Systematics of Penstemon Section Ericopsis (Plantaginaceae), a Group of Plant Species Native to the Intermountain West

Systematics of Penstemon section Ericopsis (Plantaginaceae), a group of plant species native to the Intermountain West

DISSERTATION

Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University

Aaron James Wenzel

Graduate Program in Evolution, Ecology and Organismal Biology

The Ohio State University

2016

Dissertation Committee:

Andrea Wolfe (Advisor)

John Freudenstein

Laura Kubatko

Steve Matthews

Copyrighted by

Aaron James Wenzel

2016

Abstract

Penstemon Mitchell (Plantaginaceae) is the largest plant genus endemic to North

America with approximately 283 species. Most species are only relatively recently diverged from one another, which has left questions about taxonomy and systematics in

Penstemon unanswered. This dissertation considered one section in the genus, Ericopsis

Keck, a group of 15 species from the Intermountain Region in western USA.

Evolutionary and ecological frameworks were used to investigate phylogenetic relationships, population demographic history, polyploidy, and niche divergence.

Chapter 1 presents the results of a phylogenetic study of section Ericopsis. Using a total of 39 nuclear and chloroplast loci obtained from high-throughput targeted sequencing and Sanger sequencing, the exact membership of section Ericopsis was able to be determined. This included two taxa not currently classified in section Ericopsis, P. pinifolius and P. dolius var. dolius. It was also determined that three current Ericopsis species, P. acaulis, P. yampaensis, and P. laricifolius, group in a clade with species from section Cristati with high support. Within the Ericopsis clade, however, nodal support for relationships among species was low, so strong conclusions about exact relationships are difficult to ascertain. There was support for a clade comprising the species of subsection Linarioides, as well as groups consisting of the varieties of P. caespitosus and

P. crandallii. It is likely that incomplete lineage sorting and hybridization are causing ii gene tree incongruence in these analyses, which may be alleviated by adding additional sequence data from informative loci. Chapter 1 also provides the context for questions asked in subsequent chapters of the dissertation.

Chapters 2 and 3 use a population genetics framework to study evolutionary dynamics in two widespread species from section Ericopsis. In chapter 2 the variable P. linarioides Gray is considered. This population genetics study included 299 individuals from 22 populations (representing four of the five varieties) and seven microsatellite loci.

Overall genetic structure was limited, with the majority of genetic variation distributed within individuals. However, clustering methods revealed that populations of the same varieties grouped with one another, and that varieties linarioides and coloradoensis share a close relationship. In addition there was evidence of hypothesized cryptic diversity within var. sileri, with populations forming three distinct clusters, representing the

Markagunt Plateau of southern Utah, the Beaver Dam/Bull Valley mountains of southern

Utah, and the Kaibab Plateau of northern Arizona. Finally, an historical demographic study using approximate Bayesian computation found that a lineage most likely diverged from var. sileri and then split again into varieties linarioides and coloradoensis. The timing of this event is estimated to be around the end of the Pleistocene.

Chapter 3 is a population genetics study of P. caespitosus Nutt. ex. Gray, a species with three varieties from Utah, northern Arizona, and western Colorado.

Penstemon caespitosus is an interesting case study because one of its varieties, desertipicti, is a tetraploid while varieties caespitosus and perbrevis are diploid. A total of 222 individuals from nine populations were considered in this study with the same

iii microsatellite loci from chapter 2. Genetic structure was much greater in P. caespitosus than in P. linarioides. Results from clustering analyses revealed a close relationship between var. perbrevis (from central Utah) and var. desertipicti (from southwest Utah and northern Arizona). Tetraploid var. desertipicti also contained many unique alleles, consistent with a pattern of allotetraploidy. Although one of the parent progenitors is likely var. perbrevis, the other parent is most likely another species from section

Ericopsis that shares a close geographic range with var. desertipicti (such as P. thompsoniae or a variety of P. linarioides).

Chapter 4 builds on the results of the first three chapters by exploring niche divergence between sister taxa using ecological niche modeling (ENM). ENMs were constructed in MaxEnt using presence-only data collected from herbarium records. A total of four comparisons were made between sister species and varieties. Most comparisons showed a situation of incomplete niche divergence, where niches of sister taxa were similar but not identical to one another. The comparisons made between varieties of P. laricifolius (laricifolius vs. exilifolius) and varieties of P. linarioides

(linarioides vs. coloradoensis) revealed that the two niches were more different than would be expected at random. The largest amount of niche divergence was between diploid P. caespitosus var. perbrevis and tetraploid var. desertipicti. These results support a scenario where sister taxa are diverging along environmental gradients (mostly precipitation and temperature during certain times of the year), and where polyploidy has led to even greater niche divergence.

Dedication

I dedicate this dissertation to my wife and parents, who have provided me with

unconditional love and support as I have taught, worked in the lab, and chased after

plants in the field for weeks at a time. Special thanks are in order for Beth and Mark

Wenzel, who have always encouraged my academic endeavors and have especially

supported me throughout graduate school.

I offer special thanks as well to the love of my life, Naomi McDowell. Your support of my passion for the natural world has been immeasurable, and I am so happy to have had

you as a partner throughout all of this.

Acknowledgments

This work would not have been possible without the input and assistance of many individuals, and I am indebted to all who have taken the time to help me these past six years. I would first like to express my gratitude to Andrea Wolfe, my advisor, for mentoring me from a naïve first-year grad student to PhD graduate. Your guidance and support has been immeasurable.

I would also like to thank past mentors I have had. Janet Gehring (Bradley

University), my first research advisor, introduced me to plant population genetics and piqued my interest in the broader field of evolutionary biology. I am also thankful to my mentors at my alma mater Xavier University, especially Dorothy Engle and Jen Robbins.

Your guidance during the formative years of my scientific education was invaluable and unforgettable.

I am thankful to all who helped me in the field and made collections for me, including Marc Baker, Mike Stevens, Marcel Jouse, Frank Riechenbacher, Miriam Islam, and Al Schneider. I am also thankful to my fellow graduate students who took time help me with issues and read countless drafts of grant proposals and manuscripts: Sam

Herrmann, Tony Fries, Jimmy Chiucchi, Mike Sovic, Ryan Folk, And Eric McCluskey. I appreciate all of the help and advice I have received from my committee members, as well as help from Jose Diaz, our lab technician. Finally, thank you to all of my fellow

vi comrades in the Wolfe Pack, especially Dan Robarts and Paul Blischak. Whether it was giving advice on how to resolve a certain issue in the lab, explaining a new statistical analysis, or providing company during a late night lab session, both of your friendships have been enriching to me scientifically and personally.

vii

Vita

June 2006 ...... Vandalia-Butler High School

May 2010 ...... B.S. Biology, Xavier University

2010 to present ...... Graduate Teaching Associate, Department

of Evolution, Ecology, and Organismal

Biology, The Ohio State University

Publications

Wenzel, A. (2015). Systematics of Penstemon section Ericopsis. Bulletin of the American Penstemon Society, 74: 9-21.

Blischak, P.D., Wenzel, A.W., and Wolfe, A.D. 2014. Gene Prediction and Annotation in Penstemon (Plantaginaceae): A Workflow for Marker Development from Extremely Low-Coverage Genome Sequencing. Applications in Plant Sciences 2 (12), http://dx.doi.org/10.3732/apps.1400044.

Fields of Study

Major Field: Evolution, Ecology and Organismal Biology

viii

Table of Contents

Abstract ...... ii

Dedication ...... v

Acknowledgments...... vi

Vita ...... viii

Publications ...... viii

Fields of Study ...... viii

Table of Contents ...... ix

List of Tables ...... xii

List of Figures ...... xiv

Chapter 1: Phylogenetics and taxonomic affinities of Penstemon section Ericopsis using high-throughput targeted sequencing ...... 1

Abstract ...... 1

Introduction ...... 2

Methods ...... 8

Results ...... 12

Discussion ...... 16

Tables and Figures ...... 25

Chapter 2: Population genetics, systematics, and phylogeography of Penstemon linarioides, a widespread and variable species from western North America ...... 31

Abstract ...... 31

Introduction ...... 32

Methods ...... 37

Results ...... 44

Discussion ...... 51

Tables and Figures ...... 60

Chapter 3: Population genetics, systematics, and polyploidy in Penstemon caespitosus from Utah ...... 79

Abstract ...... 79

Introduction ...... 80

Methods ...... 85

Results ...... 91

Discussion ...... 97

Tables and Figures ...... 105

Chapter 4: Investigation of niche divergence and evolution in Penstemon section

Ericopsis using ecological niche modeling...... 124

Abstract ...... 124

Introduction ...... 125

Methods ...... 128

Results ...... 132

Discussion ...... 135

Tables and Figures ...... 144

References ...... 157

Appendix A: Locus information from phylogenetics study ...... 172

Appendix B: Locality data used in ENM construction ...... 174

List of Tables

Table 1: Description of species in section Ericopsis ...... 25

Table 2: Information on accessions used in this study ...... 26

Table 3: Description of varieties of Penstemon linarioides ...... 60

Table 4: Populations of P. linarioides sampled ...... 61

Table 5: Microsatellite loci with alleles sizes for P. linarioides...... 62

Table 6: Allele counts per locus and per population for P. linarioides ...... 63

Table 7: Measures of allelic and genetic diversity for P. linarioides ...... 64

Table 8: Population pairwist Fst (below diagonal) and Nm (above diagonal) values for P. linarioides ...... 65

Table 9: Average pairwise Fst (below diagonal) and Nm (above diagonal) for populations of varieties sileri, linarioides, and coloradoensis ...... 66

Table 10: Descriptions of the three varieties of P. caespitosus ...... 105

Table 11: Populations of P. caespitosus sampled for this study ...... 106

Table 12: Sizes of alleles amplified from seven SSR loci in P. caespitosus ...... 107

Table 13: Number of alleles amplified per locus in each population of P. caespitosus . 108

Table 14: Allelic diversity for P. caespitosus populations ...... 109

Table 15: Homozygous and heterozygous genotypes for each locus in P. caespitosus . 110

xii

Table 16: Pairwise values of PhiPT between populations of P. caespitosus ...... 111

Table 17: Average pairwise PhiPT values between P. caespitosus varieties ...... 112

Table 18: Study taxa information with number of localities used in ENMs ...... 144

Table 19: Climatic layers used in ENM construction ...... 145

Table 20: Average area under the curve (AUC) score for each taxon's ENM and the two variables contributing most to the model ...... 146

Table 21: Percent contribution of each climatic layer to each ENM, as well as the average value of each variable ...... 147

Table 22: Empirical values of Schoener's D and I, as well as results from the niche identity test ...... 148

Table 23: Loci and the method of sequencing used in Chapter 1 ...... 173

Table 24: GPS coordinates for P. acaulis ...... 175

Table 25: GPS coordinates for P. yampaensis ...... 176

Table 26: GPS coordinates for P. caespitosus var. perbrevis ...... 177

Table 27: GPS coordinates for P. caespitosus var. desertipicti ...... 178

Table 28: GPS coordinates for P. laricifolius var. laricifolius ...... 179

Table 29: GPS coordinates for P. laricifolius var. exilifolius ...... 182

Table 30: GPS coordinates for P. linarioides var. linarioides ...... 184

Table 31: GPS coordinates for P. linarioides var. coloradoensis...... 186

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List of Figures

Figure 1: 50% majority rule consensus tree from SVDQuartets ...... 27

Figure 2: 50% majority rule consensus tree from SVDQuartets with compatible groups included ...... 28

Figure 3: 50% majority rule consensus tree from RAxML ...... 29

Figure 4: 50% majority rule consensus tree from RAxML with compatible groups included ...... 30

Figure 5: Distribution map for populations of P. linarioides ...... 67

Figure 6: Historical demographic scenarios modeled in DIYABC for the first set of analyses ...... 68

Figure 7: Historical demographic models used in the second set of analyses in DIYABC

...... 70

Figure 8: Neighbor-joining tree for all 22 populations of P. linarioides ...... 71

Figure 9: PCoA for all 22 populations of P. linarioides ...... 72

Figure 10: Plot of delta-K for results of Structure with all 22 populations of P. linarioides

...... 73

Figure 11: Structure plots for K=3 (above) and K=6 (below) ...... 74

xiv

Figure 12: Neighbor-joining tree for 9 populations of var. sileri ...... 75

Figure 13: PCoA for populations of var. sileri ...... 76

Figure 14: Delta-K plot for var. sileri Structure results ...... 77

Figure 15: Structure plot for var. sileri ...... 78

Figure 16: Distribution map of P. caespitosus populations used in this study ...... 113

Figure 17: PCoA plot of populations of P. caespitosus ...... 114

Figure 18: Neighbor-joining tree of P. caespitosus populations based on Nei's genetic distance ...... 115

Figure 19: Delta-K plot for Structure analysis run for populations of P. caespitosus .... 116

Figure 20: Structure plots for K=3 (above) and K=2 (below) for populations of P. caespitosus ...... 117

Figure 21: Chart showing the percent of shared alleles among the three varieties of P. caespitosus ...... 118

Figure 22: Chart showing the percentage of shared alleles among varieties of P. caespitosus plus P. linarioides var. sileri ...... 119

Figure 23: PCoA of populations of P. caespitosus and P. linarioides var. sileri ...... 120

Figure 24: Neighbor-joining tree of P. caespitosus and P. linarioides var. sileri based on

Nei's genetic distance ...... 121

Figure 25: Delta-K plot for Structure analysis of P. caespitosus and P. linarioides var. sileri ...... 122

Figure 26: Structure plots of P. caespitosus and P. linarioides var. sileri for k=3 (above) and k=4 (below) ...... 123

Figure 27: Map of the average ENM for P. acaulis as constructed in MaxEnt ...... 149

Figure 28: Map of the average ENM for P. yampaensis ...... 150

Figure 29: Map of the average ENM for P. caespitosus var. desertipicti ...... 151

Figure 30: Map of the average ENM for P. caespitosus var. perbrevis ...... 152

Figure 31: Map of the average ENM for P. laricifolius var. exilifolius...... 153

Figure 32: Map of the average ENM for P. laricifolius var. laricifolius ...... 154

Figure 33: Map of the average ENM for P. linarioides var. coloradoensis ...... 155

Figure 34: Map of the average ENM for P. linarioides var. linarioides ...... 156

xvi

Chapter 1: Phylogenetics and taxonomic affinities of Penstemon section Ericopsis using high-throughput targeted sequencing

Abstract

This study presents the findings of a molecular phylogenetic investigation of

Penstemon section Ericopsis using high-throughput targeted amplicon sequencing.

Section Ericopsis consists of 16 species (27 total taxa including subspecific varieties) native to the Four Corners states in western North America. The group’s defining morphological characteristic is its predominantly mat-forming habit; some species form mats up to a meter in width. From a taxonomic perspective, section Ericopsis has proven to be confusing, with taxa frequently moving into and out of the section throughout its history. We aimed to use molecular sequence data to (1) refine the membership of section Ericopsis and (2) elucidate relationships among species. Our dataset consisted of

39 total loci (36 nuclear low-copy loci and 3 chloroplast loci) sequenced via the Illumina platform (30 loci) and traditional Sanger sequencing (9 loci) for a total of 15,187 bp of data. The two methods of phylogenetic analysis (SVDQuartets and RAxML) agreed exactly on taxonomic membership of section Ericopsis with strong bootstrap support.

There was strong support in both analyses for membership of three species not currently in section Ericopsis (the hummingbird-pollinated P. pinifolius, P. dolius var. dolius and

P. harbourii) and for removal of three current Ericopsis species, P. acaulis, P.

1 yampaensis, and P. laricifolius, which all grouped in a clade with species of section

Cristati. Within section Ericopsis, however, support for relationships between individual species was low, with the exception of species from subsection Linarioides. It is likely that the taxa of section Ericopsis are very recently diverged from one another, therefore allowing phenomena such as incomplete lineage sorting and hybridization due to incomplete reproductive barriers to act as a complication in resolving species-level relationships.

Introduction

With ca. 283 species, the genus Penstemon Mitchell (Plantaginaceae) represents the largest plant genus endemic to North America (Wolfe et al. 2006). Although representatives occur in all states in the continental U.S. (Nold 1999), the Intermountain

Region of western North America corresponds to the genus’ center of diversity (Wolfe et al. 2006). The genus is divided into six subgenera that have traditionally been classified based on anther dehiscence patterns; three of these subgenera are further classified into sections and subsections (Nold 1999). Section Ericopsis Keck is found within the subgenus Penstemon and includes 16 recognized species distributed among three subsections (Ericopsis Keck, Caespitosi Keck, and Linarioides Keck). With a few exceptions, members of section Ericopsis are typically mat-forming subshrubs with stems that are prostrate-to-ascending and 10-30 cm tall. Leaves vary in shape from linear to oblanceolate and vary in pubescence from glabrous to puberulent to scabrous.

Inflorescences for most of the species range from thyrses that are secund, thyrses with

2 one-flowered cymes, or reduced inflorescences with solitary flowers. Corollas are blue to violet. Each flower has four fertile stamens with anthers that are divaricate and, like other members of subgenus Penstemon, dehisce completely from the distal ends of each anther cell across the connective tissue that joins the cells. A fifth sterile stamen

(staminode) is bearded with yellow hairs (Holmgren 1984).

Species of section Ericopsis have a distribution that includes the Intermountain

Region and extends east into the Rocky Mountains, south into southern Arizona and New

Mexico, west into southern California, and north into Wyoming and Montana. The majority of species occur in relatively restricted ranges while several of the larger complexes that have multiple subspecific taxa (e.g., P. caespitosus, P. linarioides, P. thompsoniae) have much larger ranges comparatively. Species in Ericopsis prefer habitats with dry, well-drained, sometimes gravelly soil with exposure to significant amounts of sunlight. They can often be found in the Artemisia sagebrush and pinyon- juniper communities common to the Intermountain West, although exceptions certainly exist (i.e., P. crandallii preferring oak communities).

The taxonomic history of section Ericopsis is complicated and has involved substantial reorganization and revision. Pennell (1920) first recognized section

Caespitosi, which included six of the species currently classified in Ericopsis. Keck

(1937) was the first to describe section Ericopsis, which means “like Erica,” emphasizing the heather-like morphology of species in the group (hence their common name, the heather penstemons; Nold 1999). Keck (1937) mostly used the low, mat-forming properties of most of the species in Ericopsis as the main characteristic describing the

3 section. Keck (1937) recognized three subsections, Caespitosi, Linarioides, and

Laricifolii, each containing seven, three, and one species, respectively. Subsections

Linarioides and Laricifolii have not changed since Keck’s (1937) treatment of the group, although subsection Laricifolii has been renamed subsection Ericopsis. Subsection

Linarioides, composed of P. californicus, P. discolor, and the P. linarioides complex, is characterized by having ascending to erect stems (not low-forming mats like section

Caespitosi; Keck 1937; Nold 1999). These species occur in southern Utah and Colorado through eastern New Mexico and Arizona (Table 1). Subsection Ericopsis consists only of P. laricifolius, which is a taller plant with erect stems and is glabrous throughout its inflorescences and herbage (Keck 1937; Nold 1999). The two varieties of P. laricifolius

(laricifolius and exilifolius) have a range that includes Wyoming and southern Montana

(Table 1).

Subsection Caespitosi, however, has been subjected to substantial revision since

Keck (1937) (Table 1). Keck (1937) recognized four subspecific varieties of P. caespitosus; variety suffruticosus has since attained specific status (now P. tusharensis;

Holmgren 1979). Keck (1937) also recognized four varieties of P. crandallii, two of which were varieties glabrescens and procumbens. Pennell (1920) considered P. glabrescens a species, as did Greene (1901) for P. procumbens, before Keck (1937) lumped these two into P. crandallii. Barrell (1969), however, re-established these as separate species, mostly on the grounds of geographic and ecological separation, as well as morphological differences (e.g., P. procumbens has glabrous leaves while P. crandallii has puberulent leaves; P. glabrescens has narrow linear leaves while P. crandallii has

4 oblanceolate leaves). Finally, Nelson (1937) described P. ramaleyi just after Keck

(1937) established section Ericopsis; Nelson placed it in the section despite its non- caespitose habit. Table 1 presents all of the species in section Ericopsis, as well as distributional and habitat information.

Wolfe et al. (2006) is the only study to date that has used phylogenetic methods to analyze members in section Ericopsis. In their study they used DNA sequence data from the nuclear (ITS) and chloroplast (trnCD, trnTL) genomes to infer the phylogenetic tree of Penstemon, as well as to evaluate the current taxonomic circumscription of the genus in terms of the recognized subgenera and sections. The two datasets produced consensus trees that were inconsistent with each other and did not resolve many relationships among individual species. Both trees contained groupings of members from section Ericopsis, but because of the lack of resolution mentioned above, questions about the systematics of the section remain. For example, Wolfe et al. (2006) found that two species included in section Ericopsis, P. acaulis and P. laricifolius, were not found in the Ericopsis clade, instead grouping with species from another section, Cristati. These results call into question the placement of these two species in section Ericopsis, in addition to another

Ericopsis species, P. yampaensis, which is similar morphologically to P. acaulis

(Holmgren 1984). Conversely, two species currently not included in section Ericopsis, P. dolius and P. pinifolius, are included in the Ericopsis clade in the ITS consensus tree and show a close affinity to P. linarioides (and to each other) in the cpDNA consensus tree.

A third non-Ericopsis species, P. harbourii, was also included in the Ericopsis clade in the ITS tree (Wolfe et al. 2006).

This was not the first time that the taxonomic affinities of P. dolius and P. pinifolius had been questioned. Penland (1958) emphasized the relationship between sections Ericopsis and Cristati (to which P. dolius belongs) through P. dolius.

Penstemon dolius shares the smaller habit common to some of the species in section

Ericopsis and also part of its geographic range (central Utah to Nevada; Holmgren 1984).

Penstemon pinifolius is a hummingbird-pollinated species with red corollas native to southern Arizona and New Mexico (Nold 1999). Similar to P. dolius, P. pinifolius shares the low, mat-forming habit with members of section Ericopsis. Straw (1962) admitted that the placement of P. pinifolius was unclear and was hesitant to place it in section

Fasciculus, going so far as to say that P. pinifolius should represent its own, separate monotypic subsection because it did not fit in well with other members of section

Fasciculus subsection Fasciculi. Crosswhite and Crosswhite (1981) actually suggested that P. pinifolius would be a better fit in section Ericopsis, arguing that P. pinifolius is associated with section Fasciculus simply because it has red corollas, a suggestion reiterated by Wolfe et al. (2006).

One of the reasons for the lack of resolution in the trees from Wolfe et al. (2006) was the lack of a sufficient amount of variation in sequence data to fully elucidate relationships among closely related species, a common issue in the phylogenetics community prior to high-throughput sequencing (HTS) techniques (Wolfe et al. 2006;

Egan et al. 2012; Lanier et al. 2014). Until recently researchers had to rely on time- consuming and costly gene-by-gene sequencing approaches in order to obtain sufficient sequence data to address evolutionary questions of interest. However, recent advances

6 in technology have made HTS methods much more readily available and affordable to researchers working with non-model organisms (Egan et al. 2012; Faircloth et al. 2012;

Stull et al. 2013). Still, these sequencing processes, such as sequence capture and genome skimming, require construction of libraries for each sample, increasing both the time spent and cost of a project. A potential solution to this issue is to use microfluidic

PCR to generate barcoded sequencing libraries of targeted regions that can then be sequenced using an HTS platform. Such microfluidic PCR-based target enrichment techniques using Fluidigm Access Array System (Fluidigm, San Francisco, CA) have been successfully used in plant phylogenetics (Gostel et al. 2015; Uribe-Convers et al.

2016), as well as human-related genetics projects (e.g., Jones et al. 2011).

The aim of this study was to identify nuclear and chloroplast loci specific to Penstemon, sequence them using microfluidic PCR methods and HTS, and use them in a phylogenetic analysis of section Ericopsis. Specific questions include: (1) what are the relationships among species in section Ericopsis? (2) Do the three currently recognized subsections reflect phylogenetic patterns and groupings? (3) Do P. acaulis, P. yampaensis, and P. laricifolius, three species currently classified in section Ericopsis, belong to the Ericopsis clade? (4) Are P. dolius, P. harbourii, and P. pinifolius, species not classified in section Ericopsis, members of the Ericopsis clade?

Methods

Study taxa

A total of 48 accessions were included in this phylogenetic study (Table 2).

Twenty-five of the accessions represented taxa from section Ericopsis, and all but five

(P. thompsoniae var. desperatus, P. thompsoniae var. thompsoniae, P. glabrescens var. taosensis, P. linarioides var. maguirei, and P. linarioides var. compactifolius) of the described taxa in the section were included. In addition, four species from subgenus

Dasanthera were included as outgroups, as it is the earliest diverging lineage in

Penstemon (Datwyler and Wolfe 2004; Wolfe et al. 2006). To investigate taxonomic affinities for P. dolius and P. pinifolius, accessions of samples from sections Cristati and

Fasciculus were also included. Finally, 11 other accessions representing taxa taken from various clades of the Penstemon phylogeny (Wolfe et al. 2006) were also included. Most samples from section Ericopsis were collected between 2011 and 2013 by AJW, and their

DNA extracted using a modified CTAB protocol (Wolfe 2005). Other samples were from the Wolfe Lab Penstemon DNA library. Vouchers for all taxa are deposited at the

Ohio State University Herbarium (Table 2).

Target selection and primer design

Primers were designed from targeted loci using the workflow described in

Blischak et al. (2014). Briefly, whole-genome shotgun (WGS) sequencing data for two species in subgenus Dasanthera, P. davidsonii and P. fruticosus, were downloaded from

GenBank (Dockter et al. 2013). The MAKER2 pipeline was used for gene annotation and prediction for these sequences. We then looked for annotated contigs that contained

8 pentatricopeptide repeat (PPR) domains; PPR loci belong to a large multigene family and serve in a post-transciption capacity (Yuan et al. 2009). They have also been shown to be useful for phylogenetic inference in plants (Yuan et al. 2009; Yuan et al. 2010). We targeted PPR loci that were 400-500 bp long and used Primer-BLAST (Ye et al. 2012) to design primers for these loci. In addition we searched for single-copy nuclear genes from the conserved ortholog set (COSII) for euasterids (Wu et al. 2006). COSII sequences were downloaded from The Aribidopsis Information Resource (TAIR; http://arabidopsis.org). We then used TBLASTX with default settings to identify COSII loci in P. davidsonii and P. fruticosus. As with the PPR loci, we searched for loci that were 400-500 bp long. We also looked for regions that exhibited between 2-5% sequence variation between P. davidsonii and P. fruticosus. Primers for these loci were designed in Primer3Plus (Rozen and Skalestsky 2000), and the Fluidigm conserved sequence (CS) tags were added to all designed primers.

Test PCRs were run for all PPR and COSII primers with CS tags using the PCR conditions described in Li et al. (2008). We chose four species representing disparate parts of the Penstemon phylogeny to test our designed primers (P. caespitosus, P. davidsonii, P. heterophyllus, and P. humilis). We chose loci only if they produced one clear band in each species on a 1% agarose gel. This produced 34 COSII loci and 6 PPR loci. The three loci used in Wolfe et al. (2006) (trnCD and trnTL from the chloroplast and ITS from the nucleus) were included in the study as well, in addition to five other chloroplast loci from Shaw et al. (2007). Finally, we added nine more nuclear loci (six

COSII and three PPR) that were sequenced using di-deoxy termination sequencing with

9 the Big Dye terminator chemistry (Life Technologies, Grand Island, NY). Reactions for di-deoxy terminator sequencing were run on an ABI 3100 Genetic Analyzer (Life

Technologies, Grand Island, NY).

Microfluidic PCR, sequencing, and data processing

The concentration of each sample was quantified using a Qubit Fluorometer and dsDNA HS Assay Kit (Life Technologies, Grand Island, NY), and each sample was either diluted or concentrated to 30 g/L. Each array of the Fluidigm Microfluidic PCR

Access Array System allows for 48 unique loci, with each well containing a forward and reverse primer. Microfluidic PCR (as well as sequencing) took place at the Institute for

Bioinformatic and Evolutionary Studies (iBest, University of Idaho, Moscow, ID), following the manufacturer’s protocols. Sequencing of the resulting microfluidic PCR samples took place in an Illumina MiSeq at iBest. This included downstream quality control of both the microfluidic PCR and Illumina sequencing processes.

We used dbcAmplicons (https://github.com/msettles/dbcAmplicons), a python application, to bioinformatically process our Illumina data. The application recognizes and removes the target specific primer sequence, and associates barcodes to individual samples. We chose to trim 25 bp and 50 bp off of our forward and reverse primer regions, respectively; this was done in order to deal with issues of poor sequencing at the ends of reads. Consensus sequences for each sample were then generated using the software Genious v. 9.5.1 (Kearse et al. 2012) and sequences were aligned using

MUSCLE v. 3.8.21 (Edgar 2004) with default settings. In order to address allelic heterozygosity alleles were phased using the program PHASE v. 2.1.1 (Stephens et al.

2001) using the “MS” model, along with the program SEQPHASE (Flot, 2010) to interconvert sequence and allele data for phasing. For sequences generated via di-deoxy termination sequencing, forward and reverse copies of each locus for each sample were visually inspected in the alignment software CodonCode (CodonCode Corporation,

Centerville, MA). Consensus sequences were then aligned using MUSCLE as implemented in CodonCode. These sequences were also phased using the procedure described above.

Phylogenetics analyses

Two different phylogenetic methods were used to analyze the data set.

SVDQuartets (Chifman and Kubatko 2014) is a coalescent-based method implemented in

PAUP* 4.0a146 (Swofford 2002) that estimates the phylogeny of four randomly drawn samples (quartets). The quartet sampling method is repeated and a resulting species tree can be inferred from all of the quartets. Although this method assumes unlinked single nucleotide polymorphisms, simulation studies have illustrated that it works for multilocus sequence data as well (Chifman and Kubatko 2014). SVDQuartets was run by sampling all possible quartets with 100 bootstrap (BS) replicates to assess support. In addition, a concatenated approach was carried out using maximum likelihood in the program

RAxML (Stamatakis 2008) using the GTR+ substitution model with 100 rapid bootstrap iterations. Because RAxML does not have the capability to handle taxon partitioning, the concatenated dataset used for this method included sequences that were not phased and contained IUPAC ambiguity codes at heterozygous sites. The analysis in SVDQuartets, however, did use the phased sequence data.

Results

Data processing

Of the 48 loci included in the Illumina sequencing run, 30 of them produced high- quality reads from which consensus sequences could be constructed (Appendix 1). The remaining 18 loci either did not produce high quality reads or the reads produced very messy alignments, indicative that these regions may have been introns. Of the seven chloroplast loci used in this study only three produced reads that could be used in the final data matrix (psbBH, rpl16, and, rps12rpl2). The three loci used in Wolfe et al.

(2006), trnCD, trnTL, and ITS, did not work on this sequencing run and thus were not included. When the sequences from the nine loci obtained from Sanger sequencing were combined with the 30 loci from the Illumina run the data matrix contained a total of

15,187 bp. For the total data matrix, 19% of the sequence data were missing. When all

48 taxa were considered the percentage of variable sites was 12.2%; however, when only taxa from the clade comprising of members of section Ericopsis were considered the amount of variable sites dropped to 4.1%. The nuclear data set contained a greater percentage of variable sites (12.6%) than the chloroplast data set (9.22%).

Analysis of the SVDQuartets and RAxML trees

Figures 1-4 show a 50% majority rule consensus tree as well as a majority rule consensus tree with compatible groups from the SVDQuartets and RAxML analyses.

The two methods produced several similar results and relationships that did not have high

BS support, so the consensus trees with compatible groups were included as a means of

12 comparison between the two methods. The two methods agreed completely on the clade that includes members of section Ericopsis with strong support (BS=93 in the

SVDQuartets tree and 96 in the RAxML tree, Figures 1 and 3). In addition, both trees show P. harbourii as having a sister relationship to the rest of section Ericopsis with

100% BS support, a finding that Wolfe et al. (2006) found as well. Both methods also agree that three species currently included in section Ericopsis, P. acaulis, P. yampaensis, and P. laricifolius, are not included in the Ericopsis clade. They group with other species in section Cristati, a clade with moderated-to-strong support (BS=66 and

100 for the SVDQuartets and RAxML trees, respectively; Figures 1 and 3). In both analyses the branching of these three species within section Cristati is identical, with P. laricifolius as sister to the rest of the section, then a sister grouping of P. acaulis and P. yampaensis as sister to the remaining species. Both methods also agree that two taxa not currently in section Ericopsis are included in the Ericopsis clade. Penstemon pinifolius, currently a member of section Fasciculus, is not included in the strongly supported clade that includes members of section Fasciculus (BS=98 in SVDQuartets and RAxML trees).

Likewise, P. dolius var. dolius, currently classified in section Cristati, is recovered in the

Ericopsis clade instead. Interestingly, the other variety of P. dolius, var. duchesnensis, is included in section Cristati instead of grouping with var. dolius (Figures 1 and 3).

Finally, one other species in section Ericopsis, P. ramaleyi, was not included in the

Ericopsis clade in either analysis. In fact, it appears as the second-most basal lineage after the four species from subgenus Dasanthera. This may be due to missing data

13 caused by low-quality sequencing reads obtained for this accession, as the reads for P. ramaleyi were often much shorter than for the other samples.

Although support for the entire Ericopsis clade was high in both analyses, support for nodes within the section was generally very low (Figures 2 and 4). This is in contrast to nodal support values within sections Cristati and Fasciculus, which were generally higher. Unsurprisingly, the concatenated RAxML analysis produced higher BS values on nodes within section Ericopsis, as coalescent methods that account for gene tree- discordance consistently produce lower nodal support values than methods that use concatenation (Figure 4). Taxa belonging to subsection Linarioides (P. linarioides, P. californicus, and P. discolor) form a well-supported clade (BS=88) in the RAxML tree.

Varieties linarioides and coloradoensis exhibit a strong sister relationship to one another

(BS=94), consistent with findings from a population genetics study of P. linarioides

(Chapter 2). The subsection Linarioides clade forms a strongly supported (BS=92) sister relationship with sister species (BS=94) P. thompsoniae var. jaegeri and P. dolius var. dolius. Penstemon pinifolius is sister to all of the previously mentioned taxa, albeit exhibiting weak support (BS=52). The RAxML tree has two other instances of BS support greater than 50: the two varieties of P. crandallii, crandallii and atratus from eastern Utah, form a sister relationship (BS=98), and P. tusharensis forms a sister relationship to P. caespitosus varieties perbrevis and desertipicti with moderate support

(BS=74). The sister relationship between varieties perbrevis and desertipicti has low support (BS<50), but was supported in a population genetics analysis of P. caespitosus

(Chapter 3).

Bootstrap values within section Ericopsis in the SVDQuartets tree were even lower than the RAxML tree (Figure 2). Still, some common patterns emerge with the

RAxML analysis. Penstemon linarioides var. linarioides and var. coloradoensis form a sister relationship (BS=98), and they are sister to P. linarioides var. sileri (BS=63). The

SVDQuartets majority rule consensus tree with compatible groups shows that the varieties of P. linarioides are included in a clade with the other two species of subsection

Linarioides, with very low nodal support. As in the RAxML majority rule consensus tree with compatible groups (Figure 4), P. dolius var. dolius and P. pinifolius form a clade with the members of subsection Linarioides, but the BS support is very low (BS<50;

Figure 2). Unlike the RAxML tree, P. thompsoniae var. jaegeri is not included in this clade. The SVDQuartets tree also agrees with the RAxML tree in terms of the two varieties of P. crandallii having a sister relationship, although the nodal support in the

SVDQuartets analysis is lower (BS=64). The only other relationship with BS support greater than 50 in the SVDQuartets analysis was a weakly supported sister relationship between P. procumbens and P. retrorsus (BS=52), which was not found in the RAxML tree (Figures 1 and 2). As in the RAxML tree, the three varieties of P. caespitosus form a weakly supported clade in the SVDQuartets tree (BS<50), with varieties desertipicti and perbrevis forming a sister relationship with low support (Figure 2). Unlike the RAxML analysis, the P. caespitosus grouping did not include P. tusharensis, whose placement is of interest because it was originally a variety of P. caespitosus (var. suffruticosus;

Holmgren 1979).

In addition to the similarities between the two methods discussed above, the two methods also show that the P. caespitosus group is sister to the subsection Linarioides group. The subsection Linarioides group is also affiliated with P. thompsoniae var. jaegeri, P. crandallii, and P. glabrescens var. glabrescens (Figures 2 and 4). Both trees also show that P. abietinus and P. retrorsus have a weakly supported sister relationship, and that these two are sister to the rest of section Ericopsis (in the SVDQuartets tree P. procumbens is included with P. abietinus and P. retrorsus but not in the RAxML tree;

Figures 2 and 4). Of course, a large caveat to this is that the support values at internal nodes within the Ericopsis clade, including the nodes that show these relationships, are very low (BS<50), making it difficult to make strong conclusions. However, given that both trees exhibit these general patterns (albeit with weak support), there is some evidence for these relationships.

Discussion

Using the findings of Wolfe et al. (2006) as a framework, we investigated phylogenetic relationships among species in section Ericopsis in order to gain insight into what species actually belong in the section and whether or not phylogenetic relationships reflect current subsectional classifications. Support for individual relationships was generally low in both the SVDQuartets and RAxML analyses (Figures 1-4), so it is difficult to assert many strong conclusions about relationships between individual species in section Ericopsis (discussed below). However, both analyses produced similar results that warrant further discussion.

Both the SVDQuartets and RAxML trees agree on which taxa belong in section

Ericopsis, with these species forming a clade with high BS support (Figures 1 and 3). In both trees P. harbourii has a strongly supported sister relationship to the rest of section

Ericopsis, a result consistent with Wolfe et al. (2006). Currently classified in section

Penstemon, P. harbourii is found at high elevations in the La Plata and Sangre de Cristo mountains of southwest Colorado and northwest New Mexico (Nold 1999; Lindgren and

Wilde 2003). The species is also a mat-former that does not grow very tall and is very compact (Nold 1999), making its close relationship to section Ericopsis understandable.

In addition, both trees agree that three species currently classified within section

Ericopsis, P. acaulis, P. yampaensis, and P. laricifolius, are not part of the Ericopsis clade, but group with species from section Cristati (Figures 1 and 3). Species in this section tend to be small, tuft-forming plants (they are often described as “dwarfs”), instead of the mat-formers of section Ericopsis (Nold 1999). They also have a range more to the north of the rest of section Ericopsis. Penstemon acaulis and P. yampaensis

(sometimes treated as varieties of P. acaulis; Lodewick and Lodewick 2002), native to sandstone-derived soils of northeast Utah and calcareous soils of northwest Colorado, respectively, are acaulescent tuft-forming plants that Penland (1958) actually argued should have been placed in section Cristati originally. Penstemon laricifolius, from northern Colorado and Wyoming, is also a tuft-forming plant that grows to about 20 cm in height (Nold 1999; Lindgren and Wilde 2003). These three species seem much better suited in section Cristati than section Ericopsis.

In both methods of analysis P. pinifolius and P. dolius var. dolius group with members of section Ericopsis (Figures 1 and 3). Penstemon pinifolius, currently a member of section Fasciculus, is a low-growing, mat-forming species with stems reaching about 15 cm in height (Greene 1881; Nold 1999). It also has red corollas and is primarily pollinated by hummingbirds. Originally, Bennett and Keck (1953) placed P. pinifolius with P. fasciculatus in a section they named Stenanthus based on the similarity in leaf morphology between the two species, but then Bennett (1960) placed P. pinifolius in section Fasciculus, presumably based on personal correspondence with Richard Straw.

However, Straw (1962) called the association of P. pinifolius and P. fasciculatus into question, noting the difference in corolla morphology (P. pinifolius has more dissected, narrow corolla lobes). In his treatment of section Fasciculus, Straw (1962) placed P. fasciculatus in section Fasciculus subsection Fasciculus but suggested that P. pinifolius have its own monotypic subsection in section Fasciculus. Nearly two decades later,

Crosswhite and Crosswhite (1981) outright contested the placement of P. pinifolius in section Fasciculus. They argued that P. pinifolius was placed in the group partly because of its red corollas, a character state that has arisen independently in several Penstemon clades (Crosswhite and Crosswhite 1981, Wolfe et al. 2006, Wilson et al. 2007).

Crosswhite and Crosswhite (1981) suggested that P. pinifolius showed greater morphological affinity to species in section Ericopsis. Species in section Fasciculus tend to be much larger (up to 200 cm in height) than those in section Ericopsis as well, another characteristic P. pinifolius shares with section Ericopsis. Penstemon dolius var. dolius, currently placed in section Cristati, is a small plant with ascending-to-erect stems

18 reaching 20 cm in height, has oblanceolate leaves, and is found from central Utah to eastern Nevada. Interestingly, the other variety of P. dolius, var. duchesnensis, does not group with var. dolius and instead remains in the section Cristati clade (Figures 1 and 3).

Variety duchesnensis is even more of a dwarf plant than var. dolius and has a smaller range in the Uinta Basin of northeast Utah, mainly in Duchesne County (Holmgren 1984;

Nold 1999). As with P. acaulis and P. yampaensis, P. dolius var. duchesnensis is smaller than average for section Ericopsis and, with a range more to the north than most of section Ericopsis, may actually have closer affinities to section Cristati. It should be noted that there is a lot of missing data for var. duchesnensis (it produced very few high- quality reads in the Illumina run), so this result may be an artifact of incomplete data.

Therefore, additional sequence data for P. dolius var. duchesnensis should be collected before any hard conclusions are drawn about its sectional membership.

Both methods of analysis yielded a result where the three species of subsection

Linarioides form a clade (well-supported in the RAxML tree, low support in the

SVDQuartets tree; Figures 1-4). Compared to most of the other species in section

Ericopsis, these plants have stems that are ascending-to-erect, tend to be larger, and do not form mats as predominantly as other Ericopsis species (Kearney and Peebles 1960;

Martin and Hutchins 1981; Holmgren 1984; Nold 1999). Their distribution lies to the southwest of most other members of section Ericopsis, with a center of diversity in

Arizona. Also included in the clade with subsection Linarioides are P. pinifolius and P. dolius var. dolius (well-supported in the RAxML tree, low support in the SVDQuartets tree; Figures 2 and 4). Penstemon pinifolius’ range includes eastern Arizona, western

New Mexico, and adjacent areas of Mexico (Kearney and Peebles 1960; Martin and

Hutchins 1981). It is similar morphologically to P. linarioides, with individuals forming clumps with stems reaching a height of ~20 cm (Lindgren and Wilde 2003). Penstemon dolius var. dolius, however, seems an odder fit with the taxa of subsection Linarioides.

Although its range includes western Utah and central Nevada, it tends to be a smaller plant than those found in subsection Linarioides. It also has oblanceolate leaves, compared to the linear leaves found in subsection Linarioides (Holmgren 1984; Nold

1999).

Another well-supported sister relationship in both trees is that between the two varieties of P. crandallii. Variety crandallii, native to western Colorado and eastern

Utah, is a more upright version of var. atratus, which grows lower to the ground and has decumbent stems. Variety atratus also has a narrower range, as it is endemic to the La

Sal Mountains of eastern Utah (Holmgren 1984). Penstemon crandallii used to include two other varieties, procumbens and glabrescens (Keck 1937), which are now both species (Barrell 1969). Both trees provide some evidence that these two taxa should remain separate species from P. crandallii. In the SVDQuartets tree P. procumbens forms a weakly supported sister relationship with P. retrorsus (Figure 2). Although the two do not share many morphological similarities (P. procumbens is a prostrate plant with obovate, glabrous leaves while P. retrorsus is an upright plant with oblanceolate leaves with retrorse pubescence), the ranges of the two species are close to one another in western Colorado (Barrell 1969; Nold 1999). The relationship between P. procumbens and P. retrorsus, however, does not appear in the RAxML tree. Although the placement

20 of P. glabrescens within Ericopsis is ambiguous in this study because of low nodal support, it is probably also safe to assume its specific status apart from P. crandallii.

Native to southern Colorado and northern New Mexico, P. glabrescens shares more morphological characteristics with P. linarioides than P. crandallii (upright growth with linear leaves; Martin and Hutchins 1981; Nold 1999). As with all of the species in this analysis, additional sequence data may help to resolve the placement of these two in section Ericopsis.

The three varieties of P. caespitosus exhibit an interesting pattern in both analyses. All three are included in a clade with low support (BS<50) in both trees. In addition, varieties perbrevis and desertipicti, from central Utah and southwest

Utah/northern Arizona, respectively, have a sister relationship, although again with low support in both cases. This is consistent with Chapter 3, where a population genetics study using microsatellite markers showed a close relationship between varieties perbrevis and desertipicti. What is interesting is that in the RAxML tree, P. tusharensis is recovered as sister to P. caespitosus varieties perbrevis and desertipicti with moderate support (BS=74); this relationship is not found in the SVDQuartets tree. Penstemon tusharensis is native to the Tushar Mountains of central Utah and used to be another variety of P. caespitosus (var. suffruticosus). Holmgren (1979) gave it specific status, arguing that it bears a closer resemblance to P. thompsoniae than P. caespitosus, with its larger, obovate leaves and upright growing habit (Holmgren 1984; Nold 1999). The fact that it groups with P. caespitosus with moderate support in one of the trees is interesting, although it is difficult to make strong conclusions about its relationship to P. caespitosus

21 because it does not appear in the SVDQuartets tree (Figures 1 and 2). Another interesting aspect is that P. caespitosus var. desertipicti is a polyploid (Broderick et al. 2011), and

Chapter 3 presents evidence that var. perbrevis is probably one of the progenitor parent taxa to allotetraploid var. desertipicti. The other parent taxon is unknown, and P. tusharensis should be included in an expanded microsatellite study to investigate if it may be the other parent taxon.

Section Ericopsis is currently divided into three subsections. The results from this study show that subsections Linarioides and Ericopsis reflect phylogenetic relationships, although the only species in subsection Ericopsis, P. laricifolius, is more closely related to species in section Cristati (Figures 1-4). There was no evidence found for phylogenetic relatedness reflecting the largest subsection in section Ericopsis, subsection Caespitosi. Low nodal support along the backbone of the Ericopsis clade makes it difficult, however, to surmise what the actual subsectional classifications should be. It is possible that additional sequence data may provide enough information to make a stronger inference of subsections possible, but at the current moment we can conclude that subsection Linarioides is reflected in phylogenetic relationships while subsection

Caespitosi is probably not.

Figures 1 and 3 show the 50% majority rule trees with compatible groups from both analyses, and although some of the compatible groups with low (<50) support are similar between the two methods of analysis, the low support still makes it difficult to make clear conclusions about relationships. Indeed, this study still encounters some of the same difficulties of Wolfe et al. (2006) in terms of not being able to resolve

22 relationships among species. What is interesting is that BS support is stronger in other clades outside of the Ericopsis clade, especially in clades representing sections Cristati and Fasciculus (Figures 1 and 3). There are several possible reasons for why this is the case, one of which is the amount of information contained in the sequence data. A lack of informative characters is a common cause of not obtaining resolution with good support among species (Lanier et al. 2014). When all 48 taxa from this study are considered, the percentage of variable sites among all 39 loci is 12.2%. However, among only species in the Ericopsis clade that percentage drops to 4.1%. It is not surprising that when just closely related species are compared the amount of sequence variation drops, but it does indicate that part of the issue in terms of gaining more resolution among taxa may be a lack of sequence variation. Wolfe et al. (2006) hypothesized that the evolution of Penstemon resulted from a rapid evolutionary radiation dating to the events of the

Pleistocene, which would date the emergence of the genus within, at most, the past 2-3 million years. Along those same lines, chapter 2 presents the results of a historical demographic study for P. linarioides using approximate Bayesian computation (ABC) and found that the divergence between P. linarioides varieties linarioides and coloradoensis mostly took place within the past 20,000 years. Although relative dating for divergence among the rest of the species in section Ericopsis does exist, the results from the ABC analysis suggests that members of section Ericopsis may be very recently diverged from one another, possibly even more recent than other groups given higher support values outside of section Ericopsis. Therefore, incomplete lineage sorting (Liu et al. 2009) is probably complicating efforts to resolve relationships among species in

23 section Ericopsis. Another potential cause of gene tree incongruence is hybridization

(Maddison 1997). Many species in Penstemon hybridize readily (Keck 1932; Keck 1945;

Wolfe and Elisens 1993; Wolfe and Elisens 1994; Wolfe and Elisens 1995; Wolfe 1998a;

Wolfe 1998b; Datwyler and Wolfe 2004), presumably including those species in section

Ericopsis (e.g., hybrid swarm in Iron County, Utah between P. caespitosus var. desertipicti and P. thompsoniae var. thompsoniae, personal observation). Hybridization may be even more of a factor for section Ericopsis, as recently diverged species presumably have not had time to evolve effective reproductive barriers.

In conclusion, this phylogenetics study of section Ericopsis yielded a clear picture of which species belong in the section (including P. harbourii, P. pinifolius and P. dolius var. dolius) as well as species that should be segregated from it (P. acaulis, P. yampaensis, and P. laricifolius). Even though the Ericopsis clade showed strong bootstrap support in both the SVDQuartets and RAxML analyses, relationships within the section, including among species, was generally low. Species belonging to subsection

Linarioides formed weakly supported to well-supported clades, in contrast to the rest of the species in subsection Caespitosi. We hypothesize that factors causing gene tree incongruence, such as incomplete lineage sorting and hybridization, has made it difficult to obtain strong resolution among section Ericopsis species in this study. Additional high-variation loci should be sequenced and added to the existing data set in an attempt to gain resolution among the species of this group. Additional data should also be collected for taxa from this study that had substantial missing data (P. ramaleyi, P. dolius var. dolius) and for the five taxa of section Ericopsis that were not included in this study.

Tables and Figures

Table 1: Description of species in section Ericopsis

Species Name Habitat Distribution Description Subsect. Caespitosi Dry, pinyon-juniper and sage brush P. abietinus c. UT Linear leaves; erect stem; small blue flowers woodland sw. WY, Very small; leaves erect and linear; flowers small P. acaulis* Dry sandstone, clay nw CO, and and blue ne. UT s. WY, nw. Mat-forming; stems prostrate; linear pubescent P. caespitosus* Dry plateaus, canyons, sagebrush CO, c. UT leaves and n. AZ Pinyon-juniper woodlands; often dry s. CO, e. Stems erect or prostrate; glabrous to gray-green P. crandallii* roadsides UT pubescent foliage; flowers deep blue

s. CO and Stems erect to ascending; blue corollas; leaves P. glabrescens* Sub-montane, dry roadcuts n. NM narrow and linear

Subalpine, draped over large rock Stems prostrate; leaves obovate and glabrous; P. procumbens wc. CO outcroppings flowers dark blue Herbaceous; ascending stems; linear leaves; blue P. ramaleyi Along dry roadcuts c. CO corollas Erect stems (~8"); oblanceolate leaves w/ retrorse P. retrosus Sagebrush, dryland w. CO hairs

c. and wc. Linear leaves with tiny hairs; short, woody stems; P. teucrioides Appearing among P. crandallii CO blue flowers

CA, NV, Stems prostrate; leaves obovate w/ pubescence on P. thompsoniae* Pinyon-juniper woodland UT, and both sides; flowers (blue-violet) larger than AZ leaves Stems ascending or erect; leaves obovate to P. tusharensis Sandy or gravelly subalpine slopes c. UT spatulate; violet corollas Subsection Linarioides

s. CA; Baja Forms low mounds; dense, white pubescence on P. californicus Pinyon-juniper woodland CA, Mex. oblanceolate leaves; blue-violet flowers

Sub-shrub; gray-pubescent leaves; white or P. discolor Mountains NE of Tucson, AZ s. AZ purple corolla

sw. and nw. Erect stems; leaves oblanceolate-cinereous (blue- Sagebrush, pinyon-juniper NM, se. P. linarioides* gray), pubescent; blue/lavender flowers w/ white woodland, ponderosa forests and c. AZ, throats sw CO, UT

Subsection Ericopsis Erect stems (~8"); linear, glabrous leaves; purple P. laricifolius* Dry basins and foothill WY, n. CO or white corolla

Table 2: Information on accessions used in this study

Species Subgenus Section Voucher P. caespitosus var. caespitosus Penstemon Ericopsis AJW 01 P. caespitosus var. perbrevis Penstemon Ericopsis AJW 05 P. caespitosus var. desertipicti Penstemon Ericopsis AJW 15 P. abietinus Penstemon Ericopsis AJW 08 P. crandallii var. crandallii Penstemon Ericopsis AJW 20 P. crandallii var. atratus Penstemon Ericopsis AJW 19 P. procumbens Penstemon Ericopsis AJW 23 P. glabrescens var. glabrescens Penstemon Ericopsis AJW 25 P. teucrioides Penstemon Ericopsis AJW 29 P. linarioides var. linarioides Penstemon Ericopsis AJW 45 P. linarioides var. sileri Penstemon Ericopsis AJW 35 P. linarioides var. coloradoensis Penstemon Ericopsis AJW 49 P. thompsoniae var. jaegeri Penstemon Ericopsis AJW 43 P. californicus Penstemon Ericopsis AJW 42 P. tusharensis Penstemon Ericopsis Stevens 49 P. discolor Penstemon Ericopsis Reichenbacher 50 P. laricifolius var. laricifolius Penstemon Ericopsis ADW 1383 P. laricifolius var. exilifolius Penstemon Ericopsis ADW 1385 P. acaulis var. yampaensis Penstemon Ericopsis Jouse 11 P. acaulis var. acaulis Penstemon Ericopsis Jouse 35 P. retrorsus Penstemon Ericopsis Arft 9-51 P. ramaleyi Penstemon Ericopsis Islam 01 P. pinifolius Penstemon Fasciculus AJW 46 P. dolius var. dolius Penstemon Cristati ADW 818 P. dolius var. duchesnensis Penstemon Cristati ADW 1442 P. davidsonii Dasanthera Erianthera SLD 39 P. fruticosus Dasanthera Erianthera SLD 49 P. rupicola Dasanthera Erianthera ADW 575 P. montanus Dasanthera Erianthera SLD 51 P. ophianthus Penstemon Cristati ADW 835 P. jamesii Penstemon Cristati ADW 807 P. albidus Penstemon Cristati MWES 7949 P. breviculus Penstemon Cristati ADW 823 P. isophyllus Penstemon Fasciculus PJ 3 P. hartwegii Penstemon Fasciculus HBH 3319 P. campanulatus Penstemon Fasciculus HBH 3482 P. amphorellae Penstemon Fasciculus JG 392 P. harbourii Penstemon Penstemon JT 01 P. rydbergii Penstemon Penstemon MM 01 P. humilis Penstemon Penstemon MWES 7970 P. heterophyllus Saccanthera Saccanthera Malessa 13 P. richardsonii Saccanthera Serrulati ADW 585 P. pseudospectabilis Penstemon Peltanthera ADW 767 P. centranthifolius Penstemon Peltanthera PW 3521 P. barbatus Habroanthus Elmigera BJT 96-5 P. caryi Habroanthus Glabri AWL c-11 P. digitalis Penstemon Penstemon CPR 72 P. ambiguus Penstemon Ambigui PW 3898A 26

Figure 1: 50% majority rule consensus tree from SVDQuartets Members of section Ericopsis are highlighted in red.

Figure 2: 50% majority rule consensus tree from SVDQuartets with compatible groups included

Figure 3: 50% majority rule consensus tree from RAxML

Figure 4: 50% majority rule consensus tree from RAxML with compatible groups included

Chapter 2: Population genetics, systematics, and phylogeography of Penstemon linarioides, a widespread and variable species from western North America

Abstract

Penstemon linarioides (Plantaginaceae) is a species native to the Intermountain

Region of western USA, having a large distribution that ranges from southern Arizona and New Mexico to southern Utah and Colorado. It also contains five varieties that represent slight morphological variants seen throughout its range. However, questions have remained as to (1) the relationships among these varieties and (2) the potential presence of more varieties, especially in var. sileri from southwest Utah and Arizona

(Holmgren 1984). This study presents the results from a population genetics study of P. linarioides using seven Penstemon-specific microsatellite loci. Twenty-two populations were included in the study, with most sampling including the varieties linarioides, coloradoensis, and sileri; one population of var. compactifolius was included as well.

Within-population genetic diversity was relatively high, although populations of var. coloradoensis consistently showed lower measures of allelic richness, number of alleles, and observed/expected heterozygosity compared to varieties linarioides and sileri.

Variety coloradoensis also had higher (and significant) values of the inbreeding coefficient (FIS=0.27) relative to varieties linarioides (0.15) and sileri (0.10). AMOVA found evidence for limited population structure in P. linarioides (71% of variance

31 distributed within individuals); however, results from a Neighbor-joining tree, principle coordinates analysis, and STRUCTURE revealed that populations consistently clustered with one another according to variety. These analyses also revealed a close relationship between varieties linarioides and coloradoensis. There was evidence for additional clusters within var. sileri, with populations forming three clusters: one for the Bull

Valley/Pine Valley Mountains in southwest Utah, one for the Markagunt Plateau further to the east, and one for the Kaibab Plateau in northern Arizona. Finally, a historical demographic analysis using Approximate Bayesian computation (ABC) found that the historical scenario with the highest posterior probability involved an ancestral population of var. sileri that gave rise to a lineage that ultimately split to form varieties linarioides and coloradoensis. Using estimates of divergence times from the analysis places the timing of these events during the end of the Pleistocene, when a warming/changing climate had significant impacts on the evolution of many organisms.

Introduction

With ca. 283 species, the genus Penstemon Mitchell represents a wealth of diversity in terms of morphology, habitat, pollination, and geographic range (Nold 1999;

Lingdren and Wilde 2003; Wolfe et al. 2006). Some narrowly endemic Penstemon species have very specific habitat requirements and thus occupy a relatively small range

(e.g., Wolfe et al. 2014). Others, however, occupy a much larger range and, often, these species have several described subspecific taxa, which recognize the variants included in that species. Penstemon linarioides Gray is one such widespread species found within

32 subgenus Penstemon section Ericopsis. The range of P. linarioides (Figure 5) centers on the Four Corners states of Utah, Arizona, New Mexico, and Colorado of southwest USA, although the majority of the distribution resides in Arizona and New Mexico with only southern portions of Utah and Colorado being represented (Kearney and Peebles 1960;

Martin and Hutchins 1981; Holmgren 1984; Nold 1999). In general, P. linarioides has ascending stems with linear leaves, a characteristic shared with the two other species in subsection Linarioides, P. californicus and P. discolor (Nold 1999). The size and growth habit of P. linarioides differentiates it from the other species in the other two subsections of section Ericopsis (Caespitosi and Ericopsis) that have tuft- and mat-forming habits.

There are currently five varieties within P. linarioides (Table 1), each of which is characterized by differences in geographic range, staminode morphology, leaf morphology, and habit. Variety linarioides Gray, with a range stretching from eastern

Arizona to southwest New Mexico, has mostly upright stems reaching 50 cm in height, making it the tallest member of P. linarioides (Kearney and Peebles 1960; Martin and

Hutchins 1981; Nold 1999). Variety linarioides also shows some variation in corolla color, with some populations having lighter purple-to-pink corollas, differentiating it from the violet corollas found in the rest of P. linarioides and section Ericopsis (personal observation). Variety coloradoensis (A. Nels.) Keck differs from var. linarioides in its staminode bearding: var. coloradoensis has only a tuft of yellow hairs at the tip of the staminode, while var. linarioides has a staminode with bright yellow hairs along its entire length (Martin and Hutchins 1981; Nold 1999). Variety coloradoensis is distributed in the northwestern part of New Mexico and adjacent southwest Colorado at higher

33 elevations than var. linarioides (Table 3). Variety compactifolius Keck is a smaller plant relative to the other varieties and is native to the area around Flagstaff, Arizona. As its name suggests its leaves are arranged in a compact, heathlike pattern on the stem. It also tends to be a lower growing species in terms of habit than either varieties linarioides or coloradoensis (Kearney and Peebles 1960; Nold 1999). Variety sileri (Gray) Keck has ascending-to-upright stems, leaves glabrous-to-pubescent, leaf pubescence (where it exists) that is upright (as opposed to appressed against the leaf), and a range from central

Arizona to southwest Utah (Kearney and Peebles 1960; Holmgren 1984). Of the five varieties, var. sileri is the most poorly defined, with several morphological variants existing within its range (Holmgren 1984). Finally, P. linarioides var. maguirei Keck, native to limestone valleys in western New Mexico and adjacent Arizona, represents somewhat of an oddity within the species, having oblanceolate rather than linear leaves

(Martin and Hutchins 1981; Nold 1999). Specimens of var. maguirei have rarely been collected since its description, with the last known collection from 1993 near Morenci,

Arizona (Marc Baker - Arizona State University, personal communication.).

Much like the rest of section Ericopsis, P. linarioides has experienced substantial taxonomic and systematic reorganization throughout the years. For example, varieties coloradoensis was first described as a species (Nelson 1899) before being lumped into P. linarioides (Keck 1937). More frequently, taxa were described as originally being subspecies or varieties of P. linarioides before they were removed from the species later on. Examples of this include P. glabrescens var. taosensis (Nisbet and Jackson 1960), P. seorsus (Keck 1940), and P. californicus (Keck 1937). Penstemon linarioides var. viridis

Keck was differentiated from var. sileri on the basis of it having glabrous leaves.

However, Holmgren (1984) deemed var. viridis unworthy of recognition since leaf pubescence and glabrosity appears throughout the range of var. sileri. Nold (1999) obliquely summarized the taxonomic situation of P. linarioides as so: “Other subspecies or varieties of P. linarioides have come and gone in the literature—no doubt dozens of others are waiting to be described.” (p. 152).

Variety sileri probably represents the most problematic variety within P. linarioides. As Nold (1999) notes, it seems poorly defined because it encompasses slight morphological variants throughout its range. In fact, Holmgren (1984) has hypothesized the existence of three cryptic variants within the variety that requires investigation. The first variant is from the Pine Valley, Bull Valley, and Beaver Dam mountains of

Washington County, Utah. This “mountain” form is a tall, upright plant (though not as tall as varieties linarioides or coloradoensis) with broad leaves. The second form occupies a range to the east and south of the “mountain” form on the Markagunt and

Paunsaugunt plateaus of western Kane/eastern Iron counties Utah and on the Kaibab

Plateau in Coconino County, Arizona. This “plateau” form has a lower-growing habit than the “mountain” form, with mostly ascending stems. The “plateau” form also has more narrow leaves. The last cryptic variant within var. sileri is found to the south of the range the “plateau” form in Yuma, Yavapai, and Gila counties, Arizona, and has the tall habit of the “mountain” form with the narrow leaves of the “plateau form” (Table 3).

As in most plant groups, the taxonomy of Penstemon is based on a morphological classification (Lodewick and Lodewick 1999; Nold 1999). However, one of the only

35 molecular phylogenetics studies of Penstemon (Wolfe et al. 2006) revealed that the traditional classification might not necessarily reflect evolutionary relatedness for many taxa throughout the genus. This was found to be true of P. linarioides’ section

(Ericopsis; Wolfe et al. 2006), and given the current speculation of cryptic diversity within P. linarioides, it is reasonable to hypothesize that molecular data may provide more characters with which to assess the classification within the species. Given that subspecific taxa are presumably relatively recently diverged from one another, DNA sequence may not have had enough time to accumulate enough mutations that have tracked the evolutionary history of different varieties. However, population genetic markers, such as microsatellites (short sequences repeats or SSR’s), usually have higher mutation rates than sequence data (Jarne and Lagoda 1996; Freeland 2005), making them useful for studies of closely related groups of organisms. In the field of plant systematics, putatively neutral markers (microsatellites, ISSR’s, AFLP’s) have proved useful in delimiting closely related species (Edwards et al. 2009; Duminil et al. 2011;

Spaniel et al. 2012, Dias et al. 2014) and subspecific taxa (Cavallari et al. 2010; Karberg and Gale 2010; Menz et al. 2015). Additionally, a population genetics approach using neutral markers can be employed to infer historical demographic processes that have impacted population genetic structure, such as population divergence, range expansion, and gene flow.

The goals of this study were to use microsatellite markers to investigate population genetic diversity, population differentiation, population clustering, potential cryptic subspecific groups, and historical population demographic processes within P.

36 linarioides. Specific questions were: (1) What patterns of genetic diversity exist for populations and varieties of P. linarioides? (2) How do populations of P. linariodes cluster with one another? Do clustering patterns correspond to recognized varieties? (3) Is there evidence of the undetected forms within var. sileri hypothesized in Holmgren

(1984)? (4) How have historic population processes, such as divergence, influenced the current population genetic structure and distribution of populations and varieties of P. linarioides?

Methods

Sampling

Tissue samples of individuals were collected from populations representing four of the five varieties of P. linarioides (varieties linarioides, sileri, coloradoensis, and compactifolius) between 2011 and 2013 in the “Four Corners” states of western USA

(Figure 5). The number of individuals sampled per population ranged from 10-20; an entire branch was collected from an individual and dried on silica gel. The sampling method included collecting individuals that were more than a meter apart from one another, as individuals of P. linarioides can form substantial mats. The study included samples from 299 individuals representing 22 populations (Table 4). This includes sampling of the hypothetical geographic forms within var. sileri (Holmgren 1984) (Table

4). This sampling consisted of two populations from the Markagunt Plateau in western

Kane County, Utah, (“plateau” form) and four populations from the Pine Valley

Mountains and Bull Valley Mountains (“mountain form”) in Iron and Washington

37 counties, Utah. Samples of three populations from the Kaibab Plateau in Coconino

County, Arizona were also collected. According to Holmgren (1984), populations from this area should be the “plateau” form. However, these samples showed morphological characteristics consistent with the “southern Arizona” form that exists further to the south

(Table 4). These samples were therefore labeled “kaibab 1-3.” Samples were transported back to the lab at Ohio State on silica gel.

Sampling of the enigmatic var. maguirei could not be completed for this study, as it has not been collected nor seen since 1993. The site of that collection is now in the middle of a heavy mining operation in Morenci, Arizona that has dramatically altered the landscape of that environment. Although it is possible that var. maguirei has been extirpated, efforts to locate any existing populations are underway (Anne Frances -

NatureServe, personal communication.

DNA extraction and microsatellite analysis

DNA from dried samples was extracted following a modified CTAB protocol

(Wolfe 2005). Seven simple sequence repeat (SSR) loci were PCR-amplified using primers specifically developed for Penstemon by Kramer and Fant (2007). PCR was carried out in 10 L reactions consisting of 0.5 L genomic DNA, 5.725 L purified

PCR water, 1.0 L RedTaq 10X buffer, 1.6 L 1.25 M dNTP mixture, 0.175 L 50 mM

MgCl2, 0.25 L of both the forward and reverse primers (10 M each; the forward primer was fluorescently tagged), and 0.5 L of RedTaq polymerase (Sigma-Aldrich, St. Louis,

Missouri). PCR reactions took place in a SimpliAmp Thermal Cycler (Life

Technologies, Carlsbad, California). Thermal cycler protocols followed those of Kramer

38 and Fant (2007): (For Pen02, Pen04, Pen05, Pen18, Pen21, and Pen23) 5 min at 94 C followed by 10 cycles at 94 C for 30 s, 30 s at 60 C, with a 1 C decrease in temperature every cycle, and 2 min extension at 72 C, followed by 30 cycles at 94 C for

30 s, 50 C for 30 s, and 72 C for 2 min, and a final extension at 72 C for 10 min. For

Pen24, the protocol consisted of 5 min at 94 C, 10 cycles of 94 C for 15 s, followed by

55 C for 15 s, 23 cycles of 89 C for 15 s, followed by 55 C for 15 s, and a final extension at 72 C for 30 min. Four microliters of PCR product were run on a 1% agarose gel to confirm successful amplification.

After successful PCR amplification 1 L of the each PCR product was mixed with 9.5 L of HiDi Formamide (Life Technologies, Grand Island, New York) and 0.25

L of a lab-made fluorescently labeled size standard (ROX509 for Pen02, Pen04, Pen05,

Pen21, and Pen24; ROX799 for Pen18 and Pen23; DeWoody et al. 2004). This mixture of PCR product, formamide, and size standard was denatured at 95C for 5 minutes, cooled on ice, and run on an Applied Biosystems 3100 Genetic Analyzer (Life

Technologies, Grand Island, New York). Six of the seven loci were paired in combination with the blue+green dye system of the Genetic Analyzer so as to run duplexed reactions; the pairings (Pen18+Pen23, Pen02+Pen21, Pen04+Pen24) included two loci whose alleles could be separated based on fragment size. The last SSR locus,

Pen05, was not paired with another locus. Genoptyping of microsatelite alleles took place using the program GENEMAPPER 3.1 (Life Technologies, Grand Island, New

York). If a reaction failed it was re-run, and if the re-run failed the data for the individual at that SSR locus was scored as missing. In order to ensure consistency the first three 39

PCR products of each 96-well plate used in an individual Genetic Analyzer run were re- run in each subsequent plate and scored. If a single individual lacked data at more than three loci it was removed from the study.

Data analysis

Genetic diversity within populations

Standard population genetic statistics, such as allele counts and frequencies, observed (HO) and expected (HE) heterozygosity, were calculated in GenAlEx v. 6.5

(Peakall and Smouse 2006). The program FSTAT v. 2.9.3.2 (Goudet 2001) was used to calculate mean allelic richness across loci, as well as to compute population inbreeding coefficients (FIS) with significance assessed by running 4000 randomizations in FSTAT.

GENEPOP v. 4.2 (Rousset 2008) was used to test for pairwise linkages disequilibrium among loci with Markov chain parameters set to default (1000 dememorization steps, 100 batches, and 1000 iterations per batch). An estimation of null allele frequency was obtained in GENEPOP using the methods of Brookfield (1994) and Dempster et al.

(1977). GENECLONE v. 2.0 (Arnaud-Haond and Belkhir 2007) was used to test for clonality by determining the number of distinct multilocus genotypes (MLGs).

GENECLONE cannot analyze missing data, so only individuals who had data at all seven microsatellite loci were included. In addition, individuals with missing data were assessed manually to see if their MLG matched another in the population.

Genetic diversity among populations

In order to assess genetic divergence among populations, pairwise FST values were calculated using analysis of molecular variance (AMOVA) in GenAlEx with 9999

40 permutations used to assess significance. AMOVA was also used to estimate how much genetic variation was partitioned within and between populations. Additionally,

GenAlEx was used to calculate the pairwise values of indirect estimator of gene flow

(Nm=(1-FST)/4FST) (Wright 1969).

Genetic relationships among populations

Two sets of analyses were carried out in order to investigate relationships among populations of P. linarioides. The first set included all sampled populations and varieties of P. linarioides while the second included only the nine samples of var. sileri (This was done in order to more closely evaluate the hypothesis of unrecognized forms within var. sileri (Holmgren 1984)). In both sets of analyses, a pairwise distance matrix of populations was calculated in GenAlEx using Nei’s genetic distance (Nei 1973). This distance matrix was used to conduct a principle coordinates analysis (PCoA) in GenAlEx.

In addition, PHYLIP (Felsenstein 2005) was used to construct consensus neighbor- joining (NJ) trees (using CONSENSE) from 1000 bootstrap replicates (using SEQBOOT) based on Nei’s genetic distance.

Finally, population structure was analyzed in both sets of analyses with the

Bayesian clustering program STRUCTURE 2.3.4 (Pritchard et al. 2000). STRUCTURE estimates the probability an individual’s assignment into one of k genetic clusters. For both sets of analyses, STRUCTURE was run using the admixture ancestry model. For the full P. linarioides data set (all 22 populations) the program was run for k=1 to 22, while for the sileri-only data set (nine sileri populations) the program was run for k=1 to

9. In both cases, each value of k was replicated 10 times, with each replicate including a

41 burn-in of 100,000 steps before running 100,000 Monte chain Monte Carlo (MCMC) steps. The results from the STRUCTURE runs were summarized and visualized in the program CLUMPAK (http://clumpak.tau.ac.il). In order to determine the most likely number of clusters the method of Evanno et al. (2005) was implemented in the web-based program Structure Harvester (Earl and von Holdt 2012).

ABC analyses of population demographic history

Approximate Bayesian computation (ABC) was used to investigate multiple scenarios of population demographic history for P. linarioides. An ABC framework uses simulated genetic datasets from pre-defined scenarios and compares them to empirical data, allowing for a comparison of several potential models of demographic history. The program DIYABC v. 2.1.0 (Beaumont et al. 2002; Cornuet et al. 2014) was implemented to carry out these analyses. For the DIYABC analysis three “populations” were specified based on results from population clustering analyses: var. sileri (population 1), var. linarioides (population 2), and var. coloradoensis (population 3). Note that the two var. coloradoensis populations from northern New Mexico were included in the var. linarioides population, as they consistently clustered with the latter. Additionally, the lone var. compactifolius population was excluded from this analysis. We did two sets of

ABC analyses. The first set included nine scenarios, which are described in Figure 6.

9,000,000 simulated data sets were generated in DIYABC using the nine models and a

1:1 sex ratio as well as the default mutation model (stepwise mutation model, = 1  10-4

– 1  10-3). All available summary statistics in DIYABC were used to compare the fit of the empirical data to simulated data. The summary statistics for one sample are mean

42 number of alleles, mean heterozygosity, mean size variance, and mean Garza-

Williamson’s M. The summary statistics available for two samples are the mean number of alleles, mean heterozygosity, mean size variance, FST, classification index, shared allele distance, and (d)2 distance. The nine scenarios were compared to one another by calculating the posterior probability of each using the direct approach, and the scenario with the highest posterior probability was selected as the best.

The results of these first sets of runs indicated that a scenario where var. sileri branches off first from a lineage that leads to varieties linarioides and coloradoensis was the most likely model (see Results). In order to evaluate how effective population size may have changed throughout time, we set up a second set of four scenarios that consisted of this general branching pattern but differed in changes in effective population size (Figure 7). This second set of analyses was analyzed in the same way as the first set except that 4,000,000 data sets were generated in DIYABC. Additionally, the posterior distributions of the parameters (e.g., effective population sizes, divergence times) for the most likely scenario were estimated using 1,000,000 of the simulated data sets. Finally, the confidence in scenario choice was evaluated by estimating type I and II errors for the scenario with highest probability. To estimate type I error, 1,000,000 datasets were simulated based on the scenario with the highest probability. Then, the number of times that this scenario did not have the highest posterior probability out of 1,000 test data sets were counted. A similar calculation was done to estimate type II error, where 1,000,000 datasets were simulated for each of the lower probability scenarios. Then, the number of

43 times that the previously determined highest probability scenario had the highest posterior probability out of 1,000 test data sets were counted.

Results

Microsatellite amplification and genetic diversity within populations

The seven SSR loci easily amplified across most individuals with allele sizes comparable (but not identical) to those reported by Kramer and Fant (2007) (Table 5). In addition, no significant linkage disequilibrium was found among loci (data not shown).

Table 6 shows information for allele counts per locus and per population. Pen02, Pen05, and Pen18 had the largest total number of alleles across all populations with 29, 27, and

28 alleles, respectively; Pen04 and Pen21 had the fewest total alleles across populations with 9 and 12, respectively. Numbers of alleles ranged from 1 to 16 per population and 1 to 16 alleles per locus per population. On average, each population contained anywhere from 22% to 44% of the total alleles at each locus, and no population contained all of the recorded alleles at any one locus. Populations of var. sileri had an average of 53 alleles across all loci, whereas populations of varieties linarioides and coloradoensis had 42 and

39 alleles, respectively, on average. In addition, instances of a population only having one allele at a locus took place in both varieties linarioides and coloradoensis but not in var. sileri (Table 6).

The mean number of alleles observed (Na) in each population per locus ranged from 5.14 to 8.71 and allelic richness ranged from 3.66 to 5.40 (Table 7). HO ranged from 0.33 to 0.70, while HE ranged from 0.52 to 0.78. Fifteen of the 22 populations had

44 private alleles (PA); the number of private alleles in each population ranged from 1 to 3.

Inbreeding coefficients (FIS) spanned from -0.01 to 0.43. Five populations exhibited values of FIS that were significant, indicating inbreeding having an impact on the genetic diversity within those populations. When varieties are considered instead of just single populations, var. sileri exhibited the largest amount of genetic diversity (Na=7.59,

AR=4.90, HO=0.66, HE=0.71). Both varieties linarioides and coloradoensis had lower values in each of those measures. Variety compactifolius had genetic diversity values comparable to var. sileri; however, there was only one population of this variety included in the study. HE was greater than HO in six of nine populations of var. sileri, four of five populations of var. linarioides, and all of the populations of var. coloradoensis.

Inbreeding coefficients were also higher in varieties linarioides and coloradoensis

(Average FIS=0.15 and 0.27, respectively) than in var. sileri (Average FIS=0.10), and of the five populations with significant values of FIS four were found in populations of var. coloradoensis and the other was a population of var. linarioides (Table 7). Interestingly, the genetic diversity values reported here for varieties of P. linarioides are slightly lower on average than those reported for three other species of Penstemon (Kramer et al. 2011), although the average values for populations of var. sileri are comparable. However, the values were higher than those estimated for P. debilis, a rare species with a limited geographic range (Wolfe et al. 2014). Populations of P. linarioides do have comparable values of HO and HE to the estimates reported in Nybom (2004) for a plant species with a widespread geographic distribution.

Estimations of null allele frequency based on the methods of Brookfield (1996) and Dempster et al. (1977) were 6.43% and 6.01%, respectively. The number of MLGs equaled the number of individuals included in the GENECLONE analysis, and vales of pgen and pgen(fis) were consistent with each individuals belong to different genets (Parks and Werth, 1993). Additionaly, the manual comparison of MLGs revealed that individuals with missing data also had unique MLGs.

Genetic diversity among populations

Results from AMOVA revealed that the majority of genetic diversity was found within individuals (71%), with smaller portions found among individuals within populations (16%) and among populations (13%). This suggests a scenario of limited population genetic structure with admixture among populations. The population pairwise

FST table (Table 8) illustrates a similar pattern of limited population differentiation.

Values of FST ranged from 0 to 0.24, with an average pairwise value of 0.12. This is modest compared to the average FST of 0.25 for species with a widespread geographic range reported in Nybom (2004). Pairwise estimations of gene flow (Nm) predictably followed similar patterns to pairwise FST values, ranging from 0.858 to 42.67, with an average of 2.65. However, even with relatively low values, most pairwise FST values were found to be significant (P<0.05) after correcting for multiple comparisons, indicative of some differentiation and structure among populations. Most instances of non-significant pairwise FST values took place between populations of the same varieties: six instances between populations of var. sileri, five instances within var. linarioides, and

16 instances within var. coloradoensis (Table 8). In addition, pairwise values between

46 populations of the two varieties linarioides and coloradoensis were often non-significant

(13 instances).

Average values of FST between populations of the same variety were lower than the average value (FST=0.08, 0.07, and 0.07 for varieties sileri, linarioides, and coloradoensis, respectively), and average values of Nm between populations of the same varieties were higher than average (Nm=4.42, 5.20, and 5.04 for varieties sileri, linarioides, and coloradoensis, respectively). Average pairwise values of FST and Nm between varieties are shown in Table 9. A low FST of 0.09 between varieties linarioides and coloradoensis suggests little genetic differentiation between these two varieties, which is corroborated with a higher-than-average value of Nm (3.02). Variety sileri exhibits a higher level of differentiation from both var. linarioides (FST=0.16, Nm=1.58) and var. coloradoensis (FST=0.17, Nm=1.23). Overall these pairwise values of FST suggest generally low levels of differentiations. Still, these data provide evidence that varieties linarioides and coloradoensis are more closely related to one another than they are to var. sileri.

Genetic relationships among populations

The consensus NJ tree for all 22 populations is shown in Figure 8. In general, bootstrap (BS) values are moderate to weak. Two of the varieties, sileri and coloradoensis cluster together with either moderate support (var. coloradoensis cluster

BS=731) or weak support (var. sileri cluster BS=450, Figure 8). The main var. coloradoensis cluster includes five populations sampled from southwest Colorado and does not include two populations sampled from northwest New Mexico (labeled

ColoNM-1 and -2 in Figure 8). These two populations were in the northern part of the range of var. linarioides but exhibited the sparsely bearded staminode of individuals of var. coloradoensis. All of the populations belonging to either varieties linarioides or coloradoensis form a cluster with moderate support (BS=581, Figure 8). The PCoA

(Figure 9) of all 22 populations shows a similar pattern to the NJ tree, with sileri+compactifolius populations clearly segregating from linarioides+coloradoensis populations on the first axis. Additionally the 5 southwest Colorado populations of var. coloradoensis cluster with one another apart from a cluster that includes var. linarioides and the two northwest New Mexico populations of var. coloradoensis.

The K graph from StructureHarvester (Figure 10) shows that the most likely number of clusters is 3, with the second most likely number of clusters being 6 (Figure

11). In the K=3 plot the populations mostly cluster by variety, with the lone var. compactifolius population being a mixture between varieties sileri and linarioides (Figure

11). In this plot the two New Mexico coloradoensis populations belong mostly to same cluster as var. linarioides. In the K=6 plot, var. coloradoensis once again forms its own cluster. Populations of var. linarioides, however, are split mostly between two clusters: lin-1, lin-2, and lin-4 form a cluster with the two New Mexico coloradoensis populations, while lin-3 forms a cluster with the var. compactifolius population. The populations of var. sileri are split between 3 clusters: one cluster consists of the three populations from the Kaibab Plateau in Northern Arizona, one cluster for three of the “mountain” form populations, and a third cluster containing the two “plateau” form populations plus the fourth “mountain” form population (Figure 11). In both plots (especially for K=6) there

48 is evidence for substantial admixture among population within and among varieties

(Figure 11).

In order to further evaluate the hypothesis of cryptic forms within var. sileri from

Holmgren (1984) these analyses were run with just the 9 var. sileri populations. The consensus NJ tree (Figure 12) shows strong support (BS=938) for a cluster containing the

Kaibab Plateau populations. The “plateau” populations from the Markagunt Plateau form a weakly supported cluster (BS=479), while three of the “mountain” populations (from the Pine Valley and Bull Valley mountains) also form a weakly supported cluster

(BS=420). The fourth “mountain” population (also from the Pine Valley Mountains) is not included in this cluster. The distinct Kaibab Plateau grouping is also present in the

PCoA, as well as the clustering of the first three “mountain” populations (Figure 13).

Interestingly the two “plateau” populations do not cluster with one another in the PCoA.

Finally, the results from the StructureHarvester analysis for var. sileri indicated that the most likely number of clusters is three (Figure 14). The STRUCTURE plot (Figure 15) shows a similar pattern to the NJ tree and PCoA: there is one cluster for each of the three cryptic sileri forms. As in the NJ tree and PCoA the STRUCTURE analysis likewise shows that the Mtn-4 population does not cluster with the other “mountain” populations, instead having approximately equal contributions of all three groups (Figure 15). Like the full 22-population analysis, the STRUCTURE results for var. sileri shows substantial admixture between groups.

Population demographic analyses with ABC

The first analysis based on nine scenarios (Figure 6) showed that scenarios where var. sileri diverged first from an ancestral population had higher probability than any other scenarios. Scenario 1 and 4 have this branching pattern, and these two had the highest posterior probabilities at 0.2214 and 0.2118, respectively. For the second run of

DIYABC, where four scenarios showing this branching pattern with differences in effective population size were considered (Figure 7), scenario 13 had the highest posterior probability (0.3988). However, scenario 12 had only slightly lower probability

(0.35536). These two scenarios represent similar demographic histories, the difference being whether var. coloradoensis originated and split from var. linarioides (scenario 12) or vice versa (scenario 13). Scenarios 10 and 11 had lower probabilities comparatively

(0.1354 and 0.1104, respectively).

In order to assess confidence in the scenario with the highest probability (scenario

13), estimates of type I and II error were calculated. Type I error describes the proportion of times the true scenario is rejected among simulated datasets, while type II error describes the proportion of times a false scenario is not rejected. For scenario 13 both types of error were high (>0.50), presumably because of the similarity between scenarios

12 and 13 (i.e., scenario 12 was frequently chosen over 13 even when the simulated data sets were based off of scenario 13). Therefore, type I and II error rates were calculated for both scenarios 12 and 13 when compared to the first two scenarios but not to each other. Doing this gave lower values of type I error (scenario 12=4.5%, scenario

13=8.5%). Type II error, however, remained large (scenario 12=58.8%, scenario

13=55.5%). Three of the 36 summary statistics simulated according to scenario 12 were

50 significantly (P<0.05) smaller than the observed data (mean Garza-Williamson’s distances for varieties linarioides and coloradoensis, and the classification index between varieties sileri and coloradoensis), while two were significantly smaller for scenario 13

(mean GW distance for var. coloradoensis and the classification index between varieties coloradoensis and sileri). Based on scenario 13, estimates (means) of effective population size for var. sileri were 6890 with 95% highest posterior densities = 3160-

9810, for var. linarioides, 8410 with 95% HDP = 5360-9930, and for var. coloradoensis,

2640 with 95% HDP = 651-7520. According to these estimates the lineage eventually leading to varieties linarioides and coloradoensis split from var. sileri 965 generations ago (95% HDP = 174-4250 generations), and varieties linarioides and coloradoensis diverged from each other 396 generations ago (95% HDP = 74.8-1070 generations).

Discussion

Penstemon linarioides has long presented taxonomic confusion to systematists and botanists. In addition to receiving substantial taxonomic work in the past (Nelson

1899, Keck 1937; Keck 1940; Nisbet and Jackson 1960), individual populations and varieties of P. linarioides can be difficult to identify in the field (Nold 1999).

Additionally, unrecognized forms have gone undetected within P. linarioides var. sileri according to Holmgren (1984). This study presents the first population genetics approach to the longstanding P. linarioides conundrum.

Considering within-population genetic diversity, populations of var. sileri consistently had higher estimates of genetic diversity than varieties linarioides and

51 coloradoensis, with var. coloradoensis having the lowest estimates of all three (Table 7).

In addition, four of the five populations of var. coloradoensis (from Colorado) showed significant levels of inbreeding (FIS). Although pairwise values of FST between populations are low and pairwise estimators of gene flow (Nm) are relatively high (Tables

8 and 9), the data suggest populations of varieties linarioides and especially coloradoensis are more isolated from one another compared to populations of var. sileri.

One explanation for the pattern seen in var. coloradoensis is the fact that it tends to exist at higher elevations than the other varieties (Table 3). Previous studies have shown that species that exist at altitudinal gradients tend to exhibit different levels of population genetic diversity due to factor such as isolation and barriers to gene flow at higher elevations (Garcia-Fernandez et al. 2012; Hargreaves et al. 2015). Both varieties linarioides and coloradoensis have within-population genetic diversity estimates comparable to the average values found in widespread plant species (Nybom 2004), with var. coloradoensis having slightly lower values. Considering that estimates of gene flow were still relatively high between populations and that these varieties are common plants

(Nold 1999), neither of these varieties is likely to be of conservation concern. The frequency of null alleles in this study was ~6%, which is a comparable value to that found using these microsatellite loci in P. debilis (Wolfe et al. 2014). Chapuis and

Estoup (2007) found that intermediate levels of null alleles (0.05

Considering that these taxa all belong to the same species, it is not surprising that

AMOVA found that the majority (71%) of variation existed within individuals. This is reflected in pairwise FST values that consistently show limited differentiation between populations (Table 8). That said, populations of varieties linarioides and coloradoensis exhibit lower average pairwise FST values between each other than between populations of varieties sileri (Table 9). Variety linarioides and coloradoensis are close to each other geographically, with their ranges contacting one another in western New Mexico. These two varieties also share morphological similarities, with the extent of staminode bearding representing the only distinguishing difference between the two. In this study, two populations that showed the var. coloradoensis staminode morphology (i.e., only a tuft at the tip of the staminode) that were sampled from northwest New Mexico consistently clustered with populations of var. linarioides in PCoA, a STRUCTURE analysis, and a

NJ tree (Figures 8, 9, and 11). This suggests a close relationship between varieties linarioides and coloradoensis. Likewise, although there was only one population of var. compactifolius sampled in this study, average pairwise FST between that population and populations of var. sileri tended to be lower than those between sileri and coloradoensis/linarioides populations (average compactifolius/sileri FST=0.090). In addition to measures of population differentiation, var. compactifolius shares geographic proximity with var. sileri (Figure 10), as well as morphological similarities (Table 3), suggestive of a close relationship between varieties sileri and compactifolius.

Results from the STRUCTURE analysis (including all populations) indicated that the most likely number of clusters was 3, and the bar plot for k=3 shows the three

53 varieties clustering with one another (Figure 11). Interestingly the lone population of var. compactifolius shows approximately equal admixture between varieties sileri and linarioides. It might be expected that, given var. compactifolius’ close clustering relationship to var. sileri in PCoA and the NJ tree, it would follow a similar pattern in the

STRUCTURE results. One potential explanation for this is that var. compactifolius lies between the ranges of varieties sileri and linarioides, with var. sileri to the north and west and var. linarioides to the east. Variety compactifolius may therefore represent a transitional form for P. linarioides between eastern and western populations. Increased population sampling of var. compactifolius is needed to clarify its relationships to other varieties.

We also addressed Holmgren’s (1984) hypothesis that additional forms exist within P. linarioides var. sileri. In general, the analyses that included only the populations of var. sileri did provide evidence for these currently unrecognized forms.

The most noticeable result is that the three populations from the Kaibab Plateau in

Coconino County, Arizona consistently cluster with one another (Figure 12, 13, and 15).

In the NJ tree, the cluster that includes the three Kaibab populations is much more strongly supported (BS=938) than any other grouping (Figure 12). Holmgren (1984) hypothesized that the “plateau” form included populations of var. sileri from the

Markagunt and Paunsaugunt plateaus in Utah as well as the Kaibab Plateau further south, so it was expected that the Kaibab populations would cluster with the two Utah “plateau” populations. Morphologically the Kaibab and Utah plateau populations have the characteristic narrow leaves of the “plateau” form, but the Kaibab populations have the

54 upright habit characteristic of the “mountain” form. Holmgren (1984) hypothesized a third form within var. sileri that existed to the south of the Kaibab Plateau with the habit of the “mountain” form and the leaves of the “plateau” form (“southern Arizona” form in

Table 3). It is therefore likely that these populations (kaibab 1-3) represent that third

“southern Arizona” form and that the Kaibab Plateau contains populations of both of these forms.

Evidence also exists for the presence of the other two forms, although it is somewhat more equivocal. Results from STRUCTURE (Figure 15) and the NJ tree

(Figure 12) show that the two populations from the Markagunt Plateau (“plateau” form) group with one another, although the support in the NJ tree is weak (BS=479). The

PCoA (Figure 13) does not reveal a close grouping of these two populations, however.

The first three “mountain” form populations (mtn 1-3) show a close grouping in all three analyses but the fourth “mountain” population (mtn-4) is not included in any of these groupings. The Structure plot reveals that this population (mtn-4) contains admixture from all three forms, and the PCoA places it close to the middle of the other groupings.

Mtn-4 is located in the southern part of the Pine Valley Mountains of southwest Utah, the same mountain range as mtn-1, which is from the northern part of the range. The other two “mountain” populations come from the Bull Valley Mountains that lie to the west of the Pine Valley Mountains. Mtn-4 is the closest “mountain” population to the Markagunt

Plateau, so it is possible that this part of the Pine Valley Mountains represents a point of contact between the “plateau” form and “mountain” form ranges. These results show that

55 the three forms exist within P. linarioides var. sileri. A taxonomic revision is beyond the scope of this study, but new varieties may emerge after careful morphological analysis.

Investigation of historical demographic scenarios for P. linarioides provided some evidence varieties linarioides and coloradoensis originated and split from var. sileri, a result that is consistent with var. sileri having more genetic diversity than the other two varieties (Table 7). This scenario is also consistent with varieties linarioides and coloradoensis clustering with one another (Figures 8 and 9) and generally showing low amounts of differentiation (Tables 8 and 9). We could not differentiate between scenarios 12 and 13, and thus could not determine if the “source” population for the second split was varieties linarioides or coloradoensis (Figure 7). Likewise, estimates of type II error were high (>0.50) for both scenarios 12 and 13. This is most likely due to the similarities between the four scenarios in Figure 7, making it difficult to distinguish between them. Therefore it can be concluded that P. linarioides exhibited this general demographic pattern in the past, but that we cannot make definite conclusions about changes in the species’ effective population size. Given that var. coloradoensis shows lower levels of genetic diversity (Table 7) it may make sense for var. linarioides to be this “source” population (i.e., scenario 12). Conversely, if scenario 13 is correct, var. coloradoensis could have experienced a bottleneck after giving rise to var. linarioides, explaining its lower level of genetic diversity and lower estimates of effective population size (average estimate=2640). A similar pattern was discovered in the arctic grass

Puccinellia phryganodes (Kvist et al. 2014), and ABC has been used to detect decreases in genetic diversity in eastern hog-nosed snakes (Xuereb et al. 2015) and the invasive

56 plant Haracleum persicum (Rijal et al. 2015). Variety coloradoensis also tends to exist at higher elevations, a pattern that can lead to eventual isolation and a decrease in genetic diversity (Garcia-Fernandez et al. 2012; Hargreaves et al. 2015). Elevational gradients combined with geologic activity have also played a role in shaping speciation and phylogeography in other taxa in the Colorado Plateau region (e.g., Leache and Mulcahy

2007; Burbrink et al. 2011).

Results from ABC estimated the divergence times as 965 generations (t2) and 396 generations (t1) for scenario 13. Although the generation time for P. linarioides is unknown, Way and James (1998) state that lifespans for woody Penstemon species are

10-30 years. Using lifespan as a proxy for generation time would put the first split

(between var. sileri and the other two varieties) at 9,650-28,950 years ago and the second split (between varieties linarioides and coloradoensis) at 3,965-11,880 years ago.

Obviously these are imprecise estimates for these divergence times, but the general timing would coincide with the events of the last glacial maximum at the end of the

Pleistocene, a time period that Wolfe et al. (2006) hypothesized to be important in shaping the evolutionary trajectory of Penstemon. During the end of the Pleistocene and beginning of the Holocene (~18,000 ya) western North America began to experience gradual warming as glaciers retreated (Cronquist et al. 1972). As a result there was an aridification of the region, causing the ranges of conifer (Wells 1983) and angiosperm

(Harper et al. 1978) species to contract significantly, creating “sky islands” of suitable habitat at higher elevations. This may explain the current situation of var. coloradoensis as it pertains to its higher elevation distribution and lower levels of genetic diversity.

This demographic scenario describes a situation where P. linarioides diverged and expanded its range in an eastward progression. This fits the biogeographic hypothesis for Penstemon proposed by Datwyler and Wolfe (2004) and Wolfe et al.

(2006), where Penstemon originated in the northern Rocky Mountains/Pacific Northwest, spread to the southwest, and then radiated eastward through the Intermountain Region and into the rest of North America. Additionally, Penstemon californicus and P. discolor are the two other species classified with P. linarioides in subsection of Linarioides of section Ericopsis. Results from a phylogenetic analysis indicate that these two species form a clade with the varieties of P. linarioides (Chapter 1). The varieties of P. linarioides, however, do not form a monophyletic group, suggesting that P. californicus and P. discolor may actually represent additional varieties of P. linarioides. Further population-level studies that include P. californicus and P. discolor will be needed in order to see if this trend of eastward expansion/divergence is still supported and to investigate their relationships to the varieties of P. linarioides.

In conclusion, this study represents the first population genetics study of the varieties of P. linarioides. Overall estimates of within population genetic diversity were average for a species with a large geographic range, although there were differences between varieties (especially within var. coloradoensis). Populations generally clustered according to their varieties, and two of the varieties (linarioides and coloradoensis) were shown to share a close relationship in terms of population genetics and morphology.

Variety sileri was found to be the most likely “source” population with the other two varieties originating and splitting from an ancestral sileri population, although greater

58 population sampling will make conclusions about changes in effective population size stronger. These demographic events most likely coincided with events at the end of the

Pleistocene. Finally, the results of this study provide evidence for the hypothesis presented in Holmgren (1984) about unrecognized “forms” existing within var. sileri.

Tables and Figures

Table 3: Description of varieties of Penstemon linarioides

Variety Range Elevation Staminode Habit Leaves 60 Fully Upright to ascending, Linear, 2 mm wide, hairs linarioides sw. NM, e. AZ 1300-2300 m bearded 50 cm flattened Beard tuft at Upright to ascending, Linear, 2 mm wide, hairs coloradoensis sw. CO, nw. NM 2300-2600m tip 50 cm flattened Linear, overlapping and Fully compacty arranged, compactifolius c. AZ 2100 m bearded Ascending, decumbent heathlike sileri Pine Valley Mtns and adj. Beard tuft at Linear and broad, 2.8 "mountain" form areas, sw. UT 1200-2300 m tip Upright, 30 cm mm wide, hairs erect Markagunt, Paunsaugunt, and Low-growing, Kaibab Plateaus, s. UT and n. Beard tuft at decumbent to Linear and narrow, 1.5 "plateau" form AZ 1200-2300 m tip ascending, 20 cm mm wide, hairs erect s. and sc. AZ 1200-2300 m "southern Arizona" Beard tuft at Linear and narrow, 1.5 form tip Upright, 30 cm mm wide, hairs erect Fully maguirei sw. NM and adj. AZ 1200-1500m bearded Upright Oblanceolate

Table 4: Populations of P. linarioides sampled

Population number Population designation Variety N State County 1 mtn-1 sieri Mountain 15 Utah Iron 2 plat-1 sileri Plateau 15 Utah Kane 3 mtn-2 sileri Mountain 15 Utah Washington 4 mtn-3 sileri Mountain 15 Utah Washington 5 lin-1 linarioides 5 Arizona Navajo 6 lin-2 linarioides 16 New Mexico Catron 7 colo-1 coloradoensis 15 Colorado Montezuma 8 colo-2 coloradoensis 17 Colorado Montezuma 9 colo-3 coloradoensis 14 Colorado Montezuma 10 colo-4 coloradoensis 17 Colorado Montezuma 11 colo-5 coloradoensis 15 Colorado Montezuma 12 coloNM-1 coloradoensis 10 New Mexico McKinley

61 13 coloNM-2 coloradoensis 10 New Mexico McKinley

14 lin-3 linarioides 10 New Mexico Socorro 15 lin-4 linarioides 10 New Mexico Catron 16 lin-5 linarioides 15 Arizona Gila 17 compact compactifolius 14 Arizona Yavapai 18 kaibab-1 sileri Plateau* 10 Arizona Coconino 19 kaibab-2 sileri Plateau* 15 Arizona Coconino 20 kaibab-3 sileri Plateau* 15 Arizona Coconino 21 mtn-4 sileri Mountain 15 Utah Washington 22 plat-2 sileri Plateau 16 Utah Kane

Table 5: Microsatellite loci with alleles sizes for P. linarioides

Locus Fluorescent label Size (bp) range for P. linarioides Size (bp) range listed in Kramer and Fant (2007) Pen02 6-FAM 160-222 175-199 Pen04 6-FAM 216-232 221-249 Pen05 6-FAM 156-228 194-238 Pen18 6-FAM 520-590 556-594 Pen21 5HEX 92-152 81-98 Pen23 5HEX 160-196 158-182 Pen24 5HEX 124-170 123-153

Table 6: Allele counts per locus and per population for P. linarioides

Locus Total No. of alleles mtn-1 (15) plat-1 (15) mtn-2 (15) mtn-3 (15) lin-1 (5) lin-2 (16) colo-1 (15) colo-2 (17) colo-3 (14) colo-4 (17) colo-5 (15) Pen02 29 13 9 11 7 8 14 9 13 10 10 14 Pen04 9 2 4 2 2 1 3 1 3 1 2 1 Pen05 27 13 8 14 8 7 8 8 6 12 10 8 Pen18 28 11 10 11 11 7 7 7 7 7 5 10 Pen21 12 4 7 8 4 3 3 3 2 3 3 4 Pen23 16 4 5 5 5 3 2 2 2 2 2 3 Pen24 21 6 8 6 9 5 10 6 7 4 6 4

Locus coloNM-1 (10) coloNM-2 (10l)in-3 (10) lin-4 (10) lin-5 (15) compact (14) kaibab-1 (10) kaibab-2 (15) kaibab-3 (15) mtn-4 (15) plat-2 (16) Pen02 9 7 8 10 12 8 11 12 9 10 11 Pen04 2 2 2 2 1 4 4 4 4 4 6 Pen05 8 6 6 7 11 10 9 9 10 11 12 Pen18 11 10 5 10 11 10 7 10 13 16 12 Pen21 2 2 4 2 5 4 3 3 3 4 3 Pen23 2 2 2 2 5 4 5 6 3 5 7 Pen24 6 7 6 9 7 9 6 10 10 9 10

Table 7: Measures of allelic and genetic diversity for P. linarioides

Population Allelic # PA number Population designation Na Ne Richness HO HE (#loci) FIS 1 mtn-1 7.57 5.38 4.86 0.69 0.67 n/a 0.01 2 plat-1 7.29 4.33 4.95 0.60 0.73 2 (1) 0.22 3 mtn-2 8.14 5.09 4.99 0.66 0.69 3 (2) 0.08 4 mtn-3 6.57 4.13 4.41 0.62 0.68 1 (1) 0.13 5 lin-1 4.86 3.95 4.86 0.60 0.59 2 (2) 0.10 6 lin-2 6.71 4.05 4.29 0.59 0.62 1 (1) 0.08 7 colo-1 5.14 3.36 3.66 0.40 0.55 n/a 0.30 8 colo-2 5.71 2.99 3.50 0.36 0.52 n/a 0.33 9 colo-3 5.57 3.21 3.60 0.33 0.55 3 (2) 0.43 10 colo-4 5.43 3.38 3.74 0.48 0.56 2 (2) 0.17 11 colo-5 6.29 3.97 4.06 0.45 0.56 2 (2) 0.23 12 coloNM-1 5.71 4.21 4.26 0.53 0.60 1 (1) 0.16 13 coloNM-2 5.14 3.24 3.89 0.49 0.59 n/a 0.23

64 14 lin-3 4.71 2.98 3.66 0.46 0.54 n/a 0.21

15 lin-4 6.00 3.84 4.28 0.54 0.59 3 (3) 0.14 16 lin-5 7.43 4.79 4.77 0.52 0.64 3 (3) 0.23 17 compact 7.00 4.32 4.67 0.70 0.72 n/a 0.06 18 kaibab-1 6.43 4.70 4.83 0.60 0.70 2 (2) 0.19 19 kaibab-2 7.71 5.21 5.08 0.64 0.71 1 (1) 0.14 20 kaibab-3 7.43 4.07 4.53 0.70 0.67 1 (1) -0.01 21 mtn-4 8.43 5.55 5.08 0.75 0.74 n/a 0.02 22 plat-2 8.71 5.71 5.40 0.69 0.78 2 (2) 0.16 Average sileri 7.59 4.91 4.90 0.66 0.71 1.33 (1.11) 0.10 Average linarioides 5.94 3.92 4.37 0.54 0.60 1.8 (1.8) 0.15 Average coloradoensis 5.57 3.48 3.82 0.44 0.56 1.14 (1) 0.27

Table 8: Population pairwist Fst (below diagonal) and Nm (above diagonal) values for P. linarioides

Note: Bold values designate statistical significance (P<0.05). * no value for Nm between lin-1 and coloNM-1 because the FST value is 0.00

Table 9: Average pairwise Fst (below diagonal) and Nm (above diagonal) for populations of varieties sileri, linarioides, and coloradoensis

sileri linarioides coloradoensis sileri - 1.58 1.23 linarioides 0.15 - 3.01 coloradoensis 0.17 0.09 -

Figure 5: Distribution map for populations of P. linarioides

Figure 6: Historical demographic scenarios modeled in DIYABC for the first set of analyses

Figure 6 continued. Scenarios 1, 4 and 7 show sileri splitting off first from a lineage that eventually gives rise to coloradoensis and linarioides. They differ in changes in effective population size and which variety is considered the “source” variety. Scenarios 2, 5, and 8 show linarioides splitting off first, and scenarios 3, 6, and 9 show coloradoensis splitting off first

Figure 7: Historical demographic models used in the second set of analyses in DIYABC All scenarios depict sileri branching off first. Scenario 10 depicts a large ancestral population that split into varieties sileri and linarioides, with var. coloradoensis splitting off from var. linarioides later. Scenario 11 is similar, except that the original split is between varieties sileri and coloradoensis, and var. linarioides originates and splits from var. coloradoensis later. Scenario 12 has var. sileri as the original “source” population with var. linarioides first splitting off from var. sileri and var. coloradoensis originating from the var. linarioides branch. Scenario 13 is similar to 12, except that the positions of varieties coloradoensis and linarioides have been switched.

Figure 8: Neighbor-joining tree for all 22 populations of P. linarioides

mtn-2 mtn-1 plat-1

mtn-3

colo-5 colo-4 colo-1 colo-3 colo-2 mtn-4 plat-2

Coord.2 lin-5 lin-1 lin-3 coloNM-1 lin-4 colo-NM-2 lin-2 kaibab-1 kaibab-3 compact kaibab-2

Coord. 1

Figure 9: PCoA for all 22 populations of P. linarioides Axis 1 explains 43.34% of the variation and Axis 2 explains 14.57%. Color codes: green=var. sileri, blue=var. coloradoensis, red=var. linarioides, pink=var. compactifolius.

Figure 10: Plot of delta-K for results of Structure with all 22 populations of P. linarioides

Figure 11: Structure plots for K=3 (above) and K=6 (below)

Figure 12: Neighbor-joining tree for 9 populations of var. sileri

plat-2

plat-1

Coord.2 kaibab-2 mtn-4 kaibab-1 kaibab-3 mtn-2 mtn-1 mtn-3

Coord. 1

Figure 13: PCoA for populations of var. sileri Axis 1 explains 42.87% of the variation and axis 2 explains 25.72%. Red= “plateau” form, blue= “mountain” form, green= “southern Arizona” form.

Figure 14: Delta-K plot for var. sileri Structure results

Figure 15: Structure plot for var. sileri

Chapter 3: Population genetics, systematics, and polyploidy in Penstemon caespitosus from Utah

Abstract

Penstemon caespitosus is one of several widespread species in section Ericopsis of Penstemon, with a range stretching from Utah into western Colorado and southern

Wyoming. The species consists of three subspecific varieties that have been described based on morphological variations existing throughout the species’ range. However, no study has considered the varieties of P. caespitosus using molecular markers. In addition, a recent flow cytometry study found that one of the varieties, desertipicti from southwest

Utah and northern Arizona, is a tetraploid (4x=2n=32), differing from diploid varieties caespitosus and perbrevis (2x=2n=16). The nature of the polyploidy of var. desertipicti

(i.e., autopolyploidy vs. allopollyploidy) is not known. The aim of this study was to use microsatellite markers in a population genetics study of the varieties of P. caespitosus in

Utah in order to investigate patterns of population genetic diversity, population differentiation, and polyploidy in var. desertipicti. Seven microsatellite loci were used for 9 populations of P. caespitosus collected in Utah (222 total individuals). Results indicated varying levels of genetic diversity in the three varieties, with var. caespitosus consistently showing lower measures of allelic diversity and heterozygosity. Variety desertipicti, comparatively, had the highest values of these measures, with total

79 heterozygosity over all loci equaling 89%. Analysis of molecular variance found that the majority of variation (88%) occurred within populations, suggestive of strong population genetic structuring. This was corroborated in high and significant pairwise PT values

(averaged PT=0.124). Varieties perbrevis and desertipicti, however, exhibited a closer relationship as measured by PT values and three clustering analyses (PCoA, Neighbor joining tree, and STRUCTURE). These results indicate that the northern var. caespitosus may be experiencing isolation from the other two varieties. Variety desertipicti contains many unique alleles that are not present in either the two varieties of P. caespitosus or P. linarioides var. sileri (a related species from southern Utah), a pattern consistent with an allotetraploid origin. Variety desertipicti did, however, share a substantial percentage of alleles with var. perbrevis (17% of total alleles), and the two varieties cluster close to one another in all analyses. It is concluded that var. perbrevis is mostly likely one of the parent progenitors of var. desertipicti; P. linarioides var. sileri can be neither confirmed nor rejected as the other progenitor, so other species (especially P. thompsoniae) should be considered in future studies.

Introduction

Penstemon caespitosus Nutt. ex A. Gray is a widespread, common species native to the Intermountain region of western North America. Its range includes most of Utah, stretching down into northern Arizona, east into Colorado, and north into southern

Wyoming (Figure 16; Holmgren 1984; Nold 1999). The most striking characteristic of P. caespitosus is its substantial mat-forming, prostrate habit (hence its common name, the

80 caespitose penstemon). In fact, some of the mats of P. caespitosus can reach up to a meter in width (Holmgren 1984; Nold 1999). Like most other species of its section

(Ericopsis) it has violet-to-blue corollas that are 2-ridged ventrally, a sterile staminode covered throughout its length in yellow hairs, and anther cells that dehisce across the connective tissue joining the thecae and to the distal ends of each theca (Holmgren 1984;

Nold 1999; Lindgren and Wilde 2003; Wolfe et al. 2006).

Like some other species in section Ericopsis (e.g., P. linarioides, P. crandallii, and P. thompsoniae), P. caespitosus represents a complex group characterized by different morphological variants throughout its range. There are three recognized subspecific varieties of P. caespitosus (Table 10). Variety caespitosus Nutt. is native to sagebrush communities in northeast Utah and adjacent Colorado and Wyoming and has oblanceolate leaves with pubescence and thecae that are 0.6-0.8 mm long (Holmgren

1984; Nold 1999). Variety perbrevis (Pennell) N. Holmgren is found to the southwest of var. caespitosus in central to east-central Utah on the Tavaputs, Wasatch, and Aquarius plateaus (Holmgren 1984). This variety is very similar to var. caespitosus except that it has obovate-to-spatulate leaves and slightly larger thecae (~0.9 mm). The third variety, var. desertipicti (A. Nelson) N. Holmgren, is native to the Red and Bryce canyons around the Paunsaugnt Plateau in southwest Utah and adjacent northern Arizona. Variety desertipicti tends to be a smaller plant than the previous two varieties, usually forming dense tufts rather than wide mats. Its leaves are oblanceolate-to-linear and it has larger thecae than varieties caespitosus and perbrevis (0.9-1.2 mm; Holmgren 1984; Nold

1999).

The taxonomic history of P. caespitosus is not as complicated as another variable species in section Ericopsis, P. linarioides (Chapter 2). The three varieties were originally described as varieties before being categorized as varieties by Holmgren

(1979). The systematic history of P. caespitosus includes three other published varieties: var. humifusus R.A. Nelson (1937) has not been repeated by any other author. Variety incanus Gray (1872) was equated to P. thompsoniae by Holmgren (1984), a species that shares both physical similarities and geographic proximity to var. desertipicti (Holmgren

1984; Nold 1999). Finally, var. suffruticosus Gray (1878) was elevated to species status as P. tusharensis N. Holmgren (1979). This species, from the Tushar Mountains in central Utah, differs from P. caespitosus in have ascending-to-erect stems (Holmgren

1984; Nold 1999). The taxonomy of P. caespitosus, like the rest of Penstemon and many other plant taxa, is based on morphological characters – no studies have used molecular data to investigate taxonomic boundaries in P. caespitosus.

The majority of Penstemon species are diploid with a base chromosome number of 8, but chromosome counts have revealed polyploidy in some species (Taylor and

Brockman 1966; Crosswhite and Kawano 1965; Love and Love 1982; Freeman 1983).

Using flow cytometry to estimate ploidy levels, Broderick et al. (2011) found that P. caespitosus var. desertipicti is a tetraploid (4x=2n=32). The study also included var. perbrevis, as well as several other species from section Ericopsis; these samples were found to be diploid (2x=2n=16; Broderick et al. 2011). Polyploidy has had a tremendous impact in terms of shaping plant evolution and its consequences have been well covered in the literature (Stebbins 1950; Grant 1981; Comai 2005; Soltis and Soltis 2009; Parisod

82 et al. 2010). Polyploidy generally comes in one of two forms: autpolyploidy is genome doubling caused by the union of two diploid gametes from the same species, while allopolyploidy results from the union of two diploid gametes from different species. The two classes differ in their inheritance pattern of chromosomes during meiosis (polysomic in autopolyploids vs. disomic in allopolyploids), and allopolyploidy is generally viewed as being more common in plants (Stebbins 1950; Comai 2005; Soltis and Soltis 2009).

Polyploidy is often seen as a speciation mechanism, as organisms with different ploidies sometimes (but not always) have difficulty producing viable offspring (Hegarty and

Hiscock 2005; Soltis and Soltis 2009).

It is not known if P. caespitosus var. desertipicti is an autopolyploid or allopolyploid. However, population genetic markers, such as allozymes, AFLP’s, and microsatellites, can be used in a “DNA fingerprinting” approach to investigate the nature of polyploidy in organisms (Soltis and Rieseberg 1986; Rieseberg and Doyle 1989;

Horandl and Greilhuber 2002; Baumel et al. 2003; Paun et al. 2006; Robertson et al.

2010; Shinohara et al. 2010; Meudt 2011). Using this approach we can make predictions on the patterns and distributions of these markers based on whether the organism is an autopolyploid or allopolyploid. First, allopolyploids should generally show higher levels of heterozygosity than autopolyploids because of disomic inheritance: the two sets of chromosomes in the allopolyploid come from two divergent species, so recombination of variation between homeologous chromosomes should happen less frequently than in autopolyploids. The result, therefore, is that heterozygosity in allopolyploids can become fixed (Comai 2005; Soltis and Soltis 2009; Cosendai et al. 2011). Second, we would

83 expect an autopolyploid to share most of its alleles with a diploid progenitor, while having very few private alleles of its own (Soltis and Rieseberg 1986; Rieseberg and

Doyle 1989; Horandl and Greilhuber 2002). Since an allopolyploid is the result of a hybridization event between two divergent genomes, we would expect it to share alleles with two diploid parents, or show a profile of additive genetic diversity (Baumel et al.

2003; Salmon et al. 2005; Paun et al. 2006; Shinohara et al. 2010). Third, in the case of allopolyploidy, the allopolyploid should show an intermediate position between its two diploid parents in distance-based (e.g., principal coordinates analysis) and Bayesian (e.g.,

STRUCTURE (Pritchard et al. 2001)) clustering analyses due to the fact that the two diploid parents are contributing divergent genetic material to the allopolyploid (Paun et al. 2006; Robertson et al. 2010; Meudt 2011).

The aim of this study was to use putatively neutral microsatellite markers in a population genetics study of P. caespitosus in order to investigate patterns of population genetic diversity, assess taxonomy and systematics, and evaluate the nature of polyploidy in var. desertipicti. Specific questions included: (1) how is genetic variation distributed in P. caespitosus? Is there significant genetic differentiation between populations? Are there any differences between populations and varieties in terms of within-population genetic diversity? (2) Does the distribution of genetic variation correspond to the three recognized varieties of P. caespitosus? Is there evidence for cryptic forms and additional varieties within the complex, as was seen in P. linarioides (Chapter 2)? (3) Is var. desertipicti an autopolyploid or allopolyploid? In the case of the former what is its

84 progenitor parent, and in the case of the later can the two parent progenitor species be identified among other varieties of P. caespitosus (or other species of Penstemon)?

Methods

Sampling

Sampling of populations of P. caespitosus took place in Utah in the summer of

2011. The number of individuals sampled per populations ranged from 10 to 25. For each collection an entire branch from an individual was selected and placed in its own coin envelope, which was in turn stored on silica gel desiccant. Individuals were sampled at intervals greater-than-or-equal-to one meter so as to avoid collecting the same individual twice (individuals of P. caespitosus can form mats that are several feet wide

(Holmgren 1984; Nold 1999)). Sampling for this study included populations from the three described varieties of P. caespitosus: four populations of var. caespitosus from

Daggett and Uintah counties in northeast Utah, three populations of var. perbrevis from

Emery County in central Utah, and four populations of var. desertipicti from Iron and

Garfield counties in southwest Utah (Table 11 and Figure 16). In total, 222 individuals were sampled and analyzed for this study. Individuals were stored on silica gel and transported back to the lab at Ohio State for DNA extraction.

DNA extraction and microsatellite analysis

DNA from dried samples was extracted following a modified CTAB protocol

(Wolfe 2005), and then seven simple sequence repeat (SSR, or microsatellite) loci were

PCR-amplified using primers specifically developed for Penstemon by Kramer and Fant

(2007). PCR was carried out in 10 L reactions consisting of 0.5 L genomic DNA,

5.725 L purified PCR water, 1.0 L RedTaq 10X buffer, 1.6 L 1.25 M dNTP mixture, 0.175 L 50 mM MgCl2, 0.25 L of both the forward (fluorescently-tagged) and reverse primers (10 M each), and 0.5 L of RedTaq polymerase (Sigma-Aldrich, St.

Louis, Missouri). PCR reactions took place in a SimpliAmp Thermal Cycler (Life

Technologies, Carlsbad, California). Thermal cycler protocols followed those of Kramer and Fant (2007): (For Pen02, Pen04, Pen05, Pen18, Pen21, and Pen23) 5 min at 94 C followed by 10 cycles at 94 C for 30 s, 30 s at 60 C, with a 1 C decrease in temperature every cycle, and 2 min extension at 72 C, followed by 30 cycles at 94 C for

30 s, 50 C for 30 s, and 72 C for 2 min, and a final extension at 72 C for 10 min. For

Pen24, the protocol consisted of 5 min at 94 C, 10 cycles of 94 C for 15 s, followed by

55 C for 15 s, 23 cycles of 89 C for 15 s, followed by 55 C for 15 s, and a final extension at 72 C for 30 min. Four microliters of PCR product was run on a 1% agarose gel to confirm successful amplification.

After successful PCR amplification one microliter of the each PCR product was mixed with 9.5 L of HiDi Formamide (Life Technologies, Grand Island, New York) and

0.25 L of a lab-made fluorescently labeled size standard (ROX509 for Pen02, Pen04,

Pen05, Pen21, and Pen24; ROX799 for Pen18 and Pen23; DeWoody et al. 2004). This mixture of PCR product, formamide, and size standard was denatured at 95C for 5 minutes, cooled on ice, and run on an Applied Biosystems 3100 Genetic Analyzer (Life

Technologies, Grand Island, New York). Six of the seven loci were paired in

86 combination with the blue+green (6-FAM+5HEX) dye system of the Genetic Analyzer so as to run duplexed reactions; the pairings (Pen18+Pen23, Pen02+Pen21, Pen04+Pen24) included two loci whose alleles could be separated based on fragment size. The last SSR locus, Pen05, was not paired with another locus. Genotyping of microsatelite alleles took place using the program GENEMAPPER 3.1 (Life Technologies, Grand Island, New

York). If a reaction failed it was re-run, and if the re-run failed the data for the individual at that SSR locus were scored as missing. In order to ensure consistency the first three

Data analysis

Genetic diversity within populations

Samples of var. desertipicti frequently had more than two alleles and as many as four alleles, consistent with a pattern of tetraploidy (Broderick et al. 2011). A well- known issue with polyploidy in regard to population genetics is the phenomenon of allelic dosage uncertainty (ADU), or not knowing the exact number of copies of each allele (Bruvo et al. 2004; De Silva et al. 2005; Clark and Jasieniuk 2011; Blischak et al.

2016). The ambiguity caused by ADU makes calculations of traditional population genetic statistics, such as observed and expected heterozygosity, problematic (Clark and

Jasieniuk 2011). One potential solution to ADU is to treat codominant microsatellite data as dominant data and convert the data set into a binary presence/absence matrix

(Sampson and Byrne 2012). The conversion of codominant SSR data to binary

87 presence/absence means that each allele from a microsatellite locus becomes the equivalent of a “band,” as in analyses using RAPD’s and AFLP’s. This procedure was used for the P. caespitosus dataset and used to calculate the total number of alleles summed over loci (A), the number of different alleles per population per locus (A’), and the number of different alleles per individual per locus (H’). In addition, GenAlEx v. 6.5

(Peakall and Smouse 2006) was used to calculate the number of private alleles (PA) per population. In order to see if linkage disequilibrium (LD) was significant among the 7

SSR loci, a test for pairwise LD among loci was carried out in GENEPOP v. 4.2 (Rousset

2008) with Markov chain parameters set to default (1000 dememorization steps, 100 batches, and 1000 iterations per batch). GENEPOP was also used to estimate the frequency of null alleles using the methods of Brookfield (1994) and Dempster et al.

(1977). As GENEPOP can only be used for diploid data, the LD test and estimation of null alleles were implemented using data from varieties caespitosus and perbrevis only.

GENECLONE v. 2.0 (Arnaud-Haond and Belkhir 2007) was used to test for clonality by determining the number of distinct multilocus genotypes (MLGs). GENECLONE cannot analyze missing data, so only individuals who had data at all seven microsatellite loci were included. In addition, individuals with missing data were assessed manually to see if their MLG matched another in the population. Like GENEPOP, GENECLONE can only handle diploid data, so the assessment of clonality was carried out using data from only varieties caespitosus and perbrevis.

For each variety the number of individuals having both a homozygote and heterozygote genotype was calculated for each of the seven SSR loci and then averaged

88 for all loci. Additionally, for tetraploid var. desertipicti, the number of diallelic, triallelic, and tetrallelic heterozygote individuals was calculated for each locus and then averaged for all loci.

Genetic diversity among populations

An analysis of molecular variance (AMOVA) was carried out in GenAlEx in order to estimate the percentage of genetic variance distributed within and among populations. In order to assess genetic differentiation between populations of P. caespitosus, pairwise values of PT were calculated using AMOVA in GenAlEx with

9999 permutations used to assess significance. PT is an analogue of FST that can be calculated for binary presence/absence data (Peakall et al. 1995).

Genetic relationships among populations

In order to investigate relationships and patterns of clustering among populations and varieties, three analyses were carried out. First, a pairwise population distance matrix using Nei’s genetic distance (Nei 1973) in GenAlEx. This distance matrix was then used to conduct a principal coordinates analysis (PCoA) in GenAlEx. Additionally a consensus Neighbor-joining (NJ) tree was constructed in PHYLIP (Felsenstein 2005) based on Nei’s genetic distance with 1000 bootstrap (BS) replicates performed in order to assess support. The commands used in PHYLIP to construct the tree were SEQBOOT

(BS replicates), GENDIST (calculating Nei’s distance), NEIGHBOR (constructing NJ trees), and CONSENSE (constructing consensus tree).

The Bayesian clustering program STRUCTURE 2.3.4 (Pritchard et al. 2000) was employed to further investigate patterns of population genetic structure and clustering.

STRUCTURE assumes a number of user-specified genetic clusters (k) and estimates what proportion of each individual belongs to each of the clusters. STRUCTURE has the ability to handle polyploid data (Pritchard et al. 2000), but allele dosage for heterozygote individuals must be known and stated in the input file. In order to deal with ADU in the

P. caespitosus data set, the R package POLYSAT (Clark and Jasieniuk 2011) was used to create the input file for STRUCTURE. For diallelic and triallelic heterozygote individuals (where ADU is an issue), the “write.Structure” command in POLYSAT randomly chooses an allele in the individual’s genotype and copies it as many times as is necessary to give that individual a number of alleles that matches its ploidy level. The

STRUCTURE analysis was run for k=1 to 11 genetic clusters using the admixture ancestry model. Each k was run for 10 iterations, and each iteration included a 100,000- step burn-in period before running 100,000 Markov Chain Monte Carlo (MCMC) steps.

The results from the STRUCTURE analysis were visualized in the program CLUMPAK

(http://clumpak.tau.ac.il/). To determine the most likely number of genetic clusters (k), the method of Evanno et al. (2005) was implemented in the web-based program

StructureHarvester (Earl and von Holdt 2012).

Assessment of polyploidy in var. desertipicti

In order to evaluate the nature of the polyploidy of var. desertipicti, the percentage of alleles shared between the three varieties was calculated. This was done to test the prediction that an autotetraploid should share most of its alleles with its diploid progenitor (Guo et al. 2005; Cosendai et al. 2011; see above). In the case of allotetraploidy for var. desertipicti, individuals should share alleles with two diploid

90 parent species. Therefore, the same allele sharing analysis was carried out with data generated from a microsatellite analysis of P. linarioides var. sileri (Chapter 2), whose range overlaps with P. caespitosus var. desertipicti in southern Utah. Nine populations of

P. linarioides var. sileri were included (Table 11). To see if individuals of var. desertipicti clustered with individuals of P. linarioides var. sileri, three additional clustering analyses were run for all individuals of P. caespitosus and P. linarioides: a NJ tree based on Nei’s genetic distance, a PCoA carried out in GenAlEx, and a

STRUCTURE analysis. The STRUCTURE analysis included the same settings as the previous analysis (e.g., 100,000 burn-in and MCMC steps each, 10 iterations of k), except that k was run from 1 to 20.

Results

Microsatellite amplification and genetic diversity within populations

The seven microsatellites from Kramer and Fant (2007) amplified easily across most samples in this study. The sizes of the microsatellite fragments were comparable to those reported in Kramer and Fant (2007), although they were closer in size to the microsatellite fragments amplified in the various varieties of P. linarioides (Table 12), a species related to P. caespitosus. Mean number of alleles per locus per population (Table

13) ranged from a low of five (Pen04) to a high of 14.91 (Pen18). No population contained all of the observed alleles at a given locus – each population contained on average 30-70% of all loci, with individuals from var. desertipicti having higher proportions of alleles. A pairwise test of LD among loci revealed no significant linkage

91 in this data (not shown). Estimates of null alleles according to the methods of Brookfield

(1994) and Dempster et al. (1977) were 13.75% and 14.15%, respectively. The number of MLGs equaled the number of individuals included in the GENECLONE analysis, and vales of pgen and pgen(fis) were consistent with each individual belonging to different genets (Parks and Werth, 1993). Additionally, the manual comparison of MLGs revealed that individuals with missing data also had unique MLGs.

Table 14 shows measures of allelic diversity for all of the populations averaged over loci. Total number of different alleles observed (A) ranged from 41 in caes-1 and -2 to 121 in dese-2, and likewise number of different alleles per population per locus (A’) and number of different alleles per individual per locus (H’) ranged from 7.86 (in perb-1) to 20.86 (in dese-2) and 2.71 (in caes-1 and -2) to 9.50 (in dese-4). Number of private alleles (PA) varied from 0 (in caes-1, -2, and perb-3) to 10 (in dese-2; Table 14).

Populations of var. desertipicti consistently showed higher values allelic diversity, and averaged values of each statistic were much higher for var. desertipicti than in the other two varieties. When considered as one population, var. desertipicti also had many more private alleles (55) as compared to varieties caespitosus and perbrevis (8 each; Table 14).

The two diploid varieties caespitosus and perbrevis tended to have lower values of heterozygosity than the tetraploid var. desertipicti (Table 15). For var. caespitosus heterozygosity values from each locus ranged from 4.71% to 64.77%, with an average of

35.67% heterozygotes per locus. Variety perbrevis exhibited higher heterozygosity than var. caespitosus, ranging from 11.11% to 83.64%, with an average of 50.82% per locus.

For var. desertipicti, total heterozygosity per locus ranged from 46.58% to 100%, with an

92 average value of 89.39%. Table 15 also shows a breakdown of heterozygosity as measured by different classes of multiple allelism for var. desertipicti. Among the three possible classes (diallelic, triallelic, and tetrallelic), the average values per locus are similar (28.45%, 32.60%, and 38.34% for diallelic, triallelic, and tetrallelic genotypes per locus, respectively), although there is variation when looking at individual loci. For example, tetrallelic heterozygotes make up 54.05% of individuals in Pen02 but only

6.67% of individuals in Pen04 (Table 15). Most strikingly, levels of homozygosity for var. desertipicti are very low when compared to the other two varieties (10.61% on average over all loci), with two loci (Pen02 and Pen23) having no homozygous individuals (Table 15).

Genetic diversity and relationships among populations

AMOVA revealed that 88% of variation occurred within populations and 12% distributed among populations, suggestive of a substantial amount of population genetic structuring. This pattern is reflected in pairwise population PT values (Table 16), which are generally high with an average of 0.124. Approximately two-thirds of pairwise PT values also showed significance (P<0.05) after correcting for multiple comparisons, indicating significant differentiation between populations. In general comparisons of populations within the same variety did not have significant PT pairwise values, but PT values between populations of different varieties frequently were significant (Table 16).

Interestingly, the population perb-1 (from var. perbrevis) only had a significant pairwise

PT value with one other population – caes-3 (from var. caespitosus). Table 17 shows averaged pairwise PT values between each of the varieties. Differentiation is greatest

93 between varieties caespitosus and desertipicti (average pairwise PT=0.166) and least between varieties perbrevis and desertipicti (0.122), suggestive of a closer relationship between varieties perbrevis and desertipicti than between var. caespitosus and either varieties perbrevis or desertipicti (Table 17).

Principle coordinates analysis (PCoA, Figure 17) shows that populations of varieties caespitosus and desertipicti form close clusters with populations of the same variety; these two varieties are clearly separated along the first axis. The three populations of var. perbrevis form a looser cluster than the other two varieties and are situated about halfway between varieties caespitosus and desertipicti (Figure 17). This result is similar to the NJ tree of the three varieties (Figure 18). Populations of varieties caespitosus and desertipicti form well supported clusters (BS=1000 and 987 for varieties caespitosus and desertipicti, respectively), whereas the var. perbrevis cluster is only weakly supported (BS=471). Varieties perbrevis and desertipicti cluster next to one another as well with strong support (BS=1000, Figure 18), again indicating a close relationship between those two varieties.

Finally, results from a STRUCTURE analysis revealed that the most likely number of clusters (k) was three, with the second mostly likely scenario being k=2, although the likelihood of k=2 was substantially lower than that for k=3 (Figure 19).

STRUCTURE plots for both k=3 and 2 are shown in Figure 20. For k=3, the clusters correspond to the three varieties with some admixture between clusters (especially in varieties perbrevis and desertipicti). The plot for k=2 shows two distinct clusters for

94 varieties caespitosus and desertipicti, with var. perbrevis mostly belonging to the desertipicti cluster (Figure 20).

Polyploidy in var. desertipicti

When considering only varieties of P. caespitosus, a large percentage (31%) of alleles were shared among all three varieties (Figure 21). Alleles found strictly in either variety caespitosus or perbrevis made up a relatively small percent of total alleles (4% and 5%, respectively), while alleles found exclusively in var. desertipicti made up a much larger share of total alleles (32% - the largest percentage in Figure 21). When considering alleles shared between just two varieties, the largest percentage was between varieties perbrevis and desertipicti (17%), with a smaller amount (9%) shared between varieties caespitosus and desertipicti.

In the case that var. desertipicti is an allotetraploid, it would be important to evaluate another potential parent species, so SSR data from P. linarioides var. sileri was included in this analysis of shared alleles (Figure 22). The comparison between P. caespitosus var. desertipicti and P. linarioides var. sileri was appropriate because the two taxa have ranges that overlap in southern Utah and northern Arizona (Holmgren 1984).

The largest percentage of alleles comes from alleles shared by all four taxa (26%).

Alleles shared between P. caespitosus var. desertipicti and P. linarioides var. sileri made up 12% of all alleles, the highest percentage of any comparison between two taxa (Figure

22). By contrast, only 7% of all alleles were shared between P. caespitosus varieties perbrevis and desertipicti. Even with allelic information from P. linarioides var. sileri

95 added in, the share of alleles exclusively found in P. caespitosus var. desertipicti was still relatively high (18%), the second highest share in Figure 22.

PCoA of all four taxa (Figure 23) revealed that the three varieties of P. caespitosus separate distinctly from P. linarioides var. sileri along axis 1. Furthermore, var. desertipicti does not show a clustering pattern with any population of P. linarioides var. sileri. The NJ tree of the four taxa shows a consistent pattern with the PCoA (Figure

24), with the three P. caespitosus varieties forming a moderately supported group

(BS=639) and the populations of P. linarioides var. sileri forming a strongly supported cluster (BS=890). Interestingly, in this NJ tree, varieties caespitosus and perbrevis cluster next to one another with strong support (BS=990), whereas in the P. caespitosus- only NJ tree (Figure 18) var. perbrevis exhibited this pattern with var. desertipicti.

The k plot for the STRUCTURE analysis reveals that the most likely number of clusters is k=3, with k=4 as the second most likeliest scenario (Figure 25). For k=3

(Figure 26) the genetic clusters correspond to P. caespitosus var. caespitosus, P. linarioides var. sileri, and a cluster combining P. caespitosus varieties perbrevis and desertipicti. In this plot the three var. perbrevis populations show a substantial amount of admixture from var. caespitosus, whereas the four var. desertipicti populations show much less admixture. In the plot for k=4 (Figure 26) each genetic cluster represents one of the four taxa, although with greater amounts of admixture mostly seen in var. perbrevis from varieties caespitosus and desertipicti. Variety desertipicti shows approximately equal amounts of admixture from the three other taxa as well (Figure 26).

Discussion

This study considered population genetics in P. caespitosus in Utah using microsatellite markers in order to evaluate patterns of genetic diversity, systematics of the species, and the nature of polyploidy in the tetraploid variety desertipicti. This study also represents the first population genetics investigation of the P. caespitosus complex as well as the first time microsatellites have been used to study polyploidy in Penstemon. In terms of within-population genetic diversity, the populations of var. desertipicti consistently exhibited higher levels of allelic diversity according to all measurements calculated (A, A’ and H’, Table 14). When considered all together, var. desertipicti also had a much higher number of private alleles (55) than the other two varieties (8 each). In addition, levels of heterozygosity in var. desertipicti were much higher than in the two diploid varieties (Table 15), a result consistent with measures of allelic diversity. In terms of both allelic diversity and heterozygosity var. perbrevis populations showed greater within-population genetic diversity than var. caespitosus. In fact, 64% of all individuals belonging to var. caespitosus were homozygous at any given locus, a substantially higher percentage than the other two varieties (Table 15). These results, coupled with results from the clustering analyses (see below), suggest potential isolation in var. caespitosus relative to the other two varieties. The frequency of null alleles in this study was ~14%, which is a comparable value to that found using these microsatellite loci in P. debilis (Wolfe et al. 2014). Chapuis and Estoup (2007) found that intermediate levels of null alleles (0.05

The results from our GENECLONE analysis, as well as the sampling method, indicate that clonality most likely does not impact our results.

Estimates of pairwise-population differentiation as measured by PT were generally high and significant at the P<0.05 level (Table 16). Not surprisingly the majority of significant values occurred between populations belonging to different varieties. Besides belonging to different taxonomic groups the populations are separated by large distances (Figure 16), thus potentially limiting the impact of gene flow. When pairwise population values are averaged together (Table 17), varieties perbrevis and desertipicti show the lowest amount of differentiation, while var. caespitosus shows a higher level of differentiation with the other two varieties. Geographically, the range of var. perbrevis occurs in between varieties caespitosus and desertipicti. These results indicate a greater relatedness between varieties perbrevis and desertipicti and potentially more gene flow between those two varieties than with var. caespitosus. This is also consistent with the allelic diversity and heterozygosity estimates that suggested var. caespitosus may be experiencing isolation from the other two varieties.

Results from various clustering analyses (PCoA, NJ tree, and STRUCTURE) all reveal strong clustering of populations according to variety (Figures 17029), consistent with results from the pairwise PT table. It can therefore be concluded that there is no evidence for the kind of cryptic forms found in P. linarioides (Chapter 2) for P. caespitosus (in Utah at least). Even though there was strong structuring by variety, the clustering analyses also revealed some admixture, especially between varieties perbrevis and desertipicti. The most likely number of clusters in STRUCTURE was 3 (Figure 19),

98 and even though var. perbrevis forms its own distinct cluster, admixture from the other two varieties exists (Figure 20). The second most likely number of clusters was 2 (albeit the likelihood was quite lower than that of k=3, Figure 19), with one cluster making up the var. caespitosus populations and another cluster consisting of populations from the other two varieties (Figure 20). For the k=2 situation the populations of var. perbrevis are not as uniform as the populations of var. desertipicti, having admixture with the var. caespitosus cluster. The PCoA (Figure 17) also shows var. perbrevis as having an intermediate position, with varieties caespitosus and desertipicti clearly separated from one another. Therefore, the conclusion is that each variety has its own genetically distinct cluster. However, consistent with results from pairwise PT values (Tables 16 and 17) varieties perbrevis and desertipicti share a closer relationship with each other than either one does to var. caespitosus. Given var. perbrevis’ intermediate geographic location between varieties caespitosus and desertipicti, it may represent an intermediate form in the P. caespitosus complex. These results also support the notion that var. caespitosus is experiencing greater levels of isolation and a lack of gene flow with the other two varieties.

Populations of var. desertipicti consistently showed higher levels of total heterozygosity than either varieties caespitosus or perbrevis (83% overall all loci, Table

15). This is not surprising, as polyploid organisms (both autopolyploids and allopolyploids) typically exhibit higher levels of heterozygosity than diploids (Comai

2005; Parisod et al. 2010; Cosendai et al. 2011). Within polyploids it is predicted that an allopolyploid would exhibit greater levels of heterozygosity than an autotetraploid

99 because of disomic inheritance in allopolyploids (Comai 2005; Soltis and Soltis 2009;

Cosendai et al. 2011). Unfortunately, we do not have heterozygosity information for either auto- or allopolyploids in Penstemon with which to compare this data. However, var. desertipicti shows greater heterozygosity than autotetraploids Tolmiea menziesii

(Soltis and Rieseberg 1986), Ranunculus cassubicus (Horandl and Greilhuber 2002), and

Ranunculus kuepferi (Cosendai et al. 2011). Moreover, Paun et al. (2006) found heterozygosity in allotetraploid Ranunculus carpaticola to be 100%, a closer value of heterozygosity for var. desertipicti than any of the previously mentioned autotetraploid studies.

The second prediction for distinguishing the two types of polyploids is that an autotetraploid should share most of its alleles with a diploid progenitor, while an allotetraploid should show additive genetic diversity, sharing alleles with two progenitor parent species (Soltis and Rieseberg 1986; Rieseberg and Doyle 1989; Horandl and

Greilhuber 2002). When SSR alleles from just varieties of P. caespitosus are considered, the two highest percentages of alleles were found in all three varieties (31% of all alleles) or found exclusively in var. desertipicti (32% of all alleles, Figure 21). Variety desertipicti also shared more alleles with var. perbrevis (17% of all alleles) than with var. caespitosus (9%, Figure 21). Two conclusions can be drawn from this result: first, the fact that var. desertipicti has a large number of exclusive alleles is evidence for allopolyploidy – in other words, var. desertipicti has a large number of alleles that it received from a source not included in this analysis. This conclusion is supported by the levels of heterozygosity observed in var. desertipicti (Table 15). Second, between

100 varieties caespitosus and perbrevis, var. perbrevis is more likely to be one of the progenitor parent species for var. desertipicti given that the two share more alleles (17% of all alleles, Figure 21) than varieties caespitosus and desertipicti share (9% of all alleles). The geographic proximity of varieties perbrevis and desertipicti make var. perbrevis a more likely potential progenitor as well (Figure 16).

If var. perbrevis is one of the parents to allotetraploid var. desertipicti, what is the other progenitor parent? Data from the same seven SSR loci was available for P. linarioides var. sileri (chapter 2) and analyzed to investigate if it could be the second parent. The ranges of P. linarioides var. sileri and P. caespitosus var. desertipicti overlap extensively (Holmgren 1984; Nold 1999), so it is a possible parental species for this analysis. Figure 22 shows the distribution of shared alleles between the three P. caespitosus varieties and P. linarioides var. sileri. The largest percentage of alleles is shared between all four taxa (26%, Figure 22), an unsurprising result given that these species are relatively recently diverged from one another (Wolfe et al. 2006).

Interestingly 12% of all alleles are shared between var. desertipicti and P. linarioides var. sileri, the highest percentage between any two taxa. The next highest, 9%, represents alleles shared between varieties perbrevis and desertipicti. However, even with the alleles from P. linarioides var. sileri added, 18% of all alleles are still found exclusively in var. desertipicti, meaning that it still has a substantial number of alleles received from another source not considered here.

The third prediction is that an allopolyploid should occupy a space intermediate to its two diploid progenitor parents in clustering analyses (Paun et al. 2006; Robertson et

101 al. 2010; Meudt 2011). In the three clustering analyses performed with all four taxa

(PCoA, NJ tree, and STRUCTURE) var. desertipicti does not cluster between var. perbrevis and P. linarioides var. sileri (Figures 23-26). The PCoA shows a clear separation between all of P. caespitosus and P. linarioides var. sileri (Figure 723). For the STRUCTURE analysis, the most likely number of clusters was 3 (Figure 25), with one cluster for var. caespitosus, one cluster for varieties perbrevis and desertipicti, and one cluster for P. linarioides var. sileri (Figure 26). Additionally, in the k=3 plot the populations of var. desertipicti show approximately equal amounts of admixture from var. caespitosus and P. linarioides var. sileri. The next most likely number of clusters (4) includes a cluster for each taxon, and in this scenario var. desertipicti still receives more admixture from the var. perbrevis cluster than P. linarioides var. sileri (Figure 26).

Therefore var. perbrevis exhibits a pattern (shared alleles and clustering) that would make it a strong candidate for one of the parent progenitors. The evidence for the parental status of P. linarioides var. sileri is a bit more equivocal, as it shares a lot of alleles with var. desertipicti (Figure 22) but does not cluster with it (Figures 23-26).

There are several possible explanations for this. First, var. perbrevis and P. linarioides var. sileri may in fact represent the true parent progenitors of var. desertipicti. In this case the number of alleles still unique to var. desertipicti (Figure 22) may be the result of substantial genome reorganization that is known to take place after genome doubling

(Parisod et al. 2009; Hegarty and Hiscock 2005; Paun et al. 2006). Additionally, many polyploids become apomictic after genome doubling, something that can cause mutations to accumulate and thus lead to more unique alleles in the polyploid (Birky 1996; Paun et

102 al. 2006). The extent of asexuality in var. desertipicti is not known, so this represents a valuable area of study in the future. Additionally it is possible that the unique alleles in var. desertipicti were simply unsampled in P. linarioides var. sileri.

If one assumes that P. linarioides var. sileri is one of the parent progenitors of var. desertipicti it is still difficult to overlook that the two taxa do not cluster with each other in any of the analyses included here (Figures 23-26). Therefore, additional species should be considered for the second parent progenitor of var. desertipicti. One species that should be investigated in this regard is P. thompsoniae, another widespread species in section Ericopsis. Unlike P. linarioides, P. thompsoniae shares the caespitose habit with P. caespitosus (Holmgren 1984; Nold 1999). P. thompsoniae’s range is also similar to that of var. desertipicti but stretches further west into southern Nevada and California

(Holmgren 1984), and a putative hybrid swarm between the two taxa exists around Old

Iron Town in Iron County, Utah (personal observation). Unfortunately, sufficient population sampling of P. thompsoniae has not been completed to date for inclusion in a study such as this. Such a study with the trio of P. caespitosus, P. linarioides, and P. thompsoniae should be undertaken as the next step into investigating the parentage of var. desertipicti. Other potential taxa to consider after P. thompsoniae are P. crandallii from the Las Sal Mountains in Utah, P. glabrescens from southern Colorado and northern New

Mexico, or one of the other varieties of P. linarioides (linarioides, coloradoensis, or compactifolius). All things considered, var. perbrevis is a strong candidate for one of the progenitors of allotetraploid var. desertipicti. Although there is some evidence in support

103 of P. linarioides var. sileri being the other parent progenitor, other taxa cannot be ruled out at this time.

In conclusion, we found that the distribution of genetic variation corresponded to the three recognized and described varieties. Genetic differentiation between populations was strong, but there is evidence for a close relationship between varieties perbrevis and desertipicti. Variety caespitosus, by contrast, consistently showed a pattern of isolation from the other two varieties. Investigation into the polyploid nature of var. desertipicti revealed that it is likely of allopolyploid origin. Although var. perbrevis is a good candidate for one of the progenitor parents, P. linarioides var. sileri could neither be fully supported nor rejected as the other. Further studies should consider other species of

Penstemon section Ericopsis for the second parent, especially P. thompsoniae, which shares several morphological and geographic similarities with P. caespitosus var. desertipicti.

104

Tables and Figures

Table 10: Descriptions of the three varieties of P. caespitosus

Anther cell Variety Range Leaves length Ploidy nw. CO, sw. WY, ne. caespitosus UT Oblanceolate 0.6-0.9 mm 2x=16 perbrevis e. central Utah Obovate-spatulate 0.8-0.9 mm 2x=16 Linear- desertipicti sw. UT, n. AZ oblanceolate 0.9-1.2 mm 4x=32

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Table 11: Populations of P. caespitosus sampled for this study

Name Variety N County (UT) caes-1 caespitosus 24 Daggett caes-2 caespitosus 24 Daggett caes-3 caespitosus 25 Uintah caes-4 caespitosus 19 Uintah perb-1 perbrevis 10 Emery perb-2 perbrevis 25 Emery perb-3 perbrevis 20 Emery dese-1 desertipicti 20 Iron dese-2 desertipicti 25 Garfield dese-3 desertipicti 20 Garfield dese-4 desertipicti 10 Garfield

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Table 12: Sizes of alleles amplified from seven SSR loci in P. caespitosus

Fluorescent Size (bp) range for Size (bp) range for Size (bp) range listed in Kramer Locus label P. caespitosus P. linarioides and Fant (2007) Pen02 6-FAM 158-238 160-222 175-199 Pen04 6-FAM 208-254 216-232 221-249 Pen05 6-FAM 156-214 156-228 194-238 Pen18 6-FAM 536-630 520-590 556-594 Pen21 5HEX 114-144 92-152 81-98 Pen23 5HEX 146-208 160-196 158-182 Pen24 5HEX 122-170 124-170 123-153

107

Table 13: Number of alleles amplified per locus in each population of P. caespitosus

caes- caes- caes- perb- perb- perb- dese- dese- dese- dese- Average alleles per caes-1 2 3 4 1 2 3 1 2 3 4 population Pen02 6 7 15 12 8 14 12 19 26 24 15 14.36 Pen04 3 4 4 3 5 5 5 8 7 6 5 5.00 Pen05 9 8 10 9 7 13 15 14 16 20 15 12.36 Pen18 10 8 11 13 8 18 14 17 26 24 15 14.91 Pen21 6 6 5 3 6 8 6 8 8 7 5 6.18

108 Pen23 1 3 5 3 6 4 5 23 25 22 19 10.55 Pen24 6 5 8 7 5 11 7 10 13 12 11 8.64

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Table 14: Allelic diversity for P. caespitosus populations

Population Variety A A' H' PA caes-1 caespitosus 41 9.29 2.71 0 caes-2 caespitosus 41 9.29 2.71 3 caes-3 caespitosus 58 11.86 3.32 4 caes-4 caespitosus 50 9.86 3.63 0 perb-1 perbrevis 45 7.86 5.50 1 perb-2 perbrevis 73 14.00 3.92 5 perb-3 perbrevis 64 12.00 4.20 0 dese-1 desertipicti 99 17.00 5.95 5 dese-2 desertipicti 121 20.86 5.84 10 dese-3 desertipicti 115 19.29 6.75 4 dese-4 desertipicti 85 13.57 9.50 2 All var. caespitosus 47.50 10.07 3.09 8 All var. perbrevis 60.67 11.29 4.54 8 All var. desertipicti 105.00 17.68 7.01 55 Key: A: total number of alleles, summed over loci, A': number of different alleles per population per locus, H': number of different alleles per individual per locus, PA: number of private alleles

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Table 15: Homozygous and heterozygous genotypes for each locus in P. caespitosus

Pen0 Pen02 4 Pen05 Pen18 Pen21 Pen23 Pen24 Average Num Number % ber % Number % Number % Number % Number % Number % Number % var. caespitosus 2x Homozygo te 36 39.13% 84 91.30% 35 38.46% 31 35.23% 60 65.22% 80 95.24% 78 85.71% 57.71 64.33% Heterozygo te diallelic 56 60.87% 8 8.70% 56 61.54% 57 64.77% 32 34.78% 4 4.76% 13 14.29% 32.29 35.67% var. perbrevis 2x Homozygo te 9 16.36% 19 34.55% 17 34.00% 12 23.08% 45 84.91% 48 88.89% 30 62.50% 25.71 49.18% Heterozygo te diallelic 46 83.64% 36 65.45% 33 66.00% 40 76.92% 8 15.09% 6 11.11% 18 37.50% 26.71 50.82% var. desertipicti 4x Homozygo te 0 0.00% 5 6.67% 1 1.35% 6 8.70% 39 53.42% 0 0.00% 3 4.11% 7.71 10.61% Heterozygo

110 te diallelic 8 10.81% 43 57.33% 21 28.38% 15 21.74% 26 35.62% 4 5.56% 29 39.73% 20.86 28.45% Heterozygo te triallelic 26 35.14% 22 29.33% 36 48.65% 31 44.93% 6 8.22% 15 20.83% 30 41.10% 23.71 32.60%

Heterozygo te tetrallelic 40 54.05% 5 6.67% 16 21.62% 17 24.64% 2 2.74% 53 73.61% 11 15.07% 20.57 28.34% All heterozygo 100.00 tes 74 % 70 93.33% 73 98.65% 63 91.30% 34 46.58% 72 100.00% 70 95.89% 65.14 89.39%

110

Table 16: Pairwise values of PhiPT between populations of P. caespitosus

caes1 caes2 caes3 caes4 perb1 perb2 perb3 dese1 dese2 dese3 dese4 caes1 ------caes2 0.017 ------caes3 0.054 0.051 ------caes4 0.045 0.077 0.051 ------perb1 0.176 0.206 0.227 0.193 ------perb2 0.152 0.149 0.131 0.134 0.160 ------perb3 0.143 0.143 0.115 0.120 0.106 0.023 - - - - - dese1 0.148 0.176 0.183 0.164 0.115 0.131 0.121 - - - - dese2 0.128 0.163 0.165 0.133 0.121 0.130 0.119 0.053 - - - dese3 0.149 0.174 0.169 0.144 0.129 0.112 0.118 0.055 0.013 - -

111 dese4 0.179 0.210 0.194 0.183 0.107 0.141 0.125 0.063 0.026 0.024 -

111

Table 17: Average pairwise PhiPT values between P. caespitosus varieties

caespitosus perbrevis desertipicti caespitosus - perbrevis 0.157 - desertipicti 0.166 0.122 -

112

Figure 16: Distribution map of P. caespitosus populations used in this study

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perb1

perb3

perb2 Coord.2

dese1 caes3caes2 dese4 caes4 caes1 dese3 dese2 Coord. 1

Figure 17: PCoA plot of populations of P. caespitosus Axis 1 explains 45.13% of the variation and axis 2 explains 23.59%.

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Figure 18: Neighbor-joining tree of P. caespitosus populations based on Nei's genetic distance

115

Figure 19: Delta-K plot for Structure analysis run for populations of P. caespitosus

116

Figure 20: Structure plots for K=3 (above) and K=2 (below) for populations of P. caespitosus

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only caespitosus 4% 5% only perbrevis 31% only desertipicti 32% caespitosus+perbrevi s 17% caespitosus+desertip 2% 9% icti perbrevis+desertipict i all

Figure 21: Chart showing the percent of shared alleles among the three varieties of P. caespitosus

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only caespitosus 2% 4% 12% only perbrevis

only desertipicti 18% only sileri

caespitosus+desertipicti 26% 6% perbrevis+desertipicti

4% sileri+desertipicti

7% perbrevis+desertipicti+sileri

9% all 12%

other combination

Figure 22: Chart showing the percentage of shared alleles among varieties of P. caespitosus plus P. linarioides var. sileri

119

dese3 dese4 dese2 dese1

kaibab-1 kaibab-3 kaibab-2

perb2 Coord.2

120 plat-2 mtn-4 perb1 perb3

mtn-3 mtn-1 plat-1 mtn-2 caes4 caes3 caes1 caes2

Coord. 1

Figure 23: PCoA of populations of P. caespitosus and P. linarioides var. sileri Axis 1 explains 39.08% of the variation and Axis 2 explains 23.91%. Note: populations denoted as “mtn,” “plat,” and “kaibab” are the populations of var. sileri.

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Figure 24: Neighbor-joining tree of P. caespitosus and P. linarioides var. sileri based on Nei's genetic distance

121

Figure 25: Delta-K plot for Structure analysis of P. caespitosus and P. linarioides var. sileri

122

Figure 26: Structure plots of P. caespitosus and P. linarioides var. sileri for k=3 (above) and k=4 (below)

123

Chapter 4: Investigation of niche divergence and evolution in Penstemon section Ericopsis using ecological niche modeling

Abstract

The concept of ecological speciation holds that two lineages will become isolated from one another as a result of adapting to different environmental conditions. As such it is expected that the niches of sister taxa will diverge as well. In this study, GIS-based ecological niche modeling (ENM) was used to test hypotheses of niche differentiation between two pairs of sister taxa in Penstemon section Ericopsis as well as two other pairs of Penstemon sister taxa from the Intermountain Region. The constructed ENMs performed well at predicting suitable habitat and reflected each taxon’s observed distribution. Evidence was found for little niche divergence between the sister species P. acaulis and P. yampaensis, and incomplete niche divergence in two of the species

(between P. laricifolius varieties laricifolius and exilifolius and P. linarioides varieties linarioides and coloradoensis). The highest amount of niche differentiation, however, was found between diploid P. caespitosus var. perbrevis and tetraploid P. caespitosus var. desertipicti. The results suggest that although these taxa are putatively recently diverged from one another, niche differentiation is taking place and is incomplete. There is also evidence that differing ploidy levels correspond to differing niches in P. caespitosus, although additional studies of the reproductive biology of var. desertipicti 124 should be undertaken in order to rule out other mechanisms (such as apomixis or dispersal) that may account for apparent niche differentiation.

Introduction

One of the overriding goals of evolutionary biology is to understand the process of speciation and diversification, including events that lead to reproductive isolation between diverging lineages (Futuyma 1998; Loera et al. 2012). Speciation may involve genetic, ecological, geographic, or stochastic events that can act alone or in some combination to produce divergence among lineages (Peterson et al. 1999; Schneider et al.

1999; Warren et al. 2008). One of the drivers of speciation and divergence is isolation via ecological barriers (Glennon et al. 2012), and the term “ecological speciation”

(Hatfield and Schluter 1999) refers to reproductive isolation that evolves as a consequence of divergent selection between populations that adapt to different environmental conditions. The model of ecological speciation, however, has proven to be controversial: the concept of “niche conservatism” argues that speciation takes place mostly due to geographic isolation instead of divergence in niche preferences between two lineages (Peterson 1999; Wiens 2004; Peterson 2011). Regardless, there has been a recent increase in the number of studies investigating the role of ecology in speciation and diversification (e.g., Graham et al. 2004; Givnish 2010; Nakazato et al. 2010;

Glennon et al. 2012; Loera et al. 2012; Lopez-Alvarez et al. 2015; Ortego et al. 2015;

Machado et al. 2016; Schwallier et al. 2016).

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Whereas in the past it was difficult to integrate environmental data into evolutionary studies, the development of GIS-based ecological niche modeling (ENM; also referred to as species distribution modeling) has allowed evolutionary biologists to study the impact ecology has on phylogeography, speciation, and hybridization (Kozak et al. 2008). Ecological niche modeling uses data about species occurrence (and sometimes species absence) along with GIS-based maps of environmental variables, such as temperature, precipitation, soil information, vegetation, and elevation (Stockwell and

Peters 1999; Phillps et al. 2006; Kozak et al. 2008). The ENM method then takes the environmental conditions present at occurrence data points and predicts that species’ environmental requirements, along with areas of suitable habitat for that organism based on those requirements (Kozak et al. 2008). Once ENMs are constructed they can also be used in a phylogenetic framework to study the impact of niche divergence between sister species or varieties (Kozak et al. 2008; Loera et al. 2012). In addition, such comparative methods allow us to investigate which environmental variables may be contributing most to divergence between sister taxa (Loera et al. 2012).

In this study, niche evolutionary dynamics among species and subspecific taxa of

Penstemon section Ericopsis were investigated using ENM. Wolfe et al. (2006) suggested that the seemingly rapid evolutionary radiation of Penstemon might have, at least in part, been caused by adaptation to new ecological niches made available by retreating glaciers during the Pleistocene. Straw (1966) referenced the broad distribution of the genus, as well as the diversity of environments in which its species are found, as a testament to the ecological adaptations that Penstemon species underwent throughout the

126 evolution of the genus. Penstemon species are found in a diversity of habitats, from the dry, well-drained soils of the Intermountain Region to more mesic environments in the southeastern United States (Holmgren 1984; Wolfe et al. 2006). Selective pressures in the form of pollinator types have also played a role in adaptation in the genus; for example, evolution to a hummingbird-pollinated syndrome has arisen multiple times in

Penstemon (Wolfe et al. 2006; Wilson et al. 2007). Species in section Ericopsis have distributions in the western United States in the “Four Corners” states of Utah, Arizona,

New Mexico, and Colorado (Holmgren 1984). Although all species are found in the dry habitat that dominates this region, little research has been done to investigate ecological differences between taxa in section Ericopsis. In addition, if the hypothesis of adaptation to novel niches for Penstemon species (Wolfe et al. 2006) is supported, we would expect to find niche differentiation among pairs of sister species and varieties.

An interesting application of ENM in a phylogenetic context is to consider potential niches of sister taxa with differing ploidies. Polyploidy has had a tremendous impact shaping plant evolution in general (Stebbins 1950; Grant 1981; Comai 2005;

Soltis and Soltis 2009; Parisod et al. 2010) and has been hypothesized to be an important mechanism of adaptation. It has also been considered a process that can confer polyploids the ability to occupy different niches than diploid relatives, including the ability to tolerate harsher environments than diploid relatives (Levin 1983; Kearney et al.

2005). The evidence for a link between polyploidy and the ability to occupy novel niches is equivocal, however, with studies showing evidence for (Hijmans et al. 2007;

Sonnleitner et al. 2010; Theodoridis et al. 2013) and against (Martin and Husband, 2012;

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Glennon et al. 2014) niche shifts between relatives of different ploidies, as well as studies that show mixed results (Glennon et al. 2012; Kirchheimer et al. 2016). Penstemon caespitosus var. desertipicti, native to southwest Utah and northern Arizona, is a tetraploid (Broderick et al. 2011), while the two other varieties of P. caespitosus are diploid. Variety desertipicti is sister to P. caespitosus var. perbrevis (Chapters 1 and 3) from central and east-central Utah; in addition, there is evidence that var. desertipicti is an allotetraploid and var. perbrevis most likely represents one of its diploid progenitor parents (Chapter 3).

This study sought to explore patterns of niche differentiation, conservatism, and evolution among sister taxa in Penstemon section Ericopsis. Specific goals were (1) generate ENMs for focal taxa and compare them to the taxon’s described distribution, and (2) investigate niche divergence among sister taxa, including among P. caespitosus varieties perbrevis and desertipicti, in order to gain insight into niche evolution between

Penstemon taxa and to explore the potential impact of polyploidy on niche evolution in

Penstemon.

Methods

Study taxa and locality data

To explore environmental niche conservation and divergence within section

Ericopsis, pairs of species and varieties that exhibited well-supported sister relationships to one another were examined. This included two pairs of varieties (P. linarioides var. linarioides vs. var. coloradoensis, P. caespitosus var. perbrevis vs. var. desertipicti). The

128 two varieties of P. linarioides consistently clustered close to one another in a population genetics study (Chapter 2). The two varieties of P. caespitosus were included because of a difference in ploidy (var. perbrevis is diploid while var. desertipicti is a tetraploid) and because var. desertipicti was concluded to be a likely allotetraploid with var. perbrevis representing one of the parent progenitor species (Chapter 3). In addition, comparisons were made for P. acaulis vs. P. yampaensis and P. laricifolius var. laricifolius vs. var. exilifolius. Although currently classified in section Ericopsis, these three species group in a clade with members of Penstemon section Cristati (Wolfe et al. 2006; Chapter 1).

However, P. acaulis, P. yampaensis, and P. laricifolius all occur in the Intermountain

Region with species of section Ericopsis, so these comparisons were made in order to gain a greater understanding of niche evolution among Penstemon species in this region.

Geo-referenced location data (GPS coordinates: latitude and longitude) were collected from herbarium specimens (NY, RM, KANU, ISC, NEB, WIS, COLO, UNM,

CAS, KSC, MICH, and UTC). As a quality control measure only specimens that could confidently be identified as representing the taxon in question were included in the data set and prior to modeling all geo-referenced points were mapped and inspected. In the case of duplicate records only one record was included in the final data set. The data set for this study included a total of 469 locality points (Appendix 1); Table 18 shows a breakdown of locality points per taxon.

Niche modeling

In order to construct ENMs we used MaxEnt v. 3.3.3k (Phillips et al. 2006; Elith et al. 2011). Although other methods exist to construct ENMs (e.g., GARP (Stockwell

129 and Nobel 1992)), MaxEnt was chosen because it has been demonstrated to perform better than other presence-only ENM construction methods (Elith et al. 2006). The input for MaxEnt is a set of locality data for the taxon of interest as well as environmental layers that describe a suite of ecological and climatic variables. MaxEnt then uses the environmental data present at each locality data to estimate the taxon’s environmental requirements, and thus predict a suitable niche. It accomplishes this using the principle of maximum entropy, a machine-learning concept that estimates a target probability distribution that is closest to uniform (i.e., the most spread out; Phillips et al. 2006). The target probability distribution is constrained in such a way that sample points taken from the target distribution should match the empirical average of environmental data from the given locality data (Phillips et al. 2006).

Niche models were constructing using the 19 WorldClim environmental layers

(Hijmans et al. 2005), which were downloaded from the WorldClim database

(www.worldclim.org) at a spatial resolution of 30 arc-seconds (~1 km2). The study area was defined as a rectangle from -115.00 to -103.00 longitude and 46.00 to 31.00 latitude; this bounding rectangle includes the distributions of all species and varieties/varieties considered here. The WorldClim environmental layers were clipped to these boundaries using the “Extract by Mask (folder)” and “Raster to ASCII” tools in SDMtoolbox (Brown

2014) as implemented in ArcMap 10.3.1 (ESRI, Redlands, CA, USA). Correlation among environmental layers was assessed using ENMtools (Warren et al. 2010). When two layers were highly correlated (r > 0.75) the layer with the highest number of correlations with other layers was discarded, resulting in 10 layers used in ENM

130 construction (Table 19). In MaxEnt we partitioned our data so that 75% of the locality points were used to train the model and 25% were used to test the model in each of 100 bootstrap replicates. Each niche model was evaluated with an average AUC value (Area under the Receiving Operating Curve) generated from the 100 bootstrap replicates. The

AUC score is the probability that a randomly chosen presence site is ranked above a random background site in terms of habitat suitability. Niche models were then converted from ASCII to rasters in ArcMap for visualization. The tool “Extract Multi

Values to Points” was used to extract climatic measurements for each locality point in

ArcMap.

Niche divergence and evolution

Several methods exist for testing hypotheses of niche divergence/conservation

(Peterson 1999; Graham et al. 2004; Peterson 2011; Warren et al. 2008; Warren et al.

2010). We chose the method of Warren et al. (2008), which involves calculating two measures of niche identity: Schoener’s D is a measure of niche overlap that implies a biological interpretation of the probability of a species occupying a certain area. The second measure, I, is a Hellinger-based distance that does not invoke biological interpretations about the probability of a species occupying a certain area (Warren et al.

2008). Both D and I range from 0 (complete niche divergence, no overlap) to 1

(complete niche identity), with values in between representing incomplete niche overlap.

This method was chosen because it has been used extensively in the systematics literature to investigate niche evolutionary dynamics among related taxa (e.g., Nakazato et al.

2010; Glennon et al. 2012; Lorea et al. 2012; Lopez-Alvarez et al. 2015; Ortego et al.

131

2015; Machado et al. 2016; Schwallier et al. 2016). This method also provides a standard measure to investigate niche divergence not present in other methods (see Warren et al.

2008).

ENMTools 1.3 (Warren et al. 2010) was used to calculate both D and I for each comparison using the average ENM of each taxon generated in MaxEnt. In addition, we carried out the identity hypothesis test in ENMTools for each pair. This involves creating a null distribution of D and I values by randomly choosing pairs of population points from the two taxa. A one-tailed t-test can then be carried out to see how the empirical values of D and I compare to the null distribution and if there is evidence to reject the null hypothesis of niche identity. We implemented the identity test by running 100 pseudoreplicates to generate the null distribution for each pair. Empirical values of D and I were considered significant if P < 0.05.

Results

Ecological niche modeling

Evaluations of ENMs produced high AUC scores (mean AUC = 0.981, SD =

0.004; Table 20), indicative that the models reliably predicted suitable habitat for all of the taxa. Interestingly, the cases with the lowest AUC scores were also the instances of high taxon sampling (mean AUC for P. linarioides var. linarioides = 0.950, 97 locality points; Tables 18 and 20), which is an artifact of the AUC statistic (Phillips et al. 2006).

A map for each predicted niche are presented in Figures 27-34, and Table 21 shows the contribution of each climatic variable to each taxon’s ENM, as well as the average values

132 of those climatic variables from the locality data. The ENMs of both P. acaulis and P. yampaensis had the highest contribution from the variables BIO13 (Precipitation of the wettest month; P. acaulis = 31.9%, average = 33.07 mm; P. yampaensis = 18.5%, average = 32.12 mm) and BIO9 (Mean temperature of the driest quarter; P. acaulis =

35.7%, average = -4.73 C; P. yampaensis = 22.7%, average = -5.88 C). For P. caespitosus the ENMs of both varieties received the most contribution from BIO15

(Precipitation seasonality; var. perbrevis = 52.7%, average = 16.15%; var. desertipicti =

28.5%, average = 30.19%) and BIO3 (Isothermality; var. perbrevis = 10.9%, average =

36.71%; var. desertipicti = 23.4%, average = 42.77%). P. laricifolius var. laricifolius had high contributions to its ENM from BIO9 (49.4%, average = -6.02 C) and BIO8 (Mean temperature of the wettest quarter, 15.8%, average = 9.1 C), while the ENM for P. laricifolius var. exilifolius also had a high contribution from BIO9 (40.1%, average = -

5.59 C) but also from BIO4 (Temperature seasonality, 11.9%, average = 8.13 C). The

ENMs of both varieties of P. linarioides had the highest contributions from BIO19

(Precipitation of the coldest quarter; var. linarioides = 29.2%, average = 105.72 mm; var. coloradoensis = 22.9%, average = 104.79 mm) and BIO9 (var. linarioides = 25%, average = 12.60 C; var. coloradoensis = 30%, average = 10.93 C). Of the variables considered here, the one that may be driving divergence among Penstemon species and varieties in the Intermountain Region the most is BIO9 (Mean temperature of the driest quarter; Table 21), as it was either the highest or second highest contributor to ENMs for

3 of 4 comparisons.

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In general the ENMs captured the observed ranges of the study taxa well. For P. acaulis and P. yampaensis, both species show a large area of suitable habitat in southwest

Wyoming and northeast Colorado (Figure 27 and 28). The ENM of P. acaulis shows more suitable habitat in northeast Utah (around the Flaming Gorge), while the ENM of P. yampaensis shows more suitability in northwest Colorado (in Moffat County), consistent with both of their observed ranges (Holmgren 1984). Interestingly, the ENMs for both species show a larger area of suitable habitat than the two species’ observed ranges, with predicted habitat suitability found further west in Utah and eastern Nevada for both. By contrast, the varieties of P. caespitosus show less overlap among their habitat suitability

(Figure 29 and 30). The ENM for variety perbrevis predicts high suitability in central and east-central Utah, consistent with where it is found on the Wasatch Plateau and surrounding areas. Variety desertipicti shows greater suitability to the southwest of var. perbrevis, consistent with its observed range in the Paunsaugunt Plateau region of southwest Utah and the Kaibab Plateau region of northern Arizona (Kearney and Peebles

1960; Holmgren 1984). The ENM for P. laricifolius var. laricifolius shows suitable habitat in most of Wyoming and stretching into southern Montana, while var. exilifolius has a smaller range of suitable habitat in southwest Wyoming and northern Colorado

(Figure 31 and 32). Lastly, the ENM for P. linarioides var. linarioides shows a large swath of suitable habitat stretching from southwest Utah into Arizona and eastern New

Mexico, while var. coloradoensis shows suitable habitat in southwest Colorado and northern New Mexico (Figure 33 and 34). The ENM for var. coloradoensis also shows that it has patches of suitable habitat that would overlap with the range of var. linarioides

134 in Arizona and southwest Utah. The ENMs of both varieties of P. linarioides are consistent with their described ranges (Kearney and Peebles 1960; Martin and Hutchins

1981; Holmgren 1984).

Niche divergence/conservatism

Niche identity as measured by Schoener’s D and I was highest for the comparison between P. acaulis and P. yampaensis (D=0.727, I=0.899) and P. linarioides (D=0.542,

I=0.828), although both D and I for P. linarioides was significantly smaller (P<0.05) than the null distribution generated by the niche identity test. A significantly smaller D and I were also found for the comparison involving the two varieties of P. laricifolius

(D=0.518, I=0.812; Table 22). Penstemon acaulis and P. yampaensis show little niche divergence from one another, as the null hypothesis of niche identity between them was unable to be rejected. Although values of D and I were significant for P. linarioides and

P. laricifolius, they suggest incomplete niche divergence with some similarity between the two niches. Schoener’s D and I were lowest for the comparison between diploid P. caespitosus var. perbrevis and tetraploid var. desertipicti (D=0.196, I=0.425, both significant), suggesting substantial niche divergence and a lack of niche conservatism between these two varieties.

Discussion

This study aimed to test hypotheses of niche differentiation between sister taxa in

Penstemon section Ericopsis, something that has been a topic of recent debate (Peterson et al. 1999; Wiens 2004; Warren et al. 2008; Peterson 2011) and research (Graham et al.

135

2004; Givnish 2010; Nakazato et al. 2010; Glennon et al. 2012; Loera et al. 2012; Lopez-

Alvarez et al. 2015; Ortego et al. 2015; Machado et al. 2016; Schwallier et al. 2016). In addition, this is one of only two studies to use ENM with Penstemon species (other than

Brown et al. 2016). The high AUC scores suggest that the constructed ENMs performed well at predicting suitable habitat for each taxon (Table 20), and overall each ENM reflects the observed distribution of each taxon (Figures 27-34).

For the diploid comparisons (P. acaulis, P. yampaensis, P. laricifolius, and P. linarioides), values of Schoener’s D and I were intermediate (Table 22), suggestive of incomplete niche divergence between sister taxa (Warren et al. 2008). Of the three comparisons P. acaulis and P. yampaensis had the highest values of D and I. In addition, the niche identity test for P. acaulis and P. yampaensis indicated that the null hypothesis of niche identity between taxa could not be rejected. The comparisons for P. laricifolius and P. linarioides produced lower values of D and I, in addition to being significant in the niche identity test. Visual inspection of ENMs also provide a comparison between the results for P. acaulis/P. yampaensis and P.laricifolius/P. linarioides: the ENMs for P. acaulis and P. yampaensis overlap substantially, while the ENMs for varieties/varieties of P. laricifolius and P. linarioides show some overlap that is not to the extent of the former. Therefore we conclude that P. acaulis and P. yampaensis are likely experiencing mostly geographic separation or divergence along some other environmental gradient

(see below), while niche differentiation between varieties/varieties of P. laricifolius and

P. linarioides is incomplete yet significantly greater than what would be expected at random. The idea of incomplete niche divergence, where niches may be similar but not

136 identical between closely related species/taxa (Warren et al. 2008), has been found in plant genera such as Houstonia (Glennon et al. 2012), Ephedra (Loera et al. 2012),

Brachypodium (Lopez-Alvarez et al. 2015), and Quercus (Ortego et al. 2015). However, according to the idea of niche conservatism, niche differentiation is something that evolves between more distantly related species, while speciation at more shallow levels of a phylogeny is due to geographic separation and not adaptation to diverging niches

(Peterson et al. 1999; Peterson 2011). In fact, Peterson (2011) argues that divergence of niches associated with speciation during and after the events of the Pleistocene is unlikely to happen, and that there will be “a considerable tendency towards [niche] conservatism.”

Wolfe et al. (2006) hypothesized that the events of the Pleistocene impacted the evolutionary trajectory and diversification of Penstemon, and Chapter 2 found evidence that the divergence between varieties of P. linarioides took place during the Pleistocene.

Penstemon acaulis and P. yampaensis show a pattern of niche conservatism consistent with Peterson (2011), but there is evidence that the niches of varieties/varieties of P. laricifolius and P. linarioides are significantly non-identical, and that this niche differentiation may be due in part to the species’ response to climatic changes during the

Pleistocene.

For all three diploid species, the climatic variable BIO9 (temperature of the direst quarter) was the variable that had either the highest (P. yampaensis, P. laricifolius varieties laricifolius and exilifolius, and P. linarioides var. coloradoensis) or second highest (P. acaulis, P. linarioides var. linarioides) contribution to the ENM (Table 21), suggesting that this variable is important in determining habitat suitability for these taxa.

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For P. laricifolius, var. laricifolius prefers a slightly cooler environment than var. exilifolius during the driest three months of the year (-6.20° C vs. -5.59° C, Table 21). P. linarioides var. coloradoensis, found to the northeast of var. linarioides, prefers a cooler environment during this quarter as well (10.93° C vs. 12.6° C, Table 21). Additionally,

BIO19 (precipitation of the coldest quarter) was an important contributor to both varieties of P. linarioides, with var. linarioides preferring more precipitation than var. coloradoensis during the coldest quarter of the year (105.72 mm vs. 104.79 mm, Table

21). Interestingly, Loera et al. (2012) also found that Bio19 contributed substantially to

ENMs of plant species from southwestern USA. In general, the variables BIO2 (annual mean diurnal range), BIO4 (temperature seasonality), and BIO14 (precipitation of the driest month) had the smallest contributions to ENMs, suggesting that they play a limited role in determining a taxon’s habitat suitability (Table 21). These results are evidence that the taxa considered here are diverging on temperature and precipitation gradients during certain times of the year.

The last niche comparison was between diploid P. caespitosus var. perbrevis and tetraploid P. caespitosus var. desertipicti. The results from this comparison show that the niches of these two taxa are by far the most diverged by having the lowest Schoener’s D

(0.196) and I (0.425) of all of the comparisons (Table 22). These values were also significant in the niche identity test. Maps of the two varieties’ ENMs show very limited overlap (Figure 29 and 30), the least amount of overlap all of the comparisons made. For both varieties the highest-contributing variable was BIO15 (precipitation seasonality) and

BIO3 (isothermality; Table 21). Precipitation seasonality captures the variation in

138 monthly precipitation totals. Our data suggest that var. desertipicti can tolerate greater precipitation variation than var. perbrevis. Likewise, the average values of isothermality

(how large the day-to-night temperature oscillations compare to annual temperature oscillations, O’Donnell and Ignizio, 2012)) indicate that var. desertipicti can tolerate greater daily temperature variation than can var. perbrevis. A study of two related species in central Utah, Townsendia aprica and T. jonesii, found that these two climatic variables contributed a lot of variation in the construction of ENMs, and that the two species’ niches diverged on those variable gradients (Lipsen et al. 2013). This suggests that precipitation seasonality and isothermality may be important factors in determining ecological tolerances for plant species in this region.

One of the goals of this study was to see if there was evidence for niche differentiation between sister taxa of differing ploidies. The principle of minority cytotype exclusion (Levin 1975) holds that in a situation where individuals of differing ploidies are coexisting in the same population, members of the minority ploidy will have a difficult time reproducing due to their smaller numbers and will therefore go extinct

(this assumes that differing ploidy is an effective reproductive barrier). It would therefore be advantageous for members of the minority cytotype to have different ecological tolerances than the majority cytotype in order to colonize their own niche and ensure successful reproduction. Levin (1983) proposed that polyploidy prepares an organism to do this by conferring greater physiological tolerances as a result of whole genome duplication. This has led to hypotheses of polyploids being able to tolerate

“harsher” environments, such colder temperatures, poorer and more acidic soils, and

139 drought conditions (Levin 1983; Brochmann et al. 2004; Kearney et al. 2004; Hijmans et al. 2007).

At first pass our results seem to agree with the idea that the niche’s of sister taxa with differing ploidies diverge, as the two varieties of P. caespitosus show the smallest level of niche overlap of all of the comparisons made in this study. Additionally, if greater climatic variability is included in the definition of a “harsher” environment, P. caespitosus is consistent with this pattern as well, as tetraploid var. desertipicti occupies a niche with greater temperature and precipitation variability. However, results from elsewhere paint a much more ambiguous picture of niche differentiation between ploidy levels. For example, Martin and Husband (2009) found that the level of niche differentiation between two sister species of differing ploidies is likely to be no more higher than between two diploid sister species. Glennon et al. (2014) found no evidence for differences in niches between diploid and polyploid relatives and argued that mechanisms such as dispersal and competitive exclusion may better explain allopatry between these taxa. Although Kirchheimer et al. (2016) found evidence of niche shifts among different ploidies in Ranunculus kuepferi, they question if this represents a true shift in ecological niches or if it may be a result of asexual reproduction among tetraploids. The reproductive biology of P. caespitosus var. desertipicti has not been investigated, so studying this may provide greater insight into the nature of the niche divergence between varieties perbrevis and desertipicti. One caveat to this is that these studies considered mostly autopolyploids, and there is evidence that P. caespitosus var. desertipicti is probably an allopolyploid (Chapter 3). Martin and Husband (2009) noted

140 that allopolyploids may possess greater ecological tolerances and the ability to shift niches more than autotetraploids since they contain two divergent parent genomes. With all of this considered, we tentatively conclude that the niches of P. caespitosus varieties perbrevis and desertipicti are diverged, since they show the lowest amount of overlap of all of the other diploid comparisons in this study. However, studies investigating the reproductive biology of var. desertipicti could help to differentiate whether this is an example of two taxa adapting to different niches or if another mechanism (such as apomixis) explains the shift. In addition, finding the other parent progenitor species of var. desertipicti (possibly P. thompsoniae or one of the varieties of P. linarioides) and comparing their niches will also shed light on this question.

One piece of information that would be helpful in interpreting these results is divergence times among sister taxa. In particular it would be interesting to see if taxa with greater niche identity (e.g., P. acaulis and P. yampaensis) exhibit more recent divergence times than other taxa. Although this information is currently not available, a study investigating adaptive radiation dynamics in Penstemon is currently underway, and those results will provide some insight into relative divergence times.

Finally, this study relied on climatic data (based on temperature and precipitation) to build ENMs, but did not consider other ecological information such as soil type, vegetation community, or pollinators, all of which have been hypothesized to have played a role in the evolution of Penstemon (Wolfe et al. 2006). Therefore, examination of these characteristics may give a more robust picture of each taxon’s niche. The comparison that yielded the lowest measurement of niche divergence was between P. acaulis and P.

141 yampaensis (Table 22). These species also have the narrowest ranges of all the taxa considered. Penstemon acaulis is native to the Flaming Gorge Reservoir area in Utah and adjacent Wyoming at an elevation of ~1800 meters, while P. yampaensis is found further east in Moffat County, Colorado, at slightly higher elevations (~1900 m; Lingdren and Wilde 2003). Both species can grow in sandstone-derived soils, but P. yampaensis is frequently found in areas where calcareous soils are dominant (NSSCS 1998), possibly suggesting it is more tolerant of a higher soil pH. Additionally, P. acaulis occurs in an area where the sagebrush steppe Artemisia community is prevalent, while P. yampaensis is found more commonly in pinyon-juniper communities (West 1988). A similar edaphic difference is present for the varieties of P. laricifolius. Variety laricifolius, native from central Wyoming into Montana, is commonly found in calcareous soils like P. yampaensis (NSSCS 1998; personal observation). Variety exilifolius occurs more commonly in red, sandy soils derived from sandstone. Penstemon linarioides var. coloradoensis occurs at a substantially higher elevation (2300-2600 m) than var. linarioides (1300-2300 m; Kearney and Peebles 1960). The soils where var. coloradoensis are found in southwest Colorado and northwest New Mexico are loose, gravelly, and sandy, while the soils where var. linarioides occurs further south and west are clay-based, with a higher content of aluminum and iron (NSSCS 1998). Finally, P. caespitosus var. perbrevis, from central Utah, occurs at an elevation of about 2200 m

(Holmgren 1984). Its vegetation association is the pinyon-juniper community that exists at higher elevations throughout the Intermountain Region (Cronquist et al. 1972).

Variety perbrevis grows in the clay soils there that are lower in salinity (Cronquist et al.

142

1972). Variety desertipicti, from southwest Utah and northern Arizona, occurs at a lower elevation (~1500 m) and is common in the shadscale vegetation zone dominated by

Atriplex confertifolia and Artemesia filifolia. The soil in this area is sandy and more saline than the area where var. perbrevis is found. Therefore, we hypothesize that other factors other than climate, such as soil and vegetation associates, have played a role in shaping niches of Penstemon species.

In conclusion, this study found evidence for significantly non-identical niches between taxa in two diploid species (P. laricifolius and P. linarioides) as well as between diploid P. caespitosus var. perbrevis and tetraploid var. desertipicti. For the two diploid comparisons, we describe the situation as incomplete niche divergence, while the two varieties of P. caespitosus showed the greatest amount of niche differentiation. Variables that contributed most to ENM construction were precipitation of the coldest quarter, temperature of the driest quarter, temperature seasonality, and isothermality, corroborating the results of two other studies of plant species in this region. It is therefore likely that these variables have an important role in shaping the ecological tolerances of species in section Ericopsis as well as other Penstemon species in the

Intermountain Region. Although the evidence from the literature for niche differentiation between relatives of different ploidies is mixed, it is tentatively concluded that the two varieties of P. caespitosus have undergone niche divergence, keeping in mind that more studies of the tetraploid var. desertipicti will provide additional insight into the nature of this niche evolution.

143

Tables and Figures

Table 18: Study taxa information with number of localities used in ENMs

Taxon # of localities P. acaulis 27 P. yampaensis 26 P. caespitosus var. desertipicti 31 P. caespitosus var. perbrevis 39 P. laricifolius var. exilifolius 74 P. laricifolius var. laricifolius 122 P. linarioides var. coloradoensis 53 P. linarioides var. linarioides 97 Total 469

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Table 19: Climatic layers used in ENM construction

Variable ID Description BIO2 Mean diurnal range (Mean of monthly (max temp - min temp)) BIO3 Isothermality BIO4 Temperature seasonality (standard deviation x 100) BIO6 Min temperature of coldest month BIO8 Mean temperature of wettest quarter BIO9 Mean temperature of driest quarter BIO13 Precipitation of wettest month BIO14 Precipitation of driest month BIO15 Precipitation seasonality (coefficient of variation) BIO19 Precipitation of coldest quarter

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Table 20: Average area under the curve (AUC) score for each taxon's ENM and the two variables contributing most to the model

Mean AUC AUC standard 2 variables contributing Taxon Score deviation greatest P. acaulis 0.997 0.001 BIO 13, BIO 9 P. yampaensis 0.997 0.001 BIO 9, BIO 13 P. caespitosus var. desertipicti 0.985 0.006 BIO 15, BIO 3 P. caespitosus var. perbrevis 0.985 0.005 BIO 15, BIO 3 P. laricifolius var. exilifolius 0.985 0.004 BIO 9, BIO 4 P. laricifolius var. laricifolius 0.971 0.003 BIO 9, BIO 8 P. linarioides var. coloradoensis 0.981 0.005 BIO 9, BIO 19 P. linarioides var. linarioides 0.950 0.007 BIO 19, BIO 9 Average 0.981 0.004

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Table 21: Percent contribution of each climatic layer to each ENM, as well as the average value of each variable

P. caespitosus P. laricifolius P. linarioides P. P. var. P. caespitosus P. laricifolius var. var. P. linarioides acaulis yampaensis desertipicti var. perbrevis var. exilifolius laricifolius coloradoensis var. linarioides BIO2 Contribution (%) 12 13.6 0.8 0.7 10.2 4.1 0.8 1.5 Average value (°C) 14.97 17.59 16.96 15.1 15.04 15.54 16.29 17.15 BIO3 Contribution (%) 2.1 2.8 23.4 10.9 3.2 2.3 5.6 4.7 Average value (%) 36.56 39.38 42.77 36.71 38.86 37.02 40.38 45.38 BIO4 Contribution (%) 8.9 1.5 1.7 0.1 11.9 3.2 2.7 0.6 Average value (°C) 87.14 90.09 77.44 86.38 81.3 88.1 81.21 73.65 BIO6 147 Contribution (%) 2.3 0.8 8.1 9.4 4.9 5.1 13.8 6.9 Average value

(°C) -12.68 -14.72 -11.98 -13.74 -12.59 -14.64 -11.35 -7.7 BIO8 Contribution (%) 12.9 10.9 4.4 5.4 5.5 15.8 12.4 10.4 Average value (°C) 9.07 7.74 14.71 10 11.51 9.1 15.84 18.54 BIO9 Contribution (%) 22.7 35.7 17.3 8.2 40.1 49.4 30 25 Average value (°C) -4.73 -5.88 8.98 3.12 -5.59 -6.02 10.93 125.97 BIO13 Contribution (%) 31.9 18.5 4.5 0.3 10.9 7.8 1.1 2.7 Average value (mm) 33.07 32.12 51.29 40.44 50.46 48.66 55.13 69.44 BIO14 Contribution (%) 1.2 2.1 5.4 9.7 4 0.5 0.9 7.9 Average value (mm) 13.33 14.92 15.29 22.23 17.76 15.9 15.92 11.69 BIO15 Contribution (%) 2.6 13.5 28.5 52.7 8.2 7.3 9.8 11.2 Average value (%) 26.41 21.77 30.19 16.15 34.82 36.57 30.4 47.8 BIO19 Contribution (%) 3.4 0.7 6 2.7 1.1 4.5 22.9 29.2 Average value (mm) 45.33 51.11 88.61 88.54 19.94 52.21 104.79 105.72

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Table 22: Empirical values of Schoener's D and I, as well as results from the niche identity test

Schoener's D I Comparison Empirical value Mean SD Empirical value Mean SD P. acaulis vs. P. yampaensis 0.727 0.694 0.046 0.899 0.888 0.021 P. caespitosus var. perbrevis vs. var. desertipicti 0.196 0.733 0.061 0.425 0.933 0.030 P. laricifolius var. laricifolius vs. var. exilifolius 0.518 0.781 0.026 0.812 0.945 0.012 P. linarioides var. linarioides vs. var. coloradoensis 0.542 0.804 0.034 0.828 0.955 0.013 Bold values indicate significance at P<0.05.

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Figure 27: Map of the average ENM for P. acaulis as constructed in MaxEnt Warmer colors indicate a higher probability of suitable habitat.

149

P. yampaensis

Figure 28: Map of the average ENM for P. yampaensis

150

Figure 29: Map of the average ENM for P. caespitosus var. desertipicti

151

Figure 30: Map of the average ENM for P. caespitosus var. perbrevis

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Figure 31: Map of the average ENM for P. laricifolius var. exilifolius

153

Figure 32: Map of the average ENM for P. laricifolius var. laricifolius

154

Figure 33: Map of the average ENM for P. linarioides var. coloradoensis

155

Figure 34: Map of the average ENM for P. linarioides var. linarioides

156

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Appendix A: Locus information from phylogenetics study

172

Table 23: Loci and the method of sequencing used in Chapter 1

Sequencing Locus method PPR 985 Illumina PPR 1839 Illumina PPR 369 Illumina PPR 950 Illumina PPR 1250 Illumina PPR 1561 Illumina COS34130 Illumina COS59820 Illumina COS80460 Illumina COS20370 Illumina COS21370 Illumina COS30360 Illumina COS35920 Illumina COS27260 Illumina COS28040 Illumina COS53950 Illumina COS62010 Illumina COS2350 Illumina COS18520 Illumina COS33495 Illumina COS38180 Illumina COS4810 Illumina COS37450 Illumina COS57850 Illumina COS66330 Illumina COS1331 Illumina COS48730 Illumina psbBH Illumina rpl16 Illumina rps12rpl20 Illumina PPR 876 Sanger PPR 1651 Sanger PPR 5729 Sanger COS4270 Sanger COS14240 Sanger COS23460 Sanger COS24530 Sanger COS50360 Sanger COS57850 Sanger

173

Appendix B: Locality data used in ENM construction

174

Table 24: GPS coordinates for P. acaulis

dd long dd lat -109.9019 40.9378 -109.2137 40.9233 -109.8446 40.9813 -109.5961 40.9813 -109.92556 40.83418 -109.76034 40.98805 -109.8446 40.9813 -109.8828 40.9958 -109.8446 40.9813 -109.5961 40.9958 -109.8255 40.9813 -109.5961 40.9813 -109.8064 40.9813 -109.6917 40.9378 -109.92568 41.02778 -109.93528 41.02778 -109.72 40.9918 -110.05 41.08 -110.21 41.24 -109.19 41.8189 -110.19 41.09 -109.893 41.0258 -109.952 41.0351 -109.972 41.0351 -109.838 41.0063 -109.838 41.0207

175

Table 25: GPS coordinates for P. yampaensis

dd long dd lat -108.7723 40.7826 -108.76806 40.87306 -108.3321 40.4714 -108.3511 40.4714 -108.37278 40.3751 -108.33842 40.35551 -108.74563 40.88765 -108.67333 40.55872 -108.5979 40.573 -108.7342 40.7826 -108.7375 40.78806 -108.1423 40.544 -108.7885 40.7879 -108.78346 40.44944 -108.6961 40.797 -108.7287 40.8689 -108.7469 40.8903 -109.2328 40.9233 -109.2137 40.9668 -108.648 40.5783 -108.382 40.7014 -108.734 40.7826 -108.772 40.7826 -108.161 40.4423 -108.715 40.8695

176

Table 26: GPS coordinates for P. caespitosus var. perbrevis

dd long dd lat -108.7985 39.5999 -110.9157 39.7604 -110.3762 39.8606 -110.3384 39.8749 -111.26944 39.28833 -112.21667 37.58333 -111.64222 37.89535 -111.39307 39.21162 -109.42208 39.59893 -111.07722 39.92861 -108.94 40.3407 -109.3 38.48 -110.34 39.68 -110.57 40.09 -111.309 39.9697 -110.55 40.16 -111.2 39.94 -110.233 39.8801 -111.27 39.32 -110.376 39.8161 -110.85 39.71 -110.56 39.93 -110.41 39.89 -110 39.7 -112.48 37.59 -110.55 40.16 -109.38 39.56 -112.12 38.02 -110.34 39.87 -111.333 39.2278 -110.38 39.86 -110.92 39.75 -109.404 39.6648 -109.09 39.6 -111.25 39.47 -112.12 37.94

177

Table 27: GPS coordinates for P. caespitosus var. desertipicti

-112.11356 35.64685 -112.12583 35.90109 -111.41222 35.87583 -111.65056 35.19806 -112.0865 37.6167 -112.21667 37.58333 -112.17111 37.71012 -112.1925 37.6749 -112.3011 37.74138 -112.30821 37.74474 -111.60139 38.27776 -112.39 38.42 -112.007 35.596 -111.924 35.6653 -112.58 37.87 -112.201 37.6731 -111.959 37.8333 -112.188 37.3658 -112.58 37.57 -112.19 37.67 -112.218 37.6597 -113.418 37.6047 -112.17 37.7 -112.16 37.69 -112.23 38.02 -112.14 37.7 -112.03 37.78 -111.371 35.52 -112.58 37.81 -112.55 37.84 -112.435 37.5726

178

Table 28: GPS coordinates for P. laricifolius var. laricifolius

dd long dd lat -108.5325 45.32836 -108.4245 45.0667 -108.37447 45.00439 -108.38889 45.01128 -108.1098 45.1098 -108.4653 45.0523 -108.54074 45.20907 -107.5726 44.3497 -107.8733 44.8033 -107.9947 44.8033 -108.098 44.9358 -107.4753 44.2024 -107.5726 44.3786 -107.4351 44.2024 -108.04377 44.86874 -107.9745 44.8033 -107.5323 44.2049 -107.99798 44.84343 -108.04943 44.86843 -107.62034 44.58901 -108.2612 44.9216 -107.60222 44.24583 -106.18185 41.99787 -106.17567 41.96801 -107.45667 42.35167 -106.8513 41.534 -108.5325 45.32836 -107.2337 41.4037 -106.80583 41.41153 -106.4808 42.3691 -107.2337 41.4037 -107.3102 41.534 -109.5206 43.6484 -109.5804 43.634 -109.4178 43.68705 -107.565 43.4807 -108.07111 43.45833 -109.49223 43.60675 -107.70409 42.39293 -108.29027 42.58541 -108.6683 42.5713 Continued 179

Table 28 Continued -107.5877 43.4207 -108.79917 42.46833 -108.8207 43.8803 -108.3453 43.6916 -106.9581 43.8681 -106.8778 43.8394 -106.87465 43.83717 -106.89303 43.83221 -110.2954 42.2683 -110.2563 42.2683 -110.2954 42.2538 -107.0139 43.2923 -107.2316 43.2495 -106.51972 42.75806 -106.6973 43.4349 -106.8358 43.3779 -106.94225 42.49768 -107.0535 43.3779 -107.4097 43.2923 -106.8358 43.2923 -109.2016 44.0428 -109.125 44.5089 -108.8637 44.2918 -109.1285 44.5428 -107.77928 44.77304 -109.77971 42.27884 -110.11361 42.56731 -110.50685 42.53766 -110.40854 42.53795 -110.354 42.4423 -110.3149 42.3264 -110.354 42.4278 -110.2758 42.3843 -108.8214 41.5535 -109.0228 41.9268 -108.7397 42.2576 -108.7053 41.2869 -108.785 41.68028 -108.48194 41.54778 -109.1001 42.0756 -109.0615 42.0608 -108.9262 42.031 -108.9456 41.9715 Continued 180

Table 28 Continued -108.876 42.1405 -108.207 41.5832 -108.3798 41.509 -108.2646 41.5683 -108.0917 41.5535 -108.1494 41.598 -108.644 45.1375 -108.558 45.1093 -110.26 42.27 -110.3 42.25 -106.912 42.7368 -108.861 43.9985 -108.882 43.05 -106.514 42.7594 -105.55 41.37 -108.92 41.27 -108.202 44.8431 -106.142 41.2983 -109.129 44.673 -110.284 42.8442 -107.63 44.5862 -106.958 43.8681 -107.573 44.3786 -108.629 42.6446 -106.046 36.8211 -106.983 43.6647 -106.004 41.1388 -108.098 44.9358 -107.532 44.2049 -105.886 40.9374 -108.95 41.97 -106.697 43.4349 -108.81 42.835 -109.602 43.4585 -106.02 41.1253 -106.875 43.8372

181

Table 29: GPS coordinates for P. laricifolius var. exilifolius

dd long dd lat -105.93444 40.81028 -105.848 40.9084 -105.8861 40.8648 -105.8861 40.9374 -106.0194 40.9374 -105.9622 40.9374 -106.02014 41.12525 -105.56667 41.16667 -105.51388 41.68895 -106.14111 41.29833 -106.10253 41.29832 -105.75263 41.03174 -105.75263 41.03174 -106.14082 41.50394 -105.41616 41.87919 -106.0618 41.1675 -105.70429 41.32802 -105.546 41.3684 -105.50694 41.08028 -105.4314 41.1962 -105.86472 41.24769 -105.79012 41.20587 -106.0045 41.2679 -105.43418 41.23689 -105.45332 41.39022 -105.59056 41.31139 -105.5663 41.31848 -105.86264 41.26083 -106.0618 41.1675 -106.01211 41.11028 -105.59056 41.31139 -105.909 41.3397 -106.13139 41.18417 -105.85286 41.30623 -105.50494 41.65076 -105.59417 41.1825 -105.97417 41.74139 -105.97464 41.74351 -106.13147 41.29833 -106 41.20667 -105.35028 41.09778 Continued 182

Table 29 continued -105.59056 41.31139 -105.45267 41.12738 -105.55118 41.13226 -105.86306 41.23833 -105.4505 41.2967 -106.01278 41.12505 -105.9472 41.1531 -107.6331 44.4076 -106.4808 42.398 -106.09041 41.87882 -106.27565 41.63674 -106.0817 41.54388 -107.23806 41.7911 -106.31389 42.7525 -104.6093 42.8508 -109.905 42.643 -107.28722 44.09636 -106.514 42.7594 -105.55 41.37 -106.142 41.2983 -107.573 44.3786 -106.004 41.1388 -107.532 44.2049 -105.886 40.9374 -108.95 41.97 -106.02 41.1253

183

Table 30: GPS coordinates for P. linarioides var. linarioides

dd long dd lat -109.09657 36.35325 -111.65056 35.19806 -111.83278 35.20006 -111.65056 35.19806 -111.65056 35.19806 -110.21667 33.72284 -109.58444 33.91056 -111.85361 34.56361 -112.6 34.58333 -108.53833 34.0262 -108.90381 33.37062 -107.8209 34.2953 -108.79361 33.39667 -108.7393 33.6375 -108.67722 34.65333 -106.55185 32.31915 -109.0152 32.9012 -108.27972 32.77 -108.02085 32.76973 -108.51111 32.8425 -108.27972 32.77 -108.80151 33.13327 -108.81694 31.53611 -108.49444 35.22237 -108.89686 32.94714 -109.9795 36.1406 -107.75469 32.89996 -107.137 34.0186 -107 34 -109.77 37.7525 -113.63 37.51 -111.371 35.52 -106.917 35.9442 -110.224 35.3073 -107.638 38.4661 -111.402 33.9258 -108.736 33.7976 -108.053 37.3714 -109.076 35.7447 -108.916 36.1581 -107.914 37.4353 Continued 184

Table 30 continued -108.975 35.9378 -108.98 36.3004 -105.664 36.5396 -109.487 32.3264 -114.05 38.12 -109.073 35.613 -110.934 33.5442 -114.525 33.6042 -108.663 33.3236 -111.855 34.5661 -112.128 35.9381 -111.855 34.5661 -111.798 33.9824 -111.855 34.5661 -111.371 35.52 -109.313 36.53 -108.915 36.1598 -108.416 37.345 -111.439 33.9186 -112.15 34.78 -108.8 37.48 -108.31 32.82 -108.48 32.4926 -109.357 37.9661 -109.024 36.603 -109.179 36.7033 -109.296 33.5717 -109.491 35.545 -109.296 33.0517 -111.651 35.1981 -107.835 37.4153 -108.278 32.8006 -107.725 32.9145 -112.244 35.2714 -112.083 35.2486 -108.672 34.8978

185

Table 31: GPS coordinates for P. linarioides var. coloradoensis

dd long dd lat -108.96031 37.7661 -108.4405 37.6693 -107.94278 37.31077 -107.8516 37.2191 -107.87944 37.27528 -107.69721 37.27514 -107.8119 37.4335 -107.804 37.4528 -107.8094 37.44275 -107.8439 37.4297 -108.44614 37.35402 -108.43317 37.28252 -108.28861 37.345 -108.47917 37.23333 -108.48794 37.18319 -108.47917 37.23333 -108.8034 37.4791 -108.6906 37.3928 -108.1997 37.3492 -108.6635 37.1778 -108.9415 37.97967 -108.93944 37.91639 -108.88806 38.02828 -108.93438 38.00344 -108.6725 34.89778 -108.82639 35.79278 -107.41366 36.99056 -108.9795 36.3004 -106.917 35.9442 -110.224 35.3073 -107.638 38.4661 -108.053 37.3714 -109.076 35.7447 -108.916 36.1581 -107.914 37.4353 -108.975 35.9378 -108.98 36.3004 -113.13 36.4065 -108.8 37.48 -108.31 32.82 -109.024 36.603 Continued 186

Table 31 continued -109.179 36.7033 -107.835 37.4153 -108.672 34.8978

187