotypes throughout the sampled distribution.

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A lack of correlation between genetic and geographic distance was also calculated when analyzing subpopulations within populations. The average distance between subpopulations was

1.97 kilometers, although more than half (57%) of the subpopulations are less than 0.5 kilometers apart, occurring along the same river system. If pollen movement was occurring at these distances we would expect a significant positive correlation. However, there was a lack of correlation within all populations analyzed. If rhizomes were being dispersed downstream, then we would expect all subpopulations within one river to be very similar genetically, particularly with this species propensity for clonal propagation. Conversely, the majority of subpopulations within one river had high genetic distances among them, suggesting little to no gene flow within rivers. The exceptions (OH1, TN2, TN5) were very similar genetically and could likely represents dispersal and prolific clonal growth.

The one migrant rule has been commonly used in recovery plans that consider genetic issues (Mills and Allendorf 1996). However, in a natural population, which violates the assumptions of an ideal population, more migrants may be necessary, suggested to be in the range between one and 10 (Mills and Allendorf 1996, Wang 2004). Alternatively, while migration among populations is generally seen as having a positive effect on the survival of a rare species, there can be some merit to maintaining isolation. Subdivision of populations for an extended period of time can retain overall genetic diversity to a greater extent than if periodic immigration occurred (Lacy 1987). The benefit of population subdivision is particularly true if there is higher allelic richness within populations than among, if populations have adapted to specific microclimates, and if within population inbreeding is not a factor but outbreeding depression is a possibility (Templeton 1986, Storfer 1999). These factors most closely characterize historically rare species.

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Some historically rare species, such as glacial relicts, may be adapted to small population existence (Brigham 2003). These species that once had a more widespread range may now be restricted to pockets of suitable habitat as a result of glacial activity (Huenneke 1991). Glacial relict species are often classified as having a reduced distribution, low genetic variation, and high population differentiation (Lutz et al. 2000, Bauert et al.1998, Gabrielsen et al. 1997). The geographic range of S. virginiana is thought to be the result of glacial activity during the

Pleistocene (Anders and Murrell 2001), adapted to the associated freeze/thaw disturbance

(USFWS 1992).

Geographic isolation is not always represented in genetic data. For example, in eastern white pine (Pinus strobus) there was no detectable effect on genetic variation or population differentiation between ancestral populations in the central range and isolated populations on the periphery although they were separated 8000 years ago (Rajora et al. 1998). However, there is genetic evidence from this study that indicates that populations of S. virginiana have been isolated from one another long enough to become highly structured. As for time since isolation,

Luikart and Cornuet (1998) define recent bottlenecks as having occurred within approximately

0.2 - 4.0 Ne generations. Therefore, we believe that populations of S. virginiana have possibly

been reduced and isolated for longer than four generations, perhaps since the last glacial period,

therefore suggesting that S. virginiana is more representative of being historically rare as

opposed to recently rare.

Management Suggestions

Considering the information on rarity given above, it is possible to create targeted management

strategies for this and other riparian species. These are as follows:

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1) Re-establish populations with enhanced genetic variation and increase abundance of current populations.

As calculated in this study, populations of S. virginiana are isolated from one another and therefore experiencing the effects of genetic drift. When this situation occurs, populations can adapt to their local environment and any outcrossing could disrupt these genotypes and result in reduced fitness (Templeton 1986, Brigham 1996). For example, offspring of Ipomopsis aggregata that were produced from mating between populations that were 100 m apart had a

32% reduction in fitness than those offspring produced when populations were only 10 m apart

(Waser et al. 2000). Therefore, we suggest initially only one population be planted to monitor seed production and seedling establishment and compare the results with already existing populations to determine if there is a fitness cost. However, to sufficiently measure fitness costs, monitoring should take place through at least one generation, and this could be time extensive and generation time for S. virginiana is unknown. Quick actions are imperative to the conservation of a species, particularly when so few genotypes exist, so we suggest that this initial population be monitored for a full year to observe seed development and establishment.

If there are no reductions in fitness, then current populations could be more interconnected by re-establishing populations with various combinations of genotypes, which is listed as a recovery task in the S. virginiana recovery plan (USFWS 1992). First, the appropriate habitat needs to be selected, on which successful establishment and longevity heavily relies.

Spiraea virginiana occurs more commonly in the stream channel and along stream banks on second and third order streams, and some level of flooding is required for dispersal and the removal of competitors (USFWS 1992). For this reason, stabilization of water flow has negative consequences for the species but large scale floods can also increase the rate of extinction for

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species that are more naturally rare due to their generally small and isolated populations

(Oostermeijer 2003). Therefore, any restored populations should be placed within a stream or on streambanks where water flow manipulation has been at a minimum.

To enhance successful establishment, we suggest using clonal propagules for initial establishment when restoring populations. Although cuttings have not been tested for survival and longevity, seeds collected from the field exhibited low germination rates (10%) in a greenhouse setting (Brzyski and Culley, Chapter 5). Younger clones should be planted preferentially before older clones due to their greater ability to sprout and extend rhizomes

(USFWS 1992). Evidence from previous restorations of plants capable of vegetative growth suggest that clonal propagules are successful, and may even establish better than seedlings

(Bowles et al. 1998)

We suggest establishing populations composed of as many local genotypes as possible to maximize genetic variation. Local is defined here to be within one kilometer of the re- established populations (Linhart 1995). As previously stated, genetic variation allows populations to adapt to their changing environment (Frankham 1995). Genetic variation also aids in adaptation and long-term persistence for restored populations (Knapp and Dyer 1998).

Therefore, mixing different source populations could enhance the ability to adapt to environmental changes (Fenster and Dudash 1994), as long as outcrossing depression is not a problem.

Regardless if a population is re-established or already present, populations should be sufficiently large to buffer against environmental and demographic stochastic events. There have been many different recommendations as to this population size, varying from 50 to as high

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as 100 000, with the most common estimate being 100 individuals or larger (Franklin 1980,

Shaffer 1987, Lacy 1987, Barrett and Kohn 1991, Lande 1995, Lynch et al. 1995).

2) Restored populations should have high genetic variation at the self-incompatibility locus

(multiple source populations) to maximize opportunities for sexual reproduction.

Isolated and non-breeding populations may be able to persist through clonal reproduction but are not viable in the long term (Frankham 1995). Self-incompatible (SI) species that are at small population sizes may experience Allee effects at the SI locus from the reduction in allelic richness by genetic drift (Wagenius et al. 2007, Courchamp et al. 2008). Based on the theory that at least three S-alleles are necessary for a population to persist (Wright 1939, Campbell and

Lawrence 1981), we suggest that a minimum of three genets with different SI alleles be planted.

If the identity of SI alleles is not known, there is only a 27% probability of randomly picking three genets where both SI alleles are different. Therefore, if SI alleles are not identified within each plant, then an abundance of different genets should be chosen to ensure that different SI alleles are present.

Natural introduction of new alleles through migration is important, particularly for SI alleles. However, there may be a species-specific optimum distance between populations that allows for periodic migration, usually at an intermediate distance (Price and Waser 1979).

Populations should then be placed within this distance to promote migration. Previous research on S. virginiana suggested that genetic exchange via sexual reproduction was taking place where the nearest populations were 2.3 - 3.5 kilometers away (Brzyski and Culley, Chapter 5) but, in general, pollen transfer generally occurs at much shorter distances, within two meters of the donor but it can be up to 40 meters away (Escaravage and Wagner 2004). Therefore, we

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conservatively suggest that populations be placed within 40 meters of each other. Enhancing genetic variation is especially important if clonal reproduction eventually becomes the dominant reproductive method in the restored population.

3) Protect the genetic integrity of S. virginiana populations by monitoring and controlling the presence of non-native species, specifically S. japonica, in close vicinity to S. virginiana.

Rare species that are less genetically divergent and have reduced seed set, such as S. virginiana, are most susceptible to hybridization (Levin et al. 1996). One specific non-native competitor of concern is the closely related, introduced species Spiraea japonica. Spiraea japonica was introduced to the northeastern United States in 1870 and is now naturalized throughout the eastern U.S. (Remaley 2005). Commonly used as an ornamental shrub, there are numerous self-sustaining populations in natural environments, and it is frequently observed growing with or near populations of S. virginiana (R. Gardner, pers. comm., J. Brzyski, pers. observation). There is evidence that S. japonica hybridizes with other congeners such as Spiraea thunbergii (Masahide et al. 2003) and Spiraea albiflora (USDA 2008). If S. virginiana has limited mating opportunities within its own species, it may cross-pollinate with S. japonica.

Through previous hand pollination experiments, we had one incident where viable seed was produced from a cross in which S. japonica pollen was added to an emasculated S. virginiana inflorescence. One of the seeds also successfully germinated, although not all microsatellite loci adequately amplified in the sample and the genotype could not be confirmed (Brzyski and

Culley, unpubl. data). Regardless, we believe that this provides enough evidence to be concerned about hybridization between these two species. As a result, we recommend that all populations of S. virginiana, particularly those more robust populations, be monitored for the

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appearance of S. japonica within them or in the proximity. S. japonica can clonally reproduce, it is a prolific seed producer, and germination rates of the seeds can be high (Brzyski and Culley,

Chapter 5). Therefore, at first observation, all efforts should be made for the swift removal of this introduced species.

4) Increase species value

Public outreach through arboretums promotes the understanding and appreciation of plants. Botanical gardens and arboretums also play a vital role in propagating threatened and endangered species while also allowing researchers access to these species not easily studied in their natural habitat. In particular, the Arnold Arboretum of Harvard University is a participating institution of the Center for Plant Conservation and contains accessions of S. virginiana.

Educational outreach should also be done to inform land owners of the importance of retaining the biological integrity along their streamside property, not only for such purposes as protecting biodiversity but also for bank stabilization and flood abatement. For these two purposes, we also suggest additional propagation of S. virginiana along streams and rivers.

Conclusion

This study provided genetic evidence consistent with the hypothesis that populations of S. virginiana have been isolated for an extended period of time. The ability to reproduce through rhizomatous growth has allowed this shrub to persist in isolation. However, extensive clonal growth may not retain enough genetic variation to allow for the adaptation necessary for prolonged survival in changing environments (Frankham 1995). This is the fate of many glacial relict species from the past, and may be the future for many others as a consequence of habitat

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degradation and climate change (Huenneke 1991). By researching historically rare species and their tools for survival, we can design better management plans for future rare species.

Acknowledgments

The authors thank S. Matter, E. Maurer, S. Rogstad, and S. Selbo for editorial comments.

Thanks to U.S. Fish and Wildlife Service, National Park Service, Ohio Department of Natural

Resources, and the Tennessee Department of Environment and Conservation for collection permits. We also thank A. Bishop, M. Kerr, T. Littlefield, M. McAllister, J. Rock, and D. White for field assistance. Funding was provided by the Catherine H. Beatty Fellowship from the

Garden Club of America and the University Research Council Fellowship and Wendel, Weiman,

Benedict Award from the University of Cincinnati to J. Brzyski.

117

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Table 1. Results from previous research conducted on Spiraea virginiana.

Character Description Reference Highly clonal Average: 4.6 genets/population Chapter 3 Low SI-allele diversity Average: 3.1 alleles/population Chapter 4 Low seed germination 10.3% total percent germination Chapter 5

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No. of No. of Subpopulations with State Population Subpopulations Unique Alleles Ohio OH1 5 2 Kentucky KY1 2 2 Kentucky KY2 7 4 Tennessee TN1 5 3 Tennessee TN2 15 4 Tennessee TN3 3 1 Tennessee TN4 4 2 Tennessee TN5 2 0

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Table 3. Pair-wise comparisons of population differentiation (θ) for Spiraea virginiana. Those values in bold are significantly different from zero based on 95 % confidence intervals derived from bootstrapping across loci.

OH1 KY1 KY2 TN1 TN2 TN3 TN4 TN5 OH1 KY1 0.395 KY2 0.195 0.038 TN1 0.264 0.161 0.122 TN2 0.446 0.273 0.231 0.316 TN3 0.326 0.320 0.136 0.247 0.319 TN4 0.516 0.415 0.300 0.300 0.487 0.547 TN5 0.365 0.260 0.165 0.140 0.372 0.372 0.320

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Table 4. Pair-wise migration rates of sampled populations, with clones removed, of Spiraea virginiana.

OH1 KY1 KY2 TN1 TN2 TN3 TN4 TN5 OH1 0.686 KY1 0.761 1.563 KY2 0.181 0.096 0.292 TN1 0.614 0.792 1.176 3.247 TN2 0.650 0.565 1.001 0.135 0.795 TN3 0.439 0.361 0.432 0.103 0.304 0.398 TN4 0.768 0.366 0.650 0.072 0.593 0.614 0.468 TN5

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Figure 1. Map of sampling distribution of populations of Spiraea virginiana. Black dots indicate general location of sampled populations.

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Figure 2. Sample genotype distribution within one population of Spiraea virginiana (OH1).

Subpopulations are represented by ovals and the number of unique multilocus genotypes (A, B,

C) within each population is displayed.

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Figure 3. Mantel test showing no correlation (r = 0.162, p = 0.264) between the two matrices of geographic distance and genetic distance (θ) among populations of Spiraea virginiana.

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CHAPTER 7

General Conclusions

Jessica R. Brzyski

Department of Biological Sciences

University of Cincinnati

614 Rieveschl Hall

Cincinnati, OH USA 45221-0006

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Rare species face many challenges, including loss of habitat and impacts from non-native species (Wilcove et al. 1998). The autecology of a species, its interaction with its environment, can also result in negative impact on population growth and expansion (Lesica 1992, Scott and

Gross 2004). The research described in this dissertation explored species autecology and its potential impacts on rarity by investigating life history traits, specifically those related to reproduction, in the federally threatened Spiraea virginiana. The information from this study directly addressed research needs identified in the recovery plan of this species (USFWS 1992) and can be used to aid in the recovery of the species.

Before any management suggestions could be made, however, the type of rarity a species exhibits needed to be identified. Knowing the type of rarity is important because those species that are historically rare, as opposed to recently rare, may be adapted to small population sizes

(Brigham 2003). This adaptation could lead to outbreeding depression if other genotypes are brought together (Templeton 1986). In addition, these small but adapted populations could be stable in their environment and would draw attention and resources away from other population in more urgent conservation need. Due to the lack of historical records on population range and size for S. virginiana, I collected genetic information by first designing 11 microsatellite loci specifically for this species (Chapter 2). Through genetic analyses, I was able to infer that the species is more likely to be historically rare than recently rare, as indicated by the low levels of genetic variation and high levels of population differentiation in S. virginiana (Chapter 6). In addition, the estimated number of migrants among populations was low, averaging less than one migrant per generation, and there was no relationship between genetic and geographic distance.

This evidence indicates that not only has S. virginiana been rare for multiple generations, but populations have likely also been isolated from one another for multiple generations. This

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isolation has resulted in reduced genetic variation within populations but through clonal reproduction, high levels of heterozygosity have been retained (Chapter 3).

The extent of isolation that populations experience can also impact sexual reproduction.

Spiraea virginiana is capable of both sexual and asexual reproduction, as are the majority of riparian plant species (Naiman and Decamps 1997). Theoretically, being capable of both modes of reproduction prevents inbreeding (de Nettancourt 1977) while providing reproductive assurance, particularly in times of low pollinator abundance (Holsinger 2000, Charpentier 2002).

However, S. virginiana provides an example of how, instead of being a positive effect, being self-incompatible and clonal may actually be a hindrance to long-term survival. With only 38 genotypes of S. virginiana detected throughout three different states, self-incompatibility of the species could result in very few sexual reproductive opportunities (Anderson and Stebbins 1984,

Byers and Meagher 1992). Possibly as a result of this situation, the self-incompatibility system

in S. virginiana may be breaking down to now allow fertilization by self pollen (Chapter 4).

This could be seen as both beneficial and detrimental to the species. Being capable of selfing

allows the benefit of sexually reproducing even when there are few to no mates in the vicinity

and could also produce new genotypes. However, selfing could result in decreased genetic

variation, especially in levels of heterozygosity in this clonal species. It has been postulated that

heterozygosity retains additive genetic variation, which is necessary for adaptation (Hartl and

Clark 2007). Although hand pollinations suggest that selfing may be evolving in the species,

evidence from naturally pollinated inflorescences in the field indicates that outcrossing is also

occurring. Fitness of selfed seeds compared to outcrossed needs to be investigated to determine if there is a fitness cost to selfed offspring.

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In this dissertation, I also investigated the effects of an additional threat to rare species caused by non-native species. In particular, introduced species used for horticultural purposes have a high tendency to become invasive due to multiple introductions and select breeding for such traits as quick growth and high flower production (Reichard 1997, Mack 2000), which are also considered ‘weedy’ traits (Baker 1974). A majority of invasive woody plants were initially in cultivation; Reichard (1997) found that 82% of 235 woody plants became naturalized after being cultivated for landscaping purposes. In 1998, Spiraea species, which is mostly composed of Spiraea japonica cultivars (Wilson and Hoch 2009), were one of the most popular ornamental shrubs determined by number of commercial sales, second only to roses (USDA 1998). Their popularity still exists 10 years later, being the fourth most popular shrub sold in 2009 (USDA

2009). Spiraea japonica, in particular, is a non-native species of concern due to its naturalization ability (Remaley 1998) and current invasive classification in five states (Kentucky, Tennessee,

Pennsylvania, Virginia, and North Carolina) (USDA 2010). Both Spiraea species have been observed in the same habitat as well as in direct competition with one another (R. Gardner, pers. comm., J. Brzyski, pers. obs.). They are almost physically identical except when flowering as S. virginiana has white inflorescences and S. japonica has pink. As such, two location reports of S.

japonica were falsely recorded as S. virginiana (J. Brzyski, pers. obs.).

To examine the potential for the two species to interact, I compared germination rates

between them. Spiraea japonica has a reproductive advantage with a three-fold higher

germination rate (Chapter 5). In addition, I measured hybridization success through hand

pollinations and one hybrid seed was produced between the two species. This seed successfully

germinated but conclusive evidence through genotyping failed. Spiraea japonica has been

shown to produce hybrid offspring with other congeners such as the non-native shrub Spiraea

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thunbergii, with successful regeneration in a laboratory setting (Masahide et al. 2003), and hybrids are acknowledged to exist between S. japonica and Spiraea albiflora (USDA 2008).

There are S. japonica varieties that are suggested to be sterile and their use for horticultural purposes could help to combat future naturalization of this species (Li et al. 2004, Wilson and

Hoch 2009) but vigorous testing on reproductive sterility should take place.

The data gathered by this project will give land managers greater information to make more informed management decisions, specifically in the recovery of a federally threatened species, S. virginiana. These results are also applicable to other riparian species that have the same morphological and ecological characteristics as S. virginiana. Clonality, self- incompatibility, and flooding regime requirements are common in species inhabiting this particular environment (Naiman and Decamps 1997). Unfortunately, due to a lack of financial and time resources, not every species can be studied in detail. As such, information from one characteristic species can be applicable to others, thus having large implications for conservation biology, especially when time is of the essence. Therefore, if information exists for a similar species, such as now does for S. virginiana, then decision making can be quick and informed.

Lastly, this research explores how the autecology of a species can negatively impact its own survival, particularly when faced with the threats of habitat loss and modification as well as invasive species, both of which are prevalent in riparian habitat (Brinson et al. 1981, Abramovitz

1996). The more information gathered on the threats to rare species and their resulting impacts, the more prepared biologists can be to combat such threats, particularly in today’s fast changing environment.

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Appendix 1

Diagrams of Spiraea virginiana populations and their genotypes

Diagrams for each population consist of an oval to represent the subpopulations where Spiraea virginiana was sampled. Actual size of subpopulation and distance from the next subpopulation are not to scale. However, position of each subpopulation along the stream with respect to one another is accurate. Within each subpopulation, the genotype that resides there is described by an arbitrary letter, and the number of plants sampled with that genotype is represented by the number of letters present. Direction of water flow is also noted.

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Population OH1

5 subpopulations

3 genotypes: A, B, C

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Population KY1

2 subpopulation

2 genotypes: D, E

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Population KY2

6 subpopulations

8 genotypes: F, G, H, I, J, K, M, N

143

Population TN1

5 subpopulations

6 genotypes: O, P, Q, R, S, T

144

Population TN2

15 subpopulations

8 genotypes: U, V, W, X, Y, Z, AA, AB

145

Population TN3

3 subpopulations

2 genotypes: AD, AE

146

Population TN4

4 subpopulations

4 genotypes: AF, AG, AH, AI

147

Population TN5

2 subpopulations

2 genotypes: AJ, AK

148