Climatic Niche Estimation, Trait Evolution and Species Richness in North

Climatic niche estimation, trait evolution and species richness in North

American Carex (Cyperaceae)

Jocelyn E. Pender, B.Sc. (Hons.)

Thesis submitted to the

Faculty of Graduate and Postdoctoral Studies

University of Ottawa

In partial fulfilment of the requirements for the

Degree of Master of Science in the

Ottawa Carleton Institute of Biology

Supervisor:

Dr. Julian Starr

Committee Members:

Dr. Tyler Smith

Dr. Risa Sargent (Fall 2013 - Winter 2015)

Dr. Stéphane Aris-Brosou (Fall 2015 - present)

Abstract

With close to 2100 species, the flowering plant genus Carex (Cyperaceae; sedges) is an example of an evolutionary radiation. Despite its potential for use as a model taxon in evolutionary studies, the diversification of sedges remains largely unexplored. This thesis realizes the potential of Carex as an evolutionary model group by using it to ask questions about species richness patterns. More specifically, it seeks to determine the relationship, if any, between rates of trait evolution and species richness. This tests the hypothesis that organisms with increased abilities to evolve new traits, speciate more rapidly. Morphological and ecological

(habitat and climatic niche) traits are modelled on a nearly complete regional (North America north of Mexico) phylogeny and rates of trait evolution are compared among non-nested sister

groups. However, before trait evolution is modelled, this work evaluates the sensitivity of

climatic niche estimates to underlying distribution datasets. It tests the agreement of niche

estimates derived from the commonly used online repository GBIF (the Global Biodiversity

Information Facility) and county-level distributions via BONAP (the Biota of North America

Program). Results showed that in the context of phylogenetic comparative analyses, it is not vital to obtain highly accurate climatic niche estimates. The second study found significant positive

correlations between the rates of climatic niche, habitat and reproductive morphological

evolution and species richness. This result supports the role of high trait lability in generating

species richness and more generally, the idea that high trait disparity through evolutionary time

leads to species success.

iii

Statement of Contributions

The studies contained in this thesis were conceived and designed by Andrew L. Hipp,

Julian R. Starr and Jocelyn E. Pender. Molecular work was performed by J.E. Pender. Additional molecular data were provided by Brianna N. Chouinard, Marlene Hahn and A.L. Hipp. County distribution data were collected, assembled and provided by John T. Kartesz and Misako

Nishino. Morphological, specimen-based distribution and climatic niche data were gathered by

J.E. Pender. Habitat scoring was by J.R. Starr and A.L. Hipp. All data were analysed, presented and discussed by J.E. Pender.

Acknowledgements

Firstly, thank you to my supervisor Julian Starr. I thoroughly appreciate all of the guidance provided. You have revised many drafts, made many wise suggestions and provided much moral and professional support. Thank you, perhaps most importantly, for providing me with a project that has challenged me intellectually and technically (I am now a proud ‘R’tist). I am excited to see where my new skills take me.

Thank you Andrew Hipp, for your enthusiasm, creativity and knowledge. You have been integral to the development of this work. Also, thank you for facilitating my visits to the

Arboretum, which were invaluable research getaways. I am further grateful to Marlene Hahn, who provided data download protocols, assisted with molecular data organization, and with other tasks. Thanks to the Morton Arboretum team for providing ITS and ETS sequences.

Valuable feedback and advice was provided by my committee members, Tyler Smith and

Risa Sargent. Thank you for your in-depth emails and guidance.

The first Chapter was achieved in collaboration with John Kartesz and Misako Nishino.

They graciously supplied the Biota of North America Program (BONAP) data for all North

American Carex species, undoubtedly requiring much hard work to collect and assemble. Thank you for your cooperation.

Thank you Sarah Chisholm and Elyse Latreille for assistance with portions of the research. The hard work of Brianna Chouinard provided all genomic DNA and matK sequences used for the development of the phylogeny. Discussions with Étienne Léveillé-Bourret aided in the development of this work. Also, thank you Étienne for allowing me to use your sequences for outgroups in my phylogeny.

Roger Bull and Paul Sokoloff provided vital training and guidance in DNA extraction, amplification and sequencing protocols. They have been important to the development of this work, thank you. Lastly, thank you Claire Gilmour, Wayne Sawtell, Anna Ginter, Tamara

Villaverde, and Warren Cardinal-McTeague for providing advice on the graduate student process.

Table of Contents

Abstract ...... iii Statement of Contributions ...... iv Table of Contents ...... vii List of Figures ...... ix List of Tables ...... xii List of Appendices ...... xiii Chapter 1: Introduction ...... 1 1.1 FIGURES ...... 5 Chapter 2: How sensitive are climatic niche inferences to distribution data sampling? ...... 6 2.1 INTRODUCTION ...... 6 2.2 METHODS...... 9 2.2.1 Study taxon ...... 9 2.2.2 Occurrence data ...... 9 2.2.2.1 Global Biodiversity Information Facility (GBIF) dataset ...... 9 2.2.2.2 Biota of North America Program (BONAP) dataset ...... 10 2.2.3 Geographic extent ...... 11 2.2.4 Climate data ...... 11 2.2.5 Principal component analysis ...... 12 2.2.6 Correlates of error ...... 12 2.2.7 Phylogeny ...... 14 2.2.8 Ancestral state reconstruction ...... 14 2.2.9 Additional analyses...... 15 2.3 RESULTS ...... 16 2.3.1 Principal component analysis ...... 16 2.3.2 Sampling effort influencing error ...... 17 2.3.3 Elevation influencing error ...... 18 2.3.4 Ancestral state reconstruction ...... 18 2.3.5 Additional analyses...... 19 2.4 DISCUSSION ...... 20 2.4.1 Recommendations ...... 27 2.5 TABLES AND FIGURES ...... 28

vii

Chapter 3: Regional species richness and trait evolution in the genus Carex (Cyperaceae) 37 3.1 INTRODUCTION ...... 37 3.2 METHODS...... 45 3.2.1 Trait definitions ...... 45 3.2.2 Flora of North America region ...... 45 3.2.3 Phylogeny ...... 46 3.2.3.1 Taxon sampling ...... 46 3.2.3.2 Molecular markers ...... 46 3.2.3.3 DNA amplification and sequencing ...... 47 3.2.3.4 Sequence selection ...... 48 3.2.3.5 Outgroup species ...... 50 3.2.3.6 Sequence alignment ...... 50 3.2.3.7 Phylogenetic inference ...... 51 3.2.4 Trait data ...... 52 3.2.5 Trait evolution ...... 54 3.2.6 Sister clade comparison ...... 55 3.3 RESULTS ...... 58 3.3.1 Phylogeny ...... 58 3.3.2 Trait data ...... 59 3.3.3 Trait evolution ...... 59 3.4 DISCUSSION ...... 61 3.5 TABLES AND FIGURES ...... 69 Chapter 4: Conclusions ...... 78 References ...... 80 Appendix 1. Supplementary Figures for Chapter 2 ...... 92 Appendix 2. DNA sample data ...... 93 Appendix 3. Supplementary Figures for Chapter 3 ...... 102 Appendix 4: Maximum Likelihood gene trees ...... 105

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List of Figures

Fig. 1.1 Reproductive morphology of the flowering plant genus Carex. (A) A female spikelet showing the perigynium in blue and achene in green. The achene is a one-seeded fruit, surrounded by a sac-like structure called the perigynium. (B) An example of how spikelets are arranged to form an inflorescence. (A) and (B) are adapted from Starr & Ford (2009). (C) Spikelets arranged on a culm or a flower-bearing stalk. (D) Achenes removed from surrounding perigynia. (C) and (D) are from www.phytoimages.siu.edu...... 5 Fig. 2.1 Principal component (PC) climatic niche space. PCA was used to condense 19 WorldClim BIOCLIM variables into two PC axes (PC1=40% and PC2=34%) explaining the majority (74%) of bioclimatic variance. Species’ GBIF estimates in niche space are represented by circles and BONAP points are represented by triangles. Grey vectors connect species’ GBIF estimates to BONAP estimates, from which magnitude and direction are calculated. A sample calcuation in provided on the right. N=378...... 29 Fig. 2.2 The relationship between sampling effort and magnitude of differences between GBIF and BONAP climatic niche estimates. Regression lines are presented if a significant correlation was found. Correlation coefficients (ρ), p-values and r2 values are indicated in the top right-hand corner of plots with regression lines. (A) Sample calculation of GBIF county coverage for Carex lurida. Counties included in C. lurida’s GBIF data distribution are in blue and C. lurida BONAP county data are in red. (B) The relationship between GBIF county coverage and differences in climatic niche space. Each circle is one Carex species. N=363. (C) Sample calculation of relative geographic spread for C. lurida. GBIF points are in blue and BONAP points are in red. Minimum convex polygons calculated from each dataset are visualized. (D) The relationship between relative geographic spread and differences in climatic niche space. Each circle is one Carex species. N=321...... 30 Fig. 2.3 The relationship between elevation niche and differences in climatic niche space. Regression lines are presented if a significant correlation was found. Correlation coefficients (ρ), p-values and r2 values are indicated in the top right-hand corner of plots with regression lines. Each circle is one Carex species. N=363. (A) Elevation plotted against magnitude of differences in PC climatic niche space. (B) Elevation plotted against direction of differences in PC climatic niche space. Direction is in degrees...... 31 Fig. 2.4 Ancestral climatic niche PC1 reconstruction using GBIF estimates (left) and BONAP estimates (right). Colours represent trait values. The reconstruction was visualized on a Carex phylogeny using the contMap function in R. A plot of BONAP ancestral states versus GBIF ancestral states is presented in the bottom right hand corner, showing a slight offset from state equivalence. Further statistics evaluating ancestral state differences are shown (see Methods for details)...... 33 Fig. 2.5 The relationship between elevation predicted from GBIF occurrence data and elevation predicted from BONAP county data. A regression line is presented in black and a 1:1 elevation equivalence line is in grey. Elevation data were obtained from WorldClim at a

5km resolution and were combined with locality data to calculate elevation estimates. Each circle is one Carex species. N=378...... 34 Fig. 2.6 Uncertainty in ancestral state reconstruction from GBIF climatic niche PC1 estimates. Evolutionary time is on the x-axis and trait values on the y-axis. Blue transparent lines extend outwards showing 95% confidence limits. Plot was generated using the fancyTree function in the phytools package for R. Uncertainty from reconstruction of BONAP climatic niche estimates appeared qualitatively identical and is therefore not presented. N=363...... 35 Fig. 2.7 Analysis of the influence of geography on differences in climatic niche estimates. Counties in the eastern US are on average smaller than in the west. Species were separated into strictly eastern and strictly western species. Widespread species were not included. N=179...... 36 Fig. 3.1 An example of one set of non-nested sister group comparisons. Each sister contrast is shown in a different colour. Parental nodes are circled in red and sister nodes are circled in black. For each sister comparison, the ratio of species richness and ratio of trait evolution is calculated. The data then are log transformed and plotted. This procedure is performed for ten different sets of sister groups...... 72 Fig. 3.2 Maximum clade credibility phylogeny summarizing two BEAST runs of 100 million generations each. Two ougroup species and 477 North American Carex species are included. Thickness of branches correspond to Bayesian posterior probabilities. The phylogeny was constructed from the four-gene supermatrix (matK, rps16, ITS, ETS). Major clades (from Starr et al., 2015) are indicated and are accompanied by a photo of a member species. Time scale is in millions of years. Labels contain sample information (Morton Arboretum identifier, MOR and Starr Lab identifier, B code), two-letter geography information and section information...... 73

Fig. 3.3 Histogram of mean r2 values and slopes from regressions of species richness against rates of trait evolution (log transformed) using 100 continuous character evolution simulations. See methods for details on the procedure used to obtain regressions. The red line represents the 0.05 significance level...... 76 Fig. 3.4 Non-nested sister clade analysis. The ratio of species richness (i.e., the number of descendant taxa) and the ratio of rates of evolution per sister clade contrast are plotted for contrasts satisfying the criterion (= minimum of three descendants per clade). Sets of non- nested sister clades were obtained by maximizing the number of contrasts. Different colours represent different sets of non-nested sister clades, each with the maximum number of contrasts. Mean r2 and slope values are averaged regression statistics among sets.

Asterisks represent significance according to the null distribution of 100 continuous character simulations on the tree...... 77 Fig. A1.1 Supplementary analyses searching for correlates of differences in niche estimates. No significant correlations were recovered. Each circle is one Carex species. N=363...... 92 Fig. A3.1 Climate data plotted on the Carex spp. ultrametric phylogeny. Climate variables were taken from the BIOCLIM WorldClim database. Principal component analysis (PCA) was used to reduce the means of 19 BIOCLIM variables (prcomp in R) into climate PC1 and PC2. The map was generated using the contMap function in the phytools package for R. N=445...... 102 Fig. A3.2 Habitat data plotted on the Carex spp. ultrametric phylogeny. Light habitat was scored by experts. Wetness habitat was taken from the National Wetland Plant List (NWPL; Lichvar, 2012). Species missing from the NWPL were scored by experts for wetness habitat. The map was generated using the contMap function in the phytools package for R. Light habitat N=463, wetness habitat N=460...... 103 Fig. A3.3 Morphological data for those individuals with complete data sampling (data for four characters available) plotted on the Carex spp. ultrametric phylogeny. Morphological data was extracted from the Flora of North America (2002). Principal component analysis was used to reduce the number of morphological variables. Only PC1 and PC2 were analysed. The map was generated using the contMap function in the phytools package for R. N=371...... 104

List of Tables

Table 2.1. Loadings from principal component analysis of 19 WorldClim BIOCLIM variables estimated from GBIF and BONAP species localities. Only those principal components explaining a larger than expected amount of variation (=5.3%) are included (PC1=40%, PC2=34%, PC3=18%). Loadings are bolded if they are important contributors. This was assessed by comparing against the expected loading value if all variables contributed equally (square root of 1/19=0.229415). BIOCLIM variables are sorted according to contributions to PC1, PC2 and lastly PC3...... 28 Table 3.1. Primer sequences used in DNA amplification and sequencing...... 69 Table 3.2. Loadings from principal component analysis of 19 WorldClim BIOCLIM variables estimated from GBIF occurrence data. Only those principal components explaining a larger than expected amount of variation are included (>5.3%: PC1=42%, PC2=28%, PC3=16%, PC4=7%). Loadings are bolded if they are important contributors (>square root of 1/19=0.229415). BIOCLIM variables are sorted according to their contributions to PC1, PC2, PC3 and PC4...... 70 Table 3.3. Loadings from principal component analysis of six morphological characters (perigynia length, perigynia width, achene length, achene width, culm height, leaf width). Important contributors to principal components explaining a larger than expected amount of variation are bolded (PC1=49%, PC2=19%)...... 71 Table A2.1 Carex individuals selected for phylogenetic analysis. Voucher details can be found in Appendix B of Chouinard (2010). Use B numbers for correspondence. Locations where herbarium specimens were collected (column 3) are abbreviated into states or provinces, when possible...... 93 Table A2.2 Voucher information for outgroups used in this study...... 101

xii

List of Appendices

Appendix 1. Supplementary Figures for Chapter 2 ...... 92 Appendix 2. DNA sample data ...... 93 Appendix 3. Supplementary Figures for Chapter 3 ...... 102 Appendix 4: Maximum Likelihood gene trees ...... 105

xiii

Chapter 1: Introduction

The study of extant evolutionary radiations has been central to the formulation of diversification theory (Losos & Mahler, 2010). It has allowed biologists to infer, for example, processes leading to speciation, trait variation, and the establishment of geographical ranges and niches (Fritz et al., 2013). Evolutionary radiation is defined as the differentiation of a single ancestor into a diverse set of morphological and ecological forms (Schluter, 2000; Streelman &

Danley, 2003; Losos & Mahler, 2010). More concretely, a group should possess species richness of at least one order of magnitude greater than its similarly aged sister group to be considered a radiation (Sanderson & Donoghue, 1994; Bouchenak-Khelladi et al., 2015). Although significant

progress has been made in understanding biodiversity processes through the study of radiations,

central questions remain. Most significantly, it remains unclear why species richness imbalance

persists across phylogenies and how these diversity differences are related to morphological and

ecological diversity (termed “disparity” by evolutionary biologists to avoid confusion with

species diversity; Losos & Mahler, 2010).

The flowering plant genus Carex L. (ca. 2100 spp.; family Cyperaceae or “sedges”;

Govaerts et al., 2014; Global Carex Group, 2015) is one of the largest angiosperm genera worldwide (4th largest; Frodin, 2004; Global Carex Group, 2015) and the most diversified genus

in the northern temperate zone (Reznicek, 1990). It possesses 20-fold more species than its sister

clade Scirpeae (98 species; Léveillé-Bourret et al., 2014), and therefore constitutes an evolutionary radiation. Carex species can be found in forests, grasslands, montane rocky

habitats, arctic tundra and moist to wet habitats worldwide, where they are often dominant or co-

dominant (Ball & Reznicek, 2002). The extensive habitat diversity of the genus is paralleled by

Chapter 1: Introduction its global distribution, as Carex inhabits every continent except Antarctica. This distribution has

recently been shown to be the result of infrequent long-distance dispersal events (Spalink et al.,

2015), revealing that Carex is geographically coherent at the continental scale. Carex is further

exceptional in that its species frequently co-occur.

Unlike famous examples of species radiations (e.g., passerine birds, Anolis lizards),

investigations into the evolutionary history of sedges have been few. This is a notable loss for a

number of reasons. Firstly, the genus’ habitat and climate diversity provides a unique

opportunity for study of niche disparity and species richness. Furthermore, investigation of niche

partitioning and coexistence of related species within communities is possible in Carex. Lastly,

the exceptional sedge diversity in the Northern Hemisphere would allow for investigation of

temperate processes. The potential of Carex as a study taxon for evolutionary and ecological studies has been emphasized by sedge systematists (Waterway et al., 2009; Starr & Ford, 2009)

but has yet to be fully realized.

Sedge studies have been missing from the evolutionary literature due to their historically

difficult taxonomy (Starr & Ford, 2009) and the lack of accurate phylogenetic hypotheses.

However, new developments in molecular methods have increased the availability of sequence

data and have aided in new resolutions of Carex relationships (Starr & Ford, 2009; Léveillé-

Bourret et al., 2014; Starr et al., 2015; Global Carex Group, 2015). As a result, research has begun to consider character evolution and diversification processes in Carex (Gehrke & Linder,

2011; Escudero et al., 2012a; Escudero et al., 2012b; Escudero & Hipp, 2013; Maguilla et al.,

2015). Unfortunately, studies continue to be limited in taxonomic and geographic scope.

This thesis realizes the potential of Carex to investigate fundamental evolutionary and ecological questions (Chapter 3). It is the first to do so on a broad scale, considering almost all

Chapter 1: Introduction

Carex species existing in North America, north of Mexico (the Flora of North America region;

FNA). However, before it attempts to understand Carex diversity, it evaluates a commonly

employed method of climatic niche estimation (Chapter 2).

Recently, researchers have begun to investigate the phylogenetic conservation,

divergence and tempo of change of species’ niche (Warren et al., 2008). This has in part been

motivated by the increasing abundance of species distribution data and availability of high

quality climatic data (Araújo & Peterson, 2012), which are used in combination to estimate a climatic niche. The largest provider of distribution data is the Global Biodiversity Information

Facility (GBIF), hosting occurrence data submitted by hundreds of natural history collections across the world. However, despite the acknowledgement of data quality issues in GBIF occurrence datasets (Graham, 2004; Yesson et al., 2007; Newbold, 2010), little information

exists on the sensitivity of niche estimates to data inaccuracies and uncertainties. Furthermore,

the effect of erroneous GBIF data on phylogenetic comparative analyses, such as the trait

evolution analysis presented afterward in this thesis, is unknown. The appropriateness of this

method is tested in Chapter 2 by evaluating how GBIF data perform against known county-level

species distributions from the Biota of North America Program (BONAP). This study searches

for correlates of climatic niche estimation disagreements, by testing GBIF sampling effort and

elevation niche. The results are presented and discussed in the context of providing

recommendations for evolutionary biologists seeking to use GBIF-enabled climatic niche

estimates in their research. Chapter 2 provides the first broad-scale comparison of North

American GBIF distribution data to a secondary source of distribution data (BONAP) and

provides justification for climatic niche estimation methods used in the following chapter.

Chapter 1: Introduction

Chapter 3 asks the question, why do diversity differences exist across the tree of life?

More specifically, why are there so many Carex species in North America? It relates this

question to a recently proposed hypothesis that higher rates of trait evolution result in higher

abilities to evolve new morphological or ecological traits (Lovette et al., 2002; Adamowicz et

al., 2008; Pigliucci 2008, Rabosky et al., 2013). Specifically, Chapter 3 estimates rates of evolution of Carex morphology (measurements of culms, leaves, perigynia and achenes; see Fig.

1.1 for terminology), habitat niche and climatic niche on a reconstructed phylogeny. Sister clade

comparisons are used to assess statistically whether rates of trait evolution are associated with

increased species richness within the genus.

Further background information and precise hypotheses are presented at the beginning of

each study. Figures and Tables can be found at the end of each Chapter (Chapters 1-3). Lastly, in

Chapter 4, conclusions from Chapters 2 and 3 are summarized and discussed.

Chapter 1: Introduction 1.1 FIGURES

1.1 FIGURES

Culm Perigynium

C: Spike and culm

Perigynium Achene

Spikelet

A: One spikelet B: Inflorescence D: Dissected spikelets Achene

Chapter 2: How sensitive are climatic niche 2.1 INTRODUCTION inferences to distribution data sampling?

Chapter 2: How sensitive are climatic niche inferences to distribution data sampling?

2.1 INTRODUCTION

The integration of species occurrence and phylogenetic data has allowed researchers to

address questions about the role of the ecological niche in speciation and extinction. For

example, phylogenetic niche conservatism and niche divergence are two well-known hypotheses

about the nature of diversification that have resulted from the study of species’ niches (predicted

via occurrence data) along phylogenies (Peterson et al., 1999; Graham et al., 2004; Warren et al.,

2008; Pyron et al., 2014). In particular, species’ realized climatic niche is easily quantified using

occurrence datasets and climatic data, and when analyzed in a phylogenetic framework has the

possibility to elucidate the role of climate in diversification (Peterson et al., 2010).

The largest online resource for occurrence data is the Global Biodiversity Information

Facility (GBIF), an international infrastructure of millions of biological specimen records published freely by institutions across the world (www.gbif.org). Unfortunately, GBIF suffers from significant data quality issues (Soberón et al., 2002; Graham et al., 2004; Yesson et al.,

2007; Newbold, 2010). Most notably, the spatial coverage of GBIF occurrence records does not appropriately represent species ranges (e.g., in invertebrates see Beck et al., 2013). Poor spatial

coverage of data may be the result of the biases of collectors, biases of institutions (e.g.,

predisposition towards collecting in the Western Hemisphere) and which institutions submit to

GBIF (Hijmans et al., 2000; Soberón et al., 2000; Reddy & Davalos, 2003; Dennis & Thomas,

2000; Newbold, 2010). These biases pose potential problems for accurate niche estimation and

phyloclimatic analyses.

Chapter 2: How sensitive are climatic niche 2.1 INTRODUCTION inferences to distribution data sampling?

Research on the impact of occurrence data biases on ecological niche estimation has suggested that environmental bias may be avoided if localities are well placed (i.e., covering all main areas of a species’ environmental gradient) and if sampling is sufficient (Hirzel & Guisan,

2002; Newbold, 2010). However, this research has been limited in geographic and taxonomic scope, and has produced conflicting results (Kadmon et al., 2004; Hortal et al., 2008; Beck et al.,

2014). Furthermore, research has been oriented towards niche modelling applications (e.g.,

MaxEnt; Phillips et al., 2006), despite the frequent usage of GBIF occurrence data in

phylogenetic comparative analyses. An evaluation of the quality of climatic niche inferences

from GBIF occurrence data on a broad geographic scale and from a phylogenetic comparative

perspective is lacking. More generally, an appropriate strategy to correct for insufficient

sampling when environmental bias is present is needed for all users of GBIF data.

This study contributes to the assessment and improvement of climatic niche inferences from GBIF occurrence data across North America. It compares climatic niche estimates obtained from GBIF and from county-level verified distributions (Biota of North America Program;

BONAP) for 363 species of the largest angiosperm genus in the temperate zone (genus Carex,

family Cyperaceae). Specifically, the magnitude and direction of differences between species’

GBIF and BONAP-estimated locations in principal component niche space are calculated.

Subsequently, this study tests (1) how GBIF and BONAP niche differences vary with GBIF

sampling effort, (2) how differences vary with elevation (to determine if county data is biased for

high-elevation species, with the aim of supplementing GBIF data with BONAP county data), and

tests (3) ancestral state reconstruction with each occurrence dataset. GBIF sampling effort is

evaluated by its coverage of BONAP county records and its geographic spread relative to

BONAP distributions, capturing coverage and skew of GBIF data respectively. Sampling effort

Chapter 2: How sensitive are climatic niche 2.1 INTRODUCTION inferences to distribution data sampling? is expected to be correlated with differences in niche estimates (where poor sampling effort results in greater differences), high elevation species are predicted to be biased because of coarse county-level distribution data resolution, and ancestral state reconstructions are expected to differ between occurrence datasets. The utility of each dataset (GBIF and BONAP) for climatic niche inference is discussed and recommendations for dataset use and the potential for BONAP supplementation are presented.

Chapter 2: How sensitive are climatic niche 2.2 METHODS inferences to distribution data sampling?

2.2 METHODS

2.2.1 Study taxon

The genus Carex (Cyperaceae; sedges) is one of the largest flowering plant genera in the world (4th largest; Frodin, 2004; Global Carex Group, 2015), with centres of diversity in North

America (north of Mexcio; ca. 480 species) and eastern Asia (Ball & Reznicek, 2002; Starr &

Ford, 2009). Unlike other big plant genera, it inhabits a wide range of habitats (e.g., deciduous

forest, freshwater wetland, alpine tundra, deserts; Egorova, 1999; Ball & Reznicek, 2002) and

climatic niches (polar, boreal, moderate). Sedges are particularly well known and well collected

in North America. Consequently, occurrence data is most abundant and available in North

America. The combination of high biodiversity, climatic diversity and occurrence data

availability in North American Carex result in an ideal opportunity for analysis of the effects of

occurrence data quality on climatic niche estimation. The Flora of North America online

(www.efloras.org) was used as a checklist for Carex species to include in this study. Introduced

species were excluded and subspecies and varieties were not recognized (n=363 spp.) for

simplicity of analysis.

2.2.2 Occurrence data

2.2.2.1 Global Biodiversity Information Facility (GBIF) dataset – Carex occurrence data

were obtained using the function gbif in the package dismo for R version 3.0.1 (www.r-

project.org). As occurrence data can be removed or uploaded by participating institutions to

GBIF at any time, to ensure the capture of the highest quantity of specimen data possible, data

were downloaded at three time points; from 16 May to 28 May 2013, on 13 January 2014 and on

Chapter 2: How sensitive are climatic niche 2.2 METHODS inferences to distribution data sampling?

3 July 2014. These data were then merged, yielding from one to 216,475 GBIF records per

Carex species. GBIF occurrence data obtained in R contained fields describing the locality

(continent, country, administrative unit level 1, administrative unit level 2, locality, latitude,

longitude, altitude), the collection (institution, collection, catalogNumber, basisOfRecord,

collector, earliestDateCollected, latestDateCollected) and the download (gbifNotes,

downloadDate). All records missing latitude and longitude coordinates were excluded.

Additionally, duplicate records and records with unacceptably low precision were removed.

Records were deemed to have low precision if either latitude or longitude had one decimal place

or less, and these were removed because they were determined to be erroneous.

2.2.2.2 Biota of North America Program (BONAP) dataset –BONAP (www.bonap.org) is a

database containing U.S. county-level botanical species distributions. BONAP maps are

generated with the aid of floristic experts and are verified by dataset curators. Therefore, these

maps represent current knowledge on species distributions and are the highest accuracy

distribution data available. In their raw format, BONAP maps are county presence lists. To

facilitate niche estimation, the BONAP data were transformed into point data in R by calculation

of county polygon centroids (map_data and Polygon functions in the ggplot2 package).

Unfortunately, the resolution of this dataset depends on the size of the counties in the species’

distributions. However, no finer scale accurate data are readily available for all Carex species at

this time.

Chapter 2: How sensitive are climatic niche 2.2 METHODS inferences to distribution data sampling?

2.2.3 Geographic extent

Extent was limited to the continental United States due to the quality of GBIF data and

the availability of BONAP data, and to achieve a contiguous study area. The R packages maps,

sp, and maptools were used in combination to extract US border polygons from the usa database

(including mainland borders and borders of Long Island, Manhattan, Martha’s Vineyard,

Nantucket Island, Orcas Island, San Juan Island, Staten Island and Whidbey Island). The

function pnt.in.poly from the SDMTools package was used to verify whether occurrence points

fell on or within US borders. Points that fell outside of polygons were excluded.

2.2.4 Climate data

Climatic niche estimates were enabled by the WorldClim Global Climate Dataset

(www.worldclim.org; Hijmans et al., 2005) using the R package dismo. WorldClim data are a set

of global climate raster layers at a maximum resolution of one square kilometre. The BIOCLIM

dataset (www.worldclim.org/bioclim) is composed of nineteen biologically meaningful variables

derived from the WorldClim data set. Data were downloaded in R using the getData function

and name=‘worldclim’ in the nlme package. WorldClim data at a resolution of 2.5 arc-minutes

(=~5 km) were used to remain conservative in climate estimates.

All 19 BIOCLIM variables were extracted for each locality point in both the GBIF and

BONAP datasets. For each species and dataset, the mean per BIOCLIM variable was calculated.

This resulted in 19 BIOCLIM-GBIF means and 19 BIOCLIM-BONAP means for each Carex

species.

Chapter 2: How sensitive are climatic niche 2.2 METHODS inferences to distribution data sampling?

2.2.5 Principal component analysis

Climatic niche was quantified using principal component analysis (PCA). PCA is an

ordination method that reduces a number of correlated variables into a smaller number of

uncorrelated principal components. By including multiple species in a PCA, direct comparison of

species’ positions in climatic space is possible (Jongman et al., 1995). The prcomp function in

the stats package for R was used to perform PCA on BIOCLIM-GBIF and BIOCLIM-BONAP

means and to rotate, centre and scale all variables. All means were included in one PCA, to allow

for comparison of estimates.

The difference between GBIF and BONAP niche positions in principal component

climatic space was computed using vectors projected along PC1 and PC2 axes. The magnitude

and angle of the vector connecting the estimates were calculated. Vector magnitude should be

interpreted in this study as the disagreement or error separating GBIF and BONAP niche

positions and the vector angle as the direction of bias.

2.2.6 Correlates of error

Sampling effort of species GBIF data was evaluated in two ways; (1) by the number of

BONAP distribution counties corresponding GBIF data cover (i.e., county coverage) and (2) by

comparing the geographic spread of GBIF points to BONAP points. Both methods of quantifying

sampling effort assume that BONAP data appropriately represent the extent of species’

distributions. Although BONAP data are not perfectly correct, they are presence-absence

distribution data, unlike occurrence data from the GBIF data repository. This means that when no

record exists in a species’ distribution for a particular geographic location, one can confidently

assume that the species not does exist there. The data are designated presence-absence because

Chapter 2: How sensitive are climatic niche 2.2 METHODS inferences to distribution data sampling?

BONAP data managers have actively searched herbaria, institutions and experts for distribution information. Therefore, by comparing GBIF to BONAP data, the degree of missing data (or sampling effort) of GBIF data can be quantified.

To calculate county coverage of GBIF data, a list of counties GBIF points occupy was

generated per species (see Fig. 2.2A for sample calculation). Then, a coverage percentage was

calculated (GBIF counties/BONAP counties).

The function mcp in the R package adehabitatHR was used to compare geographic

spread of GBIF localities to BONAP centroids. Specifically, mcp calculates the minimum

convex polygon for a set of spatial points. The user may define a percentage of coordinate data to

utilize in the calculation, to account for outliers. Ninety-five percent of GBIF occurrences were

used (to account for outliers) and 100% of BONAP centroids were used to compute area

polygons. Outliers are only expected to be found in GBIF data. Finally, the relative area of GBIF

polygons to BONAP polygons was calculated (see Fig. 2.2C for sample calculation). Species

with fewer than five GBIF occurrences were excluded, as polygons calculated from too few

coordinates may result in inaccurate area estimates. Furthermore, after examination of the

structure of relative area data, it was determined that species with relative areas more than 1.5

times the interquartile range of the data (obtained via boxplot in R) likely possessed erroneous

GBIF data and were removed.

Elevation ranges were obtained from the Flora of North America (FNA) species

treatments online (www.efloras.org) and the mean was calculated per species (e.g., Carex

cephaloidea 20-300m, mean=160m). Despite their low accuracy and qualitative nature, FNA elevation mean data were preferred over GBIF-enabled WorldClim elevation estimates for consistency and predictive power (i.e., GBIF elevation estimates are of unknown accuracy and

Chapter 2: How sensitive are climatic niche 2.2 METHODS inferences to distribution data sampling? precision). For example, if a user wishes to predict the quality of the climatic niche estimate from

GBIF or BONAP data, they can search the FNA for the elevation range of a given species, and

use it alongside the regressions from Figure 2.3 to inform their methods decisions.

The function cor.test in the statistics package in R was used to test for significant correlations between niche differences and sampling effort or elevation. From the same R package, lm was used to fit linear regressions when significant correlations were recovered.

2.2.7 Phylogeny

To evaluate how differences in climatic niche estimates affect phylogenetic comparative

analyses, a time-calibrated Bayesian Carex phylogeny was inferred and ancestral climatic niche

PC1 states were reconstructed on the tree. Details on phylogenetic methods can be found in the

Methods section of Chapter 3.

2.2.8 Ancestral state reconstruction

Evolutionary biologists use phylogenetic comparative methods to understand how

species’ traits affect speciation and extinction. Increasingly, ecological niche is treated by

researchers as an evolving trait (Vieites et al., 2009) which may be conserved (phylogenetic

niche conservatism; Harvey & Pagel; 1991) or may rapidly change. Ancestral state

reconstruction is one method used to understand how traits have changed (Cunningham et al.,

1998).

The contMap function in the phytools package for R (Revell, 2012) was used to visualize

ancestral states. This function estimates states at internal nodes using maximum likelihood via

the fastAnc function and uses Felsenstein’s contrasts algorithm to infer states along edges

Chapter 2: How sensitive are climatic niche 2.2 METHODS inferences to distribution data sampling?

(Revell, 2013). The fastAnc function was further used to extract ancestral climatic niche values,

which were evaluated using three strategies: (1) r2 and slope from the relationship of GBIF-

inferred ancestral states to BONAP-inferred ancestral states, (2) a paired t-test and (3) sum of

squared differences calculations. By calculating r2, the similarity of each set of reconstructed

states are to each other was evaluated. Furthermore, the slope of the relationship was used to

determine if one set was consistently predicting higher or lower ancestral values. Using a paired

t-test, means were tested for a significant difference. Finally, by calculating the sum of squared

differences for each set and the sum of squared differences between sets, levels of variance

between and within sets were evaluated.

2.2.9 Additional analyses

To determine if BONAP data were consistently underestimating the elevation niche of

Carex species, a supplementary regression analysis was conducted. For each species, elevation

inferred via BONAP data was plotted against elevation inferred using GBIF occurrence points. A

regression line was plotted and compared to a line with slope of 1.

Uncertainty in ancestral state reconstructions was assessed using the fancyTree function

in the phytools package. Ancestral states were plotted and the 95% confidence interval of state

estimates was visualized using shading.

While the eastern United States are well divided into small counties, the western United

States (west of the Mississippi river) are characterized by fewer and larger counties. To

determine if a relationship exists between geography and difference in climatic niche estimates,

species were split into eastern and western species (widespread species were not considered).

Their differences in climatic niche space were plotted using a boxplot.

Chapter 2: How sensitive are climatic niche 2.3 RESULTS inferences to distribution data sampling?

2.3 RESULTS

2.3.1 Principal component analysis

The first two principal component axes explained 74% of variance (PC1=40%,

PC2=34%) and the first three principal component axes explained 91% of BIOCLIM data

variance (PC3=18%). Additional components explained less than one variable’s worth of

information (1/19 variables = 5.3% per variable; PC4=5%, PC5=2%, PC6=1%). Temperature

range and seasonality contributed most to PC1, followed closely by temperature measurements

of dry and cold periods and precipitation measurements of cold and wet periods. Precipitation of

warm and dry quarters and temperature of warm and wet quarters contributed most to PC2. All

PC1 contributions were positive and PC2 contributions were negative. Lastly, diurnal range and

maximum temperature of warmest month contributed strongly to PC3. Contributions were both

positive and negative. Details on principal component loadings for the first three PC axes can be

found in Table 2.1.

Only the first two principal components were considered in calculation of climatic niche

because these components contain the majority of the BIOCLIM information (74% of variability,

10 of 12 BIOCLIM variables loaded). Although PC3 explains more variability than would be

expected if all variables contributed equally (18%>5.3%), its inclusion would impede

interpretation and complicate computation.

The principal component biplot obtained by plotting climate PC1 against climate PC2

(Fig. 2.1) shows ‘curvilinear distortion’ (Minchin, 1987) or a ‘horseshoe artefact’. This is a

recognized phenomenon in ecology, resulting from principal component transformation of long-

distance ecological gradient data (Gauch et al., 1977; Hill & Gauch, 1980). Species on the ends

Chapter 2: How sensitive are climatic niche 2.3 RESULTS inferences to distribution data sampling? of the gradient experience climates so extreme, they begin to resemble each other after variables are transformed. Biological interpretation should not be drawn from the arch pattern.

Furthermore, it should be noted that extremes of the data may appear more related than expected.

In Figure 2.1, each species is represented by one GBIF climate estimate and one BONAP

climate estimate, connected by a change vector. From climate PC2=2 to 6, GBIF positions are

well dispersed, while BONAP positions cluster around PC2=3. This results in a group of vectors

pointing downwards. For estimates where PC2<0, GBIF and BONAP positions track each other

closely. Very few points occur from PC2=0 to 2. Along PC1, estimates are distributed evenly.

GBIF estimates tend to occur at higher PC1 values than BONAP estimates, resulting in vectors

directed towards the left of the plot. The outlier on the far right of Figure 2.1 (PC1=~10, PC2=0)

is Carex anthoxanthea, a West Coast endemic, found from Alaska to Oregon.

2.3.2 Sampling effort influencing error

The negative correlation between GBIF county coverage and differences in GBIF and

BONAP climatic niche estimates was weak and only slightly significant at the 5% level

(Pearson’s linear coefficient correlation ρ=-0.13, p=0.009). County coverage explained only

1.8% of the climatic niche estimate differences (r2=0.018). With low coverage (<20%), differences were highly variable (from 0 to 8 PC units). However, with high county coverage

(>80%), differences in climatic niche space were less variable (0 to 2 PC units).

The degree of geographic spread in GBIF locality data had no significant relationship with differences in GBIF and BONAP climatic niche estimates. Errors were distributed similarly regardless of the relative size of occurrence minimum convex polygons.

Chapter 2: How sensitive are climatic niche 2.3 RESULTS inferences to distribution data sampling?

Outliers in Figure 2.2B and D were Carex livida, C. salina, C. micropoda and C. viridula.

These species had few characteristics in common. They ranged from hybrid to strictly defined species, and from specialists to widespread in distribution.

2.3.3 Elevation influencing error

Elevation niche and climatic niche estimate differences were significantly correlated

(ρ=0.36, p=1.405x10-12). Elevation explained 13% of differences in climatic niche space

(r2=0.13). Higher elevation species were significantly biased in one direction (~200°-300°;

ρ=0.23, p=1.316x10-5, r2=0.05), which further analyses revealed to be downwards in altitude

(Fig. 2.5). Outliers seen in Figure 2.3 were Carex livida, C. salina and C. micropoda. As

previously described, no common identifying features of these species could be determined.

2.3.4 Ancestral state reconstruction

Overall patterns in the contMap visual representations of ancestral state reconstructions

were similar between the GBIF and BONAP datasets. Nodes deeper in the tree, although more

subject to uncertainty, had comparable inferred ancestral values. The regression of BONAP

states to GBIF states showed that BONAP inferred states were consistently lower than GBIF

states (slope=0.902; r2=0.829). Means between ancestral states sets were significantly different

(paired t-test p=2.2x10-16). However, variance between sets of ancestral values was lower than within sum of squared differences (GBIF SSD=698; BONAP SSD=685; SS differences=218).

Chapter 2: How sensitive are climatic niche 2.3 RESULTS inferences to distribution data sampling?

2.3.5 Additional analyses

Figure 2.5 showed that BONAP data consistently underestimated the elevation niche of

Carex species (i.e., the GIBF:BONAP regression line was more shallow than the line of elevation equivalence). Elevation was most underestimated when species’ GBIF inferred elevation approached 500m, at the intersection of the regression line and the elevation equivalence line.

Uncertainty in ancestral state reconstructions was large, and increased from the tips of the tree to the root (Fig. 2.6).

When comparing the magnitude of differences in niche estimates between western and

eastern Carex species, substantial overlap in interquartile ranges was seen (Fig. 2.7).

Chapter 2: How sensitive are climatic niche 2.4 DISCUSSION inferences to distribution data sampling?

2.4 DISCUSSION

GBIF data are commonly used to estimate species’ climatic niche in contemporary

ecology and evolutionary biology (>150 scientific papers returned in a search of ‘climatic niche’

in the GBIF Mendeley Public Library). Using a phyloclimatic perspective, this study evaluates

GBIF occurrence data against county-level species distributions in the US. Specifically, climatic

inferences from GBIF data and BONAP distribution data are compared, and the influence of

sampling effort and elevation on differences in estimated niche is evaluated. Finally, the degree

to which differences in climatic niche estimates alter ancestral state reconstruction is assessed.

This research is timely for three reasons. Firstly, relatively little attention has been paid to

how biases in GBIF data affect comparative phylogenetic analyses as most authors have focused

on the effects of biases on bioclimatic modeling (e.g., Kadmon et al., 2004; Newbold, 2010).

Secondly, the integration of geographic, environmental and phylogenetic data has been identified

as an important step for future research addressing questions about the role of geography and

ecology in diversification (Peterson et al., 2010). Lastly, the climatic niche estimates obtained from GBIF in this work will be used in a further study (Chapter 3), investigating the relationship between the rate of climatic niche evolution in Carex and species richness. An understanding of

the limits and errors of GBIF data is critical for conclusions to be drawn from trait evolution

analyses. This study is also the first to evaluate the utility of GBIF data for climatic niche

estimation on a broad geographic scale with over 360 species.

A negative relationship between the magnitude of differences and sampling effort

(captured via county coverage and geographic spread) was expected. This is because as sampling

effort is reduced, the accuracy of GBIF inferences should decrease as a result of spatial bias or

poor representation of species distributions. Greater deviations of GBIF from BONAP climatic

Chapter 2: How sensitive are climatic niche 2.4 DISCUSSION inferences to distribution data sampling? estimates (and vice versa as sampling effort increases) should ensue. This is an intuitive expectation, which has been supported by a study evaluating the spatial bias of dung beetle museum records (SCAMAD database) in Madrid and its effects on environmental niche estimates (Hortal et al., 2008). Yet, other studies investigating how spatial biases in museum data

affect niche estimates in Israel (Kadmon et al., 2004) and Egypt (BioMAP project; Newbold,

2010) have shown that spatial bias of occurrence data does not result in substantial

environmental bias. The analysis presented here aligns with studies showing that bias does not

affect niche estimates (Kadmon et al., 2004; Newbold, 2010) and does not align with the study

described above (Hortal et al,. 2008), showing bias significantly affects niche estimates. A strong

relationship between sampling effort and niche differences was not recovered (Fig. 2.2). This

means that for a large number of species in the genus Carex, GBIF data with poor coverage of the known range and geographically restricted occurrence records (i.e., low GBIF sampling effort) predict climatic niche as accurately as county centroids. The conflicting results between

Hortal et al. (2008) and the results presented here may be due to geographic scale. Hortal et al.

(2008) focused on Madrid and its surroundings, a limited geographic scope leading to more vulnerability in climatic niche estimation error. Furthermore, the city of Madrid may experience an Urban Island Effect, where climate within the city boundaries differs substantially from elsewhere (Ferguson & Woodbury, 2007). Lastly, it should be noted that these three studies

(Hortal et al., 2008; Kadmon et al., 2004; Newbold, 2010) examined spatial bias rather than sampling effort. This may account for differences in results.

Rather than studying spatial bias directly, this study examined sampling effort. Sampling effort is more easily quantified on a broad geographic scale and more readily estimated by

potential users of GBIF data. Therefore, it may be a more practical GBIF data assessment metric.

Chapter 2: How sensitive are climatic niche 2.4 DISCUSSION inferences to distribution data sampling?

However, species with similar levels of sampling effort may have varying degrees of spatial, environmental, taxonomic and temporal bias. To measure spatial bias in our dataset, GBIF estimates should be evaluated against a rigorously verified fine-resolution occurrence dataset. An understanding of the relationship between spatial bias and sampling effort would enhance this work. Unfortunately, collecting high quality occurrence records on this scale would require substantial time and effort.

Although the relationship between county coverage and differences was only weakly significant, a trend in variance of differences can be observed (Fig. 2.2B). With low coverage

(<20%), differences were highly variable, while with high coverage (>80%) differences were

consistently under 2 PC units. This suggests that while improving sampling effort does not

consistently reduce errors, it does decrease the frequency of unreliable estimates when many

species are considered. This finding is important for potential users of GBIF data; at low

distribution coverage levels, risk of inaccurate niche estimates is high, and action should be taken

to ensure high quality niche data (see Recommendations section below).

The lack of relationship between geographic spread and niche differences, and the

presence of several outliers (Fig. 2.2D), suggests that Carex GBIF data may contain misidentifications or other erroneous records, despite GBIF data cleaning conducted pre-analysis

(removal of duplicates, imprecise records, and exclusion of points outside of US continental borders). These records are undetectable without manual verification all data points, which is unfeasible. Sedges are known for their reduced morphology and challenging identification (Starr

& Ford, 2009). A dissecting microscope, a detailed flora, and a knowledge of sedge-specific

terminology are all require to identify a species. Even with the necessary knowledge and

equipment, it is common for non-sedge experts to misidentify Carex species. These specimens

Chapter 2: How sensitive are climatic niche 2.4 DISCUSSION inferences to distribution data sampling? and their identifications are rarely reviewed or revisited once stored in collections. Other sources of erroneous GBIF points include incorrectly entered label information or mistakenly georeferenced localities, usually the result of difficult-to-read labels from older specimens.

Unfortunately, a few erroneous GBIF records in key locations can be detrimental to the accuracy

of climatic niche estimates and will go overlooked unless manually verified. In this study,

incorrect GBIF records may hide inside minimum convex polygons and will yield identical

relative polygon areas yet significantly different niche estimates. This was observed in Fig. 2.2D,

and underscores a limit of GBIF data; the persistent risk of incorrect specimen records.

While the results suggest that undetectable and incorrect GBIF records exist in the data, it is also important to note the number of detectable and incorrect records that were removed pre- analysis. The restriction of GBIF data to the continental US using the pt.in.poly function revealed

3086 erroneous records of 60215 total (4.88%). In a study geographically validating GBIF data

using country borders for 6147 Fabaceae (legumes) species (i.e., a methodology identical to this

study), Yesson et al. (2007) found 16% of GBIF records to be geographically incorrect. Thus, the percentage of geographically incorrect points in this study is low in comparison. This may be due to differences in data providers or geographic extent (American versus global GBIF data).

The United States and other western countries tend to submit more data to GBIF (Yesson et al.,

2007) and have more resources to verify data. However, the nature of the incorrect localities aligned well with the findings of Yesson et al. (2007). Often, occurrence points were located just off land. A handful of points were placed in the middle of the ocean or in incorrect countries.

Several records were missing negative signs on longitude data or had latitude and longitude records reversed. Although these points can be identified by comparing coordinates to text locality descriptors (continent, country, locality) or by verifying points’ membership of country

Chapter 2: How sensitive are climatic niche 2.4 DISCUSSION inferences to distribution data sampling? polygons (e.g., by using TDWG4 areas as implemented by Yesson et al., 2007), substantial effort

is required to set up this data verification pipeline. Furthermore, once points are identified,

deletion or manual verification, if the quantity of GBIF data is low, is required. Unfortunately,

near valid points will go undetected by these strategies and will continue to bias niche estimates.

BONAP county data represent known species distributions at a varying resolutions.

County sizes range from 59.13 km2 (New York County, New York) to 51,947.24 km2 (San

Bernardino County, California) and are on average 2 584 km2 (United States Census Bureau,

2010; Alaska is not divided into counties and is not included). As a result, the spatial resolution

of the BONAP centroid data varies. This creates unequal point accuracies and regional

representations. Additionally, county size varies by state. Counties east of the Mississippi River

are on average smaller than counties to the west (average east=1558.9 km2, average west=5543

km2; United States Census Bureau, 2010). This may have effects on niche estimation (climate in

the east is predicted at a finer scale) and county coverage measurements (Fig. 2.7). The

transformation of BONAP data into point data via centroids may also incur inaccuracies

associated with habitat. For example, Carex scoparia is a meadow species. However, the

centroid data calculated using BONAP maps may fall in forests, wetlands, mountains or other

types of unrealistic habitat types. Most notably, elevation plays a large role in determining

microclimate. Elevation on mountain terrain drops off drastically, such that a drop from 2,000 m

elevation to 500 m within kilometres is possible. At higher elevations, climate is cooler and

precipitation levels are affected.

BONAP data have the potential to supplement GBIF distributions in situations where

GBIF data are particularly skewed or incomplete. However, BONAP data may be biased for

species occupying high-elevation niches (restricted areas with drastic differences in climate) due

Chapter 2: How sensitive are climatic niche 2.4 DISCUSSION inferences to distribution data sampling? to the coarse county-level scale of climate estimation. This study tested how differences in climatic niche estimates from GBIF and BONAP data vary with elevation. Species inhabiting high elevations should be poorly estimated by BONAP county centroids, thus producing an increase in the magnitude of differences. A highly significant relationship was found

(p=1.405x10-12) where 13% of the variability in differences was explained by elevation (Fig.

2.3A). Furthermore, high elevation species were found to be biased in one direction (~200°-

300°), and low elevation species were found to avoid this direction (Fig. 2.3B). BONAP

centroids underestimate elevation niche, as expected (Fig. 2.5). These results indicate that county

data become less accurate as species inhabit higher elevations, and that a large proportion of

differences between GBIF and BONAP estimates can be attributed to this effect. Specifically, a

split of species into two groups with different directions of bias appears in Figure 2.3B at

~1500m. Those that are biased at 200-300° occur at ~1500m and above, and those that are not

occur at ~1500m and below. Therefore, it is recommended that species occupying niches at

1000m or above should not be supplemented with county data (see Recommendations section).

The elevation 1000m is suggested to remain conservative.

To determine how differences in niche estimates affect phylogenetic comparative

analyses, ancestral states were reconstructed throughout a Carex species phylogeny using the

two climatic niche PC1 datasets (Fig. 2.4). In general, ancestral states constructed from BONAP

data were lower than GBIF inferred states (Fig. 2.4 regression). This may be due to the elevation

bias of BONAP data (bias inwards of GBIF to BONAP points in niche space in Fig. 2.1;

directional bias in Fig. 2.3B). However, the downwards trend of BONAP ancestral states only

explains 82.9% of the differences (r2=0.829). Remaining error may be due to inaccuracies of

GIBF data.

Chapter 2: How sensitive are climatic niche 2.4 DISCUSSION inferences to distribution data sampling?

Means between the two sets of inferred ancestral states were significantly different

(paired t-test p<2.2x10-16). This may be explained by the uniform shift downwards of BONAP states. Although the means of the sets were significantly different, general patterns appeared similar. Therefore, it is likely that largely similar conclusions would be drawn from visualizations of patterns in contMap.

When the variance in each set and between sets was calculated using the sum of squared differences, the variance within sets was three times greater than the variance between sets.

Differences between ancestral estimates were less pronounced deeper in the tree, and this was accompanied by larger uncertainty in inferred states (Fig. 2.6). Precise estimates of reconstructed

states deeper in phylogenies have been shown to be less reliable than near the tips (Oakley &

Cunningham 2000). If error within sets of estimated ancestral states is greater than in the raw

data, and uncertainty in deep nodes is large, attaining precise and accurate climatic niche

estimates may be less critical than one might assume (with the exception of severely incorrect

GBIF data, e.g. points in the middle of the ocean). Furthermore, uncertainty in phylogenetic

comparative methods are accompanied by uncertainty in phylogenetic trees. All reconstruction

methods result in phylogenies with some degree of inaccuracy and uncertainty. The results

presented here suggest that climatic niche evolution research may not be as affected by

inaccuracies in distribution data as the uncertainties of tree topology and phylogenetic models.

Chapter 2: How sensitive are climatic niche 2.4 DISCUSSION inferences to distribution data sampling?

2.4.1 Recommendations

Although only a weak relationship between county coverage and niche differences was

recovered, at low county coverages (<20%) differences in niche space were variable. To ensure

good quality climatic niche estimates, GBIF users are encouraged to supplement their GBIF data

from other occurrence data sources when coverage of the known distribution is less than 20%.

The Biota of North American Program (BONAP) may be a valuable source of occurrence data

for plant species occurring at low elevations. However, GBIF users are advised to avoid these

data if the mean value of the species’ elevation range from the Flora of North America is above

1000m.

For large scale studies, researchers should consider using BONAP data rather than GBIF-

enabled data for climatic niche estimation. This is because results obtained from BONAP data

will be similar and conclusions may be identical. Perhaps most importantly, a substantial amount

of time and effort will be saved. GBIF data require cleaning to remove duplicates and imprecise

records, to verify validity of records, and to remove erroneous points. Furthermore, GBIF data

contain misidentifications and misapplications, old records since identified as false, and show

errant reports (Kartesz, pers. comm.). BONAP is a smaller, cleaner dataset. Unfortunately,

BONAP data are not publicly accessible at this time. Communication with the data providers (J.

Kartesz at the Taxonomic Data Center, Chapel Hill, NC) is required to obtain permission to use

BONAP data. Improved mobilization of the data should be prioritized to allow for future broad

scale use.

Lastly, users of GBIF-enabled climatic niche estimates in phylogenetic comparative

analyses should note that different distribution datasets and niche estimates will yield different

results, although similar conclusions can still be made despite uncertainties.

Chapter 2: How sensitive are climatic niche 2.5 TABLES AND FIGURES inferences to distribution data sampling?

2.5 TABLES AND FIGURES

Table 2.1 Loadings from principal component analysis of 19 WorldClim BIOCLIM variables estimated from GBIF and BONAP species localities. Only those principal components explaining a larger than expected amount of variation (=5.3%) are included (PC1=40%, PC2=34%, PC3=18%). Loadings are bolded if they are important contributors. This was assessed by comparing against the expected loading value if all variables contributed equally (square root of 1/19=0.229415). BIOCLIM variables are sorted according to contributions to PC1, PC2 and lastly PC3. BIOCLIM Variable PC1 PC2 PC3 BIO7 = Temperature Annual Range (BIO5-BIO6) 0.347006 -0.02357 0.065644 BIO4 = Temperature Seasonality (standard deviation *100) 0.333774 -0.11308 -0.04759 BIO9 = Mean Temperature of Driest Quarter 0.318571 -0.00301 0.149076 BIO6 = Min Temperature of Coldest Month 0.313137 -0.15464 0.167593 BIO19 = Precipitation of Coldest Quarter 0.307952 0.043257 -0.25993 BIO13 = Precipitation of Wettest Month 0.306882 -0.02487 -0.24156 BIO16 = Precipitation of Wettest Quarter 0.29966 -0.01965 -0.26236 BIO11 = Mean Temperature of Coldest Quarter 0.288006 -0.17444 0.227529 BIO3 = Isothermality (BIO2/BIO7) (* 100) 0.286909 0.156302 0.204817 BIO18 = Precipitation of Warmest Quarter -0.07676 -0.35767 -0.07555 BIO17 = Precipitation of Driest Quarter -0.02394 -0.34506 -0.19596 BIO10 = Mean Temperature of Warmest Quarter 0.034194 -0.3438 0.242406 BIO14 = Precipitation of Driest Month -0.04488 -0.3421 -0.18639 BIO8 = Mean Temperature of Wettest Quarter -0.09437 -0.30209 0.212193 BIO1 = Annual Mean Temperature 0.174711 -0.29373 0.249478 BIO15 = Precipitation Seasonality (Coefficient of Variation) 0.180441 0.283397 0.146895 BIO5 = Max Temperature of Warmest Month 0.031265 -0.27722 0.354277 BIO2 = Mean Diurnal Range (Mean of monthly (max temp - min temp)) -0.01996 0.192329 0.401859 BIO12 = Annual Precipitation 0.203849 -0.22602 -0.3181

Chapter 2: How sensitive are climatic niche 2.5 TABLES AND FIGURES inferences to distribution data sampling?

GBIF Sample calculation BONAP Magnitude of change vector 4

2 = 2.54 variance 0 −2 −4

−5 0 5 10

0 2 4 Angle of change vector

= 182.34° Climate PC2 − 34% of −4 −2

−5 0 5 10 Climate PC1 − 40% of variance Fig. 2.1 Principal component (PC) climatic niche space. PCA was used to condense 19 WorldClim BIOCLIM variables into two PC axes (PC1=40% and PC2=34%) explaining the majority (74%) of bioclimatic variance. Species’ GBIF estimates in niche space are represented by circles and BONAP points are represented by triangles. Grey vectors connect species’ GBIF estimates to BONAP estimates, from which magnitude and direction are calculated. A sample calcuation in provided on the right. N=378.

Chapter 2: How sensitive are climatic niche 2.5 TABLES AND FIGURES inferences to distribution data sampling?

A B Sample calculation ρ=-0.13, p=0.009, r2=0.018 8

GBIF and BONAP counties

BONAP counties 6

GBIF occurrences in 4 158 counties BONAP data in 1105 counties (magnitude of change vector) 2 Difference in climatic niche space niche climatic in Difference

GBIF county coverage = 100*(158/(1105+158)) =

12.51% 0

0 20 40 60 80 100 GBIF county coverage (%) C D Sample calculation 8

● ● ● ● ● ● GBIF points and polygon ● ● ● ● ● ● ● ●●● ● ●● ● ● ● ● ●● ●●● ● ● ● ● ● ● ● ● ● ● ● BONAP points and polygon ● ● ●● ● ● ● ● ● ●● ● ●● ●●● ● ● ● ●● ●●● ● ● ●● ● ● ● ● ●●●● ●●● ●● ● ● ● ● ● 6 ●●●●● ● ●● ●●● ● ● ● ●●● ● ● ● ● ● ●●●● ● ● ●●● ●●● ● ●●● ● ● ● ●● ● ●●●●● ●●●● ● ●● ● ● ●●●● ● ● ●●●● ● ● ● ●●●●●● ●● ●● ● ● ● ● ● ● ●● ●● ●●●●●●●●●●●●●●●●●●●● ● ● ● ●●● ● ● ●●● ● ● ● ● ● ● ● ●●●●●●●●●●●●●●●●● ● ● ● ● ● ● ●● ●●● ● ●● ● ● ● ● ●●●● ● ● ● ● ● ●●●●●●●●●●●●●●●●● ● ● ● ● ● ● ● ● ●●● ●● ●● ● ●●●● ● ●●●●●●●● ● ●●●● ● ●● ● ●●● ● ●●●● ● ●● ● ●●●●●●●● ● ●●●●● ● ●● ●●●● ● ● ●●●●●●●● ●● ●●●●●● ● ● ●● ●●● ● ● ● ●●●● ● ● ● ●●●● ●● ●● ●● ● ● ● ●● ● ● ● ●● ●● ● ● ●●● ●●● ●●●●●● ● ●●● ● ● ●●● ● ●●●● ●●●●●● ● ● ● ●●●●●● ●●● ● ●● ●●●● ●●●●● ● ● ●● ●● ●●●●●●●●●●●●● ●● ● ● ● ● ●●●●● ● ●● ● ●●●● ●●●●●●●● ●●●●●●●●● ●● ●● ● ● ●● ●● ●●●● ● ●●● ●●●● ●●●● ●●●●●●●●●●● ●● ● ●●● ●● ●● ●● ● ● ●●● ● ● ●● ●●●●●●●●●●●●● ● ● ● ●●● ● ● ● ●●●●●●●●● ●●● ● ●●● ●● ●●● ●●●●●● ●● ● ●● ●● ●●● ●● ●●●● ● ● ●●●● ● ● ● ● ● ● ● ●●●●●● ●● ●● ●●● ●● ●●●● ● ●● ●●●●●●● ● ● ● ● ● ●●●●●● ● ● ●●● ● ●●●●● ●●●●● ●● ●● ●● ●● ●●●●●●● ● ●●●●●●●● ● ●●●●● ● ●●●●●●●● ● ● ●●●● ● ● ●●●●● ●●● ●●●●●●● ●●●●● ●●●● ● 4 ●●● ● ●●●● ●● ●●●● ● ●●● ● ●●● ● ● ●●●● ●● ●●●●●● ● ● ● ● ● ●● ●●● ●●● ●●●●● ● ● ●●●●●● ●● ●●●●●●● ● ● ● ●●● ● ● ● ●●● ●●●● ●●●● ● ●●●●●●●●● ●● ●●●● ●●●●● ●● ●●●● ● ●●●● ●●●●● ● ●●●●●●●● ● ●●● ●● ● ● ● ● ●●●● ● ●●●●●●●● ●●● ● ●● ● ●●● ● ● ●●● ●●●● ● ● ●●● ●●●●●● ●● ●●●●●● ● ● ● ●●●● ● ● ● ● ●● ● ● ●●●●● ●● ●●●● ●●●●●● ●●●●●●● ●● ● ●● ● ● ●●●●●●●●● ●●● ●●● ●●● ●●● ● ● ●●● ● ● ● ●●●●● ● ● ●●●●● ●●● ● ● ● ● ● ● ● ● ● ● ●●● ● ●●●●●● ● ● ● ●●●●● ● ● ● ● ● ● ● ●●● ● ● ●●●● ●●●●●●●●●●● ● ●●● ● ● Relative area GBIF ● ● ● ●● ● ● ● ● ●●●● ●● ●● ● ●●●● ● ●●● ● ●● ● ● ● ● ●●●● ● ●●● ●●●●●● ●● ● ●●●● ● ●● ● ● ●● ● ● ● ●●●● ●●●●●●● ●● ● ● ● ● ● ● ●● ● ● ● ● ●●● ● ● ● ●● ●● ●● ●● ● ●● ● ● ● ●●●●●●●●●●●●●●● ● ● ●● ● polygon/BONAP ●●●● ● ● ●●●●●●● ●● ●●● ● ● ● ● ● ●● ● ●● ●●●●●●●●●●●●● ●●● ● ● ●●●● ● ● ●● ●● ●● ●●● ●● ● ● ● ● ●●● ● ● vector) (magnitude of change ●● ●●● ●●●●●● ●●●●● ●●● ● ● ● ● ●● ● polygon = 57.55% 2 ● ●● ● ● ●●●● ● ●●● ● ●●● ● ● ●●●● ● ● ●● ●●●●●● ● ●●●●● ● ● ● ● ● ● ● space niche in climatic Difference ● ● ● ●● ● ●● ● ●●● ● ● ● ●● ● ● ● ● ● ● ● ●

● ● 0

0 20 40 60 80 100 Relative area of GBIF polygon to BONAP polygon (%) Fig. 2.2 The relationship between sampling effort and magnitude of differences between GBIF and BONAP climatic niche estimates. Regression lines are presented if a significant correlation was found. Correlation coefficients (ρ), p-values and r2 values are indicated in the top right-hand corner of plots with regression lines. (A) Sample calculation of GBIF county coverage for Carex lurida. Counties included in C. lurida’s GBIF data distribution are in blue and C. lurida BONAP county data are in red. (B) The relationship between GBIF county coverage and differences in climatic niche space. Each circle is one Carex species. N=363. (C) Sample calculation of relative geographic spread for C. lurida. GBIF points are in blue and BONAP points are in red. Minimum convex polygons calculated from each dataset are visualized. (D) The relationship between relative geographic spread and differences in climatic niche space. Each circle is one Carex species. N=321.

Chapter 2: How sensitive are climatic niche 2.5 TABLES AND FIGURES inferences to distribution data sampling?

ρ=0.36, p=1.405x10−12, r2=0.13 8 6 4 2 (magnitude of change vector) Difference in climatic niche space 0

0 1000 2000 3000 Median elevation (m) from FNA treatment B

ρ=0.23, p=1.316x10−5, r2=0.05 300 200 100 (angle of change vector, 0 to 360°) 0 to (angle of change vector, Direction of difference in climatic niche space niche in climatic difference of Direction 0

0 1000 2000 3000 Median elevation (m) from FNA treatment Fig. 2.3 The relationship between elevation niche and differences in climatic niche space. Regression lines are presented if a significant correlation was found. Correlation coefficients (ρ), p-values and r2 values are indicated in the top right-hand corner of plots with regression lines. Each circle is one Carex species. N=363. (A) Elevation plotted against magnitude of differences in PC climatic niche space. (B) Elevation plotted against direction of differences in PC climatic niche space. Direction is in degrees.

Chapter 2: How sensitive are climatic niche 2.5 TABLES AND FIGURES inferences to distribution data sampling?

GBIF ancestral states BONAP ancestral states

Carex obispoensis Carex concinna Carex richardsonii Carex concinnoides Carex collinsii Carex fissuricola Carex lemmonii Carex luzulina Carex luzulifolia Carex edwardsiana Carex abscondita Carex cumberlandensis Carex laxiculmis Carex granularis Carex crawei Carex microdonta Carex gholsonii Carex glaucodea Carex pigra Carex flaccosperma Carex impressinervia Carex hitchcockiana Carex brysonii Carex careyana Carex platyphylla Carex austrocaroliniana Carex plantaginea Carex conoidea Carex grisea Carex corrugata Carex godfreyi Carex amphibola Carex oligocarpa Carex thornei Carex bulbostylis Carex acidicola Carex calcifugens Carex planispicata Carex paeninsulae Carex floridana Carex novae-angliae Carex tonsa Carex lucorum Carex albicans Carex serpenticola Carex nigromarginata Carex inops Carex communis Carex geophila Carex pityophila Carex peckii Carex pensylvanica Carex globosa Carex rossii Carex deflexa Carex brainerdii Carex brevicaulis Carex capillaris Carex cryptolepis Carex viridula Carex flava Carex michauxiana Carex turgescens Carex lonchocarpa Carex folliculata Carex planostachys Carex lativena Carex amplifolia Carex scabrata Carex vestita Carex scabriuscula Carex curatorum Carex sartwelliana Carex congdonii Carex torreyi Carex polymorpha Carex californica Carex tenax Carex dasycarpa Carex umbellata Carex whitneyi Carex hirtifolia Carex debilis Carex gynodynama Carex hirtissima Carex mendocinensis Carex virescens Carex aestivalis Carex misera Carex complanata Carex swanii Carex bushii Carex caroliniana Carex hirsutella Carex pedunculata Carex baltzellii Carex picta Carex grayi Carex intumescens Carex frankii Carex elliottii Carex halliana Carex oligosperma Carex houghtoniana Carex atherodes Carex sheldonii Carex trichocarpa Carex laeviconica Carex striata Carex pellita Carex lacustris Carex hyalinolepis Carex baileyi Carex lurida Carex utriculata Carex schweinitzii Carex saxatilis Carex tuckermanii Carex vesicaria Carex exsiccata Carex bullata Carex thurberi Carex hystericina Carex pseudocyperus Carex comosa Carex retrorsa Carex gigantea Carex louisianica Carex lupuliformis Carex lupulina Carex aperta Carex haydenii Carex verrucosa Carex glaucescens Carex joorii Carex shortiana Carex squarrosa Carex typhina Carex barrattii Carex obnupta Carex mertensii Carex spectabilis Carex magellanica Carex limosa Carex barbarae Carex endlichii Carex nebrascensis Carex torta Carex crinita Carex mitchelliana Carex gynandra Carex emoryi Carex interrupta Carex nigra Carex stricta Carex bigelowii Carex scopulorum -4.697 PC value 10.405 Carex angustata Carex nudata Carex schottii Carex senta Carex lenticularis Carex salina Carex paleacea length=0.037 Carex lyngbyei Carex aquatilis

state equivalence BONAP states ~ GBIF states 4 BONAP slope = 0.902 states ~ r2 = 0.829 GBIF states Paired t-test of ancestral values t = 15.351, p-value < 2.2x10-16 0 2 SSD GBIF = 698 SSD BONAP = 685 BONAP ancestral state ancestral BONAP −2 SS differences = 218

−2 2 6 GBIF ancestral state Fig. 2.4 Ancestral climatic niche PC1 reconstruction using GBIF estimates (left) and BONAP estimates (right). Colours represent trait values. The reconstruction was visualized on a Carex phylogeny using the contMap function in R. A plot of BONAP ancestral states versus GBIF ancestral states is presented at the bottom, showing a slight offset from state equivalence. Further statistics evaluating ancestral state differences are shown (see Methods for details).

Chapter 2: How sensitive are climatic niche 2.5 TABLES AND FIGURES inferences to distribution data sampling?

1:1 line

GBIF:BONAP line 2000 2500 1500 1000 BONAP inferred elevation (m) elevation inferred BONAP 500 0

0 1000 2000 3000

GBIF inferred elevation (m) Fig. 2.5 The relationship between elevation predicted from GBIF occurrence data and elevation predicted from BONAP county data. A regression line is presented in black and a 1:1 elevation equivalence line is in grey. Elevation data were obtained from WorldClim at a 5km resolution and were combined with locality data to calculate elevation estimates. Each circle is one Carex species. N=378.

Chapter 2: How sensitive are climatic niche 2.5 TABLES AND FIGURES inferences to distribution data sampling?

Fig. 2.6 Uncertainty in ancestral state reconstruction from GBIF climatic niche PC1 estimates. Evolutionary time is on the x-axis and trait values on the y-axis. Blue transparent lines extend outwards showing 95% confidence limits. Plot was generated using the fancyTree function in the phytools package for R. Uncertainty from reconstruction of BONAP climatic niche estimates appeared qualitatively identical and is therefore not presented. N=363.

Chapter 2: How sensitive are climatic niche 2.5 TABLES AND FIGURES inferences to distribution data sampling?

(magnitudechange of vector) Differenceinclimatic niche space 0 1 2 3 4 5 6

Western Species Eastern Species

Group Fig. 2.7 Analysis of the influence of geography on differences in climatic niche estimates. Counties in the eastern US are on average smaller than in the west. Species were separated into strictly eastern and strictly western species. Widespread species were not included. N=179.

Chapter 3: Regional species richness and trait 3.1 INTRODUCTION evolution in the genus Carex (Cyperaceae)

Chapter 3: Regional species richness and trait evolution in the genus Carex

(Cyperaceae)

3.1 INTRODUCTION

Species richness is not distributed evenly across the tree of life. While some lineages

have little morphological diversity and are species-poor (e.g., Darwin’s ‘living fossils’; Stanley,

1979), others undergo rapid and remarkable diversification (e.g., African cichlids, Andean

lupines; Meyer et al. 1990; Hughes & Eastwood, 2006). Surprisingly, a clear understanding of

this prominent macroevolutionary pattern and the processes shaping it, is still lacking.

Exceptional species richness may arise in multiple ways. Firstly, a group may achieve

high species richness via its longevity (McPeek & Brown, 2007; Rabosky, 2009; Rabosky et al.,

2012). Older clades have had more time to accumulate species, and are expected to be more

species-rich than younger clades. This age-species richness relationship has not been consistently

observed across taxonomic groups, and researchers speculate diversity carrying capacities may

exist (Ricklefs, 2008; Wiens, 2011; Rabosky et al., 2012). Despite this, clade age is still

considered to be a valuable explanatory variable of differences in diversity (McPeek & Brown,

2007).

Alternatively, a clade may attain high species richness through high rates of

diversification. Diversification is a result of two processes, extinction and speciation. The

alteration of either extinction or speciation may increase or decrease diversification rates.

Specifically, a decrease in extinction rates and or an increase in speciation rates will result in

increased diversification rates, and vice versa to reduce diversification rates. Uniform-rate

Chapter 3: Regional species richness and trait 3.1 INTRODUCTION evolution in the genus Carex (Cyperaceae) speciation models poorly describe phylogenetic trees (Heard, 1992; Ricklefs, 2003), and evidence for differential speciation and extinction through time is mounting (Jetz et al., 2012,

Rabosky et al., 2013). Accordingly, several explanations for species richness patterns presuming

differences in macroevolutionary rates have been proposed and tested.

Lineage-specific traits or ‘key innovations’ have frequently been invoked to explain

species richness patterns (e.g., nectar spurs, hypocones, sexual dichromatism; Hodges & Arnold,

1995; Hunter, 1998; Seddon et al., 2008). For example, Isaac et al. (2005) found that species

richness in mammals was significantly correlated with length of gestation period and litter size,

where lineages with short gestation periods and large litters were more species-rich. The authors

speculated that these ‘fast’ life histories reduced the likelihood of extinction or increased the rate

of speciation by means of a higher capacity to adapt and higher rates of evolution. However, they

concluded that it would be difficult to unambiguously test this hypothesized mechanism.

Researchers have also proposed that some clades possess high species richness as a result

of ‘ecological opportunity’ (Simpson, 1953; Schluter, 2000; Glor, 2010; Yoder et al., 2010).

Ecological opportunity arises when resources unused by other taxa become available, for

example, after the arrival of a new type of resource, or after the colonization of an isolated area

with a depauperate biota. For example, Hughes and Eastwood (2006) suggested that the plant

genus Lupinus reached rapid diversification rates because of ecological opportunities provided

by the recent uplift of the Andean mountains.

Most recently, workers have proposed that the capacity of lineages to evolve

morphological or ecological novelty may regulate species richness (Lovette et al., 2002;

Adamowicz et al., 2008; Pigliucci 2008, Rabosky et al., 2013). This stems from the observation

that many lineages have failed to diversify after the arrival of new ecological opportunities, or in

Chapter 3: Regional species richness and trait 3.1 INTRODUCTION evolution in the genus Carex (Cyperaceae) other situations where adaptive radiations are predicted (Lovette et al., 2002). In fact, increased morphological or ecological flexibility is implicitly assumed by other well-supported hypotheses

(e.g., key traits of organisms that increase diversity via increased rates of evolution). If species richness is influenced by a group’s ability to evolve trait novelty, a coupling of high rates of trait evolution and high species numbers is predicted on a phylogenetic tree. With the rise in availability of time-calibrated phylogenies, hypotheses regarding diversity-trait evolution dynamics are more easily testable.

A small number of studies have investigated the relationship between morphological evolution and species richness in vertebrates (Adams et al., 2009; Venditti et al., 2011; Rabosky

& Adams, 2012; Rabosky et al., 2013; Rabosky et al., 2014; Zelditch et al., 2015). Using

diversification modelling and phylogenetic comparative methods, these studies tested the

relationship between rates of phenotypic evolution and speciation. They found conflicting

results, where in some groups (plethodontid salamanders, mammals, Scincid lizards, squirrels;

Adams et al., 2009; Venditti et al., 2011; Rabosky et al., 2014, Zelditch et al., 2015) rapid

diversification has occurred with little morphological change (and vice versa) and in others rapid

morphological change was correlated with species richness (plethodontid salamanders, ray-

finned fishes; Rabosky & Adams, 2012; Rabosky et al., 2013). More research on the relationship

between morphological trait evolution and diversity is required, to determine if morphological

lability plays an important role in diversification. Specifically, studies on plant genera are

lacking.

Hypotheses linking trait evolution and species richness are not limited to morphological

traits. The ability of species to rapidly adapt to new environmental conditions (i.e., a novel climate or habitat) may similarly be involved in diversification. In particular, Kozak & Wiens

Chapter 3: Regional species richness and trait 3.1 INTRODUCTION evolution in the genus Carex (Cyperaceae)

(2007) proposed that rapid rates of climatic niche evolution found in tropical clades may be responsible for the high biodiversity observed in the tropics. High rates of climatic niche evolution indicate lineages are able to track changing environments or occupy unfilled niche space. These groups should experience reduced competition and increased ecological opportunities, resulting in reduced extinction or increased speciation (Kozak & Wiens, 2010).

Further studies are required to determine if this mechanism is widespread across regions (e.g., in non-tropical zones) or taxonomic groups.

To understand diversity differences, it is most useful to look to groups that have unusual

taxonomic richness. The genus Carex (sedges; family Cyperaceae) is characterized by a

remarkable number of species (ca. 2100 spp.; Govaerts et al., 2014; Global Carex Group, 2015),

representing almost 40% of diversity in Cyperaceae. This stands in contrast to its sister clade

Scirpeae, containing only 98 species in 9 genera (Léveillé-Bourret et al., 2014). Carex is

distributed globally, except Antarctica, and shows high ecological diversity (deserts to

rainforests; Naczi & Ford, 2008). It is especially diverse in the Northern Hemisphere, where over

20 species can be easily found within a few hectares of a temperate forest (Ball & Reznicek,

2002). While it is highly diverse in temperate zones, it shows low diversity in tropical zones (i.e.,

it possesses a reverse diversity latitudinal gradient). Therefore, the genus Carex presents an

opportunity for study of temperate diversity, which has received less attention than tropical

diversity. Notably, it possesses the longest aneuploid chromosome sequence in living organisms

(n=6-56; Roalson, 2008) due to holocentric chromosomes, a factor which may be involved in

sedge diversification (Escudero et al., 2012b).

Historically, classification of the genus Carex was difficult due to its reduced

morphology (Starr & Ford, 2009). Although its potential as a study taxon for evolutionary

Chapter 3: Regional species richness and trait 3.1 INTRODUCTION evolution in the genus Carex (Cyperaceae) studies has been emphasized, due to high species richness and broad ecological breadth (Starr &

Ford, 2009; Waterway et al., 2009), confusing taxonomy remained a barrier. However, modern

molecular tools have enabled resolution of phylogenetic relationships and revisions of Carex

classifications (Starr & Ford, 2009). Concurrent methodological advances in computational

biology (e.g., ease of diversification rate reconstruction; Garamszegi, 2014), and new

phylogenetic research have enabled study of the evolutionary process in Carex, previously not

possible (Starr & Ford, 2009).

The high species richness in Carex may be a result of either its age or of high rates of

diversification. To determine if diversification processes are at play, one must first rule out the

possibility that clade age accounts for its diversity. The first study attempting to reconstruct

diversification rates in Carex employed a molecular phylogeny and modelled evolution as a

stochastic, time-homogeneous birth-and-death process (Escudero et al., 2012a). It estimated the

age of divergence of its family Cyperaceae at 83.67 My, of the genus Carex at 42.19 My and of its immediate sister clade Scirpeae at 62.0 My. Escudero et al. (2012a) also found a 1.5 times increase in the net rate of diversification at the crown node of Carex over the background rate for

Cyperaceae. This rate was higher than average for angiosperms (Valente et al., 2010). In a

subsequent study, Escudero & Hipp (2013) found that within Cyperaceae, clade age explains a

significant proportion of the disparity in species richness (ca. 33% of among-clade variation in

species richness). However, the authors emphasized the threefold increase in net diversification

rate in the Cariceae clade (which includes Carex) over the background rate for Cyperaceae is not

congruent with differences in clade age alone. When species numbers and ages are considered

throughout Cyperaceae (diverging in the Eocene; clades at the tribe level), clades attain modest

species numbers of 1 to 550, with the exception of tribe Cypereae, the second most diverse tribe

Chapter 3: Regional species richness and trait 3.1 INTRODUCTION evolution in the genus Carex (Cyperaceae) at 1117 species, about 700 of which belong to the genus Cyperus (Escudero & Hipp, 2013).

Carex stands out with species numbers more than double that of other genera its age. These

diversification rate reconstruction results and species number comparisons (Escudero et al.,

2012a; Escudero & Hipp, 2013) suggest that the diversity of Carex cannot be attributed to its

age.

No apparent key innovations or ecological opportunities exist to explain the high

diversity found in Carex (Gehrke & Linder, 2011). Escudero et al. (2012a) speculated that

adaptive radiation following a climatic shift, aided by rapid chromosome evolution, may explain

the latitudinal pattern of species richness in Carex. Yet, the temporal correspondence of a shift in

diversification rates, a global cooling period and a chromosome number transition is limited

evidence to explain patterns of sedge species richness. Further investigation of the response of

Carex to evolving climates, and the effects on its species richness, is required.

The high number of species found in the genus Carex has been linked to its ability to

occupy a wide range of habitats (Bell et al., 2000; Gehrke & Linder, 2011). In a study using

generalized linear models to predict Carex species richness in African sky islands (Gehrke &

Linder, 2011), habitat heterogeneity was the best predictor (with lineage age and geographic distribution) of lineage size. The authors subsequently posed the question, are ecological or habitat factors influencing sedge diversity? Because of high clade conservatism of habitat and the lack of power of any single habitat factor in the models, they concluded that their results showed no support for ecological speciation (i.e., speciation via filling of different niches).

Rather, they suspected that if allopatric or ecological speciation is acting in Carex, niche expansion may obscure any evidence. A phylogenetic approach is needed to uncover indications of ecological speciation processes. Carex is also notable for its frequent niche segregation along

Chapter 3: Regional species richness and trait 3.1 INTRODUCTION evolution in the genus Carex (Cyperaceae) environmental gradients (Vellend et al., 2000; Dabros & Waterway, 2008; Waterway et al.,

2009). The genus’ ability to finely partition niche space leads to the hypothesis that niche

differentiation (i.e., ecological speciation) and the traversing of niche space via niche evolution

may be important to the diversification process in sedges. This positions the group as an ideal

candidate for niche evolution research. Further study on broader taxonomic and geographic

scales with more complete sampling and more robust methods (e.g., take phylogeny into

account) are needed in Carex.

The biogeographic and ecological context of diversification processes is important to

consider when seeking explanations for diversity outcomes (Harmon & Harrison, 2015). For

example, dispersal limitation (Hubbell, 2001; Ozinga et al., 2005), environmental heterogeneity

(recall Gehrke & Linder, 2011; Hortal et al., 2009 and references therein) and habitat change

influence diversity in space and these factors vary among regions. Furthermore, the size of the

region in which a clade diversifies may have an effect on clade diversity (Ricklefs, 2006;

Ricklefs et al., 2007).

The existence of ecological limits or diversity carrying capacities on species richness at the continental scale has been the subject of recent debate (Harmon & Harrison, 2015; Rabosky

& Hurlbert, 2015). Consistently observed resource-species richness relationships, the stationarity of species numbers throughout time, and the predictable responses of species richness to mass extinctions, key innovations and other disturbances have been used as evidence for limits to

diversity at the continental level. If true, the number of Carex species on continents of its distribution may have upper limits and speciation processes may be diversity-dependent. This may confound attempts to investigate the generation of species richness patterns on a cross- continental scale.

Chapter 3: Regional species richness and trait 3.1 INTRODUCTION evolution in the genus Carex (Cyperaceae)

Conversely, Harmon & Harrison (2015) maintain that no limits exist to diversity at the continental level and that continental communities are highly dynamic, unsaturated entities. Yet, attributes of the continent such as dispersal limitation, resource pulses or other habitat changes, and habitat heterogeneity, nonetheless influence the filling of niche space (Harmon & Harrison,

2015). Therefore, the region in which a clade has diversified may influence its richness. By restricting a study of species richness and its correlates to a singular continental region, any impacts of niche filling on diversification processes are eliminated. Despite the increasing recognition of the importance of the regional-level processes, few authors have considered

diversification at this scale (Ricklefs, 2008).

This study focuses on the observed yet unexplained high species richness found in the

genus Carex. It investigates the relationship between rates of morphological and ecological trait

evolution (i.e., trait lability) and species richness. However, it restricts itself to a North American

north of Mexico sampling, to avoid the influence of niche filling or other pan-regional factors. It

hypothesizes that greater trait lability has led to increased Carex diversity, in a North American

context. Therefore, it predicts a positive relationship between rates of trait evolution and species

numbers, when comparing species groups within Carex. A species phylogeny is constructed for

almost all North American Carex species (477 of 482 excluding subspecies designations, tallied

from the FNA online; Ball & Reznicek, 2002) and rates of trait evolution are calculated. These

are correlated against species numbers in a non-nested species group comparison framework.

Chapter 3: Regional species richness and trait 3.2 METHODS evolution in the genus Carex (Cyperaceae)

3.2 METHODS

3.2.1 Trait definitions

For the purpose of this study, niche is defined as the set of attributes of the area occupied

by a species across its geographic range, influencing its growth rate (the ‘Grinnellian’ niche;

Grinnell, 1917; Soberón, 2007; Peterson, 2011). This definition, however, does not include

attributes that are affected by or modified by the presence of the species (e.g., biotic interactions)

and is strictly a property of the environment (Peterson, 2011). Furthermore, it does not

encompass the set of conditions under which a species can persist, only those under which it

currently exists (the realized niche; Hutchinson, 1957).

A species’ Grinnellian niche differs from morphological traits by its noninteractive,

nonlinked quality (Peterson, 2011). Morphological traits are defined as the structures of

organisms, which can change in response to their environment and are properties of the species.

In this study, trait is defined as a broad term encompassing both species’ morphological and

ecological attributes.

3.2.2 Flora of North America region

This study is focused on the Carex of the Flora of North America region (Canada, USA

& Greenland; FNA). This restriction of geographic scope not only reduces the effects of niche

filling, dispersal limitation, environmental heterogeneity and habitat change as outlined in the

Introduction, but also ensures good data availability and quality, as climatic and habitat data are

more extensive and precise for FNA Carex than for species found elsewhere on earth (e.g., GBIF

and WorldClim, habitat databases). Furthermore, by comparison to Carex floras worldwide,

Chapter 3: Regional species richness and trait 3.2 METHODS evolution in the genus Carex (Cyperaceae) these sedges are taxonomically well known (Ball & Reznicek, 2002), thoroughly collected and precisely geolocated. Therefore, the sedges of the FNA region offer one of the best opportunities to explore the effects of climactic niche and character evolution on the species richness of a major clade.

3.2.3 Phylogeny

3.2.3.1 Taxon sampling

All genomic DNA samples were extracted by Chouinard (2010) from herbarium

specimens acquired on loan from various herbaria across North America (see appendix of

Chouinard 2010 for voucher details). The FNA was used as a checklist for Carex species

sampling, with as many as 70 specimens received on loan and 22 specimens sampled per taxon

(only one specimen was used per species in the final analysis). A maximum of 3 cm x 1 cm of

leaf tissue was extracted from the specimens, preferentially drawn from recently collected plants

whose leaves were dried in silica gel. DNA extraction by Chouinard (2010) followed the silica-

column method of Alexander et al. (2007) with modifications to increase the yield and

effectiveness of DNA amplification on old or difficult herbarium specimens.

3.2.3.2 Molecular markers

Phylogenetic relationships for 477 Carex species treated in the FNA (Ball & Reznicek,

2002) were reconstructed using the chloroplast markers matK (coding) and rps16 (non-coding

intron) and the nuclear ribosomal non-coding sequences ITS and ETS.

Maturase K (matK) is a gene positioned in the intron of the lysine trnK gene (Zoschke et al., 2009). The protein it encodes may be involved in the splicing of the trnK precursor, and

Chapter 3: Regional species richness and trait 3.2 METHODS evolution in the genus Carex (Cyperaceae) further tasks are hypothesized, as it is retained in several parasitic plants and ferns that have lost trnK (Zoschke et al., 2009). It is a highly variable gene and as a result is an effective angiosperm

barcoding region (Yu et al., 2011; and in Carex; Starr et al., 2009). The rps16 marker is an

intron positioned inside of the ribosomal protein 16 encoding gene. It is often used in plant

barcoding and is flanked by two rps16 exons (Oxelman et al., 1997).

To avoid relying on uniparentally inherited regions, such as the maternally inherited chloroplast, two nuclear markers were selected for amplification and sequencing. The intergenic transcribed spacer (ITS) region of the 18S–26S nuclear ribosomal cistron is a commonly used marker for plant phylogenetic inference (Alvarez & Wendal, 2003). It is composed of the

internal transcribed spacer region 1 (ITS1), the 5.8S gene, and the internal transcribed spacer

region 2 (ITS2), all three of which were captured by the ITS primers used. The external

transcribed spacer (ETS), found in the same rDNA region, is often more phylogenetically

informative than the ITS region, but not widely used due to difficulties in primer design

(Logacheva et al., 2010). Fortunately, ETS primers have been designed for use in Cyperaceae

(Starr et al., 2003).

All four markers have been shown to be effective tools for reconstructing lower-level

phylogenies in Carex (Starr et al., 2003; Starr et al., 2009). Primers used can be found in Table

3.1.

3.2.3.3 DNA amplification and sequencing

The matK region was amplified as detailed in Chouinard (2010). Most matK sequencing

took place at the Canadian Centre for DNA Barcoding following the Centre’s sequencing

Chapter 3: Regional species richness and trait 3.2 METHODS evolution in the genus Carex (Cyperaceae) protocol (Ivanova & Grainger, 2009) and the remainder was sequenced at the Canadian Museum of Nature (CMN) using the method described in Chouinard (2010).

Sequencing of the rps16 region was performed at the CMN using the protocol described

by Chouinard (2010; additionally described by Gilmour et al., 2013 and Starr et al., 2015).

However, the following modifications were made to quantities of PCR reagents used: 0.3mM of

each dNTP, 22.5mM MgCl2, 10–50 ng of template DNA, and 0.3 units of HotStart Taq DNA

polymerase (BioShop Canada Incorporated). Furthermore, the amplification cycle program was

modified: 94°C for 120s for initial denaturing; 35 cycles of 94°C for 60s for denaturing, 46°C for

60s for primer annealing and 72°C for 4min for primer extension, followed by a final extension

of 72°C for 7min at the end of cycling. Amplification products were purified using an

Exonuclease I and Shrimp Alkaline Phosphatase protocol (MJS Biolynx Inc., Canada) and

sequenced using an ABI Prism Big Dye Terminator Kit (Applied Biosystems). Sequence data

were edited in Sequencher 5.2 (Gene Codes Corporation, Ann Arbor, MI, USA).

Both ITS and ETS regions were amplified and sequenced at the Morton Arboretum, Lisle

Illinois USA according to the molecular methods described in Hipp et al. (2006). Sequences

were obtained on a 3730 DNA Analyzer (ThermoFisher Scientific).

3.2.3.4 Sequence selection

Multiple specimens per species were sequenced by Chouinard (2010; matK sequencing)

and by the authors of this study for rps16, ITS and ETS. However, due to limits of computing power and time on the final 477 species 4 marker phylogenetic analysis and the requirement for a high quality result, the molecular dataset was limited to one specimen per species (excluding

subspecies and varieties).

Chapter 3: Regional species richness and trait 3.2 METHODS evolution in the genus Carex (Cyperaceae)

The most representative individuals for each species were determined via a preliminary

Maximum Likelihood (ML) analysis as follows. Separate trees were estimated for each marker

(four ML trees in total) using all sequences collected. RAxML v7.3.4 (Randomized Axelerated

Maximum Likelihood; Stamatakis, 2006) and its rapid bootstrapping algorithm was employed to generate 200 bootstrap trees per analysis using a GTRCAT model of evolution (General Time

Reversible model of nucleotide substitution under the Gamma model of rate heterogeneity;

GTRCAT is an approximation of GTRGAMMA that reduces computation time; Stamatakis,

2006). RAxML offers fast inference of large phylogenies implemented in a parallel program with

low memory usage (Stamatakis, 2006; Stamatakis et al., 2008).

Subsequently, the ML gene trees were used to guide the selection of individuals, based on

the following criteria: (1) individuals must have been clustered with other individuals of the

same species or closely related species in all four trees (i.e., no questionable individuals or

relationships were accepted), (2) individuals with sequences available for all four markers were

preferred, (3) when all else was equal (i.e., individuals were found at the same place in all trees

and the same amount of DNA existed), selection was random. The ML trees and individuals

chosen for final analysis can be found in Appendix 4 and Appendix 2. Finally, the program

RogueNaRok (Aberer et al., 2013) was used to ensure no rogue taxa (i.e. possible

misidentifications or contaminations) were included in the final molecular dataset. RogueNaRok

uses a graph-based algorithm to assess the improvement (consensus support) of removing subsets

of taxa from a set of trees. The gene trees were used in the web-based RogueNaRok platform

(rnr.h-its.org).

Not all individuals in the analysis could be sequenced for all four markers.

Approximately 15% percent of the data was missing in the analysis.

Chapter 3: Regional species richness and trait 3.2 METHODS evolution in the genus Carex (Cyperaceae)

3.2.3.5 Outgroup species

The species Trichophorum alpinum and T. cespitosum were selected as outgroup taxa as

they represent both major lineages discovered within the sister clade to Cariceae (which includes

the genus Carex) in a recent phylogeny (Léveillé-Bourret et al., 2014). Voucher data for these

outgroups are given in Appendix 2. Outgroups were used to ensure certainty of the reconstructed

age and position of the ingroup.

3.2.3.6 Sequence alignment

Sequences were aligned with the multiple sequence alignment program MUSCLE v3.5

(Edgar, 2004). MUSCLE uses an iterative refinement algorithm that performs more accurately

and more quickly than the commonly used program CLUSTALW (Pais et al., 2014). Although it

is less accurate than the consistency-based programs T-Coffee and MAFFT, it has superior speed

and memory usage (Edgar & Batzoglous, 2006; Pais et al., 2014) making it the most suitable

program for aligning the 479 sequence dataset used in this analysis. Each set of sequences (four

sets; matK, rps16, ITS, ETS) were aligned separately using the default parameters in MUSCLE.

The aligned sequence datasets were then concatenated into a single matrix. Although

some individuals were missing sequences for one or more regions due to amplification or other

difficulties (15% data was missing), this likely did not reduce the utility of the alignment.

PartitionFinder v1.1.1 (Lanfear et al., 2012) was used to determine optimal models of evolution

and the optimal partitioning scheme for the supermatrix. BEAST (Bayesian Evolutionary

Analysis Sampling Trees; Drummond and Rambaut, 2007) model options were selected and the

Chapter 3: Regional species richness and trait 3.2 METHODS evolution in the genus Carex (Cyperaceae)

AICc (corrected Akaike Information Criterion; Akaike, 1973) was used to evaluate candidate partitioning schemes. Results were used to set parameters of the phylogenetic analysis.

3.2.3.7 Phylogenetic inference

Model-based phylogenetic methods were preferred due to their improved consistency and reliability, over parsimony and distance-based methods (Felsenstein, 2004). Therefore,

Maximum Likelihood (ML) and Bayesian approaches were evaluated for suitability.

Phylogenetic comparative methods (e.g., estimation rates of trait evolution) have been developed to operate on ultrametric phylogenies (Garamszegi, 2014). Rather than creating an ultrametric tree from an additive ML tree using post-analysis branch length transformation, a

Bayesian analysis was preferred. Using Bayesian inference, a molecular clock can be specified and an ultrametric tree can be estimated directly. Specifically, BEAST (Bayesian Evolutionary

Analysis Sampling Trees) was the best choice due to its ability to process large alignments

(Drummond and Rambaut, 2007). BEAST is a program that uses Markov chain Monte Carlo

(MCMC) algorithms for Bayesian phylogenetic analysis and divergence time dating (Drummond and Rambaut, 2007).

PartitionFinder results recommended a three subset partitioning scheme (ITS, ETS, matK+rps16) under GTR+I+G substitution models. Ultrametric phylogenies were generated using BEAST v1.8.2 under an uncorrelated lognormal relaxed clock with a Yule speciation process tree prior, under the above partitioning scheme. Model parameter and statistic priors were left at default values, except the prior distribution of the ingroup Carex which was assigned a normal distribution of mean 35 and standard deviation 5. The dating of this prior was based on two fossil-based date estimations from previous studies (contra. phylogeny-based date estimates

Chapter 3: Regional species richness and trait 3.2 METHODS evolution in the genus Carex (Cyperaceae) presented in the introduction): Cyperaceae was estimated to have diverged at 47 My by Iles et al.

(2015) and Carex was estimated to have been widespread by the early Miocene (ca. 23 My;

Smith et al., 2010). Two chains were run in BEAST, each with 100 million generations and

sampling at every 10 000 states. Chain convergence was visually assessed in Tracer v1.6. The

first 40 million states were discarded as burn-in and the two runs were combined in

TreeAnnotator v1.8.2.

3.2.4 Trait data

Morphological data were extracted from the recent treatment of Carex for the Flora of

North America online (FNA; Ball & Reznicek, 2002). Authors of FNA treatments describe species using only mature specimens, and encompass the range of morphological plasticity they see in a species by describing characters using ranges of measurements. Numerical data following key words (e.g., ‘culm’, ‘leaves’) were parsed in R using custom-built scripts. This strategy yielded more detailed data than another method tested (beta testing of the Taxon

Concept Explorer flora tool at etc.cs.umb.edu/etcsite). The data were collapsed for subspecies and varieties to match the molecular dataset. Occasionally, data were only available as relative measurements (e.g., inflorescences 0.46-0.94(-0.99) of culm height 10-55 cm), in which case

they were transformed into absolute measurements (4.6-51.7(-54.45) cm). When character data

were missing, measurements were extracted from FNA sectional descriptions or from

Mackenzie’s Flora (1931-1935). Using these resources, data for five characters (culm height, leaf blade width, perigynia length, perigynia width and achene length; Fig. 1.1) were available for over 90% of species. Despite the presence of inflorescence length and spike descriptions in the

FNA online, data were not reported consistently by FNA contributors and therefore could not be

Chapter 3: Regional species richness and trait 3.2 METHODS evolution in the genus Carex (Cyperaceae) used in this study. The data were verified manually in Excel to ensure measurements were

reasonable (i.e., to identify outliers).

Water and light tolerance were used as habitat predictors. Water habitat was taken from the updated National Wetland Plant List (NWPL; Lichvar, 2012) which provides wetness scores from 1 to 5 for 350 FNA Carex species. Species missing from the NWPL database, as well as

light affinity for all species, was scored de novo by professionals familiar with North American

taxa (J. Starr, University of Ottawa and A. Hipp, Morton Arboretum). Scoring was completed

individually by JS and AH with scoring disagreements resolved by averaging. Light preference

was scored from 1 to 3, with 3 as shade tolerant and 1 for open canopy.

Georeferenced specimen locality data for all species in the study were collected via the

Global Biodiversity Information Facility (GBIF; www.gbif.org) from participating collections databases. Occurrence data can be removed or uploaded to GBIF by participating institutions at any time. Therefore, to ensure the capture of the highest quantity of specimen data possible, data were downloaded at three time points using the gbif function in the dismo package for R (from

16 May to 28 May 2013, 13 January 2014 and 3 July 2014). These data were then merged,

yielding one to 216,475 occurrences per Carex species. GBIF data were mapped in R and maps were visually assessed for outliers (e.g., to identify any points in the ocean or lat long reversals).

Duplicates and imprecise records were removed (either latitude or longitude had one decimal place or less). Next, climate data were extracted from the WorldClim climate database

(worldclim.org/bioclim; Hijmans et al., 2005) using the getData function in dismo. Each GBIF

locality record produced one set of BIOCLIM variables (19 in total). For each species, these

BIOCLIM data were averaged to obtain one mean and one standard deviation measure for each

of 19 BIOCLIM variables (19 means and 19 SDs for all species).

Chapter 3: Regional species richness and trait 3.2 METHODS evolution in the genus Carex (Cyperaceae)

Principal component analysis (PCA) was used to obtain two variables (PC1, PC2) for 19

BIOCLIM variables and for 5 morphological variables. PCA allows a broader description of

morphology and climatic niche in fewer uncorrelated variables. The function prcomp in the R

stats package was used to generate principal components that were rotated, centered and scaled.

3.2.5 Trait evolution

Phylogenetic comparative methods (PCMs) aim to determine correlates and causes of

species trait evolution and diversification. They allow for the acknowledgement of non-

independence of species due to shared ancestry (Felsenstein, 1985; Harvey & Pagel, 1991).

PCMs have been advocated as promising approaches to understanding evolutionary processes at

the macroevolutionary scale (Pigliucci, 2008).

Rates of evolution are estimated in PCMs by fitting models of evolutionary process to

trees. There are two models of evolution used widely in the literature; the Brownian motion

(BM) process (Felsenstein, 1985) and the Ornstein-Uhlenbeck (OU) process (Hansen, 1997;

Butler & King, 2004; Hansen et al., 2008). BM models evolution as a random-walk constant

variance process, while OU evolves towards an adaptive optimum. Model selection (AIC and

likelihood) using the fitContinuous function in the R package geiger (Harmon et al., 2008) was

used to identify which process (BM or OU) fit the Carex data best.

Numerous packages and programs exist for the estimation of evolutionary rates. Most

notably, the packages geiger and phytools (Revell, 2012) fit models (BM, OU or others) for

continuous character evolution and return parameter estimates (i.e., rates). The package ape

(Paradis et al., 2004) also provides tools to simulate continuous character evolution. For this

study, the functions extract.clade (ape package), paintSubTree and brownie.lite (phytools

Chapter 3: Regional species richness and trait 3.2 METHODS evolution in the genus Carex (Cyperaceae) package) were used to extract rate estimates. The precise usage of these functions is detailed below. When trait data did not match phylogeny tips (e.g., trait data was missing for a particular species), the tip was dropped for the analysis. Therefore, the number of species in each of the six trait evolution analyses (morphology PC1, morphology PC2, climatic niche PC1, climatic niche

PC2, wetness habitat, light habitat) was different.

3.2.6 Sister clade comparison

Sister clade contrasts test the effects of a trait on diversification, while eliminating effects

of clade age and relatedness (Barraclough et al., 1998). They are used widely in comparative studies of diversity (Rabosky, 2009). Using species richness as a proxy for diversity, a sister taxa analysis was used to identify if a relationship exists between rates of trait evolution and sedge species richness. Non-nested sister clades (or nodes) were compared, so that each species was included in the analysis only once.

Using a custom script in R, sister clade contrasts were automatically selected for use in the analysis. The script operated on parent nodes (the ancestor of sisters to be compared, identified in red in Fig. 3.1). Parent nodes must have met the following criteria to be selected: (1)

each descendant node has three species or more, and (2) the node has not already been selected,

to maintain non-nestedness of contrasts. Rates of trait evolution could not be calculated with one

descendant species, and with two descendant species the error on the rate calculation was

unacceptably high. The script tested parent nodes on the tree randomly, starting with zero parent

nodes, and adding successive parent nodes as they met the criteria. Once a full set of contrasts

was established (i.e., the tree was exhaustively searched for potential contrasts and no more

could meet the criteria), the set was saved and the search was repeated. In total, this search was

Chapter 3: Regional species richness and trait 3.2 METHODS evolution in the genus Carex (Cyperaceae) conducted 10 000 times, each starting with a different and random parent node. Out of the 10

000 potential sets of sister contrasts, the sets with the highest number of parent nodes were identified (maximization of the number of non-nested contrasts). Ten of these sets, rather than one set, were selected for further analysis to increase the power of subsequent analyses. For a visualization of one set of contrasts, see Figure 3.1.

Within each set, extract.clade was used at parent nodes to obtain clades containing only

the two sister groups of interest (i.e., clades were extracted at the parent node in red Fig. 3.1).

Next, paintSubTree mapped two different states on the clade, each corresponding to an arbitrary sister group state (either 1 or 2). The function brownie.lite was used to estimate rates of

Brownian motion trait evolution in states 1 and 2. Subsequently, the ratio of the two rates of trait

evolution was calculated and log transformed. The ratio of species richness (i.e., number of

species) per sister group was also calculated and log transformed. A sample of these calculations

can be seen in Figure 3.1. A regression analysis of the log transformed rates of trait evolution

and the number of species per comparison, was performed for each set of ten contrasts. An r2 and

a slope were computed for each, yielding ten r2 and ten slopes. The average r2 and slope were

calculated.

To determine significance of trait evolution rate and species richness correlations, the

regression analysis was conducted with 100 simulated datasets in place of real trait data (i.e., to

develop a null distribution). Continuous characters were simulated on the tree using the package

phytools (Revell, 2012). Namely, the function fastBM was used to simulate random character

states, according to a specified rate of trait evolution. The rate used was the mean rate of trait

evolution from all characters (morphology PC1, morphology PC2, wetness habitat, light habitat,

climatic niche PC1, climatic niche PC2). A relationship between trait evolution rate and species

Chapter 3: Regional species richness and trait 3.2 METHODS evolution in the genus Carex (Cyperaceae) richness was considered significant if its mean r2 and its mean slope were greater than 95% of simulated data regression statistics.

Chapter 3: Regional species richness and trait 3.3 RESULTS evolution in the genus Carex (Cyperaceae)

3.3 RESULTS

3.3.1 Phylogeny

The final four marker (ETS, ITS matK, rps16) molecular dataset consisted of 477 Carex

species, two outgroup species, 3415 aligned base pairs and contained 2044 unique patterns. The

final phylogeny ranged in Bayesian posterior support from 0.9 to 1.

Results from previous phylogenetic analyses of Carex species have found that three

major lineages exist in North American Carex (Starr et al., 2015, Global Carex Group, 2015), termed the Core Carex Clade, the Vignea Clade and the Core Unispicate Clade. While the Core

Carex Clade and the Vignea Clade have received strong support from previous reconstructions,

the Core Unispicate Clade has been poorly supported (Starr et al., 2015). This study’s results

show the Core Unispicate Clade group nested within Vignea and Core Carex (Fig. 3.2), adding to

inconsistencies seen among studies as to the position of the three clades (Global Carex Group,

2015). While this is an important phylogenetic result, the placement of major lineages has no

effect on the results of trait evolution analyses.

This study compares species numbers of sister groups. Therefore, achieving high quality

resolution of lower-level (e.g., species or sectional-level) relationships is necessary. With the

exception of a select number of species (Carex heterostachya, C. fuliginosa, C. edwardsiana, C.

squarrosa, C. typhina), species followed sectional classifications and expected relationships (Fig.

3.2).

Chapter 3: Regional species richness and trait 3.3 RESULTS evolution in the genus Carex (Cyperaceae)

3.3.2 Trait data

Principal component 1 (PC1) of the BIOCLIM climate variable PCA explained 42% of

total variance and PC2 explained 28% of variance (PC1+PC2=70%). PC3 and PC4 explained

more than one variable’s worth of information (PC3=16%, PC4=7%; >5.3%). However, they

were not included further in trait analyses due to the marked drop in the percentage of explained

variation (28% to 16%). Temperatures of cold and dry periods contributed most to PC1, followed

by contributions from annual mean temperature, annual precipitation and precipitation of wet periods (Table 3.2). PC2 was loaded most strongly by precipitation of the warmest quarter and precipitation seasonality, as well as precipitation of dry periods and temperature seasonality and annual range. Seventeen of 19 BIOCLIM variables contributed strongly to PC1 or PC2, leaving mean diurnal range and maximum temperature of warmest month, both of which contributed to

PC3.

Morphology PC1 explained 49% of variance and PC2 explained 19% of variance. No other PC explained a large portion of variance. Reproductive characters (achene and perigynia descriptors) contributed most strongly to PC1 and vegetative characters (culm and leaf descriptors) contributed strongly to PC2 (Table 3.3). Therefore, morphology PC1 can be

interpreted as reproductive and morphology PC2 as vegetative.

3.3.3 Trait evolution

The regression between log transformed species richness ratios and log transformed trait

evolution ratios for 100 simulated continuous character datasets was consistently weak (mean r2 of 100 simulated data sets=0.034, median r2=0.024). The slopes of the same regressions were weak (mean slope of 100 simulated data sets=0.169, median slope= 0.142), but positive in the

Chapter 3: Regional species richness and trait 3.3 RESULTS evolution in the genus Carex (Cyperaceae) majority of cases. Regressions with real trait evolution data can be compared to these null distributions to establish significance (Fig. 3.3).

Significant correlations between rates of trait evolution and species richness numbers (log transformed) between sister groups were recovered for 5 of 6 traits at the 0.05 level. They were, in decreasing order of correlation strength, morphology PC1, climatic niche PC2, climatic niche

PC1, light habitat and wetness habitat (Fig. 3.4). Only one trait, morphology PC2, did not show a correlation more extreme than 95% of simulations. Mean r2 values ranged from 0.07 to 0.24 and

slopes from 0.32 to 2.46.

The distribution of trait diversity through time and throughout the Carex species

phylogeny can be visualized in ancestral state reconstructions in Figures A3.1 to A3.3, found in

the Appendices. While these plots do not measure trait evolution directly, or test a specific

question, they show how diversity is distributed throughout Carex clades in North America, from

a phylogenetic perspective. The plots show that in some clades, traits are well conserved (best

seen in habitat, Fig. A3.2), while in equally as many, traits are diverse. In morphology and in climatic niche (Figures A3.1 and A3.3), extreme trait values obscure conservatism or divergence patterns.

Chapter 3: Regional species richness and trait 3.4 DISCUSSION evolution in the genus Carex (Cyperaceae)

3.4 DISCUSSION

An explanation for differences in species richness across the tree of life continues to

elude evolutionary biologists. Several hypotheses have been proposed to explain this pattern,

coining new terms such as ‘key innovations’ or ‘ecological opportunities’. Recently, it has been

proposed that increased capacities to produce novel morphologies or to occupy novel ecological

niches, measured via higher rates of morphological and ecological trait evolution, may promote

speciation. This study examined the relationship between species richness and rates of character

evolution in North American Carex, north of Mexico (Fig. 2.1). Within the genus, higher rates of

reproductive morphology, habitat and climatic niche evolution lead to greater species numbers

when comparing sister groups on a logarithmic scale (Fig. 2.4). This supports the hypothesis that

greater trait lability has increased Carex species diversity in North America.

Only one trait examined, vegetative morphology, did not show a significant correlation

with species richness differences (Fig. 2.4). This is not surprising, as vegetative characters in

Carex show much less variation than reproductive characters (Metcalfe, 1969 & 1971; Reznicek,

1990). Furthermore, it has been suggested that vegetative traits diverge less rapidly than floral

traits in angiosperms (Grant, 1949). This hypothesis has been supported by a study showing that

the relationship between molecular change and vegetative morphology is weaker than the

relationship between molecular change and reproductive morphology (Barraclough &

Savolainen, 2001). In Carex of eastern Asia, vegetative morphology is more diverse than in

North American species (Starr et al., 2015) yet species richness is reduced.

The strongest significant correlation was found between species richness and reproductive morphology (Fig. 2.4). Rates of reproductive morphology evolution explained 24%

Chapter 3: Regional species richness and trait 3.4 DISCUSSION evolution in the genus Carex (Cyperaceae) of differences in species numbers (or vice versa). The next strongest correlation was found with climatic niche PC2 (mean r2=0.16). Subsequent significant correlations had similar mean r2

values (r2=0.10-0.11). Unfortunately, the processes leading to significant correlations have not

been investigated by this study. Therefore, it is only possible to speculate on the reasons for

differences in correlation magnitudes. A possible hypothesis for why reproductive morphology is

most strongly correlated with species richness, is that it is better able to establish reproductive

isolation, leading to more rapid speciation. Reproductive isolation can be accomplished through

mechanical incompatibilities of reproductive morphology, and this is often observed in plant

genera (Rieseberg & Willis, 2007). Although the reproductive traits examined here (perigynia

and achenes) are not responsible for sedge fertilization, they represent a proxy for such

structures. Furthermore, the importance of perigynia morphology in sedge identification

(perigynium is the most important diagnostic structure; Starr, pers. comm.) lends support to this

hypothesis. Diversity of perigynia morphology is a result of the multitude of dispersal

mechanisms, including wind, water and zoochory (attachment to animals, ingestion by animals,

ants, birds, and mammals; Egorova, 1999; Handel, 1978). Further research would be required to

determine if the incompatibility of reproductive morphologies is aiding to increase speciation in

Carex.

A rate of trait evolution can be interpreted in multiple ways. The most obvious

interpretation is that the rate represents the speed at which traits change on a tree. But it is also a

phylogenetically corrected measure of trait disparity (O’Meara et al., 2006), sometimes termed

the amount of ‘morphospace’ or ‘niche space’ occupied (Hutcheon & Garland, 2004). Hence,

finding higher rates of trait evolution associated with higher species numbers implies that in

North America, Carex species groups with greater morphological and ecological diversity are

Chapter 3: Regional species richness and trait 3.4 DISCUSSION evolution in the genus Carex (Cyperaceae) more species-rich. These results not only bolster the hypothesis for trait flexibility’s effect on speciation, but also provide an explanation for diversity differences within genera inhabiting

identical geographic regions (i.e., conditions under which one would not expect to find

substantial differences in diversity).

As previously described, Carex has been found to be frequently involved in niche partitioning along environmental gradients (Waterway et al., 2009) and support has been found

for an important role of habitat heterogeneity in the generation of sedge species richness (Gehrke

& Linder, 2011). This study addresses ecological diversity and species richness in Carex not as

previous studies have before (from a phylogenetic descriptive or statistical point of view), but

from a phylogenetic data modelling framework. Using a larger sampling than any previous

study, this work finds further support for an integral role of ecological disparity in the generation

of sedge species richness.

If one considers the results from an evolutionary perspective, as this study was originally

designed, a number of alternative hypotheses may explain the results obtained. Because causality

cannot be established from correlation, it is possible that trait evolution does not result in

increased species richness. Rather, high rates of speciation, resulting in high species richness,

may increase trait disparity through time (Rabosky & Adams, 2012). Additionally, a

hypothesized phenomenon known as ‘punctuated equilibrium’ may explain the results, where

rapid speciation leads to rapid morphological change (Eldredge & Gould, 1972; Stanley, 1975).

A longstanding challenge in the study of extant biodiversity has been how to statistically

establish causality. Unfortunately, most phylogenetic comparative methods do not address

causality (Paradis, 2014), and those that do are still under development (e.g., the application of

path analysis to phylogenetic analyses; Gonzalez-Voyer & von Hardenberg, 2014). To rule out

Chapter 3: Regional species richness and trait 3.4 DISCUSSION evolution in the genus Carex (Cyperaceae) alternative hypotheses that may explain the results of this study, application of a method establishing causality is required.

The correlation of high trait disparity through time and species richness has not been consistently observed across taxonomic groups. In a study of globally distributed squirrels,

Zelditch et al. (2015) found that patterns of diversification, measured by rates of speciation and species richness, were uncorrelated with morphological disparity. However, the authors state that their finding of young, homogenous clades and older, more morphological disparate clades may be in part a result of the disparate environments they inhabit and their phylogenetic community

structure. Alternatively, they hypothesize that phenotypic evolution is governed by ecology and

speciation processes by geography. They dispute that trait evolution leads to speciation and state

that the coincidence of geographic and adaptive landscapes may explain reported positive

correlations (Rabosky & Adams, 2012; Rabosky et al., 2013). When these landscapes do not

coincide, the authors explain that results such as theirs will be found. The geographic sampling

of this study reduces the effect of geography on speciation. Therefore, the results do not reject

the proposed ideas of Zelditch et al. (2015). Instead, the findings of this study support the idea

that trait lability and trait disparity may be important in generating species richness at the

regional (continental) scale. It is possible that at larger than regional scales (e.g., at the global

scale), higher operating processes such as the influences of geographic landscapes, influence

speciation most.

Carex is more diverse than other temperate angiosperms, and this may be due to higher

overall rates of trait evolution. But what is the mechanism underpinning rapid trait evolution in

Carex? One hypothesis is that its holocentric chromosomes allow for accelerated genetic change.

Holocentric chromosomes are a unique property of sedges and few others (Hipp et al., 2010).

Chapter 3: Regional species richness and trait 3.4 DISCUSSION evolution in the genus Carex (Cyperaceae)

Centromeres in holocentric chromosomes are diffuse and kinetochore activity is distributed along the whole chromosome. This allows for extraordinary chromosome number variation (n=6-

56; Davies, 1956) and frequent chromosomal rearrangements (Luceño & Castroviejo, 1991;

Hipp et al., 2010; Escudero et al., 2010; Chung et al., 2011). Chromosome number variation can

affect total recombination rates (Bell, 1982; Nokkala et al., 2004; Escudero et al., 2012b) and the

rate of gene flow among populations of closely related species (Whitkus, 1988; Hipp et al.,

2010). Furthermore, reproductive isolation provided by genetic differentiation and chromosome

number transitions in Carex may lead to speciation (Hipp et al., 2010; Escudero et al., 2012a).

These may be adaptive properties, leading to fast colonization of new ecological niches and

adaptation of morphologies. Further research should attempt to integrate chromosomal data into

diversification analyses.

The results of Chapter 2 demonstrated that acquiring highly accurate distribution data

may not be necessary for accurate climatic niche estimates and phylogenetic comparative

analyses. Therefore, the methods used in this study (Chapter 3) to estimate climatic niche (i.e.,

the use of GBIF occurrence data), are justified. While the effects of errors in climatic niche

estimates on results are understood, it remains unclear how differences in habitat scoring may

affect results. Scoring of traits is a method used widely in ecology (Drew & Perera, 2011), but

results in personal biases in the data.

Phylogenetic data and trait data did not perfectly overlap. For example, data could not be

downloaded from the GBIF server for seven Carex species (C. echinata, C. lasiocarpa, C.

pauciflora, C. podocarpa, C. rostrata, C. scirpoidea, and C. triquetra). In situations with incomplete overlap, tips were dropped from the tree. The author of this thesis acknowledges that

this is not the most appropriate solution to deal with missing data. Tip dropping may impact

Chapter 3: Regional species richness and trait 3.4 DISCUSSION evolution in the genus Carex (Cyperaceae) results through its effect on the tree topology and species numbers. Unfortunately, however, a complete sampling was not possible due to time constraints.

In this study, data analysis methods were developed to suit the precise question posed.

This is because no appropriate method exists in the literature. However, before developing a custom analysis framework, a number of potential methods were investigated and ruled out.

Firstly, the popular State Speciation Extinction (SSE) toolbox – BiSSE, QuaSSE, GeoSSE, and

others – was considered (Maddison et al., 2007; FitzJohn et al., 2009; FitzJohn, 2010, 2012).

This is a set of likelihood methods and R packages that have been developed to test the effects of

character states on speciation or extinction rates on phylogenies. However, despite their

widespread use (Maddison et al., 2007 cited 387 times in Google Scholar search), these methods

have been shown to infer statistically significant associations with neutral traits (Rabosky &

Goldberg, 2015). This is because, among other reasons outlined by Rabosky & Goldberg (2015),

the model requires only one concurrent shift in character state and rate of diversification, which

may be incorrectly placed. Therefore, SSE was determined as inadequate for this study. A newly

developed Bayesian statistical framework (BAMM) models dynamics of speciation, extinction

and trait evolution on trees (Rabosky et al., 2013; Rabosky et al., 2014). However, the program

requires complete taxon sampling or non-random incomplete taxon sampling for analysis. The

data sampling in this study is non-random and incomplete, and therefore it was not possible to

implement BAMM methods. Lastly, the newly developed R package EvoRAG (Evolutionary

Rates Across Gradients; Lawson & Weir, 2014; Weir & Lawson, 2015), which uses likelihood

methods to compare evolutionary rates, was investigated. Unfortunately, an analysis using

EvoRAG and species richness numbers is not possible due to the high number of replicates

required.

Chapter 3: Regional species richness and trait 3.4 DISCUSSION evolution in the genus Carex (Cyperaceae)

The method developed for this study used non-nested sister groups selected from the tree for comparison, according to a set of requirements (see methods). Subsequently, rates of trait evolution were calculated for each group, compared and plotted against corresponding species richness ratios using custom scripts in R. Although, ad hoc methods suffer because they are unverified; simulation studies have not been conducted to determine their power or accuracy. A further shortfall of the method developed is that a criterion used to automatically detect appropriate contrasts – a minimum of three descendants per node while maximizing the number

of contrasts – may harbour bias. If the number of contrasts are maximized, the program will by

nature choose smaller contrasts, rather than disparate contrasts (e.g., 30 species compared to 3).

It is unclear at this point in time how to correct for this bias.

Macroevolutionary-scale species richness studies have previously recognized the

existence of a ‘taxonomic sampling’ bias (Rabosky et al., 2013). This occurs because taxonomists are more likely to split morphologically divergent species into separate lineages, than morphologically similar species. This may not affect the relationship between ecological trait disparity and species richness, but will exaggerate any relationship between morphology and species richness.

Wetness and light were used as habitat predictors in this study. However, adding a third predictor, pH as a proxy for acidity or basicity tolerance, would improve the characterization of habitat niche. Carex is frequently found in wetlands (bogs, fens, and others), but also inhabits similarly wet environments with variable pH levels. Soil pH affects the nutrient status of soils.

Consequently, different plant physiologies are required to inhabit different acid or basic

environments. This important aspect of niche is currently lacking. pH data were not readily

available for all Carex species of North America, and therefore a partnership with scientists who

Chapter 3: Regional species richness and trait 3.4 DISCUSSION evolution in the genus Carex (Cyperaceae) have extensive knowledge of the pH niche of Carex species would be required to obtain good data. Alternatively, the literature could be mined for Carex species pH tolerance data. However, this would be time consuming. Adding pH as a habitat predictor is an important avenue for further research.

The accuracy of this study’s results rely on the tree topology (Fig. 2.2). Therefore,

calculations of trait evolution rates across randomly selected trees from the BEAST post burn-in

distribution should be considered for further work. Additionally, a bootstrap analysis to

determine confidence in tree topologies would be beneficial. Unfortunately, due to time

constraints, these analyses were not possible.

Chapter 3: Regional species richness and trait 3.5 TABLES AND FIGURES evolution in the genus Carex (Cyperaceae)

3.5 TABLES AND FIGURES

Table 3.1 Primer sequences used in DNA amplification and sequencing. Type Region Forward primer Reverse primer Reference cpDNA matK matK- 5' CCT ATC CAT matK- 5' GTT CTA GCA Starr et al., 2.1F: CTG GAA ATC 5R: CAA GAA AGT CG 2009 TTA G 3' 3' cpDNA rps16 rps16F: 5’ AAA CGA rps16R: 5’ AAC ATC AAT Shaw et al., TGT GGT AGA TGC AAC GAT 2005 but AAG CAA C 3’ TCG ATA 3’ modified to remove ambiguities Nuclear ITS ITS-1: 5’ GTC CAC TGA ITS4: 5’ TCC TCC GCT Urbatsch et ACC TTA TCA TAT TGA TAT GC al., 2000 TTT AG 3’ 3’ and White et al., 1990 Nuclear ETS ETS-1F: 5’ CTG TGG CGT 18S-R: 5’ AGA CAA GCA Starr et al., CGC ATG AGT TAT GAC TAC 2003 TG 3’ TGG CAG G 3’

Chapter 3: Regional species richness and trait 3.5 TABLES AND FIGURES evolution in the genus Carex (Cyperaceae)

Table 3.2 Loadings from principal component analysis of 19 WorldClim BIOCLIM variables estimated from GBIF occurrence data. Only those principal components explaining a larger than expected amount of variation are included (>5.3%: PC1=42%, PC2=28%, PC3=16%, PC4=7%). Loadings are bolded if they are important contributors (>square root of 1/19 variables=0.229415). BIOCLIM variables are sorted according to their contributions to PC1, PC2, PC3 and PC4. BIOCLIM Variable PC1 PC2 PC3 PC4 BIO11 = Mean Temperature of Coldest Quarter 0.333849 0.01324 -0.10339 0.229201 BIO6 = Min Temperature of Coldest Month 0.329456 -0.0267 -0.02686 0.289255 BIO9 = Mean Temperature of Driest Quarter 0.309547 -0.12133 -0.0777 0.048826 BIO1 = Annual Mean Temperature 0.305478 0.160053 -0.16681 0.121889 BIO12 = Annual Precipitation 0.281465 0.06568 0.281621 -0.26876 BIO13 = Precipitation of Wettest Month 0.272504 -0.16703 0.13843 -0.29621 BIO16 = Precipitation of Wettest Quarter 0.268684 -0.16567 0.15461 -0.31028 BIO3 = Isothermality (BIO2/BIO7) (* 100) 0.244413 -0.20902 -0.25007 0.008242 BIO19 = Precipitation of Coldest Quarter 0.236629 -0.21553 0.198342 -0.3242 BIO10 = Mean Temperature of Warmest Quarter 0.230339 0.27629 -0.21324 -0.005 BIO18 = Precipitation of Warmest Quarter 0.113953 0.353102 0.139396 0.060068 BIO15 = Precipitation Seasonality (Coefficient of Variation) 0.008027 -0.3481 -0.26254 -0.07362 BIO8 = Mean Temperature of Wettest Quarter 0.090206 0.325107 -0.20311 0.19157 BIO14 = Precipitation of Driest Month 0.126601 0.318984 0.297723 -0.04934 BIO17 = Precipitation of Driest Quarter 0.148461 0.307437 0.294806 -0.0761 BIO4 = Temperature Seasonality (standard deviation *100) -0.22172 0.273964 -0.08859 -0.33225 BIO7 = Temperature Annual Range (BIO5- BIO6) -0.16802 0.240523 -0.25854 -0.44086 BIO2 = Mean Diurnal Range (Mean of monthly (max temp - min temp)) 0.105125 0.01111 -0.45553 -0.33338 BIO5 = Max Temperature of Warmest Month 0.220704 0.227562 -0.31247 -0.12354

Chapter 3: Regional species richness and trait 3.5 TABLES AND FIGURES evolution in the genus Carex (Cyperaceae)

Table 3.3 Loadings from principal component analysis of six morphological characters (perigynia length, perigynia width, achene length, achene width, culm height, leaf width). Important contributors to principal components explaining a larger than expected amount of variation are bolded (PC1=49%, PC2=19%). Variable PC1 PC2 PC3 PC4 PC5 PC6 Achene width -0.474 -0.36147 0.106515 0.385384 -0.30025 -0.62821 Perigynia length -0.46338 0.015398 -0.37295 -0.49016 0.56536 -0.29337 Perigynia width -0.45533 0.043531 -0.49912 -0.11885 -0.57944 0.437922 Achene length -0.44666 -0.3602 0.361374 0.247659 0.392534 0.569865 Culm height -0.23958 0.76264 -0.09427 0.560185 0.194292 -0.02324 Leaf width -0.31044 0.394773 0.678943 -0.47113 -0.25026 -0.0472

Chapter 3: Regional species richness and trait 3.5 TABLES AND FIGURES evolution in the genus Carex (Cyperaceae)

Comparison number Sample calculation: Comparison 11 Number of species 11 Node 1: 5 Node 2: 17 Species richness ratio = 5/17 = 0.29 log(0.29) = -1.24 7 Rate of trait evolution via BM 10 Node 1: 19.2 Node 2: 348.0 Rate ratio = 19.2/348.0 = 0.055 log(0.055) = -2.90

6 5 7 3 1 2 0 1 3 10 Different sets of non-nested 5 6

comparisons exist within the formed)

same phylogeny. 1 ans

8 (log tr 11

ratio of ratio of rate evolution 8 parent nodes sister nodes 0.0 0.5 2 ratio of number of descendant taxa (log t ransformed) 0.009 Fig. 3.1 An example of one set of non-nested sister group comparisons. Each sister contrast is shown in a different colour. Parental nodes are circled in red and sister nodes are circled in black. For each sister comparison, the ratio of species richness and ratio of trait evolution is calculated. The data then are log transformed and plotted. This procedure is performed for ten different sets of sister groups.

Trichophorum STA1816_Trichophorum_alpinum STA1817_Trichophorum_cespitosum Carex_perglobosa_MOR_1605_CO_B1196_FO Carex_macrocephala_MOR_1236_AK_B831_MC Carex_kobomugi_MOR_713_VA_B361_MC clade Carex_arkansana_MOR_471_IL_B119_PG Carex_vallicola_MOR_1788_BC_B1379_PG Carex_retroflexa_MOR_992_DE_B584_PG Carex_radiata_MOR_1000_MI_B592_PG Carex_rosea_MOR_1016_ME_B607_PG Carex_texensis_MOR_1482_CA_B1073_PG (outgroup) Carex_appalachica_MOR_455_MA_B103_PG Carex_socialis_MOR_1090_AL_B682_PG Carex_douglasii_MOR_1938_SK_B1530_DV Carex_duriuscula_MOR_1455_AK_B1046_DV Carex_chihuahuensis_MOR_1614_AZ_B1205_MF Carex_alma_MOR_437_CA_B085_MF Carex_pansa_MOR_1766_CA_B1357_DV Carex_occidentalis_MOR_1934_CA_B1526_PG Carex_praegracilis_MOR_891_STARR_B551 Carex_oklahomensis_MOR_845_AR_B505_VU Carex_nervina_MOR_1642_CA_B1233_VU Carex_crus_corvi_MOR_556_FL_B204_VU Carex_neurophora_MOR_1417_WA_B1008_VU Carex_vernacula_MOR_1264_STARR_B859 Carex_jonesii_MOR_1412_WA_B1003_VU Carex_decomposita_MOR_570_DE_B218_HE Carex_simulata_MOR_1086_CA_B678_DV Carex_cusickii_MOR_1806_BC_B1397_HE Carex_diandra_MOR_574_CA_B222_HE Carex_prairea_MOR_1753_BC_B1344_HE Carex_muehlenbergii_enervis_MOR_1768_AR_B1359_PG Carex_cephalophora_MOR_562_DE_B210_PG Carex_conjuncta_MOR_518_DE_B166_VU Carex_alopecoidea_MOR_1530_IL_B1121_VU Carex_densa_MOR_1471_OR_B1062_MF Carex_vulpinoidea_MOR_1153_CA_B746_MF Carex_annectens_MOR_464_AL_B112_MF Carex_triangularis_MOR_1146_TX_B739_MF Carex_fissa_fissa_MOR_614_TX_B262_MF Carex_mesochorea_MOR_831_AL_B491_PG Carex_perdentata_MOR_993_TX_B585_PG Carex_leavenworthii_MOR_759_AL_B407_PG Carex_austrina_MOR_524_DE_B172_PG Carex_cephaloidea_MOR_538_MA_B186_PG Carex_sparganioides_MOR_1091_DE_B683_PG Carex_aggregata_MOR_419_KY_B066_PG Carex_gravida_MOR_704_KN_B352_PG Carex_infirminervia_MOR_1200_CA_B795_DE Carex_deweyana_deweyana_MOR_773_MB_B421_DE Carex_bromoides_MD_B022_DE Carex_leptopoda_MOR_1201_BC_B796_DE Carex_bolanderi_MOR_1216_CA_B811_DE Carex_seorsa_MOR_1044_DE_B635_SL Carex_exilis_MOR_621_DE_B269_SL Carex_ruthii_MOR_1008_NC_B600a_SL Carex_atlantica_capillacea_MOR_452_FL_B100_SL Carex_sterilis_MOR_1545_MB_B1136_SL Carex_echinata_echinata_MOR_1435_AK_B1026_SL Carex_interior_MOR_706_STARR_B354 Carex_wiegandii_MOR_1155_ME_B748_SL Carex_chordorrhiza_MOR_1727_BC_B1318_CH Carex_incurviformis_MOR_1903_CO_B1495_FO Carex_siccata_MOR_1872_ON_B1464_AM Carex_sartwellii_MOR_1784_BC_B1375_HH Carex_hookerana_MOR_1915_AB_B1507_PG Carex_tumulicola_MOR_1140_CA_B733_PG Carex_hoodii_MOR_1732_CA_B1323_PG Carex_arenaria_MOR_467_DE_B115_AM Carex_stipata_stipata_MOR_1055_MB_B646_VU Carex_laevivaginata_MOR_727_AL_B375_VU Carex_disperma_MOR_1454_AK_B1045_DS Carex_divisa_MOR_1866_MD_B1458_DV Carex_spicata_MOR_1073_DE_B665_PG Carex_muricata_lamprocarpa_MOR_1912_Spain_B1504_PG Carex_divulsa_MOR_1383_WA_B974_PG Carex_gynocrates_MOR_1432_AK_B1023_PY Carex_brunnescens_MOR_498_CA_B146_GO Vignea Carex_laeviculmis_MOR_1199_CA_B794_DE Carex_illota_MOR_695_CA_B343_OV Carex_arcta_MOR_444_AK_B092_GO Carex_bonanzensis_MOR_1622_AK_B1213_GO Carex_praeceptorum_MOR_1754_CA_B1345_GO clade Carex_arctiformis_MOR_1653_BC_B1244_GO Carex_lapponica_MOR_1443_AK_B1034_PD Carex_canescens_disjuncta_MOR_1298_STARR_B895 Carex_tenuiflora_MOR_1115_MB_B708_GO Carex_marina_MOR_1548_MB_B1139_GO Carex_loliacea_MOR_1452_AK_B1043_GO Carex_trisperma_MOR_1136_MI_B729_GO Carex_heleonastes_MOR_1756_AB_B1347_GO Carex_lachenalii_MOR_1442_AK_B1033_GO Carex_mackenziei_MOR_1459_AK_B1050_GO Carex_ursina_MOR_1777_YT_B1368_GO Carex_glareosa_MOR_1558_MB_B1149_GO Carex_straminiformis_MOR_1068_UT_B660_OV Carex_mariposana_MOR_1686_AZ_B1277_OV Carex_integra_MOR_711_CA_B359_OV Carex_fracta_MOR_630_CA_B278_OV Carex_specifica_MOR_1094_CA_B686_OV Carex_multicostata_MOR_827_CA_B487_OV Carex_wootonii_MOR_1615_AZ_B1206_OV Carex_haydeniana_MOR_668_STARR_B316 Carex_arapahoensis_MOR_1527_CO_B1118_OV Carex_egglestonii_MOR_1504_CO_B1095_OV Carex_ebenea_MOR_1672_AZ_B1263_OV Carex_microptera_MOR_1682_CO_B1273_OV Carex_praticola_MOR_897_CO_B557_OV Carex_foenea_MOR_1802_BC_B1393_OV Carex_argyrantha_MOR_468_MD_B116_OV Carex_davyi_MOR_1261_CA_B856_OV Carex_phaeocephala_MOR_995_NV_B587_OV Carex_proposita_MOR_1743_CA_B1334_OV Carex_adusta_MOR_1874_AB_B1466_OV Carex_xerantica_MOR_1715_ON_B1306_OV Carex_petasata_MOR_994_UT_B586_OV Carex_tahoensis_MOR_1477_OR_B1068_OV Carex_sychnocephala_MOR_1702_ON_B1293_CP Carex_leporinella_MOR_1415_WA_B1006_OV Carex_athrostachya_MOR_461_STARR_B109 Carex_unilateralis_MOR_1394_STARR_B985 Carex_harfordii_MOR_699_CA_B347_OV Carex_gracilior_MOR_1494_CA_B1085_OV Carex_subbracteata_MOR_1757_CA_B1348_OV Carex_preslii_MOR_976_OR_B568_OV Carex_pachystachya_MOR_1666_AK_B1257_OV Carex_macloviana_MOR_1437_AK_B1028_OV Carex_abrupta_MOR_860_BC_B520_OV Carex_subfusca_MOR_1670_CA_B1261_OV Carex_stenoptila_MOR_1084_UT_B676_OV Carex_straminea_MOR_1054_DE_B645_OV Carex_hormathodes_MOR_1916_NS_B1508_OV Carex_ozarkana_MOR_857_AR_B517_OV Carex_albolutescens_MOR_428_OK_B075_OV Carex_scoparia_scoparia_MOR_1057_ME_B648_OV Carex_suberecta_MOR_1361_B953_OV Carex_vexans_MOR_1168_FLh_B761_OV Carex_longii_MOR_735_AR_B383_OV Carex_alata_MOR_421_AL_B068_OV Carex_ovalis_MOR_1582_WS_B1173_OV Carex_feta_MOR_627_CA_B275_OV Carex_cumulata_MOR_605_IL_B253_OV Carex_projecta_MOR_978_MB_B570_OV Carex_crawfordii_MOR_522_NY_B170_OV Carex_cristatella_MOR_534_KY_B182_OV Carex_tribuloides_MOR_1125_STARR_B718 Carex_bebbii_MOR_479_MB_B127_OV Carex_opaca_MOR_867_OK_B527_OV Carex_tetrastachya_MOR_1071_TXk_B663_OV Carex_reniformis_MOR_989_GA_B581_OV Fig. 3.2 Carex_hyalina_MOR_646_MS_B294_OV Carex_brevior_MOR_1625_BC_B1216_OV Carex_molestiformis_MOR_807_AR_B466_OV Carex_molesta_MOR_804_DE_B463_OV Carex_missouriensis_MOR_801_IL_B460_OV continued Carex_shinnersii_MOR_1027_KN_B618_OV Carex_tenera_tenera_MOR_1552_MB_B1143_OV Carex_tincta_MOR_1144_ME_B737_OV Carex_oronensis_MOR_1700_ME_B1291_OV Carex_silicea_MOR_1034_DE_B625_OV 73 Carex_muskingumensis_MOR_849_MI_B509_OV Carex_merritt_fernaldii_MOR_785_MB_B443_OV Carex_festucacea_MOR_626_TX_B274_OV Carex_normalis_MOR_793_AL_B451_OV Carex_bicknellii_MOR_478_IN_B126_OV Fig. 3.2 continued Carex_geyeri_MOR_676_AB_B324_FC Carex_multicaulis_MOR_826_STARR_B486 Carex_tompkinsii_MOR_1485_CA_B1076_FC Carex_fraserianus_MOR_686_STARR_B334 Carex_cordillerana_MOR_1346_BC_B943_PS Carex_latebracteata_MOR_1185_AR_B779_PS Carex_backii_MOR_1809_B1400_PS Carex_saximontana_MOR_1529_CO_B1120_PS Carex_willdenowii_MOR_358_KY_B003_PS Core Carex_superata_MOR_366_STARR_B012 Carex_juniperorum_KY_B0011_PS Carex_basiantha_MOR_371_SC_B017_PS Carex_jamesii_MOR_364_AL_B010_PS Carex_timida_MOR_359_AL_B005_PS Unispicate Carex_circinata_MOR_1779_AK_B1370_CR Carex_anthoxanthea_MOR_1370_STARR_B961 Carex_subnigricans_MOR_1476_OR_B1067_IF Carex_breweri_MOR_1378_STARR_B969 Carex_engelmannii_MOR_1933_BC_B1525_IF Carex_pauciflora_MOR_876_AK_B536_LG Clade Carex_leptalea_MOR_766_STARR_B414 Carex_nigricans_MOR_1440_AK_B1031_DO Carex_pyrenaica_MOR_1400_STARR_B991 Carex_micropoda_MOR_1434_AK_B1025_DO Carex_microglochin_Stordalen_MOR_1507_B1098_LG Carex_rupestris_MOR_1923_Spain_B1515_RU Carex_capitata_MOR_1838_B1429_CT Carex_obtusata_MOR_841_MB_B501_OB Carex_muriculata_MOR_1612_NM_B1203_PG Carex_oreocharis_AZ_B1269_FL Carex_nardina_MOR_1312_QC_B909_NA Carex_elynoides_MOR_599_STARR_B247 Carex_filifolia_MOR_1234_CA_B829_FL Carex_eburnea_MOR_576_MI_B224_AL Carex_fuliginosa_MOR_1429_AK_B1020_AU Carex_laxa_MOR_1445_AK_B1036_PN Carex_vaginata_MOR_1776_YT_B1367_PN Carex_panicea_MOR_1708_ME_B1299_PN Carex_hendersonii_MOR_1749_BC_B1340_LF Carex_leptonervia_MOR_1196_MB_B790_LF Carex_albursina_MOR_1186_STARR_B780 Carex_crebriflora_MOR_777_STARR_B425 Carex_chapmanii_MOR_566_FL_B214_LF Carex_styloflexa_MOR_1101_GA_B693_LF Carex_blanda_MOR_1621_KS_B1212_LF Carex_kraliana_MOR_715_AR_B363_LF Carex_gracilescens_MOR_661_KY_B309_LF Carex_radfordii_MOR_1240_SC_B835_LF Carex_striatula_MOR_1066_DE_B658_LF Carex_laxiflora_MOR_757_MI_B405_LF Carex_ormostachya_MOR_868_MI_B528_LF Carex_manhartii_MOR_1563_GE_B1154_LF Carex_purpurifera_MOR_1272_KY_B867_LF Carex_biltmoreana_MOR_1870_NC_B1462_PN Carex_woodii_MOR_1592_IA_B1183_PN Carex_klamathensis_MOR_1871_OR_B1463_PN Carex_livida_MOR_1212_NJ_B807_PN Carex_tetanica_MOR_1116_MB_B709_PN Carex_meadii_MOR_1544_MB_B1135_PN Carex_aurea_MOR_501_CA_B149_BI Carex_hassei_MOR_1669_CA_B1260_BI Carex_bicolor_MOR_1424_AK_B1015_BI Carex_garberi_MOR_1426_AK_B1017_BI Carex_assiniboinensis_MOR_456_MB_B104_HC Carex_sprengelii_MOR_1568_NB_B1159_HC Carex_buxbaumii_MOR_499_AK_B147_RM Carex_holostoma_MOR_1433_AK_B1024_RM Carex_adelostoma_MOR_1421_AK_B1012_RM Carex_heterostachya_MOR_1824_B1415_PD Carex_sabulosa_MOR_1448_YT_B1039_RM Carex_albonigra_MOR_1423_AK_B1014_RM Carex_helleri_MOR_1266_STARR_B861 Carex_gmelinii_MOR_1431_AK_B1022_RM Carex_atrata_MOR_527_STARR_B175 Carex_atratiformis_MOR_1553_AB_B1144_RM Carex_media_MOR_1574_NB_B1165_RM Carex_stevenii_MOR_1512_CO_B1103_RM Carex_norvegica_MOR_1418_OR_B1009_RM Carex_atrosquama_MOR_1522_MO_B1113_RM Carex_pelocarpa_MOR_997_NV_B589_RM Carex_heteroneura_MOR_659_NV_B307_RM Carex_nelsonii_MOR_1634_MO_B1225_RM Carex_epapillosa_MOR_620_UT_B268_RM Carex_bella_MOR_1523_CO_B1114_RM Carex_chalciolepis_MOR_1931_CO_B1523_RM Carex_nova_MOR_434_CO_B081_RM Carex_raynoldsii_MOR_986_CA_B578_RM Carex_idahoa_MOR_1365_STARR_B956 Carex_aboriginum_MOR_1640_ID_B1231_RM Carex_serratodens_MOR_1028_CA_B619_RM Carex_parryana_MOR_1436_AK_B1027_RM Carex_specuicola_MOR_1616_AZ_B1207_RM Carex_hallii_MOR_1556_MB_B1147_RM Carex_fissuricola_MOR_1919_ID_B1511_AU Carex_lemmonii_MOR_763_CA_B411_AU Carex_luzulina_luzulina_MOR_1710_CA_B1301_AU Carex_luzulifolia_MOR_762_CA_B410_AU Carex_collinsii_MOR_561_DE_B209_CO Carex_edwardsiana_MOR_1944_TX_B1536_GR Carex_abscondita_MOR_410_DE_B057_CY Carex_cumberlandensis_MOR_551_AR_B199_CY Carex_laxiculmis_laxiculmis_MOR_1205_PN_B800_CY Carex_granularis_MOR_1209_MB_B804_GL Carex_microdonta_MOR_1222_MS_B817_GL Carex_crawei_MOR_1273_NFLD_B868_GL Carex_gholsonii_MOR_687_AL_B335_GL Carex_glaucodea_MOR_1327_IN_B924_GR Carex_flaccosperma_MOR_405_LO_B052_GR Carex_pigra_MOR_1587_MS_B1178_GR Carex_impressinervia_MOR_1586_MS_B1177_GR Carex_ouachitana_MOR_1340_AR_B937_GR Carex_hitchcockiana_MOR_391_KY_B038_GR Carex_brysonii_MOR_389_AL_B036_GR Carex_plantaginea_MOR_1695_TN_B1286_CY Carex_austrocaroliniana_MOR_1531_NC_B1122_CY Carex_careyana_MOR_1203_KY_B798_CY Carex_platyphylla_MOR_886_MD_B546_CY Carex_conoidea_MOR_1230_DE_B825_GR Carex_grisea_MOR_390_KY_B037_GR Carex_corrugata_MOR_404_AL_B051_GR Carex_godfreyi_MOR_1589_AL_B1180_GR Carex_amphibola_MOR_388_AL_B035_GR Carex_oligocarpa_MOR_1334_AR_B931_GR Carex_bulbostylis_MOR_382_MS_B029_GR Carex_thornei_MOR_1542_GA_B1133_GR Carex_planispicata_MOR_400_MD_B047_GR Carex_paeninsulae_MOR_1247_FLc_B842_GR Carex_calcifugens_MOR_402_FL_B049_GR Carex_acidicola_MOR_392_AL_B039_GR Carex_cherokeensis_MOR_564_FL_B212_HC Carex_obispoensis_MOR_1599_CA_B1190_HC Carex_atrofusca_MOR_1456_AK_B1047_AU Carex_spissa_ultra_MOR_1617_AZ_B1208_HP Carex_flacca_MOR_1611_MI_B1202_TU Carex_supina_spaniocarpa_MOR_1596_AK_B1187_LC Carex_glacialis_MOR_1290_STARR_B887 Carex_concinna_CO_B1090_CL Carex_richardsonii_MOR_1022_MD_B613_CL Carex_concinnoides_MOR_1720_CA_B1311_CL Carex_petricosa_misandroides_MOR_1797_QC_B1388_AU Carex_floridana_MOR_640_STARR_B288 Carex_tonsa_MOR_1119_STARR_B712 Carex_lucorum_lucorum_MOR_1538_NC_B1129_AC Carex_novae_angliae_MOR_795_ME_B453_AC Carex_albicans_emmonsii_MOR_433_MD_B080_AC Carex_pensylvanica_MOR_973_MB_B565_AC Carex_peckii_MOR_1427_AK_B1018_AC Carex_communis_amplisquama_MOR_1724_GA_B1315_AC Carex_inops_inops_MOR_1803_BC_B1394_AC Carex_geophila_MOR_674_STARR_B322 Carex_pityophila_MOR_1632_NM_B1223_AC Fig. 3.2 Carex_reznicekii_MOR_1014_AL_B605_AC Carex_nigromarginata_MOR_855_AL_B515_AC Carex_turbinata_MOR_1679_AZ_B1270_AC Carex_serpenticola_MOR_1763_CA_B1354_AC Carex_globosa_MOR_654_CA_B302_AC continued Carex_rossii_MOR_1003_STARR_B595 Carex_deflexa_deflexa_MOR_1927_BC_B1519_AC Carex_brainerdii_MOR_494_CA_B142_AC Carex_brevicaulis_MOR_1375_WA_B966_AC 74 Fig. 3.2 Carex_williamsii_MOR_1771_YT_B1362_CS Carex_capillaris_MOR_1896_NT_B1488_CS Carex_krausei_MOR_1441_AK_B1032_CS Carex_triquetra_MOR_1602_CA_B1193_TQ continued Carex_turgescens_MOR_1244_MS_B839_RT Carex_michauxiana_MOR_1550_MB_B1141_RT Carex_folliculata_MOR_645_DE_B293_RT Carex_lonchocarpa_MOR_733_FL_B381_RT Carex_distans_MOR_578_STARR_B226 Carex_diluta_MO_B957_SS Carex_extensa_MOR_1655_VA_B1246_SS Carex_sylvatica_MOR_1392_WA_B983_HC Carex_pendula_MOR_999_STARR_B591 Carex_viridustellata_MOR_1820_STARR_B1411 Carex_lutea_MOR_1567_NC_B1158_CC Carex_flava_MOR_1285_NFLD_B881_CC Carex_viridula_oedocarpa_MOR_1750_NS_B1341_CC Carex_cryptolepis_MOR_1532_IL_B1123_CC Carex_hostiana_MOR_1796_QC_B1387_CC Carex_caryophyllea_Ibirica_MOR_1865_B1457_MT Large Core Carex Carex_lativena_MOR_1631_NM_B1222_HL Carex_planostachys_MOR_884_TXc_B544_HL Carex_amplifolia_MOR_449_NV_B097_AN Carex_scabrata_MOR_1045_GA_B636_AN Carex_vestita_MOR_1165_DE_B758_PD Carex_sartwelliana_MOR_1600_CA_B1191_PD Clade Carex_congdonii_MOR_1488_CA_B1079_PD Carex_scabriuscula_MOR_1048_CA_B639_SP Carex_scirpoidea_scirpoidea_MOR_1050_AK_B641_SP Carex_curatorum_MOR_1769_UT_B1360_SP Carex_californica_MOR_1487_CA_B1078_PN Carex_polymorpha_PN_B550_PN Carex_torreyi_MOR_1510_CO_B1101_PO Carex_pallescens_MOR_1810_B1401_PO Carex_acutiformis_MOR_1924_Spain_B1516_PD Carex_umbellata_MB_B772_AC Carex_whitneyi_MOR_1154_CA_B747_LG Carex_tenax_MOR_1110_STARR_B703 Carex_dasycarpa_MOR_607_GA_B255_HL Carex_aestivalis_MOR_415_PN_B062_HC Carex_roanensis_MOR_1026_NC_B617_HC Carex_virescens_MOR_1158_AL_B751_PO Carex_misera_MOR_1566_TN_B1157_HC Carex_complanata_MOR_516_TX_B164_PO Carex_swanii_MOR_1107_STARR_B700 Carex_bushii_MOR_511_DE_B159_PO Carex_caroliniana_MOR_549_AL_B197_PO Carex_hirsutella_MOR_669_DE_B317_PO Carex_venusta_MOR_1174_MS_B767_HC Carex_mendocinensis_MOR_1475_OR_B1066_HC Carex_hirtissima_MOR_1496_CA_B1087_HC Carex_gynodynama_MOR_1706_CA_B1297_HC Carex_arctata_MOR_465_WI_B113_HC Carex_castanea_MOR_1281_NFLD_B876_HC Carex_debilis_MOR_597_STARR_B245 Carex_hirtifolia_MOR_1277_STARR_B872 Carex_oxylepis_pubescens_MOR_871_KY_B531_HC Carex_davisii_MOR_592_DE_B240_HC Carex_formosa_MOR_1534_IL_B1125_HC Carex_gracillima_MOR_656_AL_B304_HC Carex_pedunculata_MOR_881_STARR_B541 Carex_picta_MOR_893_GA_B553_PT Carex_baltzellii_MOR_1716_FL_B1307_PT Carex_intumescens_MOR_709_ME_B357_LU Carex_grayi_MOR_658_KN_B306_LU Carex_elliottii_MOR_1718_FL_B1309_VC Carex_aureolensis_MOR_504_MS_B152_SQ Carex_frankii_MOR_673_AL_B321_SQ Carex_pumila_MOR_1869_NC_B1461_PD Carex_striata_MOR_1076_FL_B668_PD Carex_pellita_MOR_882_CA_B542_PD Carex_lasiocarpa_MOR_731_AK_B379_PD Carex_hyalinolepis_MOR_690_TX_B338_PD Carex_lacustris_MOR_725_MB_B373_PD Carex_melanostachya_MOR_1352_OK_B947b_PD Carex_oligosperma_MOR_846_STARR_B506 Carex_houghtoniana_MOR_1248_MB_B843_PD Carex_hirta_MOR_681_PN_B329_CX Carex_atherodes_MOR_1651_BC_B1242_CX Carex_sheldonii_MOR_1495_CA_B1086_CX Carex_trichocarpa_MOR_1133_DE_B726_CX Carex_laeviconica_MOR_1689_KS_B1280_CX Carex_halliana_MOR_1491_CA_B1082_PD Carex_retrorsa_MOR_1012_MI_B603_VC Carex_gigantea_MOR_651_FL_B299_LU Carex_louisianica_MOR_742_FL_B390_LU Carex_lupuliformis_MOR_745_FL_B393_LU Carex_lupulina_MOR_812_MD_B472_LU Carex_bullata_MOR_509_MA_B157_VC Carex_thurberi_MOR_1618_AZ_B1209_VC Carex_hystericina_MOR_815_AR_B475_VC Carex_pseudocyperus_MOR_981_B573_VC Carex_comosa_MOR_560_CA_B208_VC Carex_baileyi_MOR_485_KY_B133_VC Carex_lurida_MOR_816_FL_B476_VC Carex_saxatilis_MOR_1025_STARR_B616 Carex_tuckermanii_MOR_1147_MI_B740_VC Carex_exsiccata_MOR_1778_BC_B1369_VC Carex_vesicaria_MOR_1162_DE_B755_VC Carex_schweinitzii_MOR_1058_MI_B649_VC Carex_utriculata_MOR_1181_AK_B774_VC Carex_rotundata_MOR_1551_MB_B1142_VC Carex_rostrata_MOR_1402_STARR_B993 Carex_membranacea_MOR_784_AK_B442_VC Carex_stylosa_MOR_1292_NFLD_B889_RM Carex_aperta_MOR_1644_BC_B1235_PC Carex_haydenii_MOR_1594_IA_B1185_PC Carex_prasina_MOR_900_GA_B560_HC Carex_verrucosa_MOR_1175_FL_B768_GC Carex_joorii_MOR_719_STARR_B367 Carex_glaucescens_MOR_660_MS_B308_GC Carex_shortiana_MOR_1031_KN_B622_SH Carex_squarrosa_MOR_1083_AR_B675_SQ Carex_typhina_MOR_1132_AR_B725_SQ Carex_barrattii_MOR_482_AL_B130_LM Carex_obnupta_MOR_839_CA_B499_PC Carex_macrochaeta_MOR_1473_OR_B1064_LM Carex_mertensii_MOR_790_AK_B448_RM Carex_spectabilis_MOR_1781_BC_B1372_ST Carex_microchaeta_microchaeta_MOR_1748_YT_B1339_ST Carex_barbarae_MOR_1251_CA_B846_PC Carex_nebrascensis_MOR_850_CA_B510_PC Carex_endlichii_MOR_1897_AZ_B1489_PC Carex_rariflora_MOR_1801_YT_B1392_LM Carex_pluriflora_MOR_1758_AK_B1349_LM Carex_limosa_MOR_769_AK_B417_LM Carex_paupercula_MOR_898_STARR_B558 Carex_magellanica_MOR_1439_AK_B1030_LM Carex_torta_MOR_1122_PN_B715_PC Carex_crinita_crinita_MOR_535_ME_B183_PC Carex_mitchelliana_MOR_835_AL_B495_PC Carex_gynandra_MOR_698_DE_B346_PC Carex_podocarpa_MOR_1734_BC_B1325_ST Carex_emoryi_MOR_619_DE_B267_PC 0.009 Carex_interrupta_MOR_1468_OR_B1059_PC Carex_nigra_MOR_1297_NFLD_B894_PC Carex_eleusinoides_MOR_1425_AK_B1016_PC Carex_stricta_MOR_1098_TX_B690_PC Carex_bigelowii_lugens_MOR_476_AK_B124_PC Carex_angustata_MOR_447_CA_B095_PC Carex_nudata_MOR_1242_CAs_B837_PC Carex_schottii_MOR_1772_CA_B1363_PC Carex_senta_MOR_1687_AZ_B1278_PC Carex_scopulorum_MOR_1039_STARR_B630 Carex_lenticularis_impressa_MOR_750_CA_B398_PC Carex_salina_MOR_1755_QC_B1346_PC Carex_vacillans_MOR_1691_ME_B1282_PC Carex_paleacea_MOR_861_ME_B521_PC Carex_ramenskii_MOR_1241_AK_B836_PC Carex_lyngbyei_MOR_819_OR_B479_PC Carex_aquatilis_aquatilis_MOR_1287_B884_PC Carex_recta_MOR_1947_B1539_PC Carex_subspathacea_MOR_1449_AK_B1040_PC Fig. 3.2 Maximum clade credibility phylogeny summarizing two BEAST runs of 100 million generations each. Two ougroup species and 477 North American Carex species are included. Thickness of branches correspond to Bayesian posterior probabilities. The phylogeny was constructed from the four-gene supermatrix (matK, rps16, ITS, ETS). Major clades (from Starr et al., 2015) are indicated and are accompanied by a photo of a member species. Time scale is in millions of years. Labels contain sample information (Morton Arboretum identifier, MOR code and Starr Lab identifier, B code), two-letter geography information and section information. 75 Chapter 3: Regional species richness and trait 3.5 TABLES AND FIGURES evolution in the genus Carex (Cyperaceae)

A 40 95% 5% 95% 5%

B 40 30 30 20 Frequency Frequency 10 20 10 0 0

0.00 0.05 0.10 0.15 0.20 −0.5 0.0 0.5 1.0 Mean r2 Mean slope Fig. 3.3 Histogram of (A) mean r2 values and (B) slopes from regressions of species richness against rates of trait evolution (log transformed) using 100 continuous character evolution simulations. See methods for details on the procedure used to obtain regressions. The red line represents the 0.05 significance level.

Chapter 3: Regional species richness and trait 3.5 TABLES AND FIGURES evolution in the genus Carex (Cyperaceae)

Morphology PC1 (reproductive)* Morphology PC2 (vegetative) mean r2: 0.24 mean r2: 0.07

mean slope: 1.15 2 mean slope: 0.32 0 0 4 8 −4 −4 −2

−1 0 1 2 −1 0 1 2

Wetness habitat* Light habitat* formed) 2 10 mean r : 0.10 10

ans mean slope: 0.82 0 0

mean r2: 0.11 mean slope: 2.46 −10 −10

ratio of ratio of rate (log tr evolution −2 0 2 −2 0 2

Climatic niche PC1* Climatic niche PC2* mean r2: 0.11 mean slope: 0.47 0 5 0 2 −5

mean r2: 0.16 −2 mean slope: 1.13 −10 −2 0 2 −2 0 2 ratio of number of descendant taxa (log transformed) Fig. 3.4 Non-nested sister clade analysis. The ratio of species richness (i.e., the number of descendant taxa) and the ratio of rates of evolution per sister clade contrast are plotted for contrasts satisfying the criterion (= minimum of three descendants per clade). Sets of non-nested sister clades were obtained by maximizing the number of contrasts. Different colours represent different sets of non-nested sister clades, each with the maximum number of contrasts. Mean r2 and slope values are averaged regression statistics among sets. Asterisks represent significance according to the null distribution of 100 continuous character simulations on the tree.

Chapter 4: Conclusions

This thesis used the exceptionally diverse flowering plant genus Carex (Cyperaceae) to

test the sensitivity of climatic niche estimates to distribution data sampling (Chapter 2) and to

evaluate the relationship between species richness and rates of trait evolution in a geographically

comprehensive sample (Chapter 3). It is among the first set of studies to realize the potential of

Carex as a model evolutionary radiation for ecological and evolutionary research.

In Chapter 2, results showed that sampling effort of GBIF data did not have a strong

effect on climatic niche estimates. However, with few counties from species’ BONAP

distributions covered by GBIF occurrence data, differences in niche space were variable.

BONAP data for high elevation species were found to be biased, with elevation explaining 13%

of niche differences. Inferred ancestral states for BONAP data were consistently lower than for

GBIF (i.e., means were significantly different), although variability between sets was less than

within sets.

Consequently, this study recommends supplementing GBIF data with BONAP centroids

when coverage of the known distribution is low, to ensure accuracy of niche estimates. However,

users should only use BONAP data to supplement species’ distribution data when their elevation

niche is below 1000m. This can be calculated using the mean from the elevation range in floral

descriptions from the Flora of North America. When the scale of the study is large, researchers

should consider using only BONAP data, to save time and avoid erroneous inferences (i.e., no

data cleaning required). Researchers should further note that different niche estimates will yield

different results in phylogenetic analyses, although conclusions that might be drawn are largely

Chapter 4: Conclusions similar. This robustness analysis is informative for researchers seeking to understand the limits of GBIF and BONAP distribution data and their use in climatic niche modeling on a phylogeny.

By comparing non-nested sister groups on a Carex species phylogeny, Chapter 3

demonstrated that rates of reproductive morphology, climatic and habitat niche evolution were

significantly related to North American Carex species richness, in decreasing order of significance. Vegetative morphology (morphology PC2) was not significantly related to species richness. These results support the posed hypothesis that greater trait lability leads to greater

diversity in North American Carex. Interpreted otherwise, the results suggest that within North

American Carex, groups that occupy higher amounts of morphospace and niche space through evolutionary time are more successful. This study’s findings add to a body of evidence suggesting niche disparity is important in the generation of Carex species richness. By restricting

the study to North America, the results are exempt from the effects of niche filling or other

broad-scale geographic processes (e.g., limits to dispersal, environmental heterogeneity, etc.).

However, when other recent works are considered (Zelditch et al., 2015), it is likely that these

processes do not extend past the regional scale.

The first study (Chapter 2) is highly relevant to how distribution data can be used to

address ecological and evolutionary questions. It enables researchers to make informed decisions

on data and methods employed. The second study (Chapter 3) contributes to knowledge of

evolutionary patterns in temperate zones. It establishes a relationship between morphological and

ecological trait evolution and species richness in a flowering plant radiation.

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Appendix 1. Supplementary Figures for Chapter 2

8 A B 6 4 (magnitudechangeof vector) 2 Differenceinclimatic niche space 0

0 500 1000 1500 2000 4000 6000 8000

Number of GBIF occurrences Average BONAP county size

8 C 6 4 (magnitudechangeof vector) 2 Differenceinclimatic niche space 0

0 500000 1000000 1500000 Sum of county areas from BONAP distribution Fig. A1.1 Supplementary analyses searching for correlates of differences in niche estimates. No significant correlations were recovered. Each circle is one Carex species. N=363.

Appendix 2. DNA sample data

Appendix 2. DNA sample data appalachica MOR455 MA B103 Phaestoglochin aquatilis MOR1287 LAB B884 Phacocystis arapahoensis MOR1527 CO B1118 Ovales Table A2.1 Carex individuals selected for phylogenetic analysis. arctata MOR465 WI B113 Hymenochlaenae Voucher details can be found in Appendix B of Chouinard (2010). arcta MOR444 AK B092 Glareosae Use B numbers for correspondence. Locations where herbarium arctiformis MOR1653 BC B1244 Glareosae specimens were collected (column 3) are abbreviated into states or arenaria MOR467 DE B115 Ammoglochin provinces, when possible. argyrantha MOR468 MD B116 Ovales Specific epithet MOR# Location B# Section arkansana MOR471 IL B119 Phaestoglochin aboriginum MOR1640 ID B1231 Racemosae assiniboinensis MOR456 MB B104 Hymenochlaenae abrupta MOR860 BC B520 Ovales atherodes MOR1651 BC B1242 Carex abscondita MOR410 DE B057 Careyanae athrostachya MOR461 CA B109 Ovales acidicola MOR392 AL B039 Griseae atlantica MOR452 FL B100 Stellulatae acutiformis MOR1924 Spain B1516 Paludosae atrata MOR527 Taiwan B175 Racemosae adelostoma MOR1421 AK B1012 Racemosae atratiformis MOR1553 AB B1144 Racemosae adusta MOR1874 AB B1466 Ovales atrofusca MOR1456 AK B1047 Aulocystis aestivalis MOR415 PN B062 Hymenochlaenae atrosquama MOR1522 MO B1113 Racemosae aggregata MOR419 KY B066 Phaestoglochin aurea MOR501 CA B149 Bicolores alata MOR421 AL B068 Ovales aureolensis MOR504 MS B152 Squarrosae albicans MOR433 MD B080 Acrocystis austrina MOR524 DE B172 Phaestoglochin albolutescens MOR428 OK B075 Ovales austrocaroliniana MOR1531 NC B1122 Careyanae albonigra MOR1423 AK B1014 Racemosae backii MOR1809 B1400 Phyllostachyae albursina MOR1186 KY B780 Laxiflorae baileyi MOR485 KY B133 Vesicariae alma MOR437 CA B085 Multiflorae baltzellii MOR1716 FL B1307 Pictae alopecoidea MOR1530 IL B1121 Vulpinae barbarae MOR1251 CA B846 Phacocystis amphibola MOR388 AL B035 Griseae barrattii MOR482 AL B130 Limosae amplifolia MOR449 NV B097 Anomalae basiantha MOR371 SC B017 Phyllostachyae angustata MOR447 CA B095 Phacocystis bebbii MOR479 MB B127 Ovales annectens MOR464 AL B112 Multiflorae bella MOR1523 CO B1114 Racemosae anthoxanthea MOR1370 WA B961 Circinatae bicknellii MOR478 IN B126 Ovales aperta MOR1644 BC B1235 Phacocystis bicolor MOR1424 AK B1015 Bicolores

Appendix 2. DNA sample data bigelowii MOR476 AK B124 Phacocystis chordorrhiza MOR1727 BC B1318 Chordorrhizae biltmoreana MOR1870 NC B1462 Paniceae circinata MOR1779 AK B1370 Circinatae blanda MOR1621 KS B1212 Laxiflorae collinsii MOR561 DE B209 Collinsiae bolanderi MOR1216 CA B811 Deweyanae communis MOR1724 GA B1315 Acrocystis bonanzensis MOR1622 AK B1213 Glareosae comosa MOR560 CA B208 Vesicariae brainerdii MOR494 CA B142 Acrocystis complanata MOR516 TX B164 Porocystis brevicaulis MOR1375 WA B966 Acrocystis concinna MOR1499 CO B1090 Clandestinae brevior MOR1625 BC B1216 Ovales concinnoides MOR1720 CA B1311 Clandestinae breweri MOR1378 WA B969 Inflatae congdonii MOR1488 CA B1079 Paludosae bromoides MD B022 Deweyanae conjuncta MOR518 DE B166 Vulpinae brunnescens MOR498 CA B146 Glareosae conoidea MOR1230 DE B825 Griseae brysonii MOR389 AL B036 Griseae cordillerana MOR1346 BC B943 Phyllostachyae bulbostylis MOR382 MS B029 Griseae corrugata MOR404 AL B051 Griseae bullata MOR509 MA B157 Vesicariae crawei MOR1273 NFLD B868 Granulares bushii MOR511 DE B159 Porocystis crawfordii MOR522 NY B170 Ovales buxbaumii MOR499 AK B147 Racemosae crebriflora MOR777 B425 #N/A calcifugens MOR402 FL B049 Griseae crinita MOR535 ME B183 Phacocystis californica MOR1487 CA B1078 Paniceae cristatella MOR534 KY B182 Ovales canescens MOR1298 LAB B895 Glareosae crus-corvi MOR556 FL B204 Vulpinae capillaris MOR1896 NT B1488 Chlorostachyae cryptolepis MOR1532 IL B1123 Ceratocystis capitata MOR1838 B1429 Capituligerae cumberlandensis MOR551 AR B199 Careyanae careyana MOR1203 KY B798 Careyanae cumulata MOR605 IL B253 Ovales caroliniana MOR549 AL B197 Porocystis curatorum MOR1769 UT B1360 Scirpinae caryophyllea MOR1865 lbirica B1457 Mitratae cusickii MOR1806 BC B1397 Heleoglochin castanea MOR1281 NFLD B876 Hymenochlaenae dasycarpa MOR607 GA B255 Hallerianae cephaloidea MOR538 MA B186 Phaestoglochin davisii MOR592 DE B240 Hymenochlaenae cephalophora MOR562 DE B210 Phaestoglochin davyi MOR1261 CA B856 Ovales chalciolepis MOR1931 CO B1523 Racemosae debilis MOR597 OK B245 Hymenochlaenae chapmanii MOR566 FL B214 Laxiflorae decomposita MOR570 DE B218 Heleoglochin cherokeensis MOR564 FL B212 Hymenochlaenae deflexa MOR1927 BC B1519 Acrocystis chihuahuensis MOR1614 AZ B1205 Multiflorae densa MOR1471 OR B1062 Multiflorae

Appendix 2. DNA sample data deweyana MOR773 MB B421 Deweyanae flava MOR1285 NFLD B881 Ceratocystis diandra MOR574 CA B222 Heleoglochin floridana MOR640 FL B288 Acrocystis diluta MOR1366 MO B957 Spirostachyae foenea MOR1802 BC B1393 Ovales disperma MOR1454 AK B1045 Dispermae folliculata MOR645 DE B293 Rostrales distans MOR578 Greece B226 Spirostachyae formosa MOR1534 IL B1125 Hymenochlaenae divisa MOR1866 MD B1458 Divisae fracta MOR630 CA B278 Ovales divulsa MOR1383 WA B974 Phaestoglochin frankii MOR673 AL B321 Squarrosae douglasii MOR1938 SK B1530 Divisae fraserianus MOR686 MD B334 #N/A duriuscula MOR1455 AK B1046 Divisae fuliginosa MOR1429 AK B1020 Aulocystis ebenea MOR1672 AZ B1263 Ovales garberi MOR1426 AK B1017 Bicolores eburnea MOR576 MI B224 Albae geophila MOR674 TX B322 Acrocystis echinata MOR1435 AK B1026 Stellulatae geyeri MOR676 AB B324 Firmiculmes edwardsiana MOR1944 TX B1536 Griseae gholsonii MOR687 AL B335 Granulares egglestonii MOR1504 CO B1095 Ovales gigantea MOR651 FL B299 Lupulinae eleusinoides MOR1425 AK B1016 Phacocystis glacialis MOR1290 NFLD B887 Lamprochlaenae elliottii MOR1718 FL B1309 Vesicariae glareosa MOR1558 MB B1149 Glareosae elynoides MOR599 NV B247 Filifoliae glaucescens MOR660 MS B308 Glaucescentes emoryi MOR619 DE B267 Phacocystis glaucodea MOR1327 IN B924 Griseae endlichii MOR1897 AZ B1489 Phacocystis globosa MOR654 CA B302 Acrocystis engelmannii MOR1933 BC B1525 Inflatae gmelinii MOR1431 AK B1022 Racemosae epapillosa MOR620 UT B268 Racemosae godfreyi MOR1589 AL B1180 Griseae exilis MOR621 DE B269 Stellulatae gracilescens MOR661 KY B309 Laxiflorae exsiccata MOR1778 BC B1369 Vesicariae gracilior MOR1494 CA B1085 Ovales extensa MOR1655 VA B1246 Spirostachyae gracillima MOR656 AL B304 Hymenochlaenae festucacea MOR626 TX B274 Ovales granularis MOR1209 MB B804 Granulares feta MOR627 CA B275 Ovales gravida MOR704 KN B352 Phaestoglochin filifolia MOR1234 CA B829 Filifoliae grayi MOR658 KN B306 Lupulinae fissa MOR614 TX B262 Multiflorae grisea MOR390 KY B037 Griseae fissuricola MOR1919 ID B1511 Aulocystis gynandra MOR698 DE B346 Phacocystis flacca MOR1611 MI B1202 Thuringiaca gynocrates MOR1432 AK B1023 Physoglochin flaccosperma MOR405 LO B052 Griseae gynodynama MOR1706 CA B1297 Hymenochlaenae

Appendix 2. DNA sample data halliana MOR1491 CA B1082 Paludosae integra MOR711 CA B359 Ovales hallii MOR1556 MB B1147 Racemosae interior MOR706 MI B354 Stellulatae harfordii MOR699 CA B347 Ovales interrupta MOR1468 OR B1059 Phacocystis hassei MOR1669 CA B1260 Bicolores intumescens MOR709 ME B357 Lupulinae haydeniana MOR668 NV B316 Phacocystis jamesii MOR364 AL B010 Phyllostachyae haydenii MOR1594 IA B1185 Phacocystis jonesii MOR1412 WA B1003 Vulpinae heleonastes MOR1756 AB B1347 Glareosae joorii MOR719 FL B367 Glaucescentes helleri MOR1266 NV B861 Racemosae juniperorum MOR365 KY B0011 Phyllostachyae hendersonii MOR1749 BC B1340 Laxiflorae klamathensis MOR1871 OR B1463 Paniceae heteroneura MOR659 NV B307 Racemosae kobomugi MOR713 VA B361 Macrocephalae heterostachya MOR1824 YT B1415 Paludosae kraliana MOR715 AR B363 Laxiflorae hirsutella MOR669 DE B317 Porocystis krausei MOR1441 AK B1032 Chlorostachyae hirta MOR681 PN B329 Carex lachenalii MOR1442 AK B1033 Glareosae hirtifolia MOR1277 QC B872 Hirtifoliae lacustris MOR725 MB B373 Paludosae hirtissima MOR1496 CA B1087 Hymenochlaenae laeviconica MOR1689 KS B1280 Carex hitchcockiana MOR391 KY B038 Griseae laeviculmis MOR1199 CA B794 Deweyanae holostoma MOR1433 AK B1024 Racemosae laevivaginata MOR727 AL B375 Vulpinae hoodii MOR1732 CA B1323 Phaestoglochin lapponica MOR1443 AK B1034 Paludosae hookerana MOR1915 AB B1507 Phaestoglochin lasiocarpa MOR731 AK B379 Paludosae hormathodes MOR1916 NS B1508 Ovales latebracteata MOR1185 AR B779 Phyllostachyae hostiana MOR1796 QC B1387 Ceratocystis lativena MOR1631 NM B1222 Hallerianae houghtoniana MOR1248 MB B843 Paludosae laxa MOR1445 AK B1036 Paniceae hyalina MOR646 MS B294 Ovales laxiculmis MOR1205 PN B800 Careyanae hyalinolepis MOR690 TX B338 Paludosae laxiflora MOR757 MI B405 Laxiflorae hystericina MOR815 AR B475 Vesicariae leavenworthii MOR759 AL B407 Phaestoglochin idahoa MOR1365 MO B956 Racemosae lemmonii MOR763 CA B411 Aulocystis illota MOR695 CA B343 Ovales lenticularis MOR750 CA B398 Phacocystis impressinervia MOR1586 MS B1177 Griseae leporinella MOR1415 WA B1006 Ovales incurviformis MOR1903 CO B1495 Foetidae leptalea MOR766 MI B414 Leptocephalae infirminervia MOR1200 CA B795 Deweyanae leptonervia MOR1196 MB B790 Laxiflorae inops MOR1803 BC B1394 Acrocystis leptopoda MOR1201 BC B796 Deweyanae

Appendix 2. DNA sample data limosa MOR769 AK B417 Limosae microchaeta MOR1748 YT B1339 Scitae livida MOR1212 NJ B807 Paniceae microdonta MOR1222 MS B817 Granulares loliacea MOR1452 AK B1043 Glareosae microglochin MOR1507 Stordalen B1098 Leucoglochin lonchocarpa MOR733 FL B381 Rostrales micropoda MOR1434 AK B1025 Dornera longii MOR735 AR B383 Ovales microptera MOR1682 CO B1273 Ovales louisianica MOR742 FL B390 Lupulinae misera MOR1566 TN B1157 Hymenochlaenae lucorum MOR1538 NC B1129 Acrocystis missouriensis MOR801 IL B460 Ovales lupuliformis MOR745 FL B393 Lupulinae mitchelliana MOR835 AL B495 Phacocystis lupulina MOR812 MD B472 Lupulinae molesta MOR804 DE B463 Ovales lurida MOR816 FL B476 Vesicariae molestiformis MOR807 AR B466 Ovales lutea MOR1567 NC B1158 Ceratocystis muehlenbergii MOR1768 AR B1359 Phaestoglochin luzulifolia MOR762 CA B410 Aulocystis multicaulis MOR826 AR B486 Ovales luzulina MOR1710 CA B1301 Aulocystis multicostata MOR827 CA B487 Ovales lyngbyei MOR819 OR B479 Phacocystis muricata MOR1912 Spain B1504 Phaestoglochin mackenziei MOR1459 AK B1050 Glareosae muriculata MOR1612 NM B1203 Phaestoglochin macloviana MOR1437 AK B1028 Ovales muskingumensis MOR849 MI B509 Ovales macrocephala MOR1236 AK B831 Macrocephalae nardina MOR1312 QC B909 Nardinae macrochaeta MOR1473 OR B1064 Limosae nebrascensis MOR850 CA B510 Phacocystis magellanica MOR1439 AK B1030 Limosae nelsonii MOR1634 MO B1225 Racemosae manhartii MOR1563 GE B1154 Laxiflorae nervina MOR1642 CA B1233 Vulpinae marina MOR1548 MB B1139 Glareosae neurophora MOR1417 WA B1008 Vulpinae mariposana MOR1686 AZ B1277 Ovales nigra MOR1297 NFLD B894 Phacocystis meadii MOR1544 MB B1135 Paniceae nigricans MOR1440 AK B1031 Dornera media MOR1574 NB B1165 Racemosae nigromarginata MOR855 AL B515 Acrocystis melanostachya MOR1352 OK B947b Paludosae normalis MOR793 AL B451 Ovales membranacea MOR784 AK B442 Vesicariae norvegica MOR1418 OR B1009 Racemosae mendocinensis MOR1475 OR B1066 Hymenochlaenae novae-angliae MOR795 ME B453 Acrocystis merritt-fernaldii MOR785 MB B443 Ovales nova MOR434 CO B081 Racemosae mertensii MOR790 AK B448 Racemosae nudata MOR1242 CAs B837 Phacocystis mesochorea MOR831 AL B491 Phaestoglochin obispoensis MOR1599 CA B1190 Hymenochlaenae michauxiana MOR1550 MB B1141 Rostrales obnupta MOR839 CA B499 Phacocystis

Appendix 2. DNA sample data obtusata MOR841 MB B501 Obtusatae petricosa MOR1797 QC B1388 Aulocystis occidentalis MOR1934 CA B1526 Phaestoglochin phaeocephala MOR995 NV B587 Ovales oklahomensis MOR845 AR B505 Vulpinae picta MOR893 GA B553 Pictae oligocarpa MOR1334 AR B931 Griseae pigra MOR1587 MS B1178 Griseae oligosperma MOR846 NH B506 Vesicariae pityophila MOR1632 NM B1223 Acrocystis opaca MOR867 OK B527 Ovales planispicata MOR400 MD B047 Griseae oreocharis MOR1678 AZ B1269 Filifoliae planostachys MOR884 TXc B544 Hallerianae ormostachya MOR868 MI B528 Laxiflorae plantaginea MOR1695 TN B1286 Careyanae oronensis MOR1700 ME B1291 Ovales platyphylla MOR886 MD B546 Careyanae ouachitana MOR1340 AR B937 Griseae pluriflora MOR1758 AK B1349 Limosae ovalis MOR1582 WS B1173 Ovales podocarpa MOR1734 BC B1325 Scitae oxylepis MOR871 KY B531 Hymenochlaenae polymorpha MOR890 PN B550 Paniceae ozarkana MOR857 AR B517 Ovales praeceptorum MOR1754 CA B1345 Glareosae pachystachya MOR1666 AK B1257 Ovales praegracilis MOR891 CA B551 Divisae paeninsulae MOR1247 FLc B842 Griseae prairea MOR1753 BC B1344 Heleoglochin paleacea MOR861 ME B521 Phacocystis prasina MOR900 GA B560 Hymenochlaenae pallescens MOR1810 B1401 Porocystis praticola MOR897 CO B557 Ovales panicea MOR1708 ME B1299 Paniceae preslii MOR976 OR B568 Ovales pansa MOR1766 CA B1357 Divisae projecta MOR978 MB B570 Ovales parryana MOR1436 AK B1027 Racemosae proposita MOR1743 CA B1334 Ovales pauciflora MOR876 AK B536 Leucoglochin pseudocyperus MOR981 B573 Vesicariae paupercula MOR898 B558 Limosae pumila MOR1869 NC B1461 Paludosae peckii MOR1427 AK B1018 Acrocystis purpurifera MOR1272 KY B867 Laxiflorae pedunculata MOR881 MA B541 Clandestinae pyrenaica MOR1400 WA B991 Dornera pellita MOR882 CA B542 Paludosae radfordii MOR1240 SC B835 Laxiflorae pelocarpa MOR997 NV B589 Racemosae radiata MOR1000 MI B592 Phaestoglochin pendula MOR999 Austria B591 Rhynchocystis ramenskii MOR1241 AK B836 Phacocystis pensylvanica MOR973 MB B565 Acrocystis rariflora MOR1801 YT B1392 Limosae perdentata MOR993 TX B585 Phaestoglochin raynoldsii MOR986 CA B578 Racemosae perglobosa MOR1605 CO B1196 Foetidae recta MOR1947 B1539 Phacocystis petasata MOR994 UT B586 Ovales reniformis MOR989 GA B581 Ovales

Appendix 2. DNA sample data retroflexa MOR992 DE B584 Phaestoglochin siccata MOR1872 ON B1464 Ammoglochin retrorsa MOR1012 MI B603 Vesicariae silicea MOR1034 DE B625 Ovales reznicekii MOR1014 AL B605 Acrocystis simulata MOR1086 CA B678 Divisae richardsonii MOR1022 MD B613 Clandestinae socialis MOR1090 AL B682 Phaestoglochin roanensis MOR1026 NC B617 Hymenochlaenae sparganioides MOR1091 DE B683 Phaestoglochin rosea MOR1016 ME B607 Phaestoglochin specifica MOR1094 CA B686 Ovales rossii MOR1003 CA B595 Acrocystis spectabilis MOR1781 BC B1372 Scitae rostrata MOR1402 WA B993 Vesicariae specuicola MOR1616 AZ B1207 Racemosae rotundata MOR1551 MB B1142 Vesicariae spicata MOR1073 DE B665 Phaestoglochin rupestris MOR1923 Spain B1515 Rupestres spissa MOR1617 AZ B1208 Hispidae ruthii MOR1008 NC B600a Stellulatae sprengelii MOR1568 NB B1159 Hymenochlaenae sabulosa MOR1448 YT B1039 Racemosae squarrosa MOR1083 AR B675 Squarrosae salina MOR1755 QC B1346 Phacocystis stenoptila MOR1084 UT B676 Ovales sartwelliana MOR1600 CA B1191 Paludosae sterilis MOR1545 MB B1136 Stellulatae sartwellii MOR1784 BC B1375 Holarrhenae stevenii MOR1512 CO B1103 Racemosae saxatilis MOR1025 B616 Vesicariae stipata MOR1055 MB B646 Vulpinae saximontana MOR1529 CO B1120 Phyllostachyae straminea MOR1054 DE B645 Ovales scabrata MOR1045 GA B636 Anomalae straminiformis MOR1068 UT B660 Ovales scabriuscula MOR1048 CA B639 Scirpinae striata MOR1076 FL B668 Paludosae schottii MOR1772 CA B1363 Phacocystis striatula MOR1066 DE B658 Laxiflorae schweinitzii MOR1058 MI B649 Vesicariae stricta MOR1098 TX B690 Phacocystis scirpoidea MOR1050 AK B641 Scirpinae styloflexa MOR1101 GA B693 Laxiflorae scoparia MOR1057 ME B648 Ovales stylosa MOR1292 NFLD B889 Racemosae scopulorum MOR1039 CA B630 Phacocystis subbracteata MOR1757 CA B1348 Ovales senta MOR1687 AZ B1278 Phacocystis suberecta MOR1361 AR B953 Ovales seorsa MOR1044 DE B635 Stellulatae subfusca MOR1670 CA B1261 Ovales serpenticola MOR1763 CA B1354 Acrocystis subnigricans MOR1476 OR B1067 Inflatae serratodens MOR1028 CA B619 Racemosae subspathacea MOR1449 AK B1040 Phacocystis sheldonii MOR1495 CA B1086 Carex superata MOR366 KY B012 Phyllostachyae shinnersii MOR1027 KN B618 Ovales supina MOR1596 AK B1187 Lamprochlaenae shortiana MOR1031 KN B622 Shortianae swanii MOR1107 B700 Porocystis

Appendix 2. DNA sample data sychnocephala MOR1702 ON B1293 Cyperoideae vacillans MOR1691 ME B1282 Phacocystis sylvatica MOR1392 WA B983 Hymenochlaenae vaginata MOR1776 YT B1367 Paniceae tahoensis MOR1477 OR B1068 Ovales vallicola MOR1788 BC B1379 Phaestoglochin tenax MOR1110 LO B703 Hallerianae venusta MOR1174 MS B767 Hymenochlaenae tenera MOR1552 MB B1143 Ovales vernacula MOR1264 CA B859 Foetidae tenuiflora MOR1115 MB B708 Glareosae verrucosa MOR1175 FL B768 Glaucescentes tetanica MOR1116 MB B709 Paniceae vesicaria MOR1162 DE B755 Vesicariae tetrastachya MOR1071 TXk B663 Ovales vestita MOR1165 DE B758 Paludosae texensis MOR1482 CA B1073 Phaestoglochin vexans MOR1168 FLh B761 Ovales thornei MOR1542 GA B1133 Griseae virescens MOR1158 AL B751 Porocystis thurberi MOR1618 AZ B1209 Vesicariae viridula MOR1750 NS B1341 Ceratocystis timida MOR359 AL B005 Phyllostachyae viridustellata MOR1820 B1411 Ceratocystis tincta MOR1144 ME B737 Ovales vulpinoidea MOR1153 CA B746 Multiflorae tompkinsii MOR1485 CA B1076 Firmiculmes whitneyi MOR1154 CA B747 Leucoglochin tonsa MOR1119 B712 Acrocystis wiegandii MOR1155 ME B748 Stellulatae torreyi MOR1510 CO B1101 Porocystis willdenowii MOR358 KY B003 Phyllostachyae torta MOR1122 PN B715 Phacocystis williamsii MOR1771 YT B1362 Chlorostachyae triangularis MOR1146 TX B739 Multiflorae woodii MOR1592 IA B1183 Paniceae tribuloides MOR1125 B718 Ovales wootonii MOR1615 AZ B1206 Ovales trichocarpa MOR1133 DE B726 Carex xerantica MOR1715 ON B1306 Ovales triquetra MOR1602 CA B1193 Triquetrae trisperma MOR1136 MI B729 Glareosae tuckermanii MOR1147 MI B740 Vesicariae tumulicola MOR1140 CA B733 Phaestoglochin turbinata MOR1679 AZ B1270 Acrocystis turgescens MOR1244 MS B839 Rostrales typhina MOR1132 AR B725 Squarrosae umbellata MOR1179 MB B772 Acrocystis unilateralis MOR1394 WA B985 Ovales ursina MOR1777 YT B1368 Glareosae utriculata MOR1181 AK B774 Vesicariae

100

Appendix 2. DNA sample data

Table A2.2 Voucher information for outgroups used in this study. DNA Collection Accession number Species name number Herbarium number Collector(s) Country Province STA1816 Trichophourm alpinum 861 CAN 312672 Porsild, R T Canada Yukon STA1817 Trichophorum cespitosum 1219 CAN 589883 Saarela, J M; Percy, D M Canada British Columbia

101

Appendix 3. Supplementary Figures for Chapter 3

Fig. A3.1 Climate data plotted on the Carex spp. ultrametric phylogeny. Climate variables were taken from the BIOCLIM WorldClim database. Principal component analysis (PCA) was used to reduce the means of 19 BIOCLIM variables (prcomp in R) into climate PC1 and PC2. The map was generated using the contMap function in the phytools package for R. N=445.

102

Appendix 3. Supplementary Figures for Chapter 3

Fig. A3.2 Habitat data plotted on the Carex spp. ultrametric phylogeny. Light habitat was scored by experts. Wetness habitat was taken from the National Wetland Plant List (NWPL; Lichvar, 2012). Species missing from the NWPL were scored by experts for wetness habitat. The map was generated using the contMap function in the phytools package for R. Light habitat N=463, wetness habitat N=460.

103

Appendix 3. Supplementary Figures for Chapter 3

Fig. A3.3 Morphological data for those individuals with complete data sampling (data for four characters available) plotted on the Carex spp. ultrametric phylogeny. Morphological data was extracted from the Flora of North America (2002). Principal component analysis was used to reduce the number of morphological variables. Only PC1 and PC2 were analysed. The map was generated using the contMap function in the phytools package for R. N=371.

104

Appendix 4: Maximum Likelihood gene trees

Attached are the gene trees used to select sequences for final analysis. Unfortunately, they cannot be viewed in the printed version of this thesis. In the PDF file, tree topology and label information can be seen by zooming in.

105

Carex_ovalis_MOR_1419_WA_B1010_OV 100 Maximum likelihood ETS gene tree. Constructed using Carex_ovalis_MOR_1582_WS_B1173_OV Carex_scoparia_tessellata_MOR_1698_ME_B1289_OV RAxML, with a GTRCAT model of evolution and a 200 bootstrap 43Carex_scoparia_tessellata_MOR_1038_STARR_B629 analysis. Bootstrap values are plotted on the tree. Carex_scoparia_MOR_1037_STARR_B62840 35Carex_alata_MOR_1359_STARR_B951 Carex_scoparia_tessellata_MOR_1685_ME_B1276_OV 4255 Carex_albolutescens_MOR_427_STARR_B074 65 30 45Carex_alata_MOR_422_STARR_B069 51 37 Carex_suberecta_MOR_1361_B953_OV 27Carex_albolutescens_MOR_428_OK_B075_OV Carex_scoparia_MOR_1036_STARR_B627 91 Carex_scoparia_scoparia_MOR_1057_ME_B648_OV Carex_scoparia_MOR_1319_STARR_B916 Carex_vexans_MOR_1167_STARR_B760 9641 Carex_vexans_MOR_1168_FLh_B761_OV Carex_vexans_MOR_1169_STARR_B76223 Carex_tribuloides_MOR_1124_STARR_B71719 Carex_longii_MOR_735_AR_B383_OV 1791 3210Carex_longii_MOR_734_STARR_B382 Carex_longii_MOR_740_STARR_B388 Carex_festucacea_MOR_625_STARR_B273 32 Carex_alata_MOR_421_AL_B068_OV 35Carex_alata_MOR_420_STARR_B067 22 Carex_albolutescens_MOR_435_MD_B082_OV Carex_harfordii_MOR_699_CA_B347_OV Carex_brevior_MOR_495_STARR_B143 Carex_merritt-fernaldii_MOR_1736_ON_B1327_OV 52 264676Carex_brevior_MOR_497_STARR_B145 Carex_brevior_MOR_1625_BC_B1216_OV66 52Carex_brevior_MOR_496_STARR_B144 36Carex_B0945b_MOR_1348_STARR Carex_molestiformis_MOR_809_STARR_B468 Carex_tetrastachya_MOR_1070_STARR_B662 63Carex_tetrastachya_MOR_1071_TXk_B663_OV 4063 Carex_tetrastachya_MOR_1072_STARR_B664 1 Carex_hyalina_MOR_647_STARR_B295 74 7167Carex_hyalina_MOR_646_MS_B294_OV Carex_hyalina_MOR_636_STARR_B284 39 Carex_reniformis_MOR_988_STARR_B580 81Carex_reniformis_MOR_990_STARR_B582 3557 Carex_reniformis_MOR_989_GA_B581_OV Carex_molestiformis_MOR_806_STARR_B465 Carex_molestiformis_MOR_807_AR_B466_OV Carex_molesta_MOR_804_DE_B463_OV Carex_oronensis_MOR_1700_ME_B1291_OV Carex_oronensis_MOR_869_STARR_B529 31Carex_shinnersii_MOR_1027_KN_B618_OV Carex_shinnersii_MOR_1663_KN_B1254_OV 6050 Carex_missouriensis_MOR_802_STARR_B461 7 58 6Carex_missouriensis_MOR_801_IL_B460_OV Carex_tincta_MOR_1316_STARR_B913 36 Carex_tenera_MOR_1317_STARR_B914 19 Carex_tenera_tenera_MOR_1583_WI_B1174_OV 4541 Carex_tenera_tenera_MOR_1552_MB_B1143_OV 37Carex_tenera_echinodes_MOR_1112_MI_B705_OV Carex_tenera_tenera_MOR_1113_STARR_B7065 9Carex_festucacea_MOR_624_STARR_B272 10Carex_tincta_MOR_1144_ME_B737_OV 25 Carex_bebbii_MOR_480_STARR_B128 Carex_cumulata_MOR_605_IL_B253_OV Carex_cumulata_MOR_1894_ON_B1486_OV Carex_opaca_MOR_867_OK_B527_OV 57 Carex_opaca_MOR_866_STARR_B526 Carex_bicknellii_MOR_478_IN_B126_OV 601 128Carex_merritt_fernaldii_MOR_785_MB_B443_OV 43 1Carex_festucacea_MOR_626_TX_B274_OV 1 Carex_normalis_MOR_772_STARR_B420 3 Carex_molesta_MOR_805_STARR_B464 1Carex_silicea_MOR_1570_NB_B1161_OV 24 Carex_bicknellii_MOR_477_STARR_B125 2Carex_silicea_MOR_1034_DE_B625_OV Carex_normalis_MOR_1595_IA_B1186_OV 10 Carex_B1455_MOR_1863_STARR Carex_bicknellii_MOR_1697_ON_B1288_OV Carex_tribuloides_MOR_1125_STARR_B718 37Carex_tribuloides_tribuloides_MOR_1311_STARR_B908 57Carex_tribuloides_MOR_1126_STARR_B719 60 Carex_tribuloides_tribuloides_MOR_1128_KN_B721_OV Carex_projecta_MOR_978_MB_B570_OV Carex_cristatella_MOR_792_STARR_B450 28 Carex_tribuloides_MOR_1123_STARR_B716 Carex_cristatella_MOR_533_STARR_B181 10165 Carex_cristatella_MOR_534_KY_B182_OV 5 19Carex_crawfordii_MOR_522_NY_B170_OV 3 Carex_bebbii_MOR_1917_ON_B1509_OV318 514 Carex_bebbii_MOR_479_MB_B127_OV 6 37Carex_projecta_MOR_1571_NB_B1162_OV 8Carex_projecta_MOR_1398_STARR_B989 7 18Carex_crawfordii_MOR_521_STARR_B169 Carex_tribuloides_sangamonensis_MOR_1751_LA_B1342_OV 21Carex_cristatella_MOR_557_DE_B205_OV Carex_tribuloides_sangamonensis_MOR_1127_KN_B720_OV Carex_projecta_MOR_979_STARR_B571 Carex_bebbii_MOR_1315_STARR_B912 53 82 Carex_tenera_tenera_MOR_1114_STARR_B707 Carex_muskingumensis_MOR_848_STARR_B508 47 Carex_normalis_MOR_793_AL_B451_OV 8 Carex_muskingumensis_MOR_849_MI_B509_OV 94Carex_muskingumensis_MOR_829_STARR_B489 1 95 2 Carex_muskingumensis_MOR_1746_ON_B1337_OV Carex_merritt_fernaldii_MOR_787_STARR_B445 17 2 Carex_merritt_fernaldii_MOR_786_STARR_B444 Carex_silicea_MOR_1035_STARR_B626 Carex_bebbii_MOR_1712_ON_B1303_OV Carex_suberecta_MOR_1591_IA_B1182_OV Carex_molesta_MOR_803_STARR_B462 Carex_straminea_MOR_1052_STARR_B643 20 Carex_hormathodes_MOR_635_STARR_B283 Carex_hormathodes_MOR_1916_NS_B1508_OV16 Carex_straminea_MOR_1054_DE_B645_OV 6861 Carex_straminea_MOR_1053_STARR_B644 33Carex_ozarkana_MOR_874_STARR_B53470 63 66Carex_ozarkana_MOR_857_AR_B517_OV Carex_ozarkana_MOR_858_STARR_B518 Carex_hormathodes_MOR_1309_STARR_B906 Carex_feta_MOR_627_CA_B275_OV Carex_adusta_MOR_1307_STARR_B904 63 57Carex_adusta_MOR_1874_AB_B1466_OV Carex_adusta_MOR_413_STARR_B060 Carex_feta_MOR_1403_STARR_B994 Carex_subfusca_MOR_1103_STARR_B696 20 Carex_mariposana_MOR_798_STARR_B456 Carex_subfusca_MOR_1104_STARR_B6974442 42 63Carex_abrupta_MOR_409_STARR_B056 Carex_abrupta_MOR_1259_STARR_B85463 44 65Carex_subfusca_MOR_1670_CA_B1261_OV Carex_stenoptila_MOR_1084_UT_B676_OV 89Carex_abrupta_MOR_1641_ID_B1232_OV 54Carex_abrupta_MOR_860_BC_B520_OV Carex_macloviana_MOR_1437_AK_B1028_OV46 14 4524 Carex_abrupta_MOR_1258_STARR_B853 68Carex_stenoptila_MOR_1511_CO_B1102_OV Carex_pachystachya_MOR_1666_AK_B1257_OV 79Carex_gracilior_MOR_655_STARR_B303 9 74Carex_gracilior_MOR_1719_CA_B1310_OV 80 56Carex_subbracteata_MOR_1757_CA_B1348_OV Carex_gracilior_MOR_1494_CA_B1085_OV 60Carex_preslii_MOR_976_OR_B568_OV 92 Carex_pachystachya_MOR_859_STARR_B519 Carex_unilateralis_MOR_1650_BC_B1241_OV Carex_unilateralis_MOR_1394_STARR_B985 5592 50 Carex_athrostachya_MOR_461_STARR_B109 Carex_unilateralis_MOR_1478_OR_B1069_OV33 Carex_athrostachya_MOR_460_STARR_B108 73 Carex_unilateralis_MOR_1767_BC_B1358_OV Carex_leporinella_MOR_778_STARR_B426 72 28Carex_leporinella_MOR_1415_WA_B1006_OV Carex_sychnocephala_MOR_1108_STARR_B701 86 Carex_sychnocephala_MOR_1702_ON_B1293_CP 14 49Carex_tahoensis_MOR_1477_OR_B1068_OV 71 Carex_xerantica_MOR_1715_ON_B1306_OV 42Carex_arapahoensis_MOR_1932_CO_B1524_OV 28 20 18 Carex_petasata_MOR_994_UT_B586_OV92 Carex_xerantica_MOR_1780_BC_B1371_OV Carex_shinnersii_MOR_1347_STARR_B945 Carex_sychnocephala_MOR_1782_BC_B1373_CP Carex_foenea_MOR_1739_ON_B1330_OV 23 19Carex_foenea_MOR_643_STARR_B291 Carex_foenea_MOR_1802_BC_B1393_OV 64 Carex_praticola_MOR_897_CO_B557_OV 97Carex_praticola_MOR_896_STARR_B556 81 Carex_praticola_MOR_1920_ON_B1512_OV Carex_straminiformis_MOR_1069_CA_B661_OV 92Carex_preslii_MOR_975_BC_B567_OV 91 Carex_straminiformis_MOR_1664_ID_B1255_OV 177 Carex_straminiformis_MOR_1068_UT_B660_OV Carex_mariposana_MOR_1686_AZ_B1277_OV 84 Carex_douglasii_MOR_1658_CA_B1249_DV 43 23 Carex_macloviana_MOR_1675_AZ_B1266_OV 47 99 90Carex_macloviana_MOR_1729_BC_B1320_OV Carex_microptera_MOR_832_STARR_B492 18 Carex_integra_MOR_722_STARR_B370 49 32 94Carex_integra_MOR_712_STARR_B360 Carex_integra_MOR_711_CA_B359_OV Carex_fracta_MOR_630_CA_B278_OV 82Carex_fracta_MOR_629_STARR_B277 65 Carex_fracta_MOR_631_STARR_B279 Carex_wootonii_MOR_1172_STARR_B765 84 45 Carex_wootonii_MOR_1615_AZ_B1206_OV 14Carex_egglestonii_MOR_1517_CO_B1108_OV 63 Carex_egglestonii_MOR_1504_CO_B1095_OV78 Carex_egglestonii_MOR_1610_UT_B1201_OV Carex_microptera_MOR_834_STARR_B49481 Carex_haydeniana_MOR_668_STARR_B316 4Carex_microptera_MOR_1826_YT_B1417_OV Carex_arapahoensis_MOR_1904_CO_B1496_OV Carex_microptera_MOR_833_STARR_B493 5 2 Carex_ebenea_MOR_1672_AZ_B1263_OV 99 26 62 5 2 40 1 Carex_multicostata_MOR_828_STARR_B488 Carex_multicostata_MOR_1707_OR_B1298_OV 4365 Carex_multicostata_MOR_827_CA_B487_OV91 134 Carex_multicostata_MOR_1688_OR_B1279_OV 1Carex_ebenea_MOR_683_STARR_B331 Carex_ebenea_MOR_1711_WY_B1302_OV 9Carex_ebenea_MOR_1886_UT_B1478_OV Carex_microptera_MOR_1682_CO_B1273_OV Carex_arapahoensis_MOR_1527_CO_B1118_OV Carex_B1428_MOR_1837_STARR 96Carex_petasata_MOR_1260_CA_B855_OV 67 Carex_davyi_MOR_1261_CA_B856_OV 40Carex_praticola_MOR_1671_UT_B1262_OV Carex_phaeocephala_MOR_995_NV_B587_OV 64Carex_stenoptila_MOR_1362_MO_B954_OV 90 Carex_pachystachya_MOR_1528_CO_B1119_OV 35Carex_phaeocephala_MOR_1742_BC_B1333_OV58 43 Carex_proposita_MOR_1399_STARR_B99073 78 981 Carex_proposita_MOR_1743_CA_B1334_OV Carex_proposita_MOR_1639_ID_B1230_OV Carex_congdonii_MOR_1741_STARR_B1332 Carex_argyrantha_MOR_468_MD_B116_OV Carex_argyrantha_MOR_1875_QC_B1467_OV56 49 Carex_argyrantha_MOR_469_STARR_B117 Carex_brunnescens_MOR_498_CA_B146_GO 100 100Carex_laeviculmis_MOR_377_STARR_B024 Carex_laeviculmis_MOR_1199_CA_B794_DE Carex_seorsa_MOR_1020_STARR_B611 25 100Carex_seorsa_MOR_1044_DE_B635_SL Carex_seorsa_MOR_1024_STARR_B615 66 Carex_exilis_MOR_622_STARR_B270 Carex_exilis_MOR_623_STARR_B271 6295 59Carex_exilis_MOR_621_DE_B269_SL Carex_exilis_MOR_1585_MS_B1176_SL Carex_davisii_MOR_1355_STARR_B949 Carex_echinata_phyllomanica_MOR_1786_BC_B1377_SL Carex_muricata_MOR_1738_STARR_B1329 5150Carex_echinata_MOR_604_STARR_B252 91 1248Carex_echinata_MOR_602_STARR_B250 35Carex_echinata_echinata_MOR_1435_AK_B1026_SL 49 324431Carex_echinata_phyllomanica_MOR_1457_AK_B1048_SL Carex_echinata_MOR_603_STARR_B251 Carex_echinata_ssp_echinata_MOR_1313_STARR_B910 Carex_echinata_phyllomanica_MOR_1385_WA_B976_SL Carex_atlantica_capillacea_MOR_452_FL_B100_SL 68Carex_ruthii_MOR_1009_STARR_B600b 51Carex_ruthii_MOR_1008_NC_B600a_SL Carex_ruthii_MOR_1007_STARR_B599169 3 Carex_atlantica_MOR_462_STARR_B110 57Carex_atlantica_MOR_483_STARR_B131 31 7 6938Carex_atlantica_MOR_463_STARR_B111 Carex_atlantica_capillacea_MOR_450_STARR_B098 Carex_atlantica_capillacea_MOR_451_STARR_B099 Carex_interior_MOR_706_STARR_B354 209Carex_interior_MOR_705_MD_B353_SL 42 18 Carex_melanostachya_MOR_1351_STARR_B947 81 Carex_wiegandii_MOR_1155_ME_B748_SL 64 Carex_atlantica_atlantica_MOR_1360_NC_B952_SL 56Carex_sterilis_MOR_1545_MB_B1136_SL 87 Carex_sterilis_MOR_1085_STARR_B677 Carex_leptopoda_MOR_1201_BC_B796_DE 64Carex_cephalophorum_MOR_1828_STARR_B1419 72 64Carex_leptopoda_MOR_378_STARR_B025 58Carex_leptopoda_MOR_1210_STARR_B805 Carex_bolanderi_MOR_1216_CA_B811_DE Carex_bolanderi_MOR_373_STARR_B019 5069 46 8144Carex_bolanderi_MOR_1217_STARR_B812 Carex_bolanderi_MOR_1218_STARR_B813 100 43 100Carex_deweyana_deweyana_MOR_773_MB_B421_DE Carex_deweyana_collectanea_MOR_1813_QC_B1404_DE 5790Carex_deweyana_deweyana_MOR_774_BC_B422_DE 99 Carex_deweyana_deweyana_MOR_754_STARR_B40287 Carex_deweyanavar.collectanea_MOR_1812_QC_B1403_DE99 Carex_deweyana_collectanea_MOR_1814_QC_B1405_DE Carex_deweyana_deweyana_MOR_1381_STARR_B972 Carex_bonanzensis_MOR_1622_AK_B1213_GO 97 97Carex_bonanzensis_MOR_1623_NT_B1214_GO Carex_bonanzensis_MOR_1905_YT_B1497_GO Carex_canescens_MOR_546_CA_B194_GO Carex_arctiformis_MOR_1653_BC_B1244_GO 11 29Carex_canescens_canescens_MOR_1377_STARR_B968 55 Carex_canescens_disjuncta_MOR_1561_NC_B1152_GO 40Carex_canescens_canescens_MOR_1289_NFLD_B886_GO 3538Carex_canescens_disjuncta_MOR_1298_STARR_B895 Carex_lapponica_MOR_1822_NT_B1413_GO35 22 2239 14Carex_laeviculmis_MOR_1831_BC_B1422_DE 92 Carex_canescens_disjuncta_MOR_1283_STARR_B879 Carex_canescens_MOR_545_STARR_B193 10 Carex_canescens_canescens_MOR_544_STARR_B192 5 Carex_paupercula_MOR_983_STARR_B575 77 Carex_lapponica_MOR_1443_AK_B1034_PD 74 Carex_praeceptorum_MOR_1397_STARR_B988 79Carex_praeceptorum_MOR_889_STARR_B549 39 Carex_praeceptorum_MOR_1754_CA_B1345_GO 95 84Carex_heleonastes_MOR_1458_AK_B1049_GO 60Carex_marina_MOR_1548_MB_B1139_GO 83 59Carex_heleonastes_MOR_1549_MB_B1140_GO Carex_loliacea_MOR_1452_AK_B1043_GO Carex_heleonastes_MOR_1756_AB_B1347_GO 17 Carex_ursina_MOR_1936_YT_B1528_GO 93 84 87 35Carex_ursina_MOR_1777_YT_B1368_GO Carex_glareosa_MOR_1558_MB_B1149_GO 97 Carex_lachenalii_MOR_1442_AK_B1033_GO 22 61 Carex_mackenziei_MOR_1459_AK_B1050_GO 98 75 Carex_mackenziei_MOR_1294_STARR_B891 Carex_trisperma_MOR_1256_STARR_B851 100 98Carex_trisperma_MOR_1255_STARR_B850 Carex_trisperma_MOR_1257_STARR_B852 Carex_trisperma_MOR_1138_STARR_B73198 94 Carex_trisperma_MOR_1136_MI_B729_GO98 Carex_trisperma_trisperma_MOR_1137_STARR_B730 Carex_athrostachya_MOR_1349_SK_B946_OV 98Carex_brunnescens_sphaerostachya_MOR_1880_ON_B1472_GO 98 Carex_brunnescens_MOR_507_STARR_B155 Carex_illota_MOR_1408_STARR_B999 Carex_illota_MOR_703_STARR_B351 8789 63Carex_illota_MOR_694_STARR_B342 69 68Carex_illota_MOR_1519_CO_B1110_OV Carex_illota_MOR_695_CA_B343_OV 94 Carex_arcta_MOR_1363_STARR_B955 30Carex_arcta_MOR_445_STARR_B093 49Carex_crawfordii_MOR_1832_STARR_B1423 9972 Carex_arcta_MOR_444_AK_B092_GO Carex_bebbii_MOR_1836_STARR_B1427 Carex_divisa_MOR_1913_Spain_B1505_DV 62 Carex_divisa_MOR_1866_MD_B1458_DV 77 Carex_spicata_MOR_1074_STARR_B666 86Carex_muricata_lamprocarpa_MOR_1912_Spain_B1504_PG 83Carex_divulsa_MOR_1939_STARR_B1531 9883 Carex_divulsa_MOR_1383_WA_B974_PG Carex_divulsa_divulsa_MOR_580_STARR_B228 Carex_disperma_MOR_591_STARR_B239 24 66 64Carex_disperma_MOR_1454_AK_B1045_DS 33 100Carex_disperma_MOR_590_STARR_B238 Carex_disperma_MOR_581_STARR_B229 Carex_gynocrates_MOR_1503_CO_B1094_PY 14 Carex_gynocrates_MOR_1299_STARR_B896 100 87 100Carex_gynocrates_MOR_689_STARR_B337 43 Carex_gynocrates_MOR_1432_AK_B1023_PY Carex_arenaria_MOR_467_DE_B115_AM 67 Carex_stipata_MOR_1305_STARR_B902 Carex_laevivaginata_MOR_727_AL_B375_VU 10094 Carex_laevivaginata_MOR_726_STARR_B374 67Carex_laevivaginata_MOR_728_STARR_B376 Carex_stipata_stipata_MOR_1055_MB_B646_VU16 Carex_stipata_maxima_MOR_1063_FL_B654_VU 4430 Carex_stipata_MOR_1056_STARR_B647 4 18 Carex_stipata_MOR_1064_STARR_B656 86 Carex_stipata_maxima_MOR_1062_STARR_B653 Carex_hookerana_MOR_1795_MN_B1386_PG 85 Carex_hookerana_MOR_1915_AB_B1507_PG Carex_hoodii_MOR_632_STARR_B280 63 Carex_occidentalis_MOR_1628_NM_B1219_PG26 Carex_occidentalis_MOR_1630_NM_B1221_PG Carex_tumulicola_MOR_1140_CA_B733_PG27 92 10022Carex_tumulicola_MOR_1393_STARR_B984 20Carex_occidentalis_MOR_842_STARR_B502 Carex_hoodii_MOR_634_STARR_B282 4166Carex_hoodii_MOR_1732_CA_B1323_PG 91 Carex_hoodii_MOR_633_STARR_B281 Carex_vallicola_MOR_1265_STARR_B860 37 Carex_sartwellii_MOR_1784_BC_B1375_HH 55 100Carex_sartwellii_MOR_1010_STARR_B601 77 Carex_sartwellii_MOR_1021_STARR_B612 66 Carex_chordorrhiza_MOR_567_STARR_B215 100 100Carex_chordorrhiza_MOR_1727_BC_B1318_CH Carex_chordorrhiza_MOR_1318_STARR_B915 Carex_incurviformis_MOR_1903_CO_B1495_FO Carex_incurviformis_MOR_1787_BC_B1378_FO93 42 Carex_incurviformis_MOR_1525_CO_B1116_FO 99 Carex_duriuscula_MOR_1455_AK_B1046_DV 100Carex_B1450_MOR_1858_STARR 100 74 Carex_B1451_MOR_1859_STARR Carex_siccata_MOR_1033_STARR_B624 Carex_siccata_MOR_644_CO_B292_AM 6466 61Carex_siccata_MOR_1872_ON_B1464_AM Carex_siccata_MOR_1662_NM_B1253_AM Carex_bromoides_MOR_374_STARR_B020 Carex_bromoides_montana_MOR_376_NC_B023_DE 10021 100Carex_bromoides_montana_MOR_1654_VA_B1245_DE Carex_bromoides_MOR_375_STARR_B021 Carex_nervina_MOR_1642_CA_B1233_VU 100 Carex_nervina_MOR_1692_CA_B1283_VU 100 Carex_nervina_MOR_1884_NV_B1476_VU 52 Carex_crus_corvi_MOR_555_STARR_B203 97 100Carex_crus_corvi_MOR_554_STARR_B202 Carex_crus_corvi_MOR_556_FL_B204_VU Carex_neurophora_MOR_1417_WA_B1008_VU 100 Carex_neurophora_MOR_1627_WY_B1218_VU Carex_decomposita_MOR_572_STARR_B220 66 100Carex_decomposita_MOR_571_STARR_B219 Carex_decomposita_MOR_570_DE_B218_HE Carex_pansa_MOR_1462_OR_B1053_DV Carex_occidentalis_MOR_1934_CA_B1526_PG Carex_praegracilis_MOR_891_STARR_B55113 62 Carex_praegracilis_MOR_902_STARR_B562 464 Carex_alma_MOR_430_STARR_B077 624 1415Carex_alma_MOR_437_CA_B085_MF 100 82 47Carex_occidentalis_MOR_1661_NV_B1252_PG 8645Carex_pansa_MOR_1766_CA_B1357_DV Carex_praegracilis_MOR_892_ME_B552_DV Carex_alma_MOR_1873_UT_B1465_MF Carex_chihuahuensis_MOR_1614_AZ_B1205_MF 84 Carex_simulata_MOR_1390_STARR_B981 100Carex_simulata_MOR_1086_CA_B678_DV 53 Carex_simulata_MOR_1087_STARR_B679 Carex_diandra_MOR_575_STARR_B223 64 Carex_diandra_MOR_1321_STARR_B918 57 99 61 Carex_diandra_MOR_1382_STARR_B973 Carex_prairea_MOR_1573_NB_B1164_HE 6467 63Carex_diandra_MOR_574_CA_B222_HE 21 89 Carex_prairea_MOR_1569_NB_B1160_HE Carex_prairea_MOR_1753_BC_B1344_HE 94 Carex_prairea_MOR_903_STARR_B563 79Carex_cusickii_MOR_1231_STARR_B826 96Carex_cusickii_MOR_606_STARR_B254 51 96Carex_cusickii_MOR_1806_BC_B1397_HE Carex_cusickii_MOR_1379_STARR_B970 Carex_oklahomensis_MOR_845_AR_B505_VU 100Carex_oklahomensis_MOR_843_STARR_B503 63 Carex_oklahomensis_MOR_844_STARR_B504 Carex_densa_MOR_1690_CA_B1281_MF Carex_triangularis_MOR_1146_TX_B739_MF Carex_densa_MOR_1471_OR_B1062_MF 26 Carex_densa_MOR_1380_STARR_B971 16 92 Carex_densa_MOR_573_CA_B221_MF 51 Carex_conjuncta_MOR_520_STARR_B168 75 99Carex_conjuncta_MOR_518_DE_B166_VU Carex_conjuncta_MOR_519_STARR_B167 38 82 Carex_alopecoidea_MOR_1322_STARR_B919 67Carex_alopecoidea_MOR_448_STARR_B096 52 Carex_alopecoidea_MOR_1530_IL_B1121_VU Carex_sparganioides_MOR_1091_DE_B683_PG Carex_gravida_MOR_716_STARR_B3645 4069Carex_aggregata_MOR_418_STARR_B065 7214 Carex_aggregata_MOR_419_KY_B066_PG 58Carex_sparganioides_MOR_1093_STARR_B685 19Carex_gravida_MOR_704_KN_B352_PG 50 4929Carex_cephaloidea_MOR_550_STARR_B198 24Carex_cephaloidea_MOR_538_MA_B186_PG 0 Carex_austrina_MOR_526_STARR_B174 96Carex_austrina_MOR_524_DE_B172_PG 83 5 Carex_austrina_MOR_525_STARR_B173

0 Carex_vulpinoidea_MOR_1150_STARR_B74330 Carex_annectens_MOR_440_STARR_B08838 510 Carex_vulpinoidea_MOR_1153_CA_B746_MF 54 Carex_leavenworthii_MOR_759_AL_B407_PG 33 0 Carex_muhlenbergii_muhlenbergii_MOR_823_STARR_B483 32Carex_cephalophora_MOR_543_STARR_B191 0 28Carex_mesochorea_MOR_820_STARR_B480 93 0 Carex_mesochorea_MOR_831_AL_B491_PG Carex_sparganioides_sparaganioides_MOR_1092_WI_B684_PG 0 2713 Carex_perdentata_MOR_993_TX_B585_PG 140 78 0 4 Carex_leavenworthii_MOR_760_STARR_B408 4Carex_muhlenbergii_enervis_MOR_822_STARR_B482 4Carex_cephalophora_MOR_542_STARR_B190 Carex_leavenworthii_MOR_761_STARR_B40910 0 8Carex_perdentata_MOR_984_STARR_B576 2 Carex_muehlenbergii_muehlenbergii_MOR_838_STARR_B498 Carex_annectens_MOR_464_AL_B112_MF

Carex_triangularis_MOR_1149_GA_B742_MF Carex_triangularis_MOR_1148_STARR_B741 69 Carex_annectens_MOR_439_MD_B087_MF Carex_densa_MOR_1472_OR_B1063_MF Carex_cephalophora_MOR_562_DE_B210_PG 74Carex_muehlenbergii_muehlenbergii_MOR_824_MS_B484_P 66Carex_athrostachya_MOR_1350_STARR_B946b 86Carex_muehlenbergii_enervis_MOR_1768_AR_B1359_PG 57 7970Carex_muhlenbergii_MOR_825_STARR_B485 Carex_muhlenbergii_enervis_MOR_821_STARR_B481 Carex_muhlenbergii_MOR_808_STARR_B467 96 Carex_muehlenbergii_MOR_837_FL_B497_PG Carex_jonesii_MOR_1518_CO_B1109_VU 46Carex_jonesii_MOR_1412_WA_B1003_VU 2 Carex_vernacula_MOR_1515_CO_B1106_FO Carex_kobomugi_MOR_721_STARR_B369 100 Carex_kobomugi_MOR_713_VA_B361_MC 99 Carex_macrocephala_MOR_1236_AK_B831_MC 88 100Carex_macrocephala_MOR_1830_BC_B1421_MC Carex_macrocephala_MOR_1237_STARR_B832 Carex_vallicola_MOR_1788_BC_B1379_PG 9 100 Carex_vallicola_MOR_1514_CO_B1105_PG 55 Carex_arkansana_MOR_471_IL_B119_PG 39 100Carex_arkansana_MOR_472_STARR_B120 28 Carex_arkansana_MOR_470_STARR_B118 Carex_perglobosa_MOR_1605_CO_B1196_FO 100 29 Carex_douglasii_MOR_1937_ID_B1529_DV 37 Carex_texensis_MOR_1143_STARR_B736 79 Carex_texensis_MOR_1142_STARR_B735 100Carex_texensis_MOR_1141_STARR_B734 Carex_socialis_MOR_1089_STARR_B681 66 28Carex_socialis_MOR_1088_STARR_B680 Carex_socialis_MOR_1090_AL_B682_PG 18 39 Carex_appalachica_MOR_455_MA_B103_PG Carex_radiata_MOR_1001_MA_B593_PG 25 93 Carex_appalachica_MOR_438_STARR_B086 62 95 56 Carex_radiata_MOR_1000_MI_B592_PG 95Carex_rosea_MOR_1016_ME_B607_PG 16 6719 79 Carex_rosea_MOR_1018_WI_B609_PG Carex_rosea_MOR_1017_STARR_B608 Carex_radiata_MOR_985_STARR_B577 Carex_appalachica_MOR_454_TN_B102_PG

Carex_eburnea_MOR_1384_STARR_B975 79 Carex_eburnea_MOR_582_STARR_B230 100 Carex_eburnea_MOR_576_MI_B224_AL 89 Carex_eburnea_MOR_601_STARR_B249 Carex_fuliginosa_MOR_1429_AK_B1020_AU Carex_fuliginosa_MOR_1676_NU_B1267_AU100 66 Carex_fuliginosa_MOR_1453_AK_B1044_AU 97 100 Carex_spissa_ultra_MOR_1617_AZ_B1208_HP Carex_caryophyllea_Ibirica_MOR_1865_B1457_MT Carex_lativena_MOR_1631_NM_B1222_HL 32 93 52 Carex_lativena_MOR_1868_TX_B1460_HL 100Carex_planostachys_MOR_887_STARR_B547 Carex_planostachys_MOR_884_TXc_B544_HL Carex_petricosa_petricosa_MOR_1901_YT_B1493_AU 100Carex_B1453_MOR_1861_STARR Carex_petricosa_petricosa_MOR_1446_AK_B1037_AU 7148 65Carex_petricosa_misandroides_MOR_1797_QC_B1388_AU Carex_B1454_MOR_1862_STARR Carex_reznicekii_MOR_1014_AL_B605_AC Carex_inops_inops_MOR_1803_BC_B1394_AC Carex_vallicola_MOR_1613_AZ_B1204_PG Carex_geophila_MOR_674_STARR_B322 Carex_reznicekii_MOR_1013_STARR_B604 130Carex_umbellata_MOR_1179_STARR_B772 Carex_albicans_australis_MOR_429_STARR_B076 13 10 Carex_pityophila_MOR_996_STARR_B588 8Carex_tonsa_tonsa_MOR_1156_MB_B749_AC 5 30 1 Carex_inops_heliophila_MOR_702_STARR_B350 6 2 65Carex_pityophila_MOR_1632_NM_B1223_AC Carex_pityophila_MOR_1002_CO_B594_AC Carex_tonsa_MOR_1118_STARR_B711 Carex_tonsa_rugosperma_MOR_1157_MB_B750_AC Carex_peckii_MOR_877_STARR_B537 54 Carex_peckii_MOR_1427_AK_B1018_AC Carex_pensylvanica_MOR_973_MB_B565_AC 8357 9Carex_richardsonii_MOR_1829_STARR_B1420 46Carex_pensylvanica_MOR_974_STARR_B566 3 Carex_concinnoides_MOR_1827_STARR_B1418 Carex_tonsa_rugosperma_MOR_1539_IL_B1130_AC 1865 1 Carex_tonsa_MOR_1119_STARR_B712 Carex_albicans_australis_MOR_426_STARR_B073 Carex_albicans_emmonsii_MOR_433_MD_B080_AC 53 93 3 87Carex_albicans_emmonsii_MOR_431_STARR_B078 Carex_pensylvanica_MOR_904_STARR_B564 61 66 Carex_umbellata_MOR_1178_DE_B771_AC Carex_lucorum_austrolucorum_MOR_738_STARR_B386 81 49Carex_lucorum_austrolucorum_MOR_737_STARR_B385 94 Carex_lucorum_austrolucorum_MOR_743_GA_B391_AC 3888 26 Carex_lucorum_MOR_739_STARR_B387 87Carex_lucorum_austrolucorum_MOR_1537_TN_B1128_AC 25Carex_lucorum_lucorum_MOR_1538_NC_B1129_AC Carex_novae_angliae_MOR_796_STARR_B454 Carex_novae-angliae_MOR_1580_MN_B1171_AC100 60 71 Carex_novae_angliae_MOR_795_ME_B453_AC Carex_communis_amplisquama_MOR_1724_GA_B1315_AC 47 63Carex_communis_MOR_811_STARR_B470 Carex_communis_MOR_1291_STARR_B888 5360Carex_communis_MOR_531_STARR_B179 59Carex_communis_communis_MOR_530_NC_B178_AC 876094 Carex_communis_MOR_529_STARR_B177 Carex_communis_amplisquama_MOR_1560_SC_B1151_AC Carex_communis_MOR_810_STARR_B469 Carex_tonsa_tonsa_MOR_1906_ON_B1498_AC 80 Carex_tonsa_MOR_1293_STARR_B890

Carex_serpenticola_MOR_1466_OR_B1057_AC 2212Carex_rossii_MOR_1624_BC_B1215_AC 19 Carex_rossii_MOR_1019_STARR_B610 51Carex_brevicaulis_MOR_1375_WA_B966_AC 70Carex_brainerdii_MOR_1246_STARR_B841 82 Carex_brainerdii_MOR_1252_STARR_B84776 34Carex_brainerdii_MOR_494_CA_B142_AC 24 22 95 11Carex_globosa_MOR_654_CA_B302_AC Carex_B1399_MOR_1808_STARR 83 5 Carex_serpenticola_MOR_1763_CA_B1354_AC 9Carex_rossii_MOR_1003_STARR_B595 Carex_turbinata_MOR_1773_AZ_B1364_AC 13 26 Carex_geophila_MOR_675_STARR_B323 Carex_turbinata_MOR_1679_AZ_B1270_AC 7Carex_nigromarginata_MOR_855_AL_B515_AC 61 59Carex_nigromarginata_MOR_856_STARR_B516 6Carex_reznicekii_MOR_1015_STARR_B606 Carex_albicans_albicans_MOR_423_STARR_B070 41Carex_albicans_albicans_MOR_425_KS_B072_AC 46Carex_albicans_albicans_MOR_424_STARR_B071 3728 10 Carex_albicans_emmonsii_MOR_432_STARR_B079 Carex_albicans_australis_MOR_436_MS_B083_AC47 65 53 22Carex_nigromarginata_MOR_854_STARR_B514 Carex_pensylvanica_MOR_1396_STARR_B987 Carex_inops_inops_MOR_1493_CA_B1084_AC 52 Carex_inops_inops_MOR_1410_WA_B1001_AC Carex_amplifolia_MOR_449_NV_B097_AN 100 Carex_amplifolia_MOR_1270_STARR_B865 Carex_grayi_MOR_658_KN_B306_LU 100 Carex_grayi_MOR_657_STARR_B305 90 Carex_intumescens_MOR_707_STARR_B355 100Carex_intumescens_MOR_709_ME_B357_LU 98 Carex_intumescens_MOR_708_STARR_B356 Carex_elliotti_MOR_598_STARR_B246 92 100Carex_elliottii_MOR_1718_FL_B1309_VC Carex_elliottii_MOR_1533_NC_B1124_VC Carex_frankii_MOR_671_STARR_B319 52 62 99 Carex_frankii_MOR_673_AL_B321_SQ Carex_frankii_MOR_672_STARR_B320 100 Carex_aureolensis_MOR_504_MS_B152_SQ 89 100Carex_aureolensis_MOR_505_STARR_B153 Carex_aureolensis_MOR_503_STARR_B151 Carex_hystericina_MOR_691_STARR_B339 83Carex_hystericina_MOR_693_STARR_B341 69 79Carex_hystericina_MOR_692_STARR_B340 42 100Carex_hystricina_MOR_1407_STARR_B998 Carex_hystericina_MOR_815_AR_B475_VC Carex_retrorsa_MOR_1012_MI_B603_VC 88Carex_retrorsa_MOR_1330_STARR_B927 90 Carex_retrorsa_MOR_1401_STARR_B992 Carex_lupuliformis_MOR_755_STARR_B403 82 Carex_louisianica_MOR_742_FL_B390_LU 75 77Carex_louisianica_MOR_736_STARR_B384 70 94Carex_louisianica_MOR_741_STARR_B389 Carex_lupulina_MOR_813_STARR_B473 47 Carex_lupuliformis_MOR_745_FL_B393_LU 6782 51 72Carex_lupuliformis_MOR_744_STARR_B392 Carex_lupulina_MOR_812_MD_B472_LU 13 Carex_gigantea_MOR_650_STARR_B298 100 92Carex_gigantea_MOR_648_STARR_B296 41 Carex_gigantea_MOR_651_FL_B299_LU Carex_bullata_MOR_509_MA_B157_VC 89 Carex_bullata_MOR_510_STARR_B158 Carex_pseudocyperus_MOR_1543_MB_B1134_VC 44 14 Carex_comosa_MOR_532_STARR_B180 62Carex_comosa_MOR_528_STARR_B176 6473 77Carex_comosa_MOR_560_CA_B208_VC 85Carex_pseudocyperus_MOR_980_STARR_B572 63Carex_pseudocyperus_MOR_981_B573_VC Carex_pseudocyperus_MOR_1320_STARR_B917 Carex_thurberi_MOR_1899_AZ_B1491_VC 94 Carex_thurberi_MOR_1618_AZ_B1209_VC Carex_striata_MOR_1067_STARR_B659 91Carex_striata_MOR_1076_FL_B668_PD 88 Carex_striata_MOR_1077_STARR_B669 99 Carex_pumila_MOR_1869_NC_B1461_PD Carex_hyalinolepsis_MOR_701_STARR_B349 59 49 100Carex_hyalinolepsis_MOR_649_STARR_B297 88 Carex_hyalinolepis_MOR_690_TX_B338_PD Carex_lacustris_MOR_1339_STARR_B936 39 60 100Carex_lacustris_MOR_724_STARR_B372 Carex_lacustris_MOR_725_MB_B373_PD 48 Carex_melanostachya_MOR_1745_NE_B1336_PD 89 52 Carex_melanostachya_MOR_1693_KN_B1284_PD94 25 Carex_melanostachya_MOR_1352_OK_B947b_PD Carex_lasiocarpa_MOR_729_STARR_B377 Carex_pellita_MOR_1606_YT_B1197_PD 59 Carex_missouriensis_MOR_799_STARR_B458 49 59Carex_pellita_MOR_882_CA_B542_PD 49 61Carex_pellita_MOR_885_STARR_B545 4162Carex_bella_MOR_1667_STARR_B1258 Carex_pellita_MOR_862_STARR_B522 89 47 Carex_pellita_MOR_883_STARR_B543 Carex_lasiocarpa_MOR_731_AK_B379_PD Carex_schweinitzii_MOR_1656_VA_B1247_VC 99 Carex_schweinitzii_MOR_1058_MI_B649_VC 41 Carex_rostrata_MOR_1402_STARR_B993 16 76Carex_membranacea_MOR_1338_STARR_B935 94 42 Carex_membranacea_MOR_784_AK_B442_VC Carex_utriculata_MOR_1182_STARR_B775 Carex_rotundata_MOR_1006_AK_B598_VC 90 45Carex_rotundata_MOR_1551_MB_B1142_VC Carex_utriculata_MOR_1181_AK_B774_VC 54 82Carex_utriculata_MOR_1184_STARR_B777 Carex_utriculata_MOR_1183_STARR_B77698 4595 71 Carex_rostrata_MOR_1005_STARR_B597 Carex_rostrata_MOR_1332_STARR_B929 Carex_vesicaria_MOR_1162_DE_B755_VC 89 52Carex_vesicaria_monile_MOR_1164_STARR_B757 16Carex_saxatilis_MOR_1572_NB_B1163_VC Carex_saxatilis_MOR_1025_STARR_B616 Carex_exsiccata_MOR_1778_BC_B1369_VC 45 9 81Carex_vesicaria_MOR_1163_STARR_B756 5 Carex_tuckermanii_MOR_1336_STARR_B933 100Carex_tuckermanii_MOR_1139_STARR_B732 17 89 Carex_tuckermanii_MOR_1147_MI_B740_VC 17Carex_exsiccata_MOR_1387_STARR_B978 Carex_exsiccata_MOR_1489_CA_B1080_VC Carex_oligosperma_MOR_846_STARR_B506 100 Carex_oligosperma_MOR_1555_MB_B1146_VC Carex_houghtoniana_MOR_1584_WI_B1175_PD 82Carex_houghtoniana_MOR_1248_MB_B843_PD 48 Carex_houghtoniana_MOR_1324_STARR_B921 55 Carex_sheldonii_MOR_1607_CA_B1198_CX 78 Carex_sheldonii_MOR_1495_CA_B1086_CX 98Carex_sheldonii_MOR_1636_ID_B1227_CX Carex_trichocarpa_MOR_1135_STARR_B728 72 3022Carex_laeviconica_MOR_1689_KS_B1280_CX 4888 59 Carex_laeviconica_MOR_723_STARR_B371 40Carex_trichocarpa_MOR_1133_DE_B726_CX Carex_trichocarpa_MOR_1134_STARR_B727 94Carex_atherodes_MOR_458_STARR_B106 72 100 Carex_atherodes_MOR_1331_STARR_B928 14 Carex_atherodes_MOR_1651_BC_B1242_CX 71 75 Carex_atherodes_MOR_459_STARR_B107 Carex_hirta_MOR_681_PN_B329_CX 73 99Carex_hirta_MOR_1575_NB_B1166_CX Carex_hirta_MOR_680_STARR_B328 Carex_lurida_MOR_816_FL_B476_VC 2 13Carex_lurida_MOR_1761_LA_B1352_VC Carex_lurida_MOR_814_STARR_B474 90Carex_barbarae_MOR_484_STARR_B132 57 63Carex_baileyi_MOR_487_STARR_B135 13Carex_baileyi_MOR_485_KY_B133_VC Carex_halliana_MOR_1405_STARR_B996 90Carex_halliana_MOR_1491_CA_B1082_PD 56 Carex_halliana_MOR_1469_OR_B1060_PD Carex_scirpoidea_scirpoidea_MOR_1465_OR_B1056_SP Carex_scabriuscula_MOR_1049_STARR_B640 71 Carex_scirpoidea_pseudoscirpoidea_MOR_1508_CO_B1099_SP 100 Carex_curatorum_MOR_1818_B1409_SP 41 Carex_scirpoidea_convoluta_MOR_1759_ON_B1350_SP 28Carex_scirpoidea_MOR_1308_STARR_B905 42 77Carex_scirpoidea_scirpoidea_MOR_1717_ON_B1308_SP Carex_scirpoidea_convoluta_MOR_1722_ON_B1313_SP Carex_scirpoidea_MOR_1051_STARR_B64245 14 61Carex_rupestris_MOR_1304_NFLD_B901_RU 12Carex_scirpoidea_scirpoidea_MOR_1050_AK_B641_SP Carex_scirpoidea_stenochlaena_MOR_1603_AK_B1194_SP 555521 Carex_scirpoidea_stenochlaena_MOR_1604_WA_B1195_SP 62 Carex_scirpoidea_pseudoscirpoidea_MOR_1805_BC_B1396_SP 79 74 Carex_scirpoidea_stenochlaena_MOR_1388_STARR_B979 9 Carex_scirpoidea_MOR_1060_STARR_B651 Carex_scirpoidea_MOR_1059_STARR_B650 Carex_curatorum_MOR_1769_UT_B1360_SP Carex_magellanica_MOR_1439_AK_B1030_LM Carex_magellanica_MOR_982_STARR_B574 179 26 3Carex_gracilescens_MOR_1353_STARR_B948 100Carex_magellanica_irrigua_MOR_1521_CO_B1112_LM 23 Carex_paupercula_MOR_898_STARR_B558 Carex_prasina_MOR_900_GA_B560_HC 99 Carex_prasina_MOR_901_STARR_B561100 Carex_prasina_MOR_899_STARR_B559 Carex_stylosa_MOR_1292_NFLD_B889_RM Carex_haydenii_MOR_1594_IA_B1185_PC 61Carex_aperta_MOR_1371_STARR_B962 22 44Carex_aperta_MOR_1644_BC_B1235_PC 30 2 10084Carex_aperta_MOR_453_STARR_B101 Carex_haydenii_MOR_1890_MA_B1482_PC Carex_haydenii_MOR_1282_STARR_B878 Carex_spectabilis_MOR_1781_BC_B1372_ST 9 3 38Carex_spectabilis_MOR_1804_BC_B1395_ST Carex_macrochaeta_MOR_1785_BC_B1376_LM 38 Carex_macrochaeta_MOR_1473_OR_B1064_LM 57Carex_mertensii_MOR_789_STARR_B447 43 100Carex_mertensii_MOR_788_STARR_B446 18 Carex_mertensii_MOR_790_AK_B448_RM Carex_microchaeta_nesophila_MOR_1726_AK_B1317_ST 88 89Carex_microchaeta_nesophila_MOR_1735_AK_B1326_ST Carex_spectabilis_MOR_1097_STARR_B689 Carex_limosa_MOR_768_STARR_B416 Carex_limosa_MOR_771_STARR_B419 61 49Carex_limosa_MOR_770_STARR_B418 14Carex_limosa_MOR_769_AK_B417_LM Carex_podocarpa_MOR_1744_YT_B1335_ST 96 Carex_podocarpa_MOR_1734_BC_B1325_ST 85 72 1945 Carex_microchaeta_microchaeta_MOR_1885_WY_B1477_ST 122 Carex_nebrascensis_MOR_851_STARR_B511 98 98Carex_aquatilis_aquatilis_MOR_441_STARR_B089 91Carex_nebrascensis_MOR_850_CA_B510_PC Carex_endlichii_MOR_1897_AZ_B1489_PC Carex_obnupta_MOR_839_CA_B499_PC 100 Carex_obnupta_MOR_840_STARR_B500 Carex_subspathacea_MOR_1449_AK_B1040_PC 41Carex_vacillans_MOR_1691_ME_B1282_PC Carex_ramenskii_MOR_1447_AK_B1038_PC 2 27 Carex_subspathacea_MOR_1559_MB_B1150_PC 1138Carex_paleacea_MOR_861_ME_B521_PC 32 24Carex_vacillans_MOR_1577_NB_B1168_PC 2648Carex_subspathacea_MOR_1674_QC_B1265_PC 52 Carex_lyngbyei_MOR_818_STARR_B478 34 22Carex_salina_MOR_1755_QC_B1346_PC Carex_ramenskii_MOR_1241_AK_B836_PC 62 Carex_lyngbyei_MOR_819_OR_B479_PC Carex_aquatilis_dives_MOR_1486_CA_B1077_PC Carex_aquatilis_aquatilis_MOR_1752_NL_B1343_PC 4 5Carex_aquatilis_substricta_MOR_1713_NE_B1304_PC 4 61Carex_aquatilis_aquatilis_MOR_1576_NB_B1167_PC 89 40Carex_aquatilis_MOR_443_STARR_B091 16Carex_recta_MOR_1947_B1539_PC 38Carex_aquatilis_aquatilis_MOR_442_STARR_B090 1541 Carex_lenticularis_MOR_748_STARR_B396 59Carex_aquatilis_aquatilis_MOR_1287_B884_PC Carex_macloviana_MOR_1520_STARR_B1111 25 Carex_aquatilis_substricta_MOR_1684_NB_B1275_PC Carex_lenticularis_impressa_MOR_750_CA_B398_PC 40 7Carex_lenticularis_lipocarpa_MOR_751_STARR_B399 5Carex_angustata_MOR_1233_STARR_B828 2 14Carex_lenticularis_lipocarpa_MOR_1451_AK_B1042_PC 6659Carex_lenticularis_limnophila_MOR_1882_BC_B1474_PC 82 24Carex_lenticularis_limnophila_MOR_1898_AK_B1490_PC 4Carex_lenticularis_limnophila_MOR_1413_WA_B1004_PC 0 Carex_aquatilis_dives_MOR_1643_BC_B1234_PC 95Carex_aquatilis_dives_MOR_1414_WA_B1005_PC 95 12Carex_aquatilis_dives_MOR_1430_AK_B1021_PC Carex_lenticularis_dolia_MOR_1547_AB_B1138_PC Carex_lenticularis_dolia_MOR_1807_BC_B1398_PC 5054 44Carex_lenticularis_dolia_MOR_749_STARR_B397 Carex_lenticularis_dolia_MOR_752_STARR_B400 Carex_lenticularis_impressa_MOR_747_STARR_B395 Carex_microchaeta_microchaeta_MOR_1609_YT_B1200_ST 62Carex_microchaeta_microchaeta_MOR_1748_YT_B1339_ST 83Carex_haydeniana_MOR_1888_AB_B1480_OV 66 27 Carex_macrochaeta_MOR_1747_BC_B1338_LM Carex_interrupta_MOR_1411_WA_B1002_PC 0 56 4 88Carex_angustata_MOR_1460_OR_B1051_PC Carex_angustata_MOR_447_CA_B095_PC 53 Carex_emoryi_MOR_1930_NB_B1522_PC 86 2 3 Carex_stricta_MOR_1099_STARR_B691 Carex_nigra_MOR_852_STARR_B512 100 59 Carex_nigra_Lapland_MOR_1910_B1502_PC 3 Carex_nigra_MOR_1297_NFLD_B894_PC36 Carex_bigelowii_lugens_MOR_1620_AK_B1211_PC 79 2 Carex_holostoma_MOR_1731_STARR_B1322 Carex_vacillans_MOR_1889_QC_B1481_PC 8 Carex_salina_MOR_1302_NFLD_B899_PC1 Carex_lenticularis_lipocarpa_MOR_746_CA_B394_PC Carex_lenticularis_MOR_753_STARR_B401 79Carex_eleusinoides_MOR_1893_YT_B1485_PC 69 Carex_eleusinoides_MOR_1425_AK_B1016_PC Carex_schottii_MOR_1659_CA_B1250_PC 0 66 65Carex_schottii_MOR_1772_CA_B1363_PC 64Carex_schottii_MOR_1601_CA_B1192_PC 1 Carex_schottii_MOR_1483_CA_B1074_PC 89Carex_senta_MOR_1042_STARR_B633 Carex_senta_MOR_1043_STARR_B634 0 363 6 Carex_nudata_MOR_1242_CAs_B837_PC Carex_nudata_MOR_797_STARR_B4556 Carex_senta_MOR_1687_AZ_B1278_PC Carex_interrupta_MOR_1468_OR_B1059_PC 2 77 63Carex_nudata_MOR_1461_OR_B1052_PC 68 Carex_emoryi_MOR_600_STARR_B248 74Carex_emoryi_MOR_619_DE_B267_PC 33 Carex_emoryi_MOR_610_STARR_B258 0 9 11 Carex_scopulorum_prionophylla_MOR_1389_WA_B980_PC Carex_scopulorum_scopulorum_MOR_1509_CO_B1100_PC 100 Carex_stricta_MOR_1098_TX_B690_PC Carex_bigelowii_bigelowii_MOR_1288_NFLD_B885_PC 74 Carex_scopulorum_bracteosa_MOR_1879_AK_B1471_PC 3 Carex_bigelowii_lugens_MOR_476_AK_B124_PC 8 Carex_microchaeta_microchaeta_MOR_1696_YT_B1287_ST Carex_scopulorum_MOR_1039_STARR_B630 2 Carex_baileyi_MOR_486_STARR_B134 Carex_barbarae_MOR_1254_STARR_B849100 95 Carex_barbarae_MOR_1251_CA_B846_PC Carex_verrucosa_MOR_1175_FL_B768_GC 20 100 16 Carex_verrucosa_MOR_1176_STARR_B769 Carex_glaucescens_MOR_652_STARR_B300 10065Carex_joorii_MOR_719_STARR_B367 62Carex_glaucescens_MOR_653_STARR_B301 37 44 9 Carex_glaucescens_MOR_1945_TX_B1537_GC 73Carex_joorii_MOR_718_STARR_B366 Carex_glaucescens_MOR_660_MS_B308_GC Carex_shortiana_MOR_1029_STARR_B620 69 100Carex_shortiana_MOR_1031_KN_B622_SH Carex_shortiana_MOR_1030_STARR_B621 Carex_crinita_brevicrinis_MOR_523_STARR_B171 24Carex_mitchelliana_MOR_800_STARR_B459 62Carex_crinita_crinita_MOR_535_ME_B183_PC 5664 7 Carex_crinita_crinita_MOR_541_STARR_B189 Carex_mitchelliana_MOR_836_STARR_B496 Carex_mitchelliana_MOR_835_AL_B495_PC41 3Carex_gynandra_MOR_714_STARR_B362 19Carex_gynandra_MOR_688_STARR_B336 75 12Carex_gynandra_MOR_698_DE_B346_PC Carex_crinita_brevicrinis_MOR_539_STARR_B18792 52 16Carex_crinita_brevicrinis_MOR_540_AR_B188_PC Carex_crinita_crinita_MOR_536_STARR_B184 31 Carex_torta_MOR_1130_STARR_B723 100Carex_torta_MOR_1122_PN_B715_PC 79 Carex_torta_MOR_1121_GA_B714_PC Carex_barrattii_MOR_491_STARR_B139 100Carex_barrattii_MOR_481_STARR_B129 100 Carex_barrattii_MOR_482_AL_B130_LM Carex_typhina_MOR_1132_AR_B725_SQ 100 Carex_typhina_MOR_1129_STARR_B722 100 91 Carex_typhina_MOR_1131_STARR_B724 Carex_squarrosa_MOR_1081_STARR_B673 Carex_squarrosa_MOR_1083_AR_B675_SQ100 87 Carex_squarrosa_MOR_1082_STARR_B674 Carex_sartwelliana_MOR_1239_STARR_B834 100 Carex_sartwelliana_MOR_1484_STARR_B1075 25 Carex_sartwelliana_MOR_1600_CA_B1191_PD 94Carex_congdonii_MOR_1699_CA_B1290_PD 93 Carex_congdonii_MOR_1488_CA_B1079_PD Carex_vestita_MOR_1166_STARR_B759 100 Carex_vestita_MOR_1165_DE_B758_PD Carex_scabrata_MOR_1045_GA_B636_AN 71 100Carex_scabrata_MOR_1046_STARR_B637 Carex_scabrata_MOR_1047_STARR_B638 Carex_laxa_MOR_1445_AK_B1036_PN Carex_albursina_MOR_1195_STARR_B789 100 100Carex_albursina_MOR_1186_STARR_B780 Carex_concinna_MOR_1358_STARR_B950b Carex_striatula_MOR_1075_STARR_B667 4161 28 5436 Carex_chapmanii_MOR_566_FL_B214_LF 94 Carex_kraliana_MOR_717_STARR_B365 Carex_gracilescens_MOR_661_KY_B309_LF 71 Carex_kraliana_MOR_715_AR_B363_LF Carex_leptonervia_MOR_1197_STARR_B791 45 79 38Carex_leptonervia_MOR_767_STARR_B415 Carex_leptonervia_MOR_1198_STARR_B79264 16Carex_leptonervia_MOR_1196_MB_B790_LF 10 89Carex_striatula_MOR_1066_DE_B658_LF Carex_B1412_MOR_1821_STARR 5015 87 78 Carex_ormostachya_MOR_1275_STARR_B870 43 33 Carex_glaucodea_MOR_493_STARR_B141 60 Carex_blanda_MOR_1621_KS_B1212_LF 53 273336 99 Carex_striatula_MOR_1065_STARR_B657 81 55Carex_radfordii_MOR_1240_SC_B835_LF 50 Carex_blanda_MOR_474_MD_B122_LF 56Carex_blanda_MOR_492_STARR_B140 100 Carex_kraliana_MOR_710_STARR_B358 Carex_gracilescens_MOR_662_STARR_B310 Carex_gracilescens_MOR_1188_STARR_B782 Carex_manhartii_MOR_1563_GE_B1154_LF 83 Carex_manhartii_MOR_1271_STARR_B866 Carex_biltmoreana_MOR_475_STARR_B123 Carex_woodii_MOR_1592_IA_B1183_PN 90100Carex_biltmoreana_MOR_1943_STARR_B1535 54Carex_woodii_MOR_1171_STARR_B764 6652 Carex_woodii_MOR_1170_STARR_B763 60 94 Carex_biltmoreana_MOR_1870_NC_B1462_PN Carex_purpurifera_MOR_1541_NC_B1132_LF 67 Carex_purpurifera_MOR_1540_TN_B1131_LF99 Carex_purpurifera_MOR_1272_KY_B867_LF Carex_ormostachya_MOR_868_MI_B528_LF 77Carex_hassei_MOR_1669_CA_B1260_BI Carex_klamathensis_MOR_1871_OR_B1463_PN 3Carex_garberi_MOR_1800_BC_B1391_BI 1Carex_aurea_MOR_1263_STARR_B858 Carex_aurea_MOR_501_CA_B149_BI 57 2Carex_bicolor_MOR_1424_AK_B1015_BI 23 Carex_meadii_MOR_791_STARR_B449 29 2Carex_livida_MOR_1725_CA_B1316_PN 14 Carex_tetanica_MOR_1593_IA_B1184_PN2 Carex_tetanica_MOR_1116_MB_B709_PN 21141 Carex_bicolor_MOR_1303_STARR_B9003 2227Carex_aurea_MOR_502_STARR_B150 723 4 Carex_hassei_MOR_1516_CO_B1107_BI 7726Carex_meadii_MOR_782_STARR_B440 26Carex_meadii_MOR_1544_MB_B1135_PN 8 Carex_hassei_MOR_700_STARR_B348 Carex_B1456_MOR_1864_STARR Carex_garberi_MOR_1426_AK_B1017_BI Carex_livida_MOR_1212_NJ_B807_PN Carex_bicolor_MOR_1554_AB_B1145_BI Carex_hendersonii_MOR_1749_BC_B1340_LF 100 100Carex_hendersonii_MOR_1187_STARR_B781 Carex_hendersonii_MOR_1406_STARR_B997 Carex_panicea_MOR_1708_ME_B1299_PN 100 61 Carex_panicea_MOR_1681_NS_B1272_PN Carex_vaginata_MOR_1776_YT_B1367_PN

20 100Carex_lemmonii_MOR_1480_CA_B1071_AU Carex_luzulina_luzulina_MOR_1765_CA_B1356_AU 99 3470 Carex_lemmonii_MOR_763_CA_B411_AU 10Carex_luzulina_luzulina_MOR_1710_CA_B1301_AU Carex_lemmonii_MOR_1907_CO_B1499_AU70 76 71 Carex_luzulifolia_MOR_762_CA_B410_AU Carex_luzulina_ablata_MOR_1481_CA_B1072_AU 62Carex_luzulina_MOR_817_OR_B477_AU 89Carex_luzulina_ablata_MOR_1694_WY_B1285_AU 9294 Carex_luzulina_luzulina_MOR_1740_NV_B1331_AU Carex_luzulifolia_MOR_1267_STARR_B862 78 71 63Carex_pigra_MOR_1587_MS_B1178_GR Carex_pigra_MOR_399_STARR_B046 3127Carex_gholsonii_MOR_687_AL_B335_GL 31Carex_gholsonii_MOR_697_STARR_B345 4160 68Carex_gholsonii_MOR_696_STARR_B344 Carex_pigra_MOR_1342_STARR_B939 20 Carex_pigra_MOR_1645_AL_B1236_GR Carex_glaucodea_MOR_397_STARR_B044 55 Carex_glaucodea_MOR_1227_STARR_B822 73 Carex_glaucodea_MOR_396_STARR_B043 56 100Carex_glaucodea_MOR_1327_IN_B924_GR Carex_granularis_MOR_665_STARR_B313 65Carex_granularis_MOR_1220_STARR_B815 60 97Carex_granularis_MOR_1211_STARR_B806 Carex_granularis_MOR_1209_MB_B804_GL Carex_microdonta_MOR_1222_MS_B817_GL 53 89 79Carex_microdonta_MOR_1223_STARR_B818 98Carex_microdonta_MOR_1648_NM_B1239_GL 100 Carex_crawei_MOR_1273_NFLD_B868_GL 76 Carex_crawei_MOR_1202_STARR_B797 Carex_abscondita_MOR_412_STARR_B059 100 Carex_abscondita_MOR_410_DE_B057_CY Carex_laxiculmis_copulata_MOR_1535_IL_B1126_CY Carex_laxiculmis_copulata_MOR_1536_TN_B1127_CY59 40 Carex_laxiculmis_copulata_MOR_1657_VA_B1248_CY Carex_abscondita_MOR_411_STARR_B058 11 87 9Carex_cumberlandensis_MOR_552_STARR_B200 28Carex_cumberlandensis_MOR_551_AR_B199_CY 11 95 77Carex_digitalis_micropoda_MOR_584_STARR_B232 15 86Carex_digitalis_micropoda_MOR_587_STARR_B235 77 92 96 53 Carex_digitalis_macropoda_MOR_589_AR_B237_CY Carex_cumberlandensis_MOR_553_STARR_B201 78 Carex_digitalis_MOR_586_STARR_B234 11 Carex_digitalis_digitalis_MOR_585_DE_B233_CY 59 Carex_digitalis_MOR_579_STARR_B227 6 Carex_laxiculmis_laxiculmis_MOR_1206_STARR_B801 100 82Carex_laxiculmis_laxiculmis_MOR_730_STARR_B378 Carex_laxiculmis_laxiculmis_MOR_1205_PN_B800_CY100 Carex_laxiculmis_MOR_1276_STARR_B871 Carex_conoidea_MOR_1229_STARR_B824 74 Carex_conoidea_MOR_1228_STARR_B823100 Carex_conoidea_MOR_1230_DE_B825_GR Carex_godfreyi_MOR_1329_STARR_B926 64 Carex_godfreyi_MOR_380_STARR_B027 40Carex_corrugata_MOR_404_AL_B051_GR Carex_amphibola_MOR_388_AL_B035_GR 3765Carex_amphibola_MOR_387_STARR_B034 64 4 100 7824Carex_amphibola_MOR_385_STARR_B032 Carex_grisea_MOR_390_KY_B037_GR 93 Carex_grisea_MOR_1335_STARR_B932 87 51Carex_corrugata_MOR_386_STARR_B033 65 Carex_corrugata_MOR_403_SC_B050_GR Carex_corrugata_MOR_1226_STARR_B821 69 Carex_godfreyi_MOR_1589_AL_B1180_GR Carex_oligocarpa_MOR_408_STARR_B055 Carex_bulbostylis_MOR_382_MS_B029_GR 19Carex_edwardsiana_MOR_1944_TX_B1536_GR Carex_acidicola_MOR_384_STARR_B031 14 330 726Carex_acidicola_MOR_1249_STARR_B844 95 Carex_calcifugens_MOR_401_STARR_B048 28 60Carex_thornei_MOR_394_GA_B041_GR 31Carex_planispicata_MOR_1341_STARR_B938 44 Carex_oligocarpa_MOR_1274_STARR_B869 Carex_oligocarpa_MOR_407_STARR_B054 91 Carex_thornei_MOR_1542_GA_B1133_GR Carex_paeninsulae_MOR_383_STARR_B030 61Carex_paeninsulae_MOR_1247_FLc_B842_GR 54 70Carex_paeninsulae_MOR_1253_STARR_B848 31 64Carex_thornei_MOR_395_STARR_B042 22 Carex_thornei_MOR_393_FL_B040_GR Carex_calcifugens_MOR_402_FL_B049_GR 97 6 Carex_acidicola_MOR_392_AL_B039_GR 62Carex_planispicata_MOR_1333_STARR_B930 34Carex_planispicata_MOR_400_MD_B047_GR Carex_magellanica_MOR_1354_STARR_B948b 66 75 Carex_oligocarpa_MOR_1334_AR_B931_GR 16 Carex_plantaginea_MOR_1269_STARR_B864 100 Carex_plantaginea_MOR_1695_TN_B1286_CY Carex_austrocaroliniana_MOR_1531_NC_B1122_CY Carex_austrocaroliniana_MOR_488_STARR_B136 89 85 100 97 Carex_austrocaroliniana_MOR_489_STARR_B137 Carex_austrocaroliniana_MOR_1588_TN_B1179_CY 25 Carex_careyana_MOR_1203_KY_B798_CY 100Carex_careyana_MOR_1204_STARR_B799 21 Carex_careyana_MOR_1219_STARR_B814 48 Carex_platyphylla_MOR_886_MD_B546_CY 49 63Carex_platyphylla_MOR_1278_STARR_B873 Carex_platyphylla_MOR_1268_STARR_B863 Carex_hitchcockiana_MOR_1213_STARR_B808 95 Carex_hitchcockiana_MOR_1215_STARR_B810 21 100 Carex_hitchcockiana_MOR_1214_STARR_B809 93 100Carex_hitchcockiana_MOR_391_KY_B038_GR Carex_brysonii_MOR_1900_AL_B1492_GR 100 Carex_brysonii_MOR_389_AL_B036_GR 84 Carex_impressinervia_MOR_1564_AL_B1155_GR 100 100Carex_impressinervia_MOR_1586_MS_B1177_GR Carex_impressinervia_MOR_381_STARR_B028 95Carex_ouachitana_MOR_1224_STARR_B819 83 93Carex_ouachitana_MOR_1225_STARR_B820 Carex_ouachitana_MOR_1340_AR_B937_GR Carex_collinsii_MOR_568_STARR_B216 100 100Carex_collinsii_MOR_561_DE_B209_CO Carex_collinsii_MOR_1565_GA_B1156_CO Carex_acutiformis_MOR_1924_Spain_B1516_PD 40 Carex_pallescens_MOR_1295_STARR_B892 Carex_pallescens_MOR_1811_BC_B1402_PO 99 Carex_pallescens_MOR_1810_B1401_PO89 98Carex_pallescens_MOR_864_STARR_B524 Carex_pallescens_MOR_863_STARR_B523 Carex_polymorpha_MOR_1709_ME_B1300_PN 96 Carex_polymorpha_MOR_890_STARR_B550 82Carex_californica_MOR_1637_ID_B1228_PN 95 33 67Carex_californica_MOR_1376_STARR_B967 Carex_californica_MOR_1487_CA_B1078_PN Carex_torreyi_MOR_1120_STARR_B713 100 Carex_torreyi_MOR_1581_TN_B1172_PO100 Carex_torreyi_MOR_1510_CO_B1101_PO Carex_tenax_MOR_1111_STARR_B704 98 Carex_tenax_MOR_1110_STARR_B703 89Carex_dasycarpa_MOR_608_HL_B256_FL 98Carex_dasycarpa_MOR_607_GA_B255_HL 51 95 Carex_dasycarpa_MOR_609_STARR_B257 Carex_debilis_rudgei_MOR_569_STARR_B217 81 Carex_debilis_debilis_MOR_1280_NFLD_B875_HC Carex_arctata_MOR_465_WI_B113_HC Carex_gracillima_MOR_664_STARR_B312 28 42Carex_formosa_MOR_1534_IL_B1125_HC Carex_formosa_MOR_1887_ON_B1479_HC91 92 Carex_formosa_MOR_1794_MN_B1385_HC 52 39 18Carex_gracillima_MOR_1546_MB_B1137_HC Carex_davisii_MOR_594_STARR_B242 6160 Carex_davisii_MOR_593_STARR_B241 82 Carex_davisii_MOR_592_DE_B240_HC 7 60 31Carex_B0949b_MOR_1356_STARR Carex_arctata_MOR_1652_NS_B1243_HC 37Carex_gracillima_MOR_656_AL_B304_HC 84 Carex_gracillima_MOR_663_STARR_B311 Carex_arctata_MOR_466_STARR_B114 8 Carex_oxylepis_MOR_870_STARR_B530 99Carex_oxylepis_pubescens_MOR_871_KY_B531_HC 98Carex_oxylepis_pubescens_MOR_872_STARR_B532 9192 Carex_oxylepis_pubescens_MOR_873_STARR_B533 8 Carex_oxylepis_MOR_875_STARR_B535 Carex_venusta_MOR_1174_MS_B767_HC 87 67 1 74Carex_debilis_MOR_596_STARR_B244 16Carex_debilis_rudgei_MOR_558_TN_B206_HC Carex_venusta_MOR_1173_STARR_B766 44 Carex_venusta_minor_MOR_1177_STARR_B770 18 86 88 Carex_debilis_MOR_595_STARR_B243 Carex_debilis_rudgei_MOR_559_STARR_B207 Carex_complanata_MOR_517_STARR_B165 64 Carex_hirsutella_MOR_678_STARR_B326 99 Carex_complanata_MOR_516_TX_B164_PO 48 Carex_complanata_MOR_515_STARR_B163 Carex_swanii_MOR_1107_STARR_B700 Carex_hirtifolia_MOR_1277_STARR_B872 Carex_hirsutella_MOR_679_STARR_B327 222722 18Carex_caroliniana_MOR_547_STARR_B195 Carex_caroliniana_MOR_548_STARR_B196 24 Carex_hirsutella_MOR_669_DE_B317_PO 19 44Carex_bushii_MOR_513_STARR_B161 43Carex_bushii_MOR_511_DE_B159_PO 07 54 4123Carex_oxylepis_MOR_878_STARR_B538 Carex_bushii_MOR_512_STARR_B160 Carex_caroliniana_MOR_549_AL_B197_PO Carex_swanii_MOR_1105_STARR_B698 Carex_misera_MOR_1566_TN_B1157_HC 11352Carex_aestivalis_MOR_1250_STARR_B845 56 48Carex_aestivalis_MOR_416_STARR_B063 49 161Carex_aestivalis_MOR_415_PN_B062_HC 35 Carex_aestivalis_MOR_414_STARR_B061 76 Carex_aestivalis_MOR_1590_GA_B1181_HC 73Carex_virescens_MOR_1159_STARR_B752 Carex_roanensis_MOR_1026_NC_B617_HC 6362 Carex_roanensis_MOR_1579_TN_B1170_HC 57 Carex_virescens_MOR_1160_STARR_B753 66 Carex_virescens_MOR_1158_AL_B751_PO Carex_swanii_MOR_1106_AR_B699_PO Carex_debilis_MOR_597_STARR_B245 Carex_hirtissima_MOR_1496_CA_B1087_HC 73 Carex_hirtissima_MOR_1728_CA_B1319_HC89 44Carex_hirtissima_MOR_1497_CA_B1088_HC Carex_gynodynama_MOR_1470_OR_B1061_HC 98 38 Carex_gynodynama_MOR_1490_CA_B1081_HC Carex_mendocinensis_MOR_1721_CA_B1312_HC 92 Carex_mendocinensis_MOR_1475_OR_B1066_HC Carex_castanea_MOR_537_STARR_B185 100 Carex_castanea_MOR_1281_NFLD_B876_HC 63Carex_whitneyi_MOR_1154_CA_B747_LG 100 98Carex_whitneyi_MOR_1151_STARR_B744 Carex_whitneyi_MOR_1479_OR_B1070_LG Carex_assiniboinensis_MOR_457_STARR_B105 94 100Carex_assiniboinensis_MOR_456_MB_B104_HC Carex_assiniboinensis_MOR_473_STARR_B121 Carex_sprengelii_MOR_1078_STARR_B670 99 Carex_sprengelii_MOR_1080_STARR_B672 100 Carex_sprengelii_MOR_1568_NB_B1159_HC 99 Carex_sprengelii_MOR_1079_STARR_B671 8 Carex_media_MOR_1238_STARR_B833 86Carex_norvegica_MOR_1418_OR_B1009_RM 67Carex_stevenii_MOR_1629_NM_B1220_RM 9728 Carex_stevenii_MOR_1513_CO_B1104_RM Carex_stevenii_MOR_1512_CO_B1103_RM 20Carex_media_MOR_1284_STARR_B880 51Carex_media_MOR_1597_NB_B1188_RM 98 49Carex_media_MOR_1574_NB_B1165_RM Carex_media_MOR_1825_YT_B1416_RM 36 Carex_nova_MOR_794_STARR_B452 63 Carex_nelsonii_MOR_1634_MO_B1225_RM Carex_bella_MOR_1523_CO_B1114_RM 02 Carex_atrata_MOR_527_STARR_B175 73 Carex_gmelinii_MOR_1867_AK_B1459_RM 1 98 0 Carex_gmelinii_MOR_1431_AK_B1022_RM Carex_atrosquama_MOR_1373_STARR_B964 89 1 Carex_atrosquama_MOR_1522_MO_B1113_RM Carex_albonigra_MOR_1423_AK_B1014_RM Carex_bella_MOR_1883_UT_B1475_RM 0 Carex_heteroneura_MOR_1262_STARR_B857 Carex_B0955b_MOR_1364_STARR 77Carex_nova_MOR_1935_ID_B1527_RM 4366 014Carex_pelocarpa_MOR_997_NV_B589_RM 72 Carex_epapillosa_MOR_1701_WY_B1292_RM 84Carex_heteroneura_MOR_659_NV_B307_RM 0 84 0 Carex_heteroneura_MOR_1619_NV_B1210_RM 1Carex_nelsonii_MOR_1526_STARR_B1117 Carex_chalciolepis_MOR_1524_CO_B1115_RM 97 Carex_nova_MOR_434_CO_B081_RM Carex_atrosquama_MOR_1823_YT_B1414_RM 47 0 65Carex_atratiformis_MOR_1553_AB_B1144_RM 96Carex_atratiformis_MOR_1647_MB_B1238_RM Carex_atratiformis_MOR_1877_NL_B1469_RM Carex_raynoldsii_MOR_986_CA_B578_RM 53 114 Carex_raynoldsii_MOR_1638_ID_B1229_RM 19 Carex_aboriginum_MOR_1640_ID_B1231_RM Carex_raynoldsii_MOR_987_STARR_B579 Carex_helleri_MOR_1492_CA_B1083_RM 44 83Carex_helleri_MOR_1730_CA_B1321_RM 2087 Carex_helleri_MOR_1266_STARR_B861 Carex_epapillosa_MOR_1386_STARR_B977 Carex_heteroneura_MOR_667_STARR_B315 Carex_parryana_parryana_MOR_1235_STARR_B830 2 81 13 Carex_parryana_MOR_1557_MB_B1148_RM97 Carex_parryana_MOR_1436_AK_B1027_RM98 89Carex_parryana_MOR_1502_CO_B1093_RM 2 Carex_hallii_MOR_1556_MB_B1147_RM 77 21 Carex_specuicola_MOR_1616_AZ_B1207_RM Carex_serratodens_MOR_1467_OR_B1058_RM 100 100 9 Carex_serratodens_MOR_1028_CA_B619_RM Carex_idahoa_MOR_1737_CA_B1328_RM 96 1 Carex_idahoa_MOR_1365_STARR_B956 Carex_epapillosa_MOR_1501_WY_B1092_RM 29 Carex_epapillosa_MOR_620_UT_B268_RM Carex_heterostachya_MOR_1824_B1415_PD Carex_adelostoma_MOR_1421_AK_B1012_RM Carex_buxbaumii_MOR_514_STARR_B162 5873 50Carex_buxbaumii_MOR_500_STARR_B148 100Carex_buxbaumii_MOR_499_AK_B147_RM 46 Carex_adelostoma_MOR_1422_AK_B1013_RM Carex_sabulosa_MOR_1448_YT_B1039_RM 100 Carex_sabulosa_MOR_1799_YT_B1390_RM Carex_capillaris_capillaris_MOR_1279_STARR_B874 100Carex_capillaris_MOR_1896_NT_B1488_CS 100 96 Carex_krausei_MOR_1441_AK_B1032_CS Carex_williamsii_MOR_1771_YT_B1362_CS 100 Carex_williamsii_MOR_1925_YT_B1517_CS Carex_distans_MOR_578_STARR_B226 Carex_extensa_MOR_1941_STARR_B1533 95 100 Carex_extensa_Turkey_MOR_1909_B1501_SS100 Carex_extensa_MOR_1655_VA_B1246_SS Carex_viridustellata_MOR_1820_STARR_B1411 100 98 Carex_B1532_MOR_1940_STARR Carex_lutea_MOR_1567_NC_B1158_CC 25 Carex_viridula_saxilittoralis_MOR_1819_B1410_CC 30 Carex_viridula_viridula_MOR_1775_BC_B1366_CC 38 Carex_viridula_elatior_MOR_1704_NF_B1295_CC 51 Carex_viridula_viridula_MOR_1161_MI_B754_CC31 9 21Carex_viridula_oedocarpa_MOR_1750_NS_B1341_CC Carex_viridula_viridula_viridula_MOR_1314_STARR_B911 100 31Carex_viridula_oedocarpa_MOR_1792_NS_B1383_CC 5157 38 5053 Carex_viridula_elatior_MOR_1705_NL_B1296_CC Carex_viridula_MOR_1310_STARR_B90762 Carex_cryptolepis_MOR_1532_IL_B1123_CC 44 4225Carex_cryptolepis_MOR_1881_ON_B1473_CC Carex_viridula_brachyrrhyncha_MOR_1714_QC_B1305_CC

Carex_pendula_MOR_999_STARR_B591 Carex_sylvatica_MOR_1392_WA_B983_HC 56 97 Carex_sylvatica_MOR_1921_Spain_B1513_HC 52 100 Carex_sylvatica_MOR_1922_NY_B1514_HC Carex_folliculata_MOR_645_DE_B293_RT 99Carex_folliculata_MOR_628_STARR_B276 55 100Carex_folliculata_MOR_637_STARR_B285 Carex_lonchocarpa_MOR_1764_LA_B1355_RT 94 Carex_lonchocarpa_MOR_733_FL_B381_RT 99 100 Carex_lonchocarpa_MOR_732_STARR_B380 Carex_michauxiana_MOR_1323_STARR_B920 78 100Carex_michauxiana_MOR_1550_MB_B1141_RT Carex_michauxiana_MOR_1790_NS_B1381_RT 14 49 Carex_turgescens_MOR_1244_MS_B839_RT 100 Carex_turgescens_MOR_1245_STARR_B840 Carex_triquetra_MOR_1660_CA_B1251_TQ 100Carex_triquetra_MOR_1928_CA_B1520_TQ 80 Carex_triquetra_MOR_1602_CA_B1193_TQ Carex_pedunculata_MOR_879_STARR_B539 100Carex_pedunculata_MOR_881_STARR_B541 72 Carex_pedunculata_MOR_880_MD_B540_CL 98 Carex_picta_MOR_895_STARR_B555 Carex_picta_MOR_894_STARR_B554100 86 89 Carex_picta_MOR_893_GA_B553_PT Carex_baltzellii_MOR_490_STARR_B138 100 Carex_baltzellii_MOR_1716_FL_B1307_PT Carex_cherokeensis_MOR_565_STARR_B213 78 100Carex_cherokeensis_MOR_563_STARR_B211 100Carex_cherokeensis_MOR_564_FL_B212_HC Carex_obispoensis_MOR_1599_CA_B1190_HC 100 Carex_obispoensis_MOR_1783_CA_B1374_HC Carex_supina_spaniocarpa_MOR_1596_AK_B1187_LC 100 Carex_glacialis_MOR_1428_AK_B1019_LC 100 24 Carex_glacialis_MOR_1290_STARR_B887 Carex_atrofusca_MOR_1456_AK_B1047_AU Carex_B1452_MOR_1860_STARR Carex_richardsonii_MOR_1022_MD_B613_CL 94 100 Carex_richardsonii_MOR_1683_SD_B1274_CL 98 Carex_concinnoides_MOR_1720_CA_B1311_CL 100 Carex_concinnoides_MOR_1918_ID_B1510_CL Carex_rupestris_MOR_1923_Spain_B1515_RU Carex_obtusata_MOR_841_MB_B501_OB Carex_B1438_MOR_1847_STARR 32 Carex_B1445_MOR_1853_STARR 79 63Carex_B1433_MOR_1842_STARR 24Carex_capitata_MOR_1840_B1431_CT Carex_B1434_MOR_1843_STARR78 7997 84 Carex_B1437_MOR_1846_STARR Carex_B1443_MOR_1852_STARR 16 71 65Carex_B1446_MOR_1854_STARR Carex_B1439_MOR_1848_STARR Carex_capitata_MOR_1838_B1429_CT Carex_B1440_MOR_1849_STARR 63 95Carex_capitata_MOR_1232_STARR_B827 3 Carex_capitata_MOR_1839_BC_B1430_CT 64Carex_B1435_MOR_1844_STARR 63 98Carex_B1436_MOR_1845_STARR Carex_B1432_MOR_1841_STARR 57 78 Carex_capitata_MOR_1856_SK_B1448_CT Carex_B1442_MOR_1851_STARR 96 88Carex_B1441_MOR_1850_STARR Carex_capitata_MOR_1857_B1449_CT Carex_muriculata_MOR_1770_NM_B1361_SD 100 Carex_muriculata_MOR_1612_NM_B1203_PG 94 47 100 100 Carex_nardina_MOR_1312_QC_B909_NA 73 Carex_micropoda_MOR_1673_WY_B1264_IF Carex_micropoda_None_MOR_1816_B1407_DO 97 31 1 Carex_nigricans_MOR_1834_BC_B1425_DO 26 1Carex_nigricans_MOR_1440_AK_B1031_DO 41Carex_micropoda_MOR_1434_AK_B1025_DO 95 Carex_pyrenaica_MOR_1400_STARR_B991 1 100 Carex_micropoda_None_MOR_1817_B1408_DO Carex_micropoda_MOR_1835_BC_B1426_DO Carex_nigricans_MOR_853_STARR_B513 Carex_leptalea_harperi_MOR_779_STARR_B427 59 58 Carex_leptalea_MOR_764_STARR_B412 19 100Carex_leptalea_MOR_781_STARR_B429 56 64Carex_leptalea_MOR_766_STARR_B414 72 59Carex_leptalea_MOR_780_STARR_B428 70 Carex_leptalea_MOR_765_BC_B413_LE 100 100 17 Carex_breweri_MOR_1626_CA_B1217_IF 100 Carex_subnigricans_MOR_1476_OR_B1067_IF 86Carex_breweri_MOR_1378_STARR_B969 100 Carex_engelmannii_MOR_1933_BC_B1525_IF Carex_anthoxanthea_MOR_1370_STARR_B961 100Carex_anthoxanthea_MOR_1833_BC_B1424_CI 74 94 Carex_anthoxanthea_MOR_1420_AK_B1011_CR Carex_circinata_MOR_1779_AK_B1370_CR 100 Carex_circinata_MOR_1762_STARR_B1353 Carex_macrocarpa_MOR_1633_STARR_B1224 100 Carex_bellardii_MOR_1463_STARR_B1054 Carex_geyeri_MOR_676_AB_B324_FC 100 51 Carex_geyeri_MOR_677_STARR_B325 Carex_multicaulis_MOR_1668_CA_B1259_FC 62 100 100Carex_multicaulis_MOR_826_STARR_B486 Carex_multicaulis_MOR_1474_OR_B1065_FC 100 Carex_tompkinsii_MOR_1243_STARR_B838 100 Carex_tompkinsii_MOR_1145_STARR_B738100 Carex_tompkinsii_MOR_1485_CA_B1076_FC Carex_backii_MOR_361_STARR_B007 98Carex_backii_MOR_1809_B1400_PS 67Carex_backii_MOR_1191_STARR_B785 62Carex_backii_MOR_1190_STARR_B784 62 69 Carex_backii_MOR_1189_STARR_B783 Carex_cordillerana_MOR_1346_BC_B943_PS 51 98Carex_cordillerana_MOR_1345_STARR_B942 Carex_cordillerana_MOR_1328_STARR_B925 Carex_juniperorum_MOR_365_KY_B011_PS 81 Carex_juniperorum_MOR_367_STARR_B013 89 Carex_timida_MOR_370_STARR_B016 99 71 60 56Carex_timida_MOR_359_AL_B005_PS Carex_jamesii_MOR_362_STARR_B008 Carex_jamesii_MOR_364_AL_B010_PS95 65 95 10Carex_jamesii_MOR_363_STARR_B009 Carex_willdenowii_MOR_356_STARR_B001 Carex_willdenowii_MOR_357_STARR_B0025 Carex_basiantha_MOR_1325_STARR_B922 6 96Carex_basiantha_MOR_371_SC_B017_PS 9187 65Carex_basiantha_MOR_1337_STARR_B934 25 Carex_basiantha_MOR_360_STARR_B006 42 Carex_superata_MOR_372_STARR_B018 67 Carex_superata_MOR_366_STARR_B012 Carex_willdenowii_MOR_358_KY_B003_PS Carex_saximontana_MOR_1193_STARR_B787 19Carex_saximontana_MOR_1194_STARR_B788 53 Carex_fraserianus_MOR_685_STARR_B333 19 100 100Carex_fraserianus_MOR_684_STARR_B332 3333 Carex_fraserianus_MOR_686_STARR_B334 Carex_saximontana_MOR_1344_STARR_B941 87 Carex_saximontana_MOR_1529_CO_B1120_PS Carex_saximontana_MOR_1343_STARR_B940 Carex_latebracteata_MOR_1185_AR_B779_PS 100 106 Carex_latebracteata_MOR_1192_STARR_B786 Carex_microglochin_Stordalen_MOR_1507_B1098_LG STA1817_Trichophorum_cespitosum 100 STA1816_Trichophorum_alpinum

0.04 Carex_timida_MOR_370_STARR_B016 Carex_juniperorum_MOR_365_KY_B011_PS 60 Maximum likelihood ITS gene tree. Constructed using 88Carex_juniperorum_MOR_367_STARR_B01317 Carex_jamesii_MOR_362_STARR_B00881 RAxML, with a GTRCAT model of evolution and a 200 bootstrap Carex_jamesii_MOR_363_STARR_B00982 Carex_timida_MOR_359_AL_B005_PS analysis. Bootstrap values are plotted on the tree. 83Carex_superata_MOR_368_STARR_B014 Carex_superata_MOR_366_STARR_B01252 Carex_willdenowii_MOR_358_KY_B003_PS 38 61 Carex_willdenowii_MOR_356_STARR_B001 Carex_superata_MOR_369_FL_B015_PS30 37 51 41Carex_superata_MOR_372_STARR_B01846 Carex_basiantha_MOR_360_STARR_B006 Carex_basiantha_MOR_1337_STARR_B934 98 Carex_basiantha_MOR_1325_STARR_B922 Carex_latebracteata_MOR_1192_STARR_B786 100 58 Carex_latebracteata_MOR_1185_AR_B779_PS Carex_backii_MOR_1190_STARR_B784 84 Carex_backii_MOR_1189_STARR_B78381 Carex_backii_MOR_1809_B1400_PS Carex_cordillerana_MOR_1346_BC_B943_PS 68 60 Carex_cordillerana_MOR_1328_STARR_B92586 42Carex_cordillerana_MOR_1345_STARR_B942 83 Carex_saximontana_MOR_1194_STARR_B788 51 92Carex_saximontana_MOR_1343_STARR_B940 Carex_saximontana_MOR_1344_STARR_B941 59 61Carex_saximontana_MOR_1529_CO_B1120_PS Carex_saximontana_MOR_1193_STARR_B787 Carex_fraserianus_MOR_685_STARR_B333 31 100Carex_fraserianus_MOR_684_STARR_B332 Carex_fraserianus_MOR_686_STARR_B334 100Carex_circinata_MOR_1779_AK_B1370_CR 99 Carex_circinata_MOR_1762_STARR_B1353 Carex_anthoxanthea_MOR_1370_STARR_B961 14 100Carex_leptalea_MOR_781_STARR_B429 Carex_leptalea_MOR_766_STARR_B414 37 71 0 100 Carex_micropoda_None_MOR_1816_B1407_DO 56 22 Carex_nigricans_MOR_1834_BC_B1425_DO Carex_micropoda_MOR_1673_WY_B1264_IF Carex_micropoda_MOR_1835_BC_B1426_DO Carex_micropoda_None_MOR_1817_B1408_DO 28 91 88Carex_nigricans_MOR_1440_AK_B1031_DO Carex_micropoda_MOR_1434_AK_B1025_DO Carex_breweri_MOR_1378_STARR_B969 100 1 100Carex_engelmannii_MOR_1933_BC_B1525_IF Carex_subnigricans_MOR_1476_OR_B1067_IF Carex_macrocarpa_MOR_1633_STARR_B1224 1 Carex_microglochin_Stordalen_MOR_1507_B1098_LG 3 Carex_obtusata_MOR_841_MB_B501_OB 55 Carex_B1436_MOR_1845_STARR 97Carex_B1435_MOR_1844_STARR 66 10 50 70 Carex_capitata_MOR_1839_BC_B1430_CT Carex_B1442_MOR_1851_STARR Carex_B1446_MOR_1854_STARR 39 100 Carex_capitata_MOR_1838_B1429_CT 25 Carex_capitata_MOR_1840_B1431_CT 2 34 19Carex_B1439_MOR_1848_STARR 5540 65Carex_B1437_MOR_1846_STARR 24Carex_B1434_MOR_1843_STARR60 Carex_B1445_MOR_1853_STARR Carex_B1433_MOR_1842_STARR Carex_nardina_MOR_1312_QC_B909_NA 100 Carex_oreocharis_MOR_1506_CO_B1097_FL 100Carex_elynoides_MOR_599_STARR_B247 74 92 38 Carex_nigricans_MOR_853_STARR_B513 Carex_muriculata_MOR_1612_NM_B1203_PG 100 Carex_muriculata_MOR_1770_NM_B1361_SD Carex_vallicola_MOR_1514_CO_B1105_PG100 Carex_vallicola_MOR_1788_BC_B1379_PG Carex_appalachica_MOR_438_STARR_B086 77 Carex_rosea_MOR_1016_ME_B607_PG 58 Carex_socialis_MOR_1090_AL_B682_PG 52 Carex_radiata_MOR_985_STARR_B577 82 22 Carex_radiata_MOR_1000_MI_B592_PG 85Carex_texensis_MOR_1142_STARR_B735 79 2453 Carex_texensis_MOR_1482_CA_B1073_PG 28 98Carex_texensis_MOR_1141_STARR_B734 Carex_rosea_MOR_1017_STARR_B608 33 43 Carex_appalachica_MOR_455_MA_B103_PG Carex_douglasii_MOR_1937_ID_B1529_DV 94 52 Carex_perglobosa_MOR_1605_CO_B1196_FO Carex_arkansana_MOR_470_STARR_B118 89 100Carex_arkansana_MOR_471_IL_B119_PG 95 Carex_arkansana_MOR_472_STARR_B120 Carex_kobomugi_MOR_713_VA_B361_MC Carex_kobomugi_MOR_721_STARR_B369100 100Carex_macrocephala_MOR_1236_AK_B831_MC 95 Carex_macrocephala_MOR_1237_STARR_B83299 Carex_macrocephala_MOR_1830_BC_B1421_MC Carex_melanostachya_MOR_1351_STARR_B947 Carex_wiegandii_MOR_1155_ME_B748_SL62 75 Carex_interior_MOR_706_STARR_B354 49 50Carex_atlantica_atlantica_MOR_1360_NC_B952_SL Carex_sterilis_MOR_1545_MB_B1136_SL23 Carex_sterilis_MOR_1085_STARR_B677 85 Carex_ruthii_MOR_1007_STARR_B599 72Carex_atlantica_capillacea_MOR_452_FL_B100_SL 44 34Carex_atlantica_capillacea_MOR_450_STARR_B098 62Carex_atlantica_MOR_463_STARR_B111 Carex_atlantica_capillacea_MOR_451_STARR_B099 30Carex_ruthii_MOR_1008_NC_B600a_SL 37 69 Carex_atlantica_MOR_483_STARR_B131 Carex_echinata_phyllomanica_MOR_1457_AK_B1048_SL 19 Carex_echinata_MOR_604_STARR_B252 Carex_echinata_MOR_603_STARR_B251 456 Carex_davisii_MOR_1355_STARR_B94974 Carex_echinata_phyllomanica_MOR_1385_WA_B976_SL32 Carex_echinata_ssp_echinata_MOR_1313_STARR_B910 1493 92 95Carex_echinata_MOR_602_STARR_B250 Carex_muricata_MOR_1738_STARR_B1329 Carex_echinata_phyllomanica_MOR_1786_BC_B1377_SL 1Carex_echinata_echinata_MOR_1435_AK_B1026_SL 41 Carex_exilis_MOR_1585_MS_B1176_SL 99Carex_exilis_MOR_623_STARR_B271 Carex_exilis_MOR_622_STARR_B27099 96 97 89 Carex_exilis_MOR_621_DE_B269_SL Carex_seorsa_MOR_1020_STARR_B611 72 Carex_seorsa_MOR_1044_DE_B635_SL100 Carex_seorsa_MOR_1024_STARR_B615 Carex_divulsa_MOR_1383_WA_B974_PG 50 98Carex_spicata_MOR_1074_STARR_B666 100Carex_divulsa_MOR_1939_STARR_B1531 Carex_divulsa_divulsa_MOR_580_STARR_B228 72 Carex_spicata_MOR_1073_DE_B665_PG Carex_disperma_MOR_591_STARR_B239 63 Carex_disperma_MOR_581_STARR_B229100 Carex_disperma_MOR_1454_AK_B1045_DS Carex_alata_MOR_422_STARR_B069 Carex_hormathodes_MOR_1309_STARR_B906 Carex_hormathodes_MOR_1916_NS_B1508_OV 53 Carex_straminea_MOR_1054_DE_B645_OV 238 11Carex_straminea_MOR_1053_STARR_B644 45Carex_straminea_MOR_1052_STARR_B643 0 Carex_hormathodes_MOR_635_STARR_B283 Carex_opaca_MOR_847_STARR_B507 18 Carex_alata_MOR_421_AL_B068_OV 43 215Carex_alata_MOR_420_STARR_B067 Carex_albolutescens_MOR_435_MD_B082_OV 30 100 Carex_festucacea_MOR_625_STARR_B273 Carex_longii_MOR_735_AR_B383_OV 27Carex_longii_MOR_740_STARR_B388 Carex_tribuloides_MOR_1124_STARR_B71730 39 Carex_longii_MOR_734_STARR_B382 Carex_vexans_MOR_1168_FLh_B761_OV52 89 Carex_vexans_MOR_1167_STARR_B760 Carex_multicostata_MOR_1688_OR_B1279_OV Carex_multicostata_MOR_1707_OR_B1298_OV65 44 Carex_multicostata_MOR_827_CA_B487_OV 2 Carex_foenea_MOR_1739_ON_B1330_OV Carex_foenea_MOR_1802_BC_B1393_OV71 80 18 Carex_foenea_MOR_643_STARR_B291 Carex_multicostata_MOR_828_STARR_B488 1Carex_straminiformis_MOR_1069_CA_B661_OV Carex_integra_MOR_711_CA_B359_OV 154Carex_integra_MOR_722_STARR_B370 59 5Carex_integra_MOR_712_STARR_B360 67 151 81 Carex_fracta_MOR_631_STARR_B279 Carex_straminiformis_MOR_1664_ID_B1255_OV0 Carex_fracta_MOR_630_CA_B278_OV 4 Carex_haydeniana_MOR_668_STARR_B316 23 Carex_egglestonii_MOR_1610_UT_B1201_OV 12 Carex_egglestonii_MOR_1504_CO_B1095_OV66 32 7 Carex_egglestonii_MOR_1517_CO_B1108_OV Carex_wootonii_MOR_1172_STARR_B765 11 93 Carex_wootonii_MOR_1615_AZ_B1206_OV Carex_preslii_MOR_975_BC_B567_OV Carex_microptera_MOR_832_STARR_B492 24 Carex_macloviana_MOR_1675_AZ_B1266_OV 84 51 Carex_mariposana_MOR_1686_AZ_B1277_OV Carex_douglasii_MOR_1658_CA_B1249_DV63 Carex_macloviana_MOR_1729_BC_B1320_OV Carex_crawfordii_MOR_522_NY_B170_OV Carex_molesta_MOR_803_STARR_B462 26Carex_molesta_MOR_804_DE_B463_OV 10Carex_B1455_MOR_1863_STARR 964 2Carex_molesta_MOR_805_STARR_B464 Carex_molestiformis_MOR_806_STARR_B465 Carex_bebbii_MOR_1917_ON_B1509_OV66 Carex_bebbii_MOR_1315_STARR_B912 0 0 Carex_normalis_MOR_1595_IA_B1186_OV 78Carex_tincta_MOR_1144_ME_B737_OV 56 2 Carex_tincta_MOR_1316_STARR_B913 1 Carex_opaca_MOR_866_STARR_B526 Carex_tribuloides_sangamonensis_MOR_1127_KN_B720_OV Carex_tribuloides_tribuloides_MOR_1311_STARR_B908 59Carex_projecta_MOR_978_MB_B570_OV 34Carex_tribuloides_sangamonensis_MOR_1751_LA_B1342_OV 29 3 Carex_projecta_MOR_1398_STARR_B989 116Carex_tribuloides_MOR_1126_STARR_B719 15Carex_tribuloides_MOR_1123_STARR_B71621 Carex_projecta_MOR_977_STARR_B569 1126Carex_projecta_MOR_979_STARR_B571 42Carex_projecta_MOR_1571_NB_B1162_OV Carex_bebbii_MOR_479_MB_B127_OV Carex_cristatella_MOR_534_KY_B182_OV Carex_cristatella_MOR_533_STARR_B181 88 1485 43Carex_tribuloides_MOR_1125_STARR_B718 Carex_cristatella_MOR_557_DE_B205_OV Carex_reniformis_MOR_990_STARR_B582 14Carex_reniformis_MOR_988_STARR_B58090 31 13Carex_reniformis_MOR_989_GA_B581_OV Carex_cumulata_MOR_605_IL_B253_OV 027Carex_molestiformis_MOR_809_STARR_B468 Carex_hyalina_MOR_647_STARR_B295 31 2093Carex_hyalina_MOR_646_MS_B294_OV Carex_hyalina_MOR_636_STARR_B284 11Carex_molestiformis_MOR_807_AR_B466_OV 2 20 Carex_brevior_MOR_495_STARR_B143 51Carex_merritt-fernaldii_MOR_1736_ON_B1327_OV 1 95 Carex_brevior_MOR_1625_BC_B1216_OV4871 Carex_brevior_MOR_497_STARR_B1455 0 1 80Carex_B0945b_MOR_1348_STARR Carex_brevior_MOR_496_STARR_B144 Carex_bebbii_MOR_1712_ON_B1303_OV Carex_opaca_MOR_867_OK_B527_OV 0 Carex_normalis_MOR_793_AL_B451_OV 68 Carex_shinnersii_MOR_1663_KN_B1254_OV 99Carex_missouriensis_MOR_802_STARR_B461 Carex_missouriensis_MOR_801_IL_B460_OV67 0 Carex_shinnersii_MOR_1027_KN_B618_OV56 0 0Carex_oronensis_MOR_869_STARR_B529 Carex_festucacea_MOR_624_STARR_B2724 6Carex_tenera_echinodes_MOR_1112_MI_B705_OV Carex_tenera_tenera_MOR_1583_WI_B1174_OV18 30Carex_tenera_tenera_MOR_1113_STARR_B706 134Carex_tenera_MOR_1317_STARR_B914 71 Carex_tenera_tenera_MOR_1552_MB_B1143_OV Carex_silicea_MOR_1034_DE_B625_OV Carex_silicea_MOR_1035_STARR_B62665 84 746Carex_silicea_MOR_1570_NB_B1161_OV Carex_bebbii_MOR_480_STARR_B128 2 Carex_bicknellii_MOR_478_IN_B126_OV 27 Carex_merritt_fernaldii_MOR_787_STARR_B445 2 92 Carex_festucacea_MOR_626_TX_B274_OV Carex_normalis_MOR_772_STARR_B420412 Carex_bicknellii_MOR_1697_ON_B1288_OV 24 Carex_tenera_tenera_MOR_1114_STARR_B707 2 Carex_muskingumensis_MOR_849_MI_B509_OV 3954 Carex_muskingumensis_MOR_848_STARR_B50874 76Carex_muskingumensis_MOR_829_STARR_B489 4 4 Carex_muskingumensis_MOR_1746_ON_B1337_OV Carex_merritt_fernaldii_MOR_785_MB_B443_OV Carex_cumulata_MOR_1894_ON_B1486_OV79 Carex_oronensis_MOR_1700_ME_B1291_OV Carex_ovalis_MOR_1562_NC_B1153_OV Carex_ovalis_MOR_1419_WA_B1010_OV10 73 0 Carex_ovalis_MOR_1582_WS_B1173_OV Carex_feta_MOR_627_CA_B275_OV Carex_tetrastachya_MOR_1072_STARR_B664 1 Carex_tetrastachya_MOR_1070_STARR_B662100 86 Carex_tetrastachya_MOR_1071_TXk_B663_OV Carex_ebenea_MOR_683_STARR_B331 37 49Carex_microptera_MOR_833_STARR_B493 Carex_microptera_MOR_1826_YT_B1417_OV14 Carex_arapahoensis_MOR_1904_CO_B1496_OV 3265Carex_ebenea_MOR_1886_UT_B1478_OV Carex_microptera_MOR_1682_CO_B1273_OV37 67Carex_ebenea_MOR_1711_WY_B1302_OV 62Carex_ebenea_MOR_1672_AZ_B1263_OV Carex_arapahoensis_MOR_1527_CO_B1118_OV 38 Carex_straminiformis_MOR_1068_UT_B660_OV Carex_unilateralis_MOR_1650_BC_B1241_OV 44Carex_unilateralis_MOR_1478_OR_B1069_OV Carex_leporinella_MOR_1415_WA_B1006_OV 0 19 Carex_leporinella_MOR_1369_STARR_B96084 37Carex_unilateralis_MOR_1394_STARR_B985 Carex_sychnocephala_MOR_1782_BC_B1373_CP 915Carex_athrostachya_MOR_461_STARR_B109 63 10 6Carex_shinnersii_MOR_1347_STARR_B945 0 Carex_unilateralis_MOR_1767_BC_B1358_OV Carex_sychnocephala_MOR_1108_STARR_B701 4263 26Carex_sychnocephala_MOR_1702_ON_B1293_CP 3 Carex_athrostachya_MOR_460_STARR_B108 Carex_argyrantha_MOR_1875_QC_B1467_OV 89Carex_argyrantha_MOR_468_MD_B116_OV 66 Carex_argyrantha_MOR_469_STARR_B11716 41 Carex_B1428_MOR_1837_STARR 97 Carex_petasata_MOR_1260_CA_B855_OV Carex_davyi_MOR_1261_CA_B856_OV96 57 Carex_praticola_MOR_1671_UT_B1262_OV Carex_proposita_MOR_1399_STARR_B990 65 Carex_phaeocephala_MOR_1742_BC_B1333_OV 21 678 28Carex_phaeocephala_MOR_995_NV_B587_OV Carex_pachystachya_MOR_1528_CO_B1119_OV65 Carex_stenoptila_MOR_1362_MO_B954_OV50 Carex_congdonii_MOR_1741_STARR_B1332 Carex_praticola_MOR_1920_ON_B1512_OV 91 Carex_praticola_MOR_896_STARR_B55695 2 Carex_praticola_MOR_897_CO_B557_OV Carex_adusta_MOR_1307_STARR_B904 45Carex_adusta_MOR_1874_AB_B1466_OV 28 1 Carex_adusta_MOR_413_STARR_B060 1 Carex_xerantica_MOR_1780_BC_B1371_OV 83 Carex_xerantica_MOR_1715_ON_B1306_OV 98Carex_arapahoensis_MOR_1932_CO_B1524_OV Carex_tahoensis_MOR_1477_OR_B1068_OV82 81 Carex_petasata_MOR_994_UT_B586_OV Carex_subfusca_MOR_1670_CA_B1261_OV Carex_abrupta_MOR_409_STARR_B056 33 5158Carex_abrupta_MOR_1259_STARR_B854 Carex_mariposana_MOR_798_STARR_B45630 3361Carex_subfusca_MOR_1104_STARR_B697 Carex_subfusca_MOR_1103_STARR_B696 Carex_macloviana_MOR_1437_AK_B1028_OV 32 28Carex_stenoptila_MOR_1511_CO_B1102_OV Carex_abrupta_MOR_860_BC_B520_OV Carex_pachystachya_MOR_859_STARR_B519 88 50Carex_preslii_MOR_976_OR_B568_OV 32 Carex_gracilior_MOR_1719_CA_B1310_OV 49 55Carex_gracilior_MOR_655_STARR_B303 Carex_harfordii_MOR_699_CA_B347_OV Carex_gracilior_MOR_1494_CA_B1085_OV6065 50 12Carex_subbracteata_MOR_1757_CA_B1348_OV Carex_pachystachya_MOR_1666_AK_B1257_OV 1Carex_stenoptila_MOR_1084_UT_B676_OV Carex_abrupta_MOR_1641_ID_B1232_OV 27 Carex_abrupta_MOR_1258_STARR_B853 Carex_feta_MOR_1403_STARR_B994 Carex_scoparia_MOR_1037_STARR_B628 99 Carex_scoparia_MOR_1036_STARR_B627 25Carex_scoparia_tessellata_MOR_1685_ME_B1276_OV Carex_scoparia_tessellata_MOR_1038_STARR_B62959 20 273Carex_scoparia_tessellata_MOR_1698_ME_B1289_OV Carex_albolutescens_MOR_428_OK_B075_OV 9Carex_albolutescens_MOR_427_STARR_B074 Carex_suberecta_MOR_1591_IA_B1182_OV 39 19 Carex_suberecta_MOR_1361_B953_OV Carex_scoparia_scoparia_MOR_1057_ME_B648_OV Carex_alata_MOR_1359_STARR_B95171 3 79 Carex_scoparia_MOR_1319_STARR_B916 Carex_ozarkana_MOR_874_STARR_B53463 Carex_ozarkana_MOR_858_STARR_B518 Carex_athrostachya_MOR_1349_SK_B946_OV100 Carex_brunnescens_MOR_507_STARR_B155 Carex_loliacea_MOR_1452_AK_B1043_GO 71Carex_marina_MOR_1548_MB_B1139_GO 57Carex_heleonastes_MOR_1458_AK_B1049_GO 56 Carex_heleonastes_MOR_1549_MB_B1140_GO Carex_trisperma_MOR_1255_STARR_B850 56 87 Carex_trisperma_MOR_1257_STARR_B85265 41 Carex_trisperma_MOR_1256_STARR_B851 83Carex_trisperma_MOR_1138_STARR_B731 75 37 Carex_trisperma_MOR_1136_MI_B729_GO82 Carex_trisperma_trisperma_MOR_1137_STARR_B730 12 Carex_heleonastes_MOR_1756_AB_B1347_GO Carex_lachenalii_MOR_1442_AK_B1033_GO 41 79 83 Carex_mackenziei_MOR_1459_AK_B1050_GO100 Carex_mackenziei_MOR_1294_STARR_B891 35 Carex_glareosa_MOR_1558_MB_B1149_GO 99 Carex_ursina_MOR_1936_YT_B1528_GO 100 Carex_ursina_MOR_1777_YT_B1368_GO 100 Carex_chordorrhiza_MOR_1318_STARR_B915 28 100Carex_chordorrhiza_MOR_567_STARR_B215 81 47 Carex_chordorrhiza_MOR_1727_BC_B1318_CH Carex_illota_MOR_695_CA_B343_OV 59Carex_illota_MOR_694_STARR_B342 68Carex_illota_MOR_1408_STARR_B999 26 25Carex_illota_MOR_703_STARR_B351 40Carex_illota_MOR_1519_CO_B1110_OV Carex_laeviculmis_MOR_1199_CA_B794_DE 76 70Carex_laeviculmis_MOR_377_STARR_B024 97Carex_brunnescens_MOR_498_CA_B146_GO Carex_mendocinensis_MOR_1665_ID_B1256_HC Carex_arcta_MOR_445_STARR_B093 1648 Carex_bebbii_MOR_1836_STARR_B142756 Carex_crawfordii_MOR_1832_STARR_B142364 Carex_arcta_MOR_1363_STARR_B955 61 Carex_arcta_MOR_444_AK_B092_GO Carex_arenaria_MOR_1372_STARR_B963 Carex_arenaria_MOR_467_DE_B115_AM100 40 Carex_B1451_MOR_1859_STARR 96Carex_douglasii_MOR_1938_SK_B1530_DV 68 Carex_duriuscula_MOR_1455_AK_B1046_DV100 65 Carex_B1450_MOR_1858_STARR Carex_gynocrates_MOR_1432_AK_B1023_PY 81Carex_gynocrates_MOR_689_STARR_B337 3981Carex_gynocrates_MOR_1299_STARR_B896 Carex_gynocrates_MOR_1503_CO_B1094_PY Carex_praegracilis_MOR_891_STARR_B551 Carex_pansa_MOR_1766_CA_B1357_DV 3Carex_pansa_MOR_1462_OR_B1053_DV 67 Carex_occidentalis_MOR_1934_CA_B1526_PG 1958 5695Carex_alma_MOR_437_CA_B085_MF Carex_alma_MOR_430_STARR_B077 99Carex_occidentalis_MOR_1661_NV_B1252_PG67 24 Carex_alma_MOR_1873_UT_B1465_MF Carex_praegracilis_MOR_902_STARR_B562 68 Carex_chihuahuensis_MOR_1614_AZ_B1205_MF Carex_prairea_MOR_1573_NB_B1164_HE 56 Carex_prairea_MOR_1569_NB_B1160_HE 94 Carex_diandra_MOR_575_STARR_B22350 39 98Carex_diandra_MOR_574_CA_B222_HE Carex_diandra_MOR_1382_STARR_B97364 100 Carex_diandra_MOR_1321_STARR_B918 Carex_prairea_MOR_1753_BC_B1344_HE 100 97 Carex_prairea_MOR_903_STARR_B563 Carex_cusickii_MOR_1231_STARR_B826 82 10 Carex_cusickii_MOR_1379_STARR_B970 89 100Carex_cusickii_MOR_606_STARR_B254 40 Carex_cusickii_MOR_1806_BC_B1397_HE Carex_simulata_MOR_1390_STARR_B981 Carex_bonanzensis_MOR_1623_NT_B1214_GO 100Carex_bonanzensis_MOR_1905_YT_B1497_GO 95Carex_bonanzensis_MOR_1622_AK_B1213_GO 68 Carex_praeceptorum_MOR_1754_CA_B1345_GO Carex_praeceptorum_MOR_1397_STARR_B988 Carex_canescens_MOR_545_STARR_B193 96Carex_arctiformis_MOR_1653_BC_B1244_GO 5 Carex_paupercula_MOR_983_STARR_B5756 4820Carex_canescens_canescens_MOR_1377_STARR_B968 44Carex_canescens_MOR_546_CA_B194_GO Carex_canescens_disjuncta_MOR_1283_STARR_B879 Carex_laeviculmis_MOR_1831_BC_B1422_DE4 26Carex_canescens_disjuncta_MOR_1298_STARR_B895 1349 Carex_brunnescens_brunnescens_MOR_1286_NFLD_B882_GO 181157 Carex_canescens_canescens_MOR_544_STARR_B19251 22Carex_lapponica_MOR_1822_NT_B1413_GO Carex_canescens_canescens_MOR_1289_NFLD_B886_GO Carex_lapponica_MOR_1443_AK_B1034_PD Carex_praeceptorum_MOR_889_STARR_B549 Carex_laevivaginata_MOR_726_STARR_B374 53 Carex_stipata_maxima_MOR_1063_FL_B654_VU 47 Carex_laevivaginata_MOR_728_STARR_B376 79 13Carex_stipata_stipata_MOR_1055_MB_B646_VU Carex_laevivaginata_MOR_727_AL_B375_VU Carex_stipata_MOR_1305_STARR_B9027461 Carex_stipata_MOR_1064_STARR_B656 21Carex_stipata_stipata_MOR_1061_STARR_B652 49 Carex_stipata_maxima_MOR_1062_STARR_B653 67Carex_stipata_MOR_1056_STARR_B647 Carex_densa_MOR_1471_OR_B1062_MF 41 62 Carex_densa_MOR_1472_OR_B1063_MF68 Carex_densa_MOR_1690_CA_B1281_MF Carex_gravida_MOR_704_KN_B352_PG Carex_aggregata_MOR_419_KY_B066_PG 10Carex_mesochorea_MOR_830_STARR_B490 14Carex_mesochorea_MOR_831_AL_B491_PG 55 628 Carex_mesochorea_MOR_820_STARR_B480 14Carex_cephalophora_MOR_543_STARR_B191 Carex_perdentata_MOR_993_TX_B585_PG Carex_gravida_MOR_716_STARR_B364 239 201111Carex_aggregata_MOR_418_STARR_B065 32 5Carex_cephaloidea_MOR_538_MA_B186_PG Carex_sparganioides_sparaganioides_MOR_1092_WI_B684_PG 1 Carex_cephaloidea_MOR_550_STARR_B198 Carex_sparganioides_MOR_1093_STARR_B685 91 Carex_sparganioides_MOR_1091_DE_B683_PG 20 Carex_muhlenbergii_enervis_MOR_822_STARR_B482 Carex_muehlenbergii_muehlenbergii_MOR_824_MS_B484_P 79Carex_muhlenbergii_MOR_825_STARR_B485 Carex_muhlenbergii_enervis_MOR_821_STARR_B48178 74 Carex_muehlenbergii_enervis_MOR_1768_AR_B1359_PG Carex_triangularis_MOR_1149_GA_B742_MF 1053 58Carex_vulpinoidea_MOR_1153_CA_B746_MF 50 90 Carex_vulpinoidea_MOR_1152_STARR_B745 5911 Carex_alopecoidea_MOR_448_STARR_B096 61 76Carex_alopecoidea_MOR_1322_STARR_B919 Carex_alopecoidea_MOR_1530_IL_B1121_VU 56 Carex_conjuncta_MOR_518_DE_B166_VU 6 Carex_conjuncta_MOR_520_STARR_B16895 99Carex_conjuncta_MOR_519_STARR_B167 99

77 56 96 35 Carex_triangularis_MOR_1148_STARR_B741 81Carex_triangularis_MOR_1146_TX_B739_MF Carex_annectens_MOR_439_MD_B087_MF 40Carex_annectens_MOR_464_AL_B112_MF Carex_densa_MOR_573_CA_B221_MF 92 Carex_densa_MOR_1380_STARR_B971 Carex_austrina_MOR_526_STARR_B174 45 99 59 82Carex_austrina_MOR_524_DE_B172_PG Carex_austrina_MOR_525_STARR_B173 23 Carex_muehlenbergii_MOR_837_FL_B497_PG 99 65 48 Carex_muhlenbergii_MOR_808_STARR_B467 Carex_cephalophora_MOR_562_DE_B210_PG71 49 Carex_cephalophora_MOR_542_STARR_B190 Carex_crus_corvi_MOR_554_STARR_B202 100 Carex_crus_corvi_MOR_556_FL_B204_VU 68Carex_crus_corvi_MOR_555_STARR_B203 Carex_nervina_MOR_1642_CA_B1233_VU Carex_simulata_MOR_1086_CA_B678_DV 53 100Carex_simulata_MOR_1087_STARR_B679 40 Carex_jonesii_MOR_1412_WA_B1003_VU 34 56 Carex_vernacula_MOR_1264_STARR_B859 59 Carex_neurophora_MOR_1417_WA_B1008_VU 100 68 Carex_neurophora_MOR_1627_WY_B1218_VU Carex_jonesii_MOR_1518_CO_B1109_VU Carex_decomposita_MOR_571_STARR_B219 100Carex_decomposita_MOR_572_STARR_B220 85Carex_decomposita_MOR_570_DE_B218_HE Carex_oklahomensis_MOR_844_STARR_B504 100 72Carex_oklahomensis_MOR_845_AR_B505_VU Carex_oklahomensis_MOR_843_STARR_B503 Carex_divisa_MOR_1942_VA_B1534_DV 28 Carex_bromoides_MOR_374_STARR_B020 98Carex_bromoides_montana_MOR_376_NC_B023_DE 87Carex_bromoides_montana_MOR_1654_VA_B1245_DE 65 30 Carex_bromoides_MOR_375_STARR_B021 Carex_deweyana_deweyana_MOR_1381_STARR_B972 56 Carex_deweyana_deweyana_MOR_774_BC_B422_DE80 Carex_deweyana_deweyana_MOR_754_STARR_B402 85 66 Carex_deweyana_collectanea_MOR_1814_QC_B1405_DE 78 99Carex_deweyanavar.collectanea_MOR_1812_QC_B1403_DE78 Carex_deweyana_deweyana_MOR_773_MB_B421_DE Carex_deweyana_collectanea_MOR_1813_QC_B1404_DE 98 43 33 100 Carex_bolanderi_MOR_373_STARR_B019 68Carex_bolanderi_MOR_1217_STARR_B812 Carex_cephalophorum_MOR_1828_STARR_B1419 47 79Carex_leptopoda_MOR_1201_BC_B796_DE 64 74 Carex_leptopoda_MOR_378_STARR_B025 Carex_bolanderi_MOR_1216_CA_B811_DE76 Carex_bolanderi_MOR_1218_STARR_B813 Carex_siccata_MOR_1032_STARR_B623 67 47Carex_siccata_MOR_1872_ON_B1464_AM 72Carex_siccata_MOR_1033_STARR_B624 Carex_siccata_MOR_1662_NM_B1253_AM 100Carex_incurviformis_MOR_1787_BC_B1378_FO 76 95Carex_incurviformis_MOR_1903_CO_B1495_FO Carex_incurviformis_MOR_1525_CO_B1116_FO Carex_hoodii_MOR_633_STARR_B281 Carex_occidentalis_MOR_842_STARR_B50271 Carex_hoodii_MOR_634_STARR_B28264 99 448Carex_occidentalis_MOR_1628_NM_B1219_PG Carex_tumulicola_MOR_1393_STARR_B984 934 Carex_hoodii_MOR_632_STARR_B280 Carex_hoodii_MOR_1732_CA_B1323_PG 73Carex_hookerana_MOR_1795_MN_B1386_PG 28Carex_tumulicola_MOR_1140_CA_B733_PG 35 9521Carex_vallicola_MOR_1265_STARR_B860 Carex_occidentalis_MOR_1630_NM_B1221_PG Carex_sartwellii_MOR_1010_STARR_B601 Carex_sartwellii_MOR_1021_STARR_B61296 99Carex_sartwellii_MOR_1784_BC_B1375_HH Carex_geyeri_MOR_677_STARR_B325100 Carex_geyeri_MOR_676_AB_B324_FC Carex_tompkinsii_MOR_1485_CA_B1076_FC 100 95 100Carex_tompkinsii_MOR_1145_STARR_B738 60 Carex_tompkinsii_MOR_1243_STARR_B838 Carex_multicaulis_MOR_1474_OR_B1065_FC 100 Carex_multicaulis_MOR_826_STARR_B486 Carex_hendersonii_MOR_1187_STARR_B781 Carex_hendersonii_MOR_1749_BC_B1340_LF100 25 56 19 Carex_glaucodea_MOR_493_STARR_B14170 Carex_blanda_MOR_1621_KS_B1212_LF30

2Carex_blanda_MOR_474_MD_B122_LF Carex_B1412_MOR_1821_STARR 225 100 3049 87Carex_ormostachya_MOR_1275_STARR_B870 Carex_gracilescens_MOR_661_KY_B309_LF Carex_gracilescens_MOR_1188_STARR_B782 15Carex_gracilescens_MOR_662_STARR_B310 Carex_striatula_MOR_1075_STARR_B667 5 64 80 312 Carex_chapmanii_MOR_566_FL_B214_LF 0 28Carex_striatula_MOR_1066_DE_B658_LF 3Carex_radfordii_MOR_1240_SC_B835_LF Carex_striatula_MOR_1065_STARR_B657 Carex_kraliana_MOR_710_STARR_B358 Carex_concinna_MOR_1358_STARR_B950b 100 71Carex_albursina_MOR_1186_STARR_B780 6 Carex_albursina_MOR_1195_STARR_B789 39 Carex_leptonervia_MOR_767_STARR_B415 Carex_leptonervia_MOR_1197_STARR_B79198 63 9 82 Carex_leptonervia_MOR_1198_STARR_B792 Carex_leptonervia_MOR_1196_MB_B790_LF Carex_kraliana_MOR_715_AR_B363_LF Carex_kraliana_MOR_717_STARR_B36538 Carex_manhartii_MOR_1271_STARR_B866 98 74 Carex_manhartii_MOR_1563_GE_B1154_LF34 Carex_manhartii_MOR_1578_TN_B1169_LF52 Carex_purpurifera_MOR_1272_KY_B867_LF 56Carex_woodii_MOR_1592_IA_B1183_PN Carex_biltmoreana_MOR_1870_NC_B1462_PN16 48Carex_woodii_MOR_1171_STARR_B764 10Carex_biltmoreana_MOR_475_STARR_B123 3669Carex_biltmoreana_MOR_1943_STARR_B1535 Carex_woodii_MOR_1170_STARR_B763 Carex_hassei_MOR_1669_CA_B1260_BI Carex_tetanica_MOR_1116_MB_B709_PN 59 64Carex_hassei_MOR_1516_CO_B1107_BI 47Carex_B1456_MOR_1864_STARR Carex_tetanica_MOR_1593_IA_B1184_PN 2311Carex_meadii_MOR_782_STARR_B440 56 31 12Carex_aurea_MOR_502_STARR_B150 914Carex_meadii_MOR_1544_MB_B1135_PN 99 Carex_bicolor_MOR_1303_STARR_B900 50 Carex_livida_MOR_1450_AK_B1041_PN 11 Carex_livida_MOR_1212_NJ_B807_PN Carex_bicolor_MOR_1554_AB_B1145_BI Carex_aurea_MOR_1263_STARR_B85887 5Carex_laxa_MOR_1895_YT_B1487_PN 60 9Carex_garberi_MOR_1426_AK_B1017_BI 69 1410Carex_bicolor_MOR_1424_AK_B1015_BI 99Carex_garberi_MOR_1733_YT_B1324_BI Carex_aurea_MOR_501_CA_B149_BI2 2Carex_hassei_MOR_700_STARR_B348 Carex_klamathensis_MOR_1871_OR_B1463_PN11 Carex_livida_MOR_1725_CA_B1316_PN Carex_meadii_MOR_791_STARR_B449 Carex_ormostachya_MOR_868_MI_B528_LF Carex_vaginata_MOR_1776_YT_B1367_PN 90 Carex_atratiformis_MOR_1649_BC_B1240_RM 63 Carex_laxa_MOR_1445_AK_B1036_PN 36 Carex_panicea_MOR_1681_NS_B1272_PN 100 Carex_panicea_MOR_1708_ME_B1299_PN Carex_petricosa_petricosa_MOR_1901_YT_B1493_AU 100 Carex_petricosa_misandroides_MOR_1797_QC_B1388_AU 87Carex_B1453_MOR_1861_STARR 94 Carex_B1454_MOR_1862_STARR96 6 Carex_petricosa_petricosa_MOR_1446_AK_B1037_AU Carex_atrofusca_MOR_1456_AK_B1047_AU Carex_concinnoides_MOR_1918_ID_B1510_CL 12 100 Carex_concinnoides_MOR_1720_CA_B1311_CL 74 Carex_richardsonii_MOR_1022_MD_B613_CL 100 50 Carex_richardsonii_MOR_1683_SD_B1274_CL Carex_B1452_MOR_1860_STARR 70 Carex_scirpoidea_MOR_1059_STARR_B650 14Carex_scirpoidea_scirpoidea_MOR_1050_AK_B641_SP Carex_scirpoidea_scirpoidea_MOR_1717_ON_B1308_SP 66 88Carex_scirpoidea_MOR_1308_STARR_B905 Carex_scirpoidea_convoluta_MOR_1759_ON_B1350_SP97 46 Carex_scirpoidea_convoluta_MOR_1722_ON_B1313_SP Carex_scabriuscula_MOR_1049_STARR_B640 35 100 Carex_scirpoidea_scirpoidea_MOR_1465_OR_B1056_SP Carex_scirpoidea_stenochlaena_MOR_1604_WA_B1195_SP 45 36 56Carex_scirpoidea_stenochlaena_MOR_1603_AK_B1194_SP 95Carex_scirpoidea_pseudoscirpoidea_MOR_1805_BC_B1396_SP 58 18 Carex_scabriuscula_MOR_1048_CA_B639_SP Carex_scirpoidea_MOR_1051_STARR_B642 Carex_curatorum_MOR_1818_B1409_SP 13 51 Carex_scirpoidea_pseudoscirpoidea_MOR_1508_CO_B1099_SP Carex_curatorum_MOR_1769_UT_B1360_SP 73Carex_scirpoidea_pseudoscirpoidea_MOR_1891_UT_B1483_SP Carex_williamsii_MOR_1925_YT_B1517_CS 100 Carex_williamsii_MOR_1771_YT_B1362_CS 99 Carex_capillaris_capillaris_MOR_1279_STARR_B874 100Carex_krausei_MOR_1441_AK_B1032_CS Carex_capillaris_MOR_1896_NT_B1488_CS90 Carex_limosa_MOR_768_STARR_B416 85Carex_limosa_MOR_770_STARR_B418 77 Carex_limosa_MOR_769_AK_B417_LM 82 Carex_magellanica_MOR_1439_AK_B1030_LM 62 20Carex_paupercula_MOR_898_STARR_B558 100Carex_magellanica_MOR_982_STARR_B574 Carex_magellanica_irrigua_MOR_1521_CO_B1112_LM 33 Carex_stylosa_MOR_1292_NFLD_B889_RM 26 Carex_haydenii_MOR_1282_STARR_B878 100Carex_haydenii_MOR_1890_MA_B1482_PC Carex_aperta_MOR_1644_BC_B1235_PC 56 36 23 94Carex_aperta_MOR_453_STARR_B101 Carex_aperta_MOR_1371_STARR_B962 Carex_prasina_MOR_900_GA_B560_HC 70Carex_prasina_MOR_901_STARR_B561 12 Carex_prasina_MOR_899_STARR_B559 Carex_macrochaeta_MOR_1473_OR_B1064_LM Carex_aquatilis_aquatilis_MOR_441_STARR_B089 14 100Carex_endlichii_MOR_1897_AZ_B1489_PC 10 39 76 92 68 Carex_barbarae_MOR_1251_CA_B846_PC 97 Carex_baileyi_MOR_486_STARR_B134 91 12 Carex_barbarae_MOR_1254_STARR_B849 Carex_houghtoniana_MOR_1248_MB_B843_PD 100 Carex_houghtoniana_MOR_1584_WI_B1175_PD Carex_pumila_MOR_1869_NC_B1461_PD Carex_sheldonii_MOR_1636_ID_B1227_CX Carex_laeviconica_MOR_723_STARR_B371 30Carex_trichocarpa_MOR_1135_STARR_B728 35 54 69Carex_trichocarpa_MOR_1133_DE_B726_CX 0Carex_trichocarpa_MOR_1134_STARR_B727 9 47 Carex_laeviconica_MOR_1689_KS_B1280_CX Carex_sheldonii_MOR_1495_CA_B1086_CX 17 99 Carex_sheldonii_MOR_1607_CA_B1198_CX Carex_aureolensis_MOR_504_MS_B152_SQ 100Carex_aureolensis_MOR_503_STARR_B151 66 100 Carex_aureolensis_MOR_505_STARR_B153 20 6 Carex_frankii_MOR_671_STARR_B319 100Carex_frankii_MOR_672_STARR_B320 41 64Carex_frankii_MOR_673_AL_B321_SQ Carex_atherodes_MOR_459_STARR_B107 Carex_atherodes_MOR_1331_STARR_B928 14 8063 70Carex_atherodes_MOR_458_STARR_B106 Carex_atherodes_MOR_1651_BC_B1242_CX Carex_hirta_MOR_681_PN_B329_CX 41 94Carex_hirta_MOR_1575_NB_B1166_CX 98Carex_hirta_MOR_680_STARR_B328 Carex_hirta_MOR_1326_STARR_B923 Carex_melanostachya_MOR_1352_OK_B947b_PD 100 Carex_melanostachya_MOR_1693_KN_B1284_PD100 Carex_melanostachya_MOR_1745_NE_B1336_PD 35 Carex_hyalinolepsis_MOR_701_STARR_B349 46 80 Carex_hyalinolepsis_MOR_649_STARR_B29799 Carex_hyalinolepis_MOR_690_TX_B338_PD 33 Carex_lacustris_MOR_724_STARR_B372 6 Carex_lacustris_MOR_725_MB_B373_PD100 51 88Carex_lacustris_MOR_1339_STARR_B936 3 Carex_lasiocarpa_MOR_731_AK_B379_PD 7 Carex_pellita_MOR_885_STARR_B545 Carex_pellita_MOR_882_CA_B542_PD 22Carex_pellita_MOR_883_STARR_B543644 100 19Carex_pellita_MOR_862_STARR_B522 Carex_missouriensis_MOR_799_STARR_B458 10 Carex_pellita_MOR_1606_YT_B1197_PD Carex_striata_MOR_1077_STARR_B66967 96Carex_striata_MOR_1067_STARR_B659 Carex_striata_MOR_1076_FL_B668_PD 27 Carex_exsiccata_MOR_1489_CA_B1080_VC Carex_vesicaria_MOR_1163_STARR_B756 9793 68Carex_exsiccata_MOR_1387_STARR_B978 2 Carex_exsiccata_MOR_1778_BC_B1369_VC 0 Carex_tuckermanii_MOR_1336_STARR_B933 Carex_tuckermanii_MOR_1139_STARR_B73298 89 Carex_tuckermanii_MOR_1147_MI_B740_VC Carex_schweinitzii_MOR_1656_VA_B1247_VC 0 Carex_schweinitzii_MOR_1058_MI_B649_VC91 Carex_oligosperma_MOR_846_STARR_B506 38 21Carex_utriculata_MOR_1182_STARR_B775 8 Carex_rotundata_MOR_1551_MB_B1142_VC5 Carex_rostrata_MOR_1402_STARR_B99312 6 Carex_membranacea_MOR_784_AK_B442_VC 1 60 15Carex_membranacea_MOR_1338_STARR_B935 Carex_utriculata_MOR_1184_STARR_B777 Carex_rostrata_MOR_1005_STARR_B597 3052 22Carex_utriculata_MOR_1183_STARR_B776 Carex_utriculata_MOR_1181_AK_B774_VC 77Carex_vesicaria_monile_MOR_1164_STARR_B757 Carex_vesicaria_MOR_1162_DE_B755_VC 20Carex_saxatilis_MOR_1572_NB_B1163_VC 42Carex_saxatilis_MOR_1023_CO_B614_VC 94 Carex_saxatilis_MOR_1025_STARR_B616 Carex_halliana_MOR_1469_OR_B1060_PD 33 73Carex_halliana_MOR_1491_CA_B1082_PD Carex_halliana_MOR_1405_STARR_B996 Carex_gigantea_MOR_650_STARR_B298 19 100 97Carex_gigantea_MOR_651_FL_B299_LU Carex_gigantea_MOR_648_STARR_B296 78 Carex_lupuliformis_MOR_755_STARR_B403 Carex_lupulina_MOR_812_MD_B472_LU Carex_louisianica_MOR_741_STARR_B389 70 34 100 31 Carex_louisianica_MOR_736_STARR_B384 44 Carex_louisianica_MOR_742_FL_B390_LU Carex_lupuliformis_MOR_745_FL_B393_LU 84 265 59Carex_lupuliformis_MOR_744_STARR_B392 Carex_lupulina_MOR_813_STARR_B473 Carex_bullata_MOR_509_MA_B157_VC 31 90Carex_bullata_MOR_508_STARR_B156 Carex_bullata_MOR_510_STARR_B158 Carex_hystericina_MOR_692_STARR_B340 Carex_hystericina_MOR_815_AR_B475_VC 3365 Carex_hystricina_MOR_1407_STARR_B99838 76 Carex_hystericina_MOR_693_STARR_B34137 69Carex_hystericina_MOR_691_STARR_B339 Carex_thurberi_MOR_1899_AZ_B1491_VC 3 100Carex_thurberi_MOR_1618_AZ_B1209_VC Carex_pseudocyperus_MOR_1543_MB_B1134_VC 47 72Carex_pseudocyperus_MOR_981_B573_VC 60Carex_pseudocyperus_MOR_1320_STARR_B917 39 Carex_pseudocyperus_MOR_980_STARR_B572 74Carex_comosa_MOR_528_STARR_B176 Carex_comosa_MOR_532_STARR_B18083 72 Carex_comosa_MOR_560_CA_B208_VC Carex_retrorsa_MOR_1012_MI_B603_VC 23 69Carex_retrorsa_MOR_1330_STARR_B927 Carex_retrorsa_MOR_1401_STARR_B992 Carex_lurida_MOR_816_FL_B476_VC 1 62Carex_baileyi_MOR_487_STARR_B135 48 89Carex_lurida_MOR_814_STARR_B474 44Carex_barbarae_MOR_484_STARR_B132 98 Carex_lurida_MOR_1761_LA_B1352_VC Carex_baileyi_MOR_485_KY_B133_VC Carex_intumescens_MOR_709_ME_B357_LU 100Carex_intumescens_MOR_708_STARR_B356 27 Carex_elliottii_MOR_1718_FL_B1309_VC 100Carex_elliotti_MOR_598_STARR_B246 98 Carex_elliottii_MOR_1533_NC_B1124_VC 42 Carex_grayi_MOR_666_STARR_B314 99 Carex_grayi_MOR_658_KN_B306_LU100 Carex_grayi_MOR_657_STARR_B305 Carex_torta_MOR_1130_STARR_B723 Carex_podocarpa_MOR_1734_BC_B1325_ST 100 Carex_podocarpa_MOR_1744_YT_B1335_ST Carex_nudata_MOR_1461_OR_B1052_PC 100 1 Carex_interrupta_MOR_1468_OR_B1059_PC 63Carex_emoryi_MOR_619_DE_B267_PC 98 31 98Carex_emoryi_MOR_600_STARR_B248 Carex_emoryi_MOR_610_STARR_B258 Carex_lenticularis_MOR_753_STARR_B401 Carex_bigelowii_lugens_MOR_1620_AK_B1211_PC Carex_microchaeta_microchaeta_MOR_1696_YT_B1287_ST 1Carex_holostoma_MOR_1731_STARR_B1322 Carex_scopulorum_MOR_1039_STARR_B630 8 Carex_scopulorum_scopulorum_MOR_1041_STARR_B632 22Carex_scopulorum_bracteosa_MOR_1040_STARR_B631 11 5 12 Carex_senta_MOR_1043_STARR_B634 Carex_senta_MOR_1042_STARR_B633 5548 7 Carex_nudata_MOR_1242_CAs_B837_PC59 61Carex_nudata_MOR_797_STARR_B455 12 Carex_schottii_MOR_1483_CA_B1074_PC54 61Carex_schottii_MOR_1772_CA_B1363_PC 99Carex_schottii_MOR_1601_CA_B1192_PC Carex_senta_MOR_1687_AZ_B1278_PC Carex_lenticularis_lipocarpa_MOR_746_CA_B394_PC Carex_angustata_MOR_447_CA_B095_PC 63 12 84 63 91Carex_angustata_MOR_1460_OR_B1051_PC 14 Carex_interrupta_MOR_1411_WA_B1002_PC Carex_bigelowii_lugens_MOR_476_AK_B124_PC 5 Carex_subspathacea_MOR_1674_QC_B1265_PC 47Carex_vacillans_MOR_1691_ME_B1282_PC 59 43Carex_paleacea_MOR_861_ME_B521_PC 92Carex_vacillans_MOR_1577_NB_B1168_PC Carex_salina_MOR_1755_QC_B1346_PC 32Carex_aquatilis_dives_MOR_1486_CA_B1077_PC Carex_aquatilis_dives_MOR_1414_WA_B1005_PC 6139 3 Carex_aquatilis_dives_MOR_1430_AK_B1021_PC32 Carex_aquatilis_dives_MOR_1643_BC_B1234_PC Carex_lyngbyei_MOR_819_OR_B479_PC 53 Carex_lyngbyei_MOR_818_STARR_B478 9 66Carex_ramenskii_MOR_1241_AK_B836_PC 44 56Carex_subspathacea_MOR_1559_MB_B1150_PC 23 Carex_ramenskii_MOR_1447_AK_B1038_PC 15Carex_aquatilis_aquatilis_MOR_1287_B884_PC 8 Carex_macloviana_MOR_1520_STARR_B111173 22Carex_aquatilis_substricta_MOR_1713_NE_B1304_PC 60 6 Carex_aquatilis_MOR_443_STARR_B091186548 Carex_lenticularis_MOR_748_STARR_B396 Carex_aquatilis_aquatilis_MOR_1576_NB_B1167_PC Carex_aquatilis_substricta_MOR_1684_NB_B1275_PC 42Carex_aquatilis_aquatilis_MOR_1752_NL_B1343_PC 41 29 Carex_recta_MOR_1947_B1539_PC Carex_emoryi_MOR_1930_NB_B1522_PC 96 Carex_stricta_MOR_1099_STARR_B691 Carex_lenticularis_dolia_MOR_749_STARR_B397 Carex_lenticularis_dolia_MOR_1807_BC_B1398_PC90 75 Carex_lenticularis_dolia_MOR_752_STARR_B400 Carex_lenticularis_dolia_MOR_1547_AB_B1138_PC36 Carex_lenticularis_limnophila_MOR_1413_WA_B1004_PC 2344 47Carex_lenticularis_limnophila_MOR_1882_BC_B1474_PC Carex_lenticularis_lipocarpa_MOR_1451_AK_B1042_PC5 Carex_lenticularis_limnophila_MOR_1898_AK_B1490_PC Carex_angustata_MOR_1233_STARR_B82835 31 Carex_lenticularis_impressa_MOR_750_CA_B398_PC 3 Carex_lenticularis_impressa_MOR_747_STARR_B395 13 Carex_lenticularis_lipocarpa_MOR_751_STARR_B399 Carex_nigra_MOR_1297_NFLD_B894_PC 95Carex_nigra_MOR_852_STARR_B512 84 31Carex_nigra_Lapland_MOR_1910_B1502_PC 100Carex_eleusinoides_MOR_1425_AK_B1016_PC Carex_eleusinoides_MOR_1893_YT_B1485_PC 3 9 Carex_mertensii_MOR_788_STARR_B446 Carex_mertensii_MOR_789_STARR_B447 5170 Carex_mertensii_MOR_790_AK_B448_RM 33 Carex_barrattii_MOR_482_AL_B130_LM 83 79 7 Carex_barrattii_MOR_481_STARR_B12994 Carex_barrattii_MOR_491_STARR_B139 Carex_obnupta_MOR_839_CA_B499_PC 57 Carex_scopulorum_scopulorum_MOR_1509_CO_B1100_PC Carex_stricta_MOR_1098_TX_B690_PC Carex_squarrosa_MOR_1082_STARR_B674 78 Carex_squarrosa_MOR_1083_AR_B675_SQ Carex_complanata_MOR_516_TX_B164_PO 42Carex_complanata_MOR_517_STARR_B165 31 Carex_complanata_MOR_515_STARR_B16348 10Carex_hirsutella_MOR_678_STARR_B326 Carex_swanii_MOR_1107_STARR_B700 57Carex_swanii_MOR_1105_STARR_B698 55 Carex_swanii_MOR_1106_AR_B699_PO Carex_aestivalis_MOR_414_STARR_B061 90 Carex_aestivalis_MOR_1590_GA_B1181_HC Carex_virescens_MOR_1158_AL_B751_PO40 59Carex_roanensis_MOR_1579_TN_B1170_HC 41 5 Carex_virescens_MOR_1159_STARR_B75262 Carex_virescens_MOR_1160_STARR_B753 59 Carex_roanensis_MOR_1026_NC_B617_HC Carex_tenax_MOR_1111_STARR_B704 96 Carex_tenax_MOR_1110_STARR_B703 48 Carex_dasycarpa_MOR_607_GA_B255_HL 80 89Carex_dasycarpa_MOR_609_STARR_B257 0 Carex_dasycarpa_MOR_608_HL_B256_FL 2 Carex_whitneyi_MOR_1151_STARR_B744 97 Carex_whitneyi_MOR_1479_OR_B1070_LG 95 7 Carex_whitneyi_MOR_1154_CA_B747_LG Carex_hirtifolia_MOR_1277_STARR_B872 99Carex_hirtifolia_MOR_670_STARR_B318 93 Carex_hirtifolia_MOR_682_DE_B330_HT 0 Carex_gracillima_MOR_663_STARR_B311 1 Carex_davisii_MOR_592_DE_B240_HC Carex_davisii_MOR_593_STARR_B241 6 28Carex_B0949b_MOR_1356_STARR Carex_davisii_MOR_594_STARR_B242 7 Carex_hirsutella_MOR_679_STARR_B327 Carex_caroliniana_MOR_549_AL_B197_PO 68 35 Carex_caroliniana_MOR_547_STARR_B195 0 6 73 1 11Carex_caroliniana_MOR_548_STARR_B196 0 Carex_hirsutella_MOR_669_DE_B317_PO 2 65 24Carex_bushii_MOR_511_DE_B159_PO Carex_bushii_MOR_513_STARR_B161 10 26 Carex_oxylepis_MOR_878_STARR_B53825 Carex_bushii_MOR_512_STARR_B160 Carex_oxylepis_pubescens_MOR_873_STARR_B533 81 6 Carex_oxylepis_MOR_870_STARR_B530 60 Carex_oxylepis_MOR_875_STARR_B535 4 Carex_oxylepis_pubescens_MOR_871_KY_B531_HC Carex_gracillima_MOR_656_AL_B304_HC 4 Carex_debilis_rudgei_MOR_569_STARR_B217 48 14Carex_debilis_debilis_MOR_1280_NFLD_B875_HC Carex_gracillima_MOR_664_STARR_B312 0 Carex_debilis_rudgei_MOR_558_TN_B206_HC 13 34Carex_debilis_MOR_596_STARR_B244 Carex_venusta_MOR_1174_MS_B767_HC Carex_aestivalis_MOR_416_STARR_B063 30Carex_aestivalis_MOR_1250_STARR_B845 32 Carex_aestivalis_MOR_415_PN_B062_HC Carex_misera_MOR_1566_TN_B1157_HC 0 Carex_mitchelliana_MOR_835_AL_B495_PC Carex_gynandra_MOR_714_STARR_B36280 Carex_gynandra_MOR_698_DE_B346_PC 7 Carex_crinita_brevicrinis_MOR_539_STARR_B187 90Carex_crinita_brevicrinis_MOR_540_AR_B188_PC 27 Carex_crinita_crinita_MOR_535_ME_B183_PC 10 21 42Carex_crinita_crinita_MOR_541_STARR_B189 0 13 Carex_mitchelliana_MOR_800_STARR_B459 29 33Carex_crinita_brevicrinis_MOR_523_STARR_B171 Carex_mitchelliana_MOR_836_STARR_B496 0 Carex_gynandra_MOR_688_STARR_B336 Carex_formosa_MOR_1534_IL_B1125_HC 97 95Carex_formosa_MOR_1794_MN_B1385_HC Carex_formosa_MOR_1887_ON_B1479_HC 2 8 Carex_typhina_MOR_1132_AR_B725_SQ 98Carex_typhina_MOR_1131_STARR_B724 63 0 Carex_typhina_MOR_1129_STARR_B722 11 Carex_shortiana_MOR_1031_KN_B622_SH 68 100Carex_shortiana_MOR_1030_STARR_B621 0 Carex_shortiana_MOR_1029_STARR_B620 Carex_sartwelliana_MOR_1600_CA_B1191_PD Carex_congdonii_MOR_1699_CA_B1290_PD Carex_verrucosa_MOR_1723_LA_B1314_GC 100 4 Carex_verrucosa_MOR_1176_STARR_B769100 Carex_verrucosa_MOR_1175_FL_B768_GC 100 Carex_glaucescens_MOR_660_MS_B308_GC 88 3 100Carex_glaucescens_MOR_1945_TX_B1537_GC Carex_joorii_MOR_719_STARR_B367 Carex_polymorpha_MOR_1709_ME_B1300_PN 91Carex_polymorpha_MOR_890_STARR_B550 89 Carex_californica_MOR_1637_ID_B1228_PN 93 99Carex_californica_MOR_1487_CA_B1078_PN 2 Carex_californica_MOR_1376_STARR_B967 Carex_pallescens_MOR_863_STARR_B523 0 Carex_pallescens_MOR_1295_STARR_B892 59 8020 Carex_pallescens_MOR_1810_B1401_PO64 100Carex_pallescens_MOR_864_STARR_B524 36 Carex_pallescens_MOR_1811_BC_B1402_PO Carex_acutiformis_MOR_1924_Spain_B1516_PD 46 52 Carex_torreyi_MOR_1120_STARR_B713 95 Carex_torreyi_MOR_1510_CO_B1101_PO100 11 Carex_torreyi_MOR_1581_TN_B1172_PO Carex_vestita_MOR_1165_DE_B758_PD Carex_sartwelliana_MOR_1239_STARR_B834 23 100 Carex_sartwelliana_MOR_1484_STARR_B1075 37 Carex_amplifolia_MOR_1270_STARR_B865 94 Carex_amplifolia_MOR_449_NV_B097_AN Carex_debilis_MOR_597_STARR_B245 Carex_arctata_MOR_446_STARR_B094 56 Carex_arctata_MOR_465_WI_B113_HC Carex_castanea_MOR_1281_NFLD_B876_HC 2650 3 Carex_castanea_MOR_537_STARR_B185 Carex_gynodynama_MOR_1470_OR_B1061_HC 18 99Carex_gynodynama_MOR_1490_CA_B1081_HC 64Carex_gynodynama_MOR_1706_CA_B1297_HC 37 Carex_hirtissima_MOR_1728_CA_B1319_HC 87 1 90Carex_hirtissima_MOR_1496_CA_B1087_HC 35 Carex_hirtissima_MOR_1497_CA_B1088_HC 6 Carex_mendocinensis_MOR_1475_OR_B1066_HC Carex_debilis_MOR_595_STARR_B243 27 0 Carex_venusta_MOR_1173_STARR_B766 Carex_arctata_MOR_466_STARR_B1140 Carex_venusta_minor_MOR_1177_STARR_B770 12Carex_arctata_MOR_1652_NS_B1243_HC Carex_debilis_rudgei_MOR_559_STARR_B207 Carex_lonchocarpa_MOR_1764_LA_B1355_RT 98 99Carex_lonchocarpa_MOR_733_FL_B381_RT 68 Carex_lonchocarpa_MOR_732_STARR_B380 100Carex_folliculata_MOR_637_STARR_B285 Carex_folliculata_MOR_628_STARR_B276 84 Carex_folliculata_MOR_645_DE_B293_RT 100 Carex_michauxiana_MOR_1323_STARR_B920 96 98Carex_michauxiana_MOR_1790_NS_B1381_RT 67Carex_michauxiana_MOR_1550_MB_B1141_RT Carex_turgescens_MOR_1244_MS_B839_RT 100 Carex_turgescens_MOR_1245_STARR_B840 Carex_macrochaeta_MOR_1438_AK_B1029_LM Carex_microchaeta_microchaeta_MOR_1885_WY_B1477_ST 23 Carex_microchaeta_microchaeta_MOR_1748_YT_B1339_ST2 22 Carex_microchaeta_nesophila_MOR_1726_AK_B1317_ST Carex_spectabilis_MOR_1804_BC_B1395_ST7 61Carex_spectabilis_MOR_1097_STARR_B689 22Carex_macrochaeta_MOR_1747_BC_B1338_LM 50 54100Carex_microchaeta_nesophila_MOR_1735_AK_B1326_ST Carex_spectabilis_MOR_1781_BC_B1372_ST Carex_haydeniana_MOR_1888_AB_B1480_OV Carex_microchaeta_microchaeta_MOR_1609_YT_B1200_ST31 Carex_pedunculata_MOR_879_STARR_B539 100 Carex_pedunculata_MOR_881_STARR_B541 86 Carex_baltzellii_MOR_490_STARR_B138 Carex_picta_MOR_893_GA_B553_PT 83 69 Carex_picta_MOR_894_STARR_B554100 Carex_picta_MOR_895_STARR_B555 Carex_extensa_MOR_1941_STARR_B1533100 Carex_extensa_MOR_1655_VA_B1246_SS 99 Carex_distans_MOR_578_STARR_B226 100 Carex_distans_MOR_1908_Spain_B1500_SS Carex_triquetra_MOR_1602_CA_B1193_TQ100 Carex_triquetra_MOR_1928_CA_B1520_TQ100 Carex_triquetra_MOR_1660_CA_B1251_TQ 80 Carex_lativena_MOR_1631_NM_B1222_HL 7Carex_lativena_MOR_1868_TX_B1460_HL 9100Carex_planostachys_MOR_884_TXc_B544_HL Carex_planostachys_MOR_887_STARR_B547 1 8 Carex_sylvatica_MOR_1922_NY_B1514_HC 56Carex_sylvatica_MOR_1878_ON_B1470_HC 100Carex_sylvatica_MOR_1392_WA_B983_HC92 Carex_sylvatica_MOR_1921_Spain_B1513_HC 92 Carex_pendula_MOR_998_STARR_B590 100 95 Carex_pendula_MOR_1395_WA_B986_RC Carex_pendula_MOR_999_STARR_B591 Carex_hostiana_MOR_1306_STARR_B903 Carex_viridula_brachyrrhyncha_MOR_1714_QC_B1305_CC Carex_cryptolepis_MOR_1532_IL_B1123_CC74 64 2 62Carex_cryptolepis_MOR_1881_ON_B1473_CC Carex_viridula_saxilittoralis_MOR_1819_B1410_CC 4036 3 Carex_viridula_oedocarpa_MOR_1750_NS_B1341_CC40 0 Carex_viridula_elatior_MOR_1704_NF_B1295_CC Carex_viridula_viridula_MOR_1161_MI_B754_CC 1454 8 Carex_viridula_viridula_viridula_MOR_1314_STARR_B91168 51Carex_viridula_viridula_MOR_1775_BC_B1366_CC Carex_viridula_MOR_1310_STARR_B907 990 68 100 Carex_lutea_MOR_1567_NC_B1158_CC 78 Carex_viridustellata_MOR_1820_STARR_B1411 Carex_B1532_MOR_1940_STARR100 Carex_hostiana_MOR_1914_QC_B1506_CC 32Carex_hostiana_MOR_1796_QC_B1387_CC Carex_pensylvanica_MOR_904_STARR_B564 Carex_lucorum_austrolucorum_MOR_737_STARR_B385 Carex_lucorum_austrolucorum_MOR_1537_TN_B1128_AC Carex_reznicekii_MOR_1015_STARR_B606 60 Carex_tonsa_MOR_1119_STARR_B71250 85 Carex_tonsa_rugosperma_MOR_1539_IL_B1130_AC 15Carex_albicans_albicans_MOR_425_KS_B072_AC Carex_albicans_australis_MOR_436_MS_B083_AC23 18 Carex_nigromarginata_MOR_854_STARR_B514 20Carex_albicans_albicans_MOR_423_STARR_B070 14 Carex_tonsa_rugosperma_MOR_1157_MB_B750_AC 2 Carex_tonsa_tonsa_MOR_1156_MB_B749_AC 7 8245Carex_umbellata_MOR_1178_DE_B771_AC 63Carex_umbellata_MOR_1179_STARR_B772 Carex_tonsa_MOR_1118_STARR_B7115049 57 66 Carex_umbellata_MOR_1180_STARR_B773 2 Carex_tonsa_MOR_1117_STARR_B710 5 Carex_pensylvanica_MOR_1396_STARR_B987 Carex_albicans_emmonsii_MOR_432_STARR_B079 Carex_albicans_australis_MOR_426_STARR_B07348 1 96 8 19 Carex_albicans_australis_MOR_429_STARR_B076 0 Carex_novae_angliae_MOR_796_STARR_B454 Carex_novae_angliae_MOR_795_ME_B453_AC98 79 Carex_novae-angliae_MOR_1580_MN_B1171_AC Carex_lucorum_MOR_739_STARR_B387 Carex_lucorum_austrolucorum_MOR_743_GA_B391_AC Carex_lucorum_lucorum_MOR_1538_NC_B1129_AC64 100 4 Carex_sprengelii_MOR_1080_STARR_B672 Carex_sprengelii_MOR_1568_NB_B1159_HC94 100Carex_sprengelii_MOR_1079_STARR_B67169 Carex_sprengelii_MOR_1078_STARR_B670 Carex_caryophyllea_Ibirica_MOR_1865_B1457_MT 9 Carex_fuliginosa_MOR_1429_AK_B1020_AU 100Carex_fuliginosa_MOR_1453_AK_B1044_AU 63Carex_fuliginosa_MOR_1676_NU_B1267_AU Carex_conoidea_MOR_1230_DE_B825_GR 100Carex_conoidea_MOR_1229_STARR_B824 Carex_corrugata_MOR_1226_STARR_B821 65 17 Carex_corrugata_MOR_404_AL_B051_GR 26Carex_corrugata_MOR_403_SC_B050_GR Carex_godfreyi_MOR_1329_STARR_B926 59 9Carex_godfreyi_MOR_380_STARR_B027 86 Carex_corrugata_MOR_386_STARR_B033 Carex_godfreyi_MOR_1589_AL_B1180_GR 572 Carex_amphibola_MOR_388_AL_B035_GR 25Carex_grisea_MOR_390_KY_B037_GR 32Carex_grisea_MOR_398_STARR_B045 18 Carex_grisea_MOR_1335_STARR_B932 96Carex_oligocarpa_MOR_407_STARR_B054 Carex_thornei_MOR_394_GA_B041_GR 9Carex_calcifugens_MOR_401_STARR_B048 20Carex_thornei_MOR_1542_GA_B1133_GR 2 Carex_bulbostylis_MOR_382_MS_B029_GR 1 Carex_amphibola_MOR_385_STARR_B032 64Carex_amphibola_MOR_387_STARR_B034 111 8 Carex_calcifugens_MOR_402_FL_B049_GR 47 Carex_acidicola_MOR_392_AL_B039_GR 0Carex_acidicola_MOR_1249_STARR_B844 Carex_thornei_MOR_395_STARR_B042 51 Carex_paeninsulae_MOR_1247_FLc_B842_GR Carex_paeninsulae_MOR_1253_STARR_B84866 1 13 3945Carex_paeninsulae_MOR_383_STARR_B030 Carex_thornei_MOR_393_FL_B040_GR 44Carex_planispicata_MOR_400_MD_B047_GR 47 548Carex_planispicata_MOR_1341_STARR_B938 Carex_planispicata_MOR_1333_STARR_B930 Carex_acidicola_MOR_384_STARR_B031 Carex_oligocarpa_MOR_1274_STARR_B869 60 84 61Carex_oligocarpa_MOR_1334_AR_B931_GR Carex_magellanica_MOR_1354_STARR_B948b Carex_impressinervia_MOR_1586_MS_B1177_GR Carex_ouachitana_MOR_1340_AR_B937_GR 9156 71Carex_ouachitana_MOR_1224_STARR_B819 Carex_ouachitana_MOR_1225_STARR_B820 45 Carex_pigra_MOR_399_STARR_B04647 35 64Carex_pigra_MOR_1587_MS_B1178_GR 0Carex_pigra_MOR_1342_STARR_B939 6 52 Carex_pigra_MOR_1645_AL_B1236_GR 5269Carex_gholsonii_MOR_687_AL_B335_GL Carex_gholsonii_MOR_696_STARR_B344 Carex_glaucodea_MOR_1327_IN_B924_GR 31 69Carex_glaucodea_MOR_397_STARR_B044 65 36 Carex_glaucodea_MOR_1227_STARR_B82288 17 Carex_glaucodea_MOR_396_STARR_B043 Carex_gholsonii_MOR_697_STARR_B345 Carex_microdonta_MOR_1648_NM_B1239_GL 92 Carex_crawei_MOR_1273_NFLD_B868_GL99 Carex_microdonta_MOR_1223_STARR_B81896 100 Carex_microdonta_MOR_1222_MS_B817_GL Carex_granularis_MOR_1209_MB_B804_GL 100Carex_granularis_MOR_665_STARR_B313 79 Carex_granularis_MOR_1220_STARR_B815 Carex_digitalis_macropoda_MOR_589_AR_B237_CY 73 30 9Carex_digitalis_micropoda_MOR_584_STARR_B232 91Carex_digitalis_micropoda_MOR_587_STARR_B235 86 78 56 53 3 Carex_digitalis_digitalis_MOR_585_DE_B233_CY Carex_laxiculmis_MOR_1276_STARR_B871 72 Carex_digitalis_MOR_586_STARR_B234 4 36 Carex_cumberlandensis_MOR_551_AR_B199_CY Carex_laxiculmis_copulata_MOR_1535_IL_B1126_CY Carex_laxiculmis_copulata_MOR_1536_TN_B1127_CY 133 24 25 14Carex_cumberlandensis_MOR_553_STARR_B201 38 16 Carex_abscondita_MOR_411_STARR_B058 3Carex_cumberlandensis_MOR_552_STARR_B200 Carex_abscondita_MOR_410_DE_B057_CY 97Carex_abscondita_MOR_412_STARR_B059 Carex_laxiculmis_laxiculmis_MOR_1205_PN_B800_CY 30 Carex_laxiculmis_laxiculmis_MOR_1206_STARR_B801 19 Carex_hitchcockiana_MOR_391_KY_B038_GR Carex_hitchcockiana_MOR_1215_STARR_B810100 44 100 Carex_hitchcockiana_MOR_1213_STARR_B808 Carex_brysonii_MOR_389_AL_B036_GR 100 Carex_brysonii_MOR_1900_AL_B1492_GR Carex_austrocaroliniana_MOR_489_STARR_B137 59 74Carex_austrocaroliniana_MOR_488_STARR_B136 100 Carex_austrocaroliniana_MOR_1531_NC_B1122_CY 71 Carex_austrocaroliniana_MOR_1588_TN_B1179_CY Carex_plantaginea_MOR_1695_TN_B1286_CY 100 Carex_plantaginea_MOR_1269_STARR_B864 27 Carex_platyphylla_MOR_886_MD_B546_CY 39 97 59Carex_platyphylla_MOR_1268_STARR_B863 47 Carex_platyphylla_MOR_1278_STARR_B873 Carex_careyana_MOR_1203_KY_B798_CY 93 Carex_careyana_MOR_1204_STARR_B799 Carex_luzulifolia_MOR_1267_STARR_B862 Carex_luzulina_ablata_MOR_1694_WY_B1285_AU 14 Carex_collinsii_MOR_561_DE_B209_CO 100 36 Carex_collinsii_MOR_568_STARR_B216100 38 Carex_collinsii_MOR_1565_GA_B1156_CO Carex_luzulina_MOR_817_OR_B477_AU 55 13Carex_luzulina_luzulina_MOR_1740_NV_B1331_AU 0 47Carex_luzulina_ablata_MOR_1481_CA_B1072_AU Carex_luzulifolia_MOR_762_CA_B410_AU 35Carex_luzulina_luzulina_MOR_1765_CA_B1356_AU 33 67 61Carex_luzulina_luzulina_MOR_1710_CA_B1301_AU Carex_lemmonii_MOR_763_CA_B411_AU 86Carex_lemmonii_MOR_1480_CA_B1071_AU61

Carex_assiniboinensis_MOR_456_MB_B104_HC 100Carex_assiniboinensis_MOR_473_STARR_B121 Carex_eburnea_MOR_576_MI_B224_AL 69 100Carex_eburnea_MOR_601_STARR_B249 Carex_eburnea_MOR_582_STARR_B230 Carex_heteroneura_MOR_667_STARR_B315 Carex_B0955b_MOR_1364_STARR 30 72Carex_nova_MOR_1935_ID_B1527_RM 1 Carex_pelocarpa_MOR_997_NV_B589_RM Carex_nelsonii_MOR_1526_STARR_B1117 14 Carex_chalciolepis_MOR_1931_CO_B1523_RM 5 Carex_bella_MOR_1883_UT_B1475_RM 22 78 4 Carex_bella_MOR_1523_CO_B1114_RM Carex_nova_MOR_434_CO_B081_RM Carex_epapillosa_MOR_1701_WY_B1292_RM 4 73 Carex_epapillosa_MOR_1386_STARR_B977 99 Carex_epapillosa_MOR_1501_WY_B1092_RM 26 45 Carex_epapillosa_MOR_620_UT_B268_RM Carex_nova_MOR_794_STARR_B452 1 44 45Carex_nelsonii_MOR_1634_MO_B1225_RM Carex_heteroneura_MOR_1619_NV_B1210_RM 36 93 Carex_heteroneura_MOR_659_NV_B307_RM 48Carex_helleri_MOR_1266_STARR_B861 Carex_helleri_MOR_1730_CA_B1321_RM Carex_albonigra_MOR_1423_AK_B1014_RM Carex_holostoma_MOR_1433_AK_B1024_RM Carex_adelostoma_MOR_1421_AK_B1012_RM 10050 41 54Carex_buxbaumii_MOR_514_STARR_B162 Carex_buxbaumii_MOR_499_AK_B147_RM 27 Carex_norvegica_MOR_1418_OR_B1009_RM 11 Carex_stevenii_MOR_1512_CO_B1103_RM 74 99Carex_stevenii_MOR_1629_NM_B1220_RM 88 42 Carex_stevenii_MOR_1513_CO_B1104_RM Carex_media_MOR_1238_STARR_B83361 82 Carex_media_MOR_1284_STARR_B880 16 77Carex_atratiformis_MOR_1877_NL_B1469_RM 83Carex_atratiformis_MOR_1553_AB_B1144_RM Carex_atrosquama_MOR_1823_YT_B1414_RM 97 28 Carex_media_MOR_1825_YT_B1416_RM 52Carex_media_MOR_1597_NB_B1188_RM Carex_media_MOR_1574_NB_B1165_RM73 Carex_atrata_MOR_527_STARR_B175 17 Carex_heterostachya_MOR_1824_B1415_PD 86 Carex_sabulosa_MOR_1448_YT_B1039_RM 11 98Carex_sabulosa_MOR_1799_YT_B1390_RM Carex_gmelinii_MOR_1431_AK_B1022_RM 99Carex_gmelinii_MOR_1867_AK_B1459_RM Carex_specuicola_MOR_1616_AZ_B1207_RM 92Carex_hallii_MOR_1556_MB_B1147_RM 23 Carex_parryana_parryana_MOR_1235_STARR_B830 41Carex_parryana_MOR_1557_MB_B1148_RM57 Carex_parryana_MOR_1436_AK_B1027_RM23 8235 67 Carex_parryana_MOR_1502_CO_B1093_RM Carex_hallii_MOR_1793_MN_B1384_RM Carex_aboriginum_MOR_1640_ID_B1231_RM 64 Carex_serratodens_MOR_1028_CA_B619_RM 100 1 51 Carex_serratodens_MOR_1467_OR_B1058_RM Carex_idahoa_MOR_1365_STARR_B956 Carex_heteroneura_MOR_1262_STARR_B857 11Carex_raynoldsii_MOR_986_CA_B578_RM 38 2 Carex_raynoldsii_MOR_1638_ID_B1229_RM Carex_atrosquama_MOR_1522_MO_B1113_RM Carex_atrosquama_MOR_1373_STARR_B96448 Carex_supina_spaniocarpa_MOR_1596_AK_B1187_LC 69 Carex_glacialis_MOR_1290_STARR_B887 Carex_geophila_MOR_1500_CO_B1091_AC 3 Carex_tonsa_MOR_1293_STARR_B890 17 74 Carex_geophila_MOR_1680_CO_B1271_AC 2 2 Carex_inops_inops_MOR_1410_WA_B1001_AC Carex_turbinata_MOR_1773_AZ_B1364_AC 47 Carex_vallicola_MOR_1613_AZ_B1204_PG 5 Carex_pensylvanica_MOR_973_MB_B565_AC 28 03 Carex_pensylvanica_MOR_974_STARR_B566 0 18 Carex_geophila_MOR_674_STARR_B322 Carex_pityophila_MOR_1632_NM_B1223_AC69 37 Carex_peckii_MOR_1427_AK_B1018_AC Carex_communis_communis_MOR_530_NC_B178_AC 50 Carex_communis_MOR_529_STARR_B177 47Carex_communis_MOR_1291_STARR_B888 8 Carex_communis_MOR_811_STARR_B470 3181 47Carex_communis_amplisquama_MOR_1724_GA_B1315_AC Carex_communis_MOR_531_STARR_B179 Carex_serpenticola_MOR_1763_CA_B1354_AC 34 183 Carex_albicans_emmonsii_MOR_433_MD_B080_AC 1Carex_nigromarginata_MOR_855_AL_B515_AC 1Carex_B1399_MOR_1808_STARR Carex_tonsa_tonsa_MOR_1906_ON_B1498_AC Carex_turbinata_MOR_1679_AZ_B1270_AC 43Carex_rossii_MOR_1003_STARR_B595 Carex_brainerdii_MOR_494_CA_B142_AC 49 743 Carex_brainerdii_MOR_1252_STARR_B847 Carex_brainerdii_MOR_1246_STARR_B841 24Carex_brevicaulis_MOR_1375_WA_B966_AC 23 48 2710

52 Carex_serpenticola_MOR_1466_OR_B1057_AC Carex_globosa_MOR_654_CA_B302_AC Carex_cherokeensis_MOR_565_STARR_B213 99 100Carex_cherokeensis_MOR_563_STARR_B211 98 Carex_cherokeensis_MOR_564_FL_B212_HC 107 Carex_obispoensis_MOR_1783_CA_B1374_HC Carex_obispoensis_MOR_1599_CA_B1190_HC98 STA1816_Trichophorum_alpinum 100 STA1817_Trichophorum_cespitosum

0.03 Carex_macrocarpa_MOR_1633_STARR_B1224 Maximum likelihood Carex_capitata_MOR_1838_B1429_CT Carex_capitata_MOR_1857_B1449_CT matK gene tree. Constructed 42 Carex_willdenowii_MOR_358_KY_B003_PS using RAxML, with a GTRCAT 2 Carex_manhartii_MOR_1563_GE_B1154_LF 1 25 Carex_geyeri_MOR_676_AB_B324_FC model of evolution and a 200 Carex_multicaulis_MOR_1668_CA_B1259_FC 1 65 Carex_tompkinsii_MOR_1485_CA_B1076_FC 13 Carex_timida_AR_B004_PS bootstrap analysis. Bootstrap 64 7 Carex_timida_MOR_359_AL_B005_PS73 4 46 Carex_juniperorum_MOR_365_KY_B011_PS values are plotted on the tree. Carex_jamesii_MOR_364_AL_B010_PS 7217 Carex_basiantha_MOR_371_SC_B017_PS Carex_superata_MOR_369_FL_B015_PS 3 49 Carex_fraserianus_PN_B333 80 18 Carex_latebracteata_MOR_1185_AR_B779_PS 57 Carex_backii_MOR_1809_B1400_PS Carex_saximontana_MOR_1529_CO_B1120_PS97 Carex_cordillerana_MOR_1346_BC_B943_PS Carex_circinata_MOR_1779_AK_B1370_CR 54 Carex_anthoxanthea_MOR_1420_AK_B1011_CR 42 Carex_engelmannii_MOR_1933_BC_B1525_IF 32 73 98Carex_breweri_MOR_1626_CA_B1217_IF 11 Carex_subnigricans_MOR_1476_OR_B1067_IF Carex_muriculata_MOR_1612_NM_B1203_PG Carex_nardina_MOR_1312_QC_B909_NA 49 49 100 17 41 Carex_oreocharis_AZ_B1269_FL Carex_leptalea_MOR_765_BC_B413_LE 48 60 Carex_capitata_MOR_1840_B1431_CT 47 Carex_obtusata_MOR_841_MB_B501_OB Carex_micropoda_MOR_1673_WY_B1264_IF 46 Carex_micropoda_MOR_1434_AK_B1025_DO Carex_nigricans_MOR_1440_AK_B1031_DO100 Carex_microglochin_Stordalen_MOR_1507_B1098_LG Carex_siccata_MOR_644_CO_B292_AM Carex_cephaloidea_MOR_538_MA_B186_PG 64 Carex_sparganioides_sparaganioides_MOR_1092_WI_B684_PG 0 34 Carex_annectens_MOR_439_MD_B087_MF 17 Carex_triangularis_MOR_1146_TX_B739_MF Carex_triangularis_MOR_1149_GA_B742_MF60 17 63 63 Carex_annectens_MOR_464_AL_B112_MF29 20Carex_vulpinoidea_MOR_1153_CA_B746_MF Carex_densa_MOR_1471_OR_B1062_MF 10 35 Carex_densa_MOR_573_CA_B221_MF 64 Carex_nervina_MOR_1884_NV_B1476_VU 19 Carex_neurophora_MOR_1417_WA_B1008_VU 2 Carex_decomposita_MOR_570_DE_B218_HE Carex_alopecoidea_MOR_1530_IL_B1121_VU 62 Carex_conjuncta_MOR_518_DE_B166_VU Carex_hookerana_MOR_1915_AB_B1507_PG Carex_hoodii_MOR_1732_CA_B1323_PG Carex_sartwellii_MOR_1784_BC_B1375_HH14 Carex_divulsa_MOR_1383_WA_B974_PG 0 72Carex_muricata_lamprocarpa_MOR_1912_Spain_B1504_PG Carex_spicata_MOR_1073_DE_B665_PG Carex_arkansana_MOR_471_IL_B119_PG 39 Carex_socialis_MOR_1090_AL_B682_PG43 0 77Carex_radiata_MOR_1001_MA_B593_PG 23 Carex_appalachica_MOR_455_MA_B103_PG 2 11 61 Carex_rosea_MOR_1016_ME_B607_PG 34 Carex_rosea_MOR_1018_WI_B609_PG68 7 47 Carex_radiata_MOR_1000_MI_B592_PG 2 Carex_appalachica_MOR_454_TN_B102_PG 2 Carex_texensis_MOR_1482_CA_B1073_PG 69 Carex_vallicola_MOR_1788_BC_B1379_PG Carex_disperma_MOR_1454_AK_B1045_DS 76 88 Carex_macrocephala_MOR_1236_AK_B831_MC 41 Carex_kobomugi_MOR_713_VA_B361_MC Carex_douglasii_MOR_1938_SK_B1530_DV 91Carex_duriuscula_MOR_1455_AK_B1046_DV 0 Carex_chordorrhiza_MOR_1727_BC_B1318_CH Carex_tumulicola_MOR_1140_CA_B733_PG Carex_marina_MOR_1548_MB_B1139_GO 63 Carex_mackenziei_MOR_1459_AK_B1050_GO 40 Carex_lachenalii_MOR_1442_AK_B1033_GO 03 0 Carex_gynocrates_MOR_1432_AK_B1023_PY 0Carex_heleonastes_MOR_1756_AB_B1347_GO Carex_loliacea_MOR_1452_AK_B1043_GO 0 Carex_praeceptorum_MOR_1754_CA_B1345_GO 0 Carex_brunnescens_brunnescens_MOR_1286_NFLD_B882_GO 67 65 Carex_canescens_MOR_546_CA_B194_GO 0 40Carex_canescens_canescens_MOR_1289_NFLD_B886_GO 6 9642 Carex_arctiformis_MOR_1653_BC_B1244_GO67 Carex_lapponica_MOR_1443_AK_B1034_PD 8 Carex_canescens_disjuncta_MOR_1561_NC_B1152_GO Carex_arcta_MOR_444_AK_B092_GO 56 Carex_brunnescens_sphaerostachya_NFLD_B883_GO 39 23 Carex_brunnescens_MOR_498_CA_B146_GO 68Carex_laeviculmis_MOR_1199_CA_B794_DE 0 Carex_trisperma_MOR_1136_MI_B729_GO 6 Carex_illota_MOR_695_CA_B343_OV 48 Carex_bonanzensis_MOR_1622_AK_B1213_GO 0 Carex_ursina_MOR_1777_YT_B1368_GO Carex_glareosa_MOR_1558_MB_B1149_GO71 Carex_exilis_MOR_621_DE_B269_SL Carex_seorsa_MOR_1044_DE_B635_SL 39 31Carex_sterilis_MOR_1545_MB_B1136_SL 24 91Carex_atlantica_atlantica_MOR_1360_NC_B952_SL Carex_atlantica_capillacea_MOR_452_FL_B100_SL 0 Carex_echinata_phyllomanica_MOR_1385_WA_B976_SL 51 81 3 57Carex_echinata_echinata_MOR_1435_AK_B1026_SL 0 63 Carex_interior_MOR_705_MD_B353_SL 41 30 Carex_wiegandii_MOR_1155_ME_B748_SL Carex_ruthii_MOR_1008_NC_B600a_SL Carex_laevivaginata_MOR_727_AL_B375_VU 0 Carex_stipata_stipata_MOR_1055_MB_B646_VU91 78Carex_stipata_maxima_MOR_1063_FL_B654_VU Carex_pansa_MOR_1766_CA_B1357_DV 0Carex_edwardsiana_MOR_1944_TX_B1536_GR 3Carex_occidentalis_MOR_1934_CA_B1526_PG Carex_alma_MOR_437_CA_B085_MF Carex_crus_corvi_MOR_556_FL_B204_VU 1 Carex_vernacula_MOR_1515_CO_B1106_FO 11 Carex_jonesii_MOR_1412_WA_B1003_VU Carex_aggregata_MOR_419_KY_B066_PG 88Carex_gravida_MOR_704_KN_B352_PG 50 Carex_leavenworthii_MOR_759_AL_B407_PG 0 Carex_mesochorea_MOR_831_AL_B491_PG 94Carex_muehlenbergii_enervis_MOR_1768_AR_B1359_PG5 0 9Carex_perdentata_MOR_993_TX_B585_PG14 6 Carex_cephalophora_MOR_562_DE_B210_PG Carex_austrina_MOR_524_DE_B172_PG45 0 Carex_muehlenbergii_muehlenbergii_MOR_824_MS_B484_P57 8 Carex_muehlenbergii_MOR_837_FL_B497_PG Carex_sparganioides_MOR_1091_DE_B683_PG Carex_incurviformis_MOR_1903_CO_B1495_FO 59 Carex_deweyanavar.collectanea_MOR_1812_QC_B1403_DE 52 Carex_deweyana_deweyana_MOR_774_BC_B422_DE 1 93 Carex_deweyana_deweyana_MOR_773_MB_B421_DE 77Carex_bolanderi_MOR_1216_CA_B811_DE 0 86 Carex_leptopoda_MOR_1201_BC_B796_DE Carex_sychnocephala_MOR_1702_ON_B1293_CP 0 Carex_bromoides_MD_B022_DE 93 Carex_bromoides_montana_MOR_376_NC_B023_DE Carex_praegracilis_MOR_892_ME_B552_DV 97 Carex_chihuahuensis_MOR_1614_AZ_B1205_MF Carex_oklahomensis_MOR_845_AR_B505_VU Carex_microptera_MOR_1682_CO_B1273_OV 0 43Carex_ebenea_MOR_1672_AZ_B1263_OV 2 65 Carex_straminiformis_MOR_1068_UT_B660_OV 5 Carex_egglestonii_MOR_1504_CO_B1095_OV 6 93Carex_macloviana_MOR_1675_AZ_B1266_OV 28 Carex_mariposana_MOR_1686_AZ_B1277_OV 0 Carex_leporinella_MOR_1415_WA_B1006_OV Carex_arapahoensis_MOR_1527_CO_B1118_OV Carex_fracta_MOR_630_CA_B278_OV Carex_unilateralis_MOR_1650_BC_B1241_OV 13 Carex_multicostata_MOR_827_CA_B487_OV 31 Carex_arenaria_MOR_467_DE_B115_AM 0 97 Carex_divisa_MOR_1866_MD_B1458_DV 4 Carex_integra_MOR_711_CA_B359_OV Carex_adusta_MOR_1874_AB_B1466_OV Carex_proposita_MOR_1743_CA_B1334_OV 8Carex_davyi_MOR_1261_CA_B856_OV 9Carex_foenea_MOR_1802_BC_B1393_OV0 38Carex_xerantica_MOR_1715_ON_B1306_OV 3Carex_stenoptila_MOR_1362_MO_B954_OV2 Carex_argyrantha_MOR_468_MD_B116_OV Carex_petasata_MOR_1260_CA_B855_OV Carex_praticola_MOR_897_CO_B557_OV 7 Carex_phaeocephala_MOR_995_NV_B587_OV 7 Carex_petasata_MOR_994_UT_B586_OV 19Carex_tahoensis_MOR_1477_OR_B1068_OV 51 Carex_preslii_MOR_975_BC_B567_OV 63Carex_straminiformis_MOR_1069_CA_B661_OV Carex_longii_MOR_735_AR_B383_OV 5 5Carex_scoparia_scoparia_MOR_1057_ME_B648_OV 4Carex_vexans_MOR_1168_FLh_B761_OV 10Carex_albolutescens_MOR_435_MD_B082_OV 2 0Carex_hormathodes_MOR_1916_NS_B1508_OV Carex_feta_MOR_627_CA_B275_OV 012 Carex_straminea_MOR_1054_DE_B645_OV 0 Carex_suberecta_MOR_1361_B953_OV 1 Carex_ovalis_MOR_1582_WS_B1173_OV 4 Carex_projecta_MOR_978_MB_B570_OV 71 Carex_tribuloides_sangamonensis_MOR_1127_KN_B720_OV 0 1455 Carex_cristatella_MOR_534_KY_B182_OV Carex_crawfordii_MOR_522_NY_B170_OV 3 Carex_bebbii_MOR_479_MB_B127_OV 18 Carex_tribuloides_tribuloides_MOR_1128_KN_B721_OV8 5 Carex_cumulata_MOR_605_IL_B253_OV34 Carex_cristatella_MOR_557_DE_B205_OV 14Carex_albolutescens_MOR_428_OK_B075_OV 47Carex_alata_MOR_421_AL_B068_OV Carex_scoparia_tessellata_MOR_1685_ME_B1276_OV Carex_ozarkana_MOR_857_AR_B517_OV Carex_gracilior_MOR_1494_CA_B1085_OV Carex_subbracteata_MOR_1757_CA_B1348_OV77 Carex_molesta_MOR_804_DE_B463_OV 6 0 4Carex_reniformis_MOR_989_GA_B581_OV 0Carex_hyalina_MOR_646_MS_B294_OV Carex_missouriensis_MOR_801_IL_B460_OV 10Carex_silicea_MOR_1034_DE_B625_OV 100 0Carex_shinnersii_MOR_1027_KN_B618_OV 27 Carex_cumulata_MOR_1894_ON_B1486_OV 50 Carex_bicknellii_MOR_478_IN_B126_OV 0 Carex_normalis_MOR_793_AL_B451_OV54 3 0Carex_opaca_MOR_867_OK_B527_OV 0Carex_tetrastachya_MOR_1071_TXk_B663_OV 5Carex_oronensis_MOR_1700_ME_B1291_OV 1Carex_tincta_MOR_1144_ME_B737_OV Carex_merritt_fernaldii_MOR_785_MB_B443_OV Carex_brevior_MOR_1625_BC_B1216_OV2 Carex_festucacea_MOR_626_TX_B274_OV3 1Carex_athrostachya_MOR_1349_SK_B946_OV 2 9Carex_muskingumensis_MOR_849_MI_B509_OV Carex_molestiformis_MOR_807_AR_B466_OV 4810 Carex_tenera_tenera_MOR_1552_MB_B1143_OV Carex_tenera_echinodes_MOR_1112_MI_B705_OV85 Carex_preslii_MOR_976_OR_B568_OV Carex_macloviana_MOR_1437_AK_B1028_OV 6 Carex_harfordii_MOR_699_CA_B347_OV Carex_stenoptila_MOR_1084_UT_B676_OV64 4 78Carex_subfusca_MOR_1670_CA_B1261_OV 23Carex_abrupta_MOR_860_BC_B520_OV Carex_pachystachya_MOR_1666_AK_B1257_OV Carex_phaeocephala_MOR_1742_BC_B1333_OV 28 Carex_perglobosa_MOR_1605_CO_B1196_FO Carex_wootonii_MOR_1615_AZ_B1206_OV Carex_cusickii_MOR_1806_BC_B1397_HE 27 88 Carex_prairea_MOR_1753_BC_B1344_HE 89 83 Carex_diandra_MOR_574_CA_B222_HE Carex_simulata_MOR_1086_CA_B678_DV 10 Carex_pityophila_MOR_1002_CO_B594_AC 0 Carex_geophila_MOR_1500_CO_B1091_AC Carex_turbinata_MOR_1773_AZ_B1364_AC Carex_globosa_MOR_654_CA_B302_AC 14 6914Carex_brainerdii_MOR_494_CA_B142_AC 60 18Carex_brevicaulis_MOR_1375_WA_B966_AC 505 6Carex_rossii_MOR_1624_BC_B1215_AC Carex_inops_inops_MOR_1410_WA_B1001_AC 5 Carex_peckii_MOR_1427_AK_B1018_AC Carex_turbinata_MOR_1679_AZ_B1270_AC Carex_communis_amplisquama_MOR_1560_SC_B1151_AC 84Carex_communis_communis_MOR_530_NC_B178_AC 10 Carex_serpenticola_MOR_1763_CA_B1354_AC 4 Carex_albicans_emmonsii_MOR_433_MD_B080_AC 0 Carex_novae_angliae_MOR_795_ME_B453_AC 4 Carex_lucorum_austrolucorum_MOR_743_GA_B391_AC 0Carex_umbellata_MOR_1178_DE_B771_AC 2Carex_albicans_australis_MOR_436_MS_B083_AC Carex_albicans_albicans_MOR_425_KS_B072_AC 642 12Carex_tonsa_rugosperma_MOR_1157_MB_B750_AC0 0Carex_reznicekii_MOR_1014_AL_B605_AC Carex_tonsa_tonsa_MOR_1156_MB_B749_AC 0Carex_nigromarginata_MOR_855_AL_B515_AC 6 0 Carex_pensylvanica_MOR_973_MB_B565_AC8

94Carex_spissa_ultra_MOR_1617_AZ_B1208_HP Carex_gynandra_MOR_698_DE_B346_PC 57 Carex_crinita_crinita_MOR_535_ME_B183_PC26 53Carex_mitchelliana_MOR_835_AL_B495_PC Carex_crinita_brevicrinis_MOR_540_AR_B188_PC 26 Carex_torta_MOR_1121_GA_B714_PC 78Carex_torta_MOR_1122_PN_B715_PC Carex_lenticularis_impressa_MOR_750_CA_B398_PC Carex_obnupta_MOR_839_CA_B499_PC Carex_recta_MOR_1947_B1539_PC 17Carex_aquatilis_aquatilis_MOR_1287_B884_PC 62Carex_aquatilis_dives_MOR_1430_AK_B1021_PC 2 462Carex_subspathacea_MOR_1449_AK_B1040_PC 0 Carex_aquatilis_substricta_MOR_1684_NB_B1275_PC 1 Carex_ramenskii_MOR_1447_AK_B1038_PC 16 Carex_salina_MOR_1755_QC_B1346_PC Carex_lenticularis_lenticularis_NFLD_B877_PC 058 Carex_endlichii_MOR_1897_AZ_B1489_PC 4Carex_salina_MOR_1302_NFLD_B899_PC Carex_eleusinoides_MOR_1425_AK_B1016_PC 0 Carex_podocarpa_MOR_1734_BC_B1325_ST 3750 Carex_lenticularis_dolia_MOR_1807_BC_B1398_PC Carex_ramenskii_MOR_1241_AK_B836_PC 0 70Carex_lyngbyei_MOR_819_OR_B479_PC 0 8Carex_bigelowii_lugens_MOR_476_AK_B124_PC 0 Carex_bigelowii_bigelowii_MOR_1288_NFLD_B885_PC1 7 3Carex_scopulorum_prionophylla_MOR_1389_WA_B980_PC 53Carex_emoryi_MOR_619_DE_B267_PC Carex_scopulorum_bracteosa_MOR_1879_AK_B1471_PC 0 7Carex_scopulorum_scopulorum_MOR_1509_CO_B1100_PC36 Carex_stricta_MOR_1098_TX_B690_PC Carex_vacillans_MOR_1691_ME_B1282_PC 20Carex_nudata_MOR_1242_CAs_B837_PC 0Carex_vaginata_NFLD_B898_PN 2Carex_paleacea_MOR_861_ME_B521_PC Carex_nigra_MOR_1297_NFLD_B894_PC 38 Carex_senta_MOR_1687_AZ_B1278_PC 0Carex_schottii_MOR_1483_CA_B1074_PC5 1Carex_lenticularis_limnophila_MOR_1898_AK_B1490_PC Carex_lenticularis_lipocarpa_MOR_746_CA_B394_PC0 96 5Carex_angustata_MOR_447_CA_B095_PC Carex_interrupta_MOR_1468_OR_B1059_PC Carex_barbarae_MOR_1251_CA_B846_PC 2 Carex_limosa_MOR_769_AK_B417_LM 2560 0 17 5 Carex_nebrascensis_MOR_850_CA_B510_PC 67 Carex_magellanica_MOR_1439_AK_B1030_LM Carex_mertensii_MOR_790_AK_B448_RM 7923Carex_spectabilis_MOR_1781_BC_B1372_ST Carex_macrochaeta_MOR_1438_AK_B1029_LM78 9 21Carex_microchaeta_microchaeta_MOR_1748_YT_B1339_ST 35 Carex_microchaeta_nesophila_MOR_1726_AK_B1317_ST Carex_prasina_MOR_900_GA_B560_HC Carex_verrucosa_MOR_1175_FL_B768_GC 71 Carex_glaucescens_MOR_660_MS_B308_GC 50 Carex_joorii_AR_B368_GC79 2 Carex_barrattii_MOR_482_AL_B130_LM Carex_typhina_MOR_1132_AR_B725_SQ 83 Carex_squarrosa_MOR_1083_AR_B675_SQ 25 Carex_shortiana_MOR_1031_KN_B622_SH Carex_aperta_MOR_1644_BC_B1235_PC30 0 90Carex_haydenii_MOR_1594_IA_B1185_PC Carex_stylosa_MOR_1292_NFLD_B889_RM Carex_planostachys_MOR_884_TXc_B544_HL Carex_lativena_MOR_1631_NM_B1222_HL65 Carex_williamsii_MOR_1771_YT_B1362_CS 1 79 96Carex_capillaris_MOR_1896_NT_B1488_CS 6 Carex_krausei_MOR_1441_AK_B1032_CS Carex_cherokeensis_MOR_564_FL_B212_HC 99 Carex_obispoensis_MOR_1599_CA_B1190_HC 100Carex_microdonta_MOR_1222_MS_B817_GL 21 Carex_crawei_MOR_1273_NFLD_B868_GL 68 Carex_granularis_MOR_1209_MB_B804_GL 77 Carex_gholsonii_MOR_687_AL_B335_GL Carex_glaucodea_MOR_1327_IN_B924_GR 80 Carex_pigra_MOR_1587_MS_B1178_GR78 Carex_digitalis_macropoda_MOR_589_AR_B237_CY 22 Carex_abscondita_MOR_410_DE_B057_CY 46Carex_cumberlandensis_MOR_551_AR_B199_CY Carex_digitalis_digitalis_MOR_585_DE_B233_CY23 98 50 2091Carex_laxiculmis_copulata_MOR_1536_TN_B1127_CY Carex_laxiculmis_laxiculmis_MOR_1205_PN_B800_CY Carex_impressinervia_MOR_1564_AL_B1155_GR 60 Carex_ouachitana_MOR_1340_AR_B937_GR Carex_careyana_MOR_1203_KY_B798_CY Carex_corrugata_MOR_403_SC_B050_GR 7 Carex_corrugata_MOR_404_AL_B051_GR 25 7 63Carex_godfreyi_MOR_1589_AL_B1180_GR 6 46 Carex_amphibola_MOR_388_AL_B035_GR 53 Carex_grisea_MOR_390_KY_B037_GR 50 Carex_conoidea_MOR_1230_DE_B825_GR 21Carex_thornei_MOR_393_FL_B040_GR 0 Carex_acidicola_MOR_392_AL_B039_GR 66 0 Carex_planispicata_MOR_400_MD_B047_GR90 56 17 Carex_thornei_MOR_394_GA_B041_GR 13 371 Carex_bulbostylis_MOR_382_MS_B029_GR Carex_paeninsulae_MOR_1247_FLc_B842_GR 69Carex_calcifugens_MOR_402_FL_B049_GR Carex_oligocarpa_MOR_1334_AR_B931_GR 10 Carex_platyphylla_MOR_886_MD_B546_CY 2 25 Carex_plantaginea_MOR_1695_TN_B1286_CY 83 Carex_austrocaroliniana_MOR_1531_NC_B1122_CY Carex_hitchcockiana_MOR_391_KY_B038_GR 80 Carex_brysonii_MOR_389_AL_B036_GR Carex_halliana_MOR_1491_CA_B1082_PD Carex_aureolensis_MOR_504_MS_B152_SQ 0 99 Carex_frankii_MOR_673_AL_B321_SQ 2 Carex_lemmonii_MOR_763_CA_B411_AU 100 86 Carex_lemmonii_MOR_1480_CA_B1071_AU 65Carex_luzulifolia_MOR_762_CA_B410_AU 3Carex_luzulina_luzulina_MOR_1710_CA_B1301_AU 5911Carex_luzulina_MOR_817_OR_B477_AU Carex_luzulina_ablata_MOR_1481_CA_B1072_AU Carex_collinsii_MOR_561_DE_B209_CO Carex_elliottii_MOR_1718_FL_B1309_VC 31 Carex_bullata_MOR_509_MA_B157_VC 4 Carex_retrorsa_MOR_1012_MI_B603_VC 9 43 Carex_gigantea_MOR_651_FL_B299_LU 73 Carex_lupuliformis_MOR_745_FL_B393_LU93 0 78 Carex_lupulina_MOR_812_MD_B472_LU Carex_louisianica_MOR_742_FL_B390_LU Carex_rotundata_MOR_1006_AK_B598_VC 1 Carex_exsiccata_MOR_1778_BC_B1369_VC 0 64 Carex_vesicaria_MOR_1162_DE_B755_VC Carex_saxatilis_MOR_1023_CO_B614_VC90 0 Carex_lasiocarpa_MOR_731_AK_B379_PD67 2 Carex_pellita_MOR_882_CA_B542_PD Carex_lacustris_MOR_725_MB_B373_PD Carex_hyalinolepis_MOR_690_TX_B338_PD 6 Carex_hystericina_MOR_815_AR_B475_VC 6 0 0 56 65Carex_thurberi_MOR_1618_AZ_B1209_VC 73Carex_comosa_MOR_560_CA_B208_VC Carex_pseudocyperus_MOR_981_B573_VC 5 Carex_houghtoniana_MOR_1248_MB_B843_PD 11 Carex_atherodes_MOR_1651_BC_B1242_CX 6311 Carex_trichocarpa_MOR_1133_DE_B726_CX 0 1 Carex_laeviconica_MOR_1689_KS_B1280_CX 5Carex_sheldonii_MOR_1495_CA_B1086_CX 2 Carex_hirta_MOR_681_PN_B329_CX Carex_striata_MOR_1076_FL_B668_PD Carex_baileyi_MOR_485_KY_B133_VC5 Carex_membranacea_MOR_784_AK_B442_VC 01Carex_utriculata_MOR_1181_AK_B774_VC 1906Carex_melanostachya_MOR_1352_OK_B947b_PD 1Carex_lurida_MOR_816_FL_B476_VC Carex_rostrata_AK_B596_VC Carex_schweinitzii_MOR_1058_MI_B649_VC 16 2 Carex_pumila_MOR_1869_NC_B1461_PD Carex_tuckermanii_MOR_1147_MI_B740_VC 50 Carex_intumescens_MOR_709_ME_B357_LU 13 Carex_grayi_MOR_658_KN_B306_LU Carex_oligosperma_MOR_1555_MB_B1146_VC Carex_richardsonii_MOR_1022_MD_B613_CL 61 Carex_concinna_CO_B1090_CL 13 Carex_concinnoides_MOR_1720_CA_B1311_CL Carex_glacialis_MOR_1428_AK_B1019_LC 10 Carex_picta_MOR_893_GA_B553_PT 31 Carex_pedunculata_MOR_880_MD_B540_CL 26 Carex_baltzellii_MOR_1716_FL_B1307_PT Carex_supina_spaniocarpa_MOR_1596_AK_B1187_LC 34 Carex_petricosa_misandroides_MOR_1797_QC_B1388_AU 100Carex_petricosa_petricosa_MOR_1901_YT_B1493_AU Carex_caryophyllea_Ibirica_MOR_1865_B1457_MT 6 Carex_bella_MOR_1523_CO_B1114_RM 0 Carex_sprengelii_MOR_1568_NB_B1159_HC Carex_albonigra_MOR_1423_AK_B1014_RM Carex_atrosquama_MOR_1522_MO_B1113_RM 11Carex_nova_MOR_434_CO_B081_RM 4 Carex_sabulosa_MOR_1448_YT_B1039_RM 0 Carex_heterostachya_MOR_1824_B1415_PD Carex_helleri_MOR_1492_CA_B1083_RM Carex_panicea_MOR_1708_ME_B1299_PN 0 Carex_vaginata_MOR_1776_YT_B1367_PN Carex_hendersonii_MOR_1749_BC_B1340_LF 9 Carex_ormostachya_MOR_868_MI_B528_LF Carex_garberi_MOR_1800_BC_B1391_BI 62 Carex_bicolor_MOR_1424_AK_B1015_BI 4Carex_biltmoreana_MOR_1870_NC_B1462_PN 89 01Carex_hassei_MOR_1516_CO_B1107_BI 0 Carex_aurea_MOR_501_CA_B149_BI 0 0Carex_livida_MOR_1212_NJ_B807_PN 0 Carex_hassei_MOR_1669_CA_B1260_BI 015 0 Carex_tetanica_MOR_1593_IA_B1184_PN 0Carex_tetanica_MOR_1116_MB_B709_PN Carex_laxa_MOR_1895_YT_B1487_PN 1 54 Carex_meadii_MOR_1544_MB_B1135_PN11 2 Carex_woodii_MOR_1592_IA_B1183_PN 87 565 Carex_chapmanii_MOR_566_FL_B214_LF Carex_purpurifera_MOR_1272_KY_B867_LF 0 31 13 Carex_klamathensis_MOR_1871_OR_B1463_PN 0 8 Carex_leptonervia_MOR_1196_MB_B790_LF Carex_albursina_KY_B084_LF 93Carex_manhartii_MOR_1578_TN_B1169_LF 7 Carex_blanda_MOR_1621_KS_B1212_LF 58 Carex_kraliana_MOR_715_AR_B363_LF 5 30 76 77 73Carex_striatula_MOR_1066_DE_B658_LF 12 Carex_radfordii_MOR_1240_SC_B835_LF 1 Carex_blanda_MOR_474_MD_B122_LF 94 Carex_gracilescens_MOR_661_KY_B309_LF Carex_laxa_MOR_1445_AK_B1036_PN Carex_raynoldsii_MOR_986_CA_B578_RM Carex_norvegica_MOR_1418_OR_B1009_RM53 14Carex_gmelinii_MOR_1431_AK_B1022_RM 0 Carex_media_MOR_1574_NB_B1165_RM 6316 Carex_atratiformis_MOR_1553_AB_B1144_RM 63 Carex_stevenii_MOR_1512_CO_B1103_RM 59 Carex_atratiformis_MOR_1877_NL_B1469_RM 03 Carex_heteroneura_MOR_659_NV_B307_RM Carex_nelsonii_MOR_1634_MO_B1225_RM Carex_chalciolepis_MOR_1524_CO_B1115_RM 4Carex_pelocarpa_MOR_997_NV_B589_RM 0Carex_adelostoma_MOR_1421_AK_B1012_RM Carex_holostoma_MOR_1433_AK_B1024_RM Carex_idahoa_MOR_1737_CA_B1328_RM 73Carex_parryana_MOR_1436_AK_B1027_RM23 0 65Carex_hallii_MOR_1556_MB_B1147_RM 59 Carex_specuicola_MOR_1616_AZ_B1207_RM Carex_aboriginum_MOR_1640_ID_B1231_RM 3 79Carex_serratodens_MOR_1028_CA_B619_RM Carex_buxbaumii_MOR_499_AK_B147_RM Carex_adelostoma_MOR_1422_AK_B1013_RM91 Carex_epapillosa_MOR_620_UT_B268_RM Carex_torreyi_MOR_1510_CO_B1101_PO 9 66 Carex_scabrata_MOR_1045_GA_B636_AN 89 0 Carex_sartwelliana_MOR_1600_CA_B1191_PD 24 Carex_acutiformis_MOR_1924_Spain_B1516_PD 06 Carex_scabriuscula_MOR_1048_CA_B639_SP Carex_congdonii_MOR_1488_CA_B1079_PD 6 Carex_pallescens_MOR_1810_B1401_PO 0 Carex_hirtifolia_MOR_682_DE_B330_HT 59 Carex_whitneyi_MOR_1154_CA_B747_LG Carex_tenax_AL_B702_HL 36 Carex_dasycarpa_MOR_607_GA_B255_HL 68 Carex_dasycarpa_MOR_608_HL_B256_FL 1 Carex_castanea_MOR_1281_NFLD_B876_HC 15 Carex_mendocinensis_MOR_1721_CA_B1312_HC Carex_gynodynama_MOR_1490_CA_B1081_HC11 Carex_formosa_MOR_1534_IL_B1125_HC 19 6 Carex_arctata_MOR_465_WI_B113_HC 1 Carex_debilis_debilis_MOR_1280_NFLD_B875_HC 06 Carex_venusta_MOR_1174_MS_B767_HC Carex_oxylepis_pubescens_MOR_871_KY_B531_HC 10 Carex_hirtissima_MOR_1496_CA_B1087_HC 2 59 Carex_misera_MOR_1566_TN_B1157_HC 0 23 Carex_complanata_MOR_516_TX_B164_PO 18 35Carex_hirsutella_MOR_669_DE_B317_PO 0 51Carex_bushii_MOR_511_DE_B159_PO 60Carex_caroliniana_MOR_549_AL_B197_PO 8 3 Carex_swanii_MOR_1106_AR_B699_PO Carex_aestivalis_MOR_415_PN_B062_HC 0 54Carex_virescens_MOR_1158_AL_B751_PO Carex_roanensis_MOR_1026_NC_B617_HC74 Carex_debilis_rudgei_MOR_558_TN_B206_HC11 Carex_davisii_MOR_592_DE_B240_HC Carex_gracillima_MOR_656_AL_B304_HC Carex_amplifolia_MOR_449_NV_B097_AN 70 Carex_curatorum_MOR_1818_B1409_SP 9Carex_scirpoidea_scirpoidea_MOR_1050_AK_B641_SP 9Carex_scirpoidea_pseudoscirpoidea_MOR_1805_BC_B1396_SP 946Carex_scirpoidea_stenochlaena_MOR_1603_AK_B1194_SP 6Carex_rupestris_MOR_1304_NFLD_B901_RU 6 Carex_scirpoidea_convoluta_MOR_1722_ON_B1313_SP Carex_californica_MOR_1487_CA_B1078_PN 69 Carex_polymorpha_MOR_1709_ME_B1300_PN Carex_vestita_MOR_1165_DE_B758_PD Carex_fuliginosa_MOR_1429_AK_B1020_AU Carex_assiniboinensis_MOR_456_MB_B104_HC 2 Carex_atrofusca_MOR_1456_AK_B1047_AU Carex_eburnea_MOR_576_MI_B224_AL Carex_triquetra_MOR_1602_CA_B1193_TQ 0 56 Carex_turgescens_MOR_1244_MS_B839_RT 98Carex_michauxiana_MOR_1550_MB_B1141_RT 100 Carex_lonchocarpa_MOR_733_FL_B381_RT 2 53 99Carex_folliculata_MOR_645_DE_B293_RT Carex_extensa_MOR_1655_VA_B1246_SS 98 Carex_distans_MOR_1908_Spain_B1500_SS 100 Carex_diluta_MO_B957_SS Carex_sylvatica_MOR_1392_WA_B983_HC 33 Carex_lutea_MOR_1567_NC_B1158_CC 131 18 2Carex_viridula_elatior_MOR_1704_NF_B1295_CC 16Carex_cryptolepis_MOR_1532_IL_B1123_CC 50Carex_viridula_brachyrrhyncha_MOR_1714_QC_B1305_CC 28Carex_viridula_oedocarpa_MOR_1750_NS_B1341_CC 5 100 Carex_hostiana_MOR_1796_QC_B1387_CC 108 Carex_viridula_viridula_MOR_1161_MI_B754_CC 90Carex_viridula_saxilittoralis_MOR_1819_B1410_CC Carex_pendula_MOR_1395_WA_B986_RC STA1817_Trichophorum_cespitosum 100 STA1816_Trichophorum_alpinum

0.005 2Carex_breweri_MOR_1626_CA_B1217_IF 27Carex_subnigricans_MOR_1476_OR_B1067_IF Maximum likelihood rps16 gene tree. Constructed using 100Carex_mertensii_MOR_790_AK_B448_RM Carex_engelmannii_MOR_1933_BC_B1525_IF RAxML, with a GTRCAT model of evolution and a 200 bootstrap Carex_obtusata_MOR_841_MB_B501_OB 75 Carex_capitata_MOR_1838_B1429_CT analysis. Bootstrap values are plotted on the tree. 100 Carex_capitata_MOR_1857_B1449_CT 34 49 Carex_capitata_MOR_1840_B1431_CT Carex_anthoxanthea_MOR_1420_AK_B1011_CR 50 94Carex_circinata_MOR_1779_AK_B1370_CR Carex_nardina_MOR_1312_QC_B909_NA 94 50Carex_oreocharis_AZ_B1269_FL Carex_fraserianus_PN_B333 0 Carex_geyeri_MOR_676_AB_B324_FC 5 8 100 73 66 Carex_tompkinsii_MOR_1485_CA_B1076_FC 95 Carex_multicaulis_MOR_1668_CA_B1259_FC Carex_timida_MOR_359_AL_B005_PS 5 60Carex_juniperorum_KY_B0011_PS 60 Carex_jamesii_AL_B0010_PS 27 24Carex_willdenowii_MOR_358_KY_B003_PS 0 18 Carex_superata_FL_B0015_PS 56Carex_basiantha_AL_B934_PS 81 82Carex_basiantha_GA_B922_PS 36Carex_cordillerana_MOR_1346_BC_B943_PS 30 Carex_backii_MOR_1809_B1400_PS 65Carex_saximontana_MOR_1529_CO_B1120_PS Carex_latebracteata_MOR_1185_AR_B779_PS 65 81Carex_latebracteata_AR_B786_PS Carex_nigricans_MOR_1440_AK_B1031_DO 100 28Carex_micropoda_MOR_1673_WY_B1264_IF 8 Carex_micropoda_MOR_1434_AK_B1025_DO Carex_leptalea_MOR_765_BC_B413_LE 79 Carex_muriculata_MOR_1612_NM_B1203_PG Carex_klamathensis_MOR_1871_OR_B1463_PN Carex_microglochin_Stordalen_MOR_1507_B1098_LG Carex_disperma_MOR_1454_AK_B1045_DS Carex_vexans_MOR_1168_FLh_B761_OV Carex_ozarkana_TX_B518_OV 4 3729Carex_longii_MOR_735_AR_B383_OV 77Carex_albolutescens_MOR_435_MD_B082_OV Carex_alata_MOR_421_AL_B068_OV 39Carex_feta_MOR_627_CA_B275_OV Carex_cumulata_MOR_605_IL_B253_OV 52 Carex_bebbii_MOR_479_MB_B127_OV Carex_projecta_MOR_1571_NB_B1162_OV 44 Carex_cristatella_MOR_557_DE_B205_OV 459 Carex_tribuloides_sangamonensis_MOR_1751_LA_B1342_OV 161 65Carex_tribuloides_sangamonensis_MOR_1127_KN_B720_OV 0Carex_crawfordii_MOR_522_NY_B170_OV 17 362Carex_albolutescens_MOR_428_OK_B075_OV Carex_cristatella_MOR_534_KY_B182_OV Carex_tribuloides_tribuloides_MOR_1128_KN_B721_OV Carex_ovalis_MOR_1582_WS_B1173_OV Carex_adusta_MOR_1874_AB_B1466_OV 28 Carex_xerantica_MOR_1715_ON_B1306_OV Carex_petasata_MOR_994_UT_B586_OV80 84Carex_tahoensis_MOR_1477_OR_B1068_OV Carex_phaeocephala_MOR_995_NV_B587_OV Carex_stenoptila_MOR_1362_MO_B954_OV 0Carex_proposita_MOR_1743_CA_B1334_OV Carex_phaeocephala_MOR_1742_BC_B1333_OV Carex_multicostata_MOR_827_CA_B487_OV Carex_pachystachya_MOR_1528_CO_B1119_OV 0Carex_petasata_MOR_1260_CA_B855_OV Carex_integra_MOR_711_CA_B359_OV 73 Carex_fracta_MOR_630_CA_B278_OV Carex_microptera_MOR_1682_CO_B1273_OV 0 32 3190Carex_egglestonii_MOR_1610_UT_B1201_OV 72Carex_egglestonii_MOR_1504_CO_B1095_OV 58Carex_ebenea_MOR_1672_AZ_B1263_OV 0 Carex_microptera_WA_B494_OV 85 Carex_straminiformis_MOR_1068_UT_B660_OV 0 Carex_subfusca_MOR_1670_CA_B1261_OV 1Carex_stenoptila_MOR_1084_UT_B676_OV 0 Carex_abrupta_MOR_860_BC_B520_OV 0Carex_macloviana_MOR_1437_AK_B1028_OV Carex_preslii_MOR_976_OR_B568_OV 0 56 0 Carex_gracilior_MOR_1494_CA_B1085_OV 98Carex_subbracteata_MOR_1757_CA_B1348_OV 1 Carex_reniformis_MOR_989_GA_B581_OV Carex_tenera_tenera_MOR_1552_MB_B1143_OV 0 Carex_normalis_MOR_793_AL_B451_OV63 0 1 Carex_straminea_MOR_1054_DE_B645_OV Carex_molesta_MOR_804_DE_B463_OV Carex_muskingumensis_MOR_849_MI_B509_OV Carex_silicea_MOR_1034_DE_B625_OV 0Carex_suberecta_MOR_1361_B953_OV 1 0 60Carex_missouriensis_MOR_801_IL_B460_OV 0 17 0 Carex_shinnersii_MOR_1027_KN_B618_OV 50 Carex_scoparia_scoparia_MOR_1057_ME_B648_OV 01 0 Carex_opaca_IL_B526_OV 5 Carex_brevior_MOR_1625_BC_B1216_OV 0 0 0Carex_hyalina_MOR_646_MS_B294_OV 0 0Carex_cumulata_MOR_1894_ON_B1486_OV 0Carex_merritt_fernaldii_MOR_785_MB_B443_OV Carex_oronensis_MOR_1700_ME_B1291_OV 690Carex_festucacea_MOR_626_TX_B274_OV 0 Carex_molestiformis_MOR_807_AR_B466_OV 11Carex_tincta_MOR_1144_ME_B737_OV Carex_bicknellii_MOR_478_IN_B126_OV Carex_scoparia_tessellata_MOR_1685_ME_B1276_OV 0 Carex_hormathodes_MOR_1916_NS_B1508_OV Carex_tetrastachya_MOR_1071_TXk_B663_OV 0 Carex_harfordii_MOR_699_CA_B347_OV Carex_unilateralis_BC_B141_OV 22 30Carex_mariposana_MOR_1686_AZ_B1277_OV 0 98Carex_douglasii_MOR_1658_CA_B1249_DV 71 Carex_macloviana_MOR_1675_AZ_B1266_OV Carex_arapahoensis_MOR_1527_CO_B1118_OV 100 Carex_sychnocephala_MOR_1702_ON_B1293_CP 1 Carex_davyi_MOR_1261_CA_B856_OV Carex_wootonii_MOR_1615_AZ_B1206_OV Carex_straminiformis_MOR_1069_CA_B661_OV 80Carex_preslii_MOR_975_BC_B567_OV Carex_argyrantha_MOR_468_MD_B116_OV Carex_praticola_MOR_897_CO_B557_OV Carex_foenea_MOR_1802_BC_B1393_OV Carex_echinata_echinata_MOR_1435_AK_B1026_SL 57 Carex_exilis_MOR_621_DE_B269_SL Carex_sterilis_MOR_1545_MB_B1136_SL 8872 20Carex_atlantica_DE_B110_SL 11 Carex_atlantica_capillacea_MOR_452_FL_B100_SL 97 36 Carex_seorsa_MOR_1044_DE_B635_SL Carex_echinata_phyllomanica_MOR_1786_BC_B1377_SL 53Carex_wiegandii_ON_B947_SL 68Carex_wiegandii_MOR_1155_ME_B748_SL Carex_chordorrhiza_MOR_1727_BC_B1318_CH Carex_illota_MOR_695_CA_B343_OV Carex_arcta_MOR_444_AK_B092_GO 76 68 Carex_ursina_MOR_1777_YT_B1368_GO 13 Carex_glareosa_MOR_1558_MB_B1149_GO 73 Carex_bonanzensis_MOR_1622_AK_B1213_GO 4 13 Carex_mackenziei_MOR_1459_AK_B1050_GO 1 Carex_loliacea_MOR_1452_AK_B1043_GO 66Carex_trisperma_MOR_1136_MI_B729_GO 45 Carex_heleonastes_MOR_1756_AB_B1347_GO 8378 31Carex_marina_MOR_1548_MB_B1139_GO

2 2 Carex_lapponica_MOR_1443_AK_B1034_PD Carex_praeceptorum_MOR_1754_CA_B1345_GO 90 92 15 Carex_canescens_disjuncta_MOR_1561_NC_B1152_GO 62 Carex_canescens_canescens_MOR_1289_NFLD_B886_GO 61Carex_brunnescens_brunnescens_MOR_1286_NFLD_B882_GO 6299Carex_canescens_canescens_WA_B968_GO Carex_arctiformis_MOR_1653_BC_B1244_GO 24 Carex_gynocrates_MOR_1432_AK_B1023_PY 7 Carex_athrostachya_MOR_1349_SK_B946_OV 63Carex_laeviculmis_MOR_1199_CA_B794_DE 97Carex_deweyanavar.collectanea_MOR_1812_QC_B1403_DE 74 Carex_deweyana_deweyana_MOR_773_MB_B421_DE 15 41 39Carex_leptopoda_OR_B805_DE 70Carex_bolanderi_MOR_1216_CA_B811_DE Carex_leptopoda_MOR_1201_BC_B796_DE Carex_bromoides_MD_B0022_DE 18 Carex_siccata_MOR_1872_ON_B1464_AM 63Carex_siccata_MOR_1662_NM_B1253_AM 39Carex_sartwellii_MOR_1784_BC_B1375_HH Carex_simulata_MOR_1086_CA_B678_DV 24Carex_cusickii_MOR_1806_BC_B1397_HE 98 1 Carex_prairea_MB_B563_HE 9624Carex_diandra_QC_B918_HE 34 95Carex_prairea_MOR_1573_NB_B1164_HE Carex_prairea_MOR_1753_BC_B1344_HE 26Carex_tumulicola_MOR_1140_CA_B733_PG 68Carex_arenaria_MOR_467_DE_B115_AM 0 Carex_divisa_MOR_1942_VA_B1534_DV Carex_perglobosa_MOR_1605_CO_B1196_FO 46 Carex_crus_corvi_MOR_556_FL_B204_VU Carex_aggregata_MOR_419_KY_B066_PG Carex_gravida_MOR_704_KN_B352_PG Carex_mesochorea_MOR_831_AL_B491_PG Carex_perdentata_MOR_993_TX_B585_PG 0 Carex_leavenworthii_MOR_759_AL_B407_PG 0 Carex_densa_MOR_573_CA_B221_MF 0 Carex_muehlenbergii_MOR_837_FL_B497_PG 0 88Carex_obnupta_MOR_839_CA_B499_PC 0 Carex_mesochorea_KN_B490_PG 0 38Carex_austrina_MOR_524_DE_B172_PG 0 Carex_praegracilis_MOR_892_ME_B552_DV 014 Carex_nervina_MOR_1884_NV_B1476_VU 8717 Carex_vernacula_MOR_1515_CO_B1106_FO 0 40 Carex_jonesii_MOR_1412_WA_B1003_VU 0 Carex_neurophora_MOR_1417_WA_B1008_VU 0 Carex_divulsa_MOR_1383_WA_B974_PG 97 98Carex_muricata_lamprocarpa_MOR_1912_Spain_B1504_PG 5310 22 Carex_spicata_MOR_1073_DE_B665_PG 0 Carex_conjuncta_MOR_518_DE_B166_VU 64 Carex_alopecoidea_NY_B096_VU 96Carex_alopecoidea_MOR_1530_IL_B1121_VU 3 Carex_muehlenbergii_enervis_MOR_1768_AR_B1359_PG Carex_cephalophora_MOR_562_DE_B210_PG 62 Carex_cephaloidea_MOR_538_MA_B186_PG Carex_sparganioides_MOR_1091_DE_B683_PG 94Carex_annectens_MOR_464_AL_B112_MF 80Carex_vulpinoidea_MOR_1153_CA_B746_MF 99 16 Carex_densa_MOR_1471_OR_B1062_MF 2 Carex_annectens_MOR_439_MD_B087_MF 61Carex_triangularis_MOR_1149_GA_B742_MF 89 21Carex_triangularis_MOR_1146_TX_B739_MF Carex_stipata_stipata_MOR_1055_MB_B646_VU 22 99Carex_oklahomensis_MOR_845_AR_B505_VU 0 Carex_oklahomensis_MD_B503_VU 11 Carex_laevivaginata_MOR_727_AL_B375_VU 46 Carex_stipata_maxima_MOR_1063_FL_B654_VU Carex_pansa_MOR_1766_CA_B1357_DV 4161Carex_occidentalis_MOR_1934_CA_B1526_PG_2 48Carex_occidentalis_MOR_1934_CA_B1526_PG 32 Carex_alma_MOR_437_CA_B085_MF Carex_chihuahuensis_MOR_1614_AZ_B1205_MF Carex_hoodii_MOR_1732_CA_B1323_PG Carex_hookerana_MOR_1795_MN_B1386_PG Carex_incurviformis_MOR_1903_CO_B1495_FO Carex_vallicola_MOR_1788_BC_B1379_PG Carex_macrocephala_MOR_1236_AK_B831_MC 58 Carex_kobomugi_MOR_713_VA_B361_MC Carex_texensis_TX_B734_PG 69Carex_texensis_MOR_1482_CA_B1073_PG 16 84 Carex_radiata_MOR_1001_MA_B593_PG 55 3372Carex_appalachica_MOR_455_MA_B103_PG 7 80Carex_socialis_MOR_1090_AL_B682_PG Carex_sparganioides_sparaganioides_MOR_1092_WI_B684_PG 0 Carex_appalachica_MOR_454_TN_B102_PG Carex_radiata_MOR_1000_MI_B592_PG 12 086 Carex_rosea_MOR_1018_WI_B609_PG 31Carex_rosea_MOR_1016_ME_B607_PG 70 Carex_douglasii_MOR_1938_SK_B1530_DV 30 Carex_duriuscula_MOR_1455_AK_B1046_DV Carex_arkansana_MOR_471_IL_B119_PG Carex_eburnea_MOR_576_MI_B224_AL Carex_glacialis_MOR_1428_AK_B1019_LC 41 Carex_supina_spaniocarpa_MOR_1596_AK_B1187_LC 100Carex_serratodens_MOR_1028_CA_B619_RM Carex_granularis_MOR_1209_MB_B804_GL 62 86Carex_gholsonii_MOR_687_AL_B335_GL 22 Carex_gholsonii_NC_B345_GL Carex_pigra_MOR_1587_MS_B1178_GR 85 39 100 Carex_glaucodea_MOR_1327_IN_B924_GR99 Carex_microdonta_MOR_1222_MS_B817_GL 5 100 Carex_crawei_TN_B797_GL 96 94Carex_crawei_MOR_1273_NFLD_B868_GL Carex_abscondita_MOR_410_DE_B057_CY 48 Carex_laxiculmis_laxiculmis_MOR_1205_PN_B800_CY 83Carex_cumberlandensis_MOR_551_AR_B199_CY 57 79Carex_laxiculmis_copulata_MOR_1536_TN_B1127_CY Carex_digitalis_digitalis_MOR_585_DE_B233_CY Carex_ouachitana_MOR_1340_AR_B937_GR 96 Carex_impressinervia_MOR_1564_AL_B1155_GR Carex_platyphylla_MOR_886_MD_B546_CY 75 31Carex_platyphylla_PN_B863_CY 21 97 74 Carex_careyana_MOR_1203_KY_B798_CY Carex_plantaginea_MOR_1695_TN_B1286_CY 95Carex_austrocaroliniana_MOR_1531_NC_B1122_CY 82 Carex_conoidea_MOR_1230_DE_B825_GR Carex_corrugata_SC_B0050_GR 53 Carex_godfreyi_MOR_1589_AL_B1180_GR54 85 78Carex_corrugata_MOR_404_AL_B051_GR 80Carex_grisea_KY_B0037_GR 93 97 Carex_amphibola_AL_B0035_GR 100 Carex_acidicola_MOR_392_AL_B039_GR Carex_thornei_GA_B0041_GR 81 70Carex_paeninsulae_MOR_1247_FLc_B842_GR 60Carex_thornei_FL_B0040_GR 4 Carex_oligocarpa_MOR_1334_AR_B931_GR 48Carex_planispicata_MD_B0047_GR 16Carex_calcifugens_MOR_402_FL_B049_GR Carex_brysonii_MOR_389_AL_B036_GR 83Carex_hitchcockiana_KY_B0038_GR Carex_assiniboinensis_MOR_456_MB_B104_HC 37 50 Carex_sprengelii_SD_B672_HC 100Carex_sprengelii_MOR_1568_NB_B1159_HC Carex_planostachys_MOR_884_TXc_B544_HL 90Carex_lativena_MOR_1631_NM_B1222_HL Carex_michauxiana_MOR_1550_MB_B1141_RT 80 87Carex_lonchocarpa_MOR_1764_LA_B1355_RT 12 Carex_folliculata_MOR_645_DE_B293_RT Carex_turgescens_MOR_1244_MS_B839_RT Carex_viridula_oedocarpa_MOR_1750_NS_B1341_CC 64100 4 Carex_viridula_saxilittoralis_MOR_1819_B1410_CC 55Carex_lutea_MOR_1567_NC_B1158_CC 19Carex_viridula_elatior_MOR_1704_NF_B1295_CC 1 Carex_hostiana_MOR_1796_QC_B1387_CC 63Carex_viridula_brachyrrhyncha_MOR_1714_QC_B1305_CC 4 78Carex_cryptolepis_MOR_1532_IL_B1123_CC Carex_californica_MOR_1487_CA_B1078_PN 44Carex_californica_MOR_1637_ID_B1228_PN 45Carex_californica_WA_B967_PN 1656Carex_polymorpha_PN_B550_PN 2 Carex_scirpoidea_scirpoidea_MOR_1050_AK_B641_SP 36 1861Carex_scirpoidea_stenochlaena_MOR_1603_AK_B1194_SP Carex_rupestris_MOR_1304_NFLD_B901_RU72 37Carex_scirpoidea_pseudoscirpoidea_MOR_1805_BC_B1396_SP 15Carex_curatorum_MOR_1769_UT_B1360_SP Carex_scabriuscula_MOR_1048_CA_B639_SP 33 Carex_sartwelliana_MOR_1600_CA_B1191_PD Carex_triquetra_MOR_1602_CA_B1193_TQ Carex_roanensis_MOR_1026_NC_B617_HC 57 Carex_virescens_SC_B752_PO 81 70Carex_virescens_MOR_1158_AL_B751_PO 0 Carex_aestivalis_MOR_415_PN_B062_HC Carex_hirtissima_MOR_1728_CA_B1319_HC 62Carex_hirtissima_MOR_1496_CA_B1087_HC 0 Carex_oxylepis_pubescens_MOR_871_KY_B531_HC 9 Carex_gracillima_MOR_656_AL_B304_HC Carex_misera_MOR_1566_TN_B1157_HC 36 Carex_hirsutella_MOR_669_DE_B317_PO 63Carex_caroliniana_MOR_549_AL_B197_PO 0 0 Carex_pallescens_MOR_1810_B1401_PO 40Carex_formosa_MOR_1534_IL_B1125_HC 55Carex_complanata_MOR_516_TX_B164_PO 0 Carex_gynodynama_MOR_1706_CA_B1297_HC 0 Carex_bushii_MOR_511_DE_B159_PO 20 1327 Carex_vestita_MOR_1165_DE_B758_PD 13 Carex_congdonii_MOR_1699_CA_B1290_PD 0 Carex_scabrata_MOR_1045_GA_B636_AN 65 Carex_dasycarpa_MOR_608_HL_B256_FL 2 Carex_dasycarpa_MOR_607_GA_B255_HL 0 Carex_mendocinensis_MOR_1721_CA_B1312_HC Carex_torreyi_MOR_1510_CO_B1101_PO Carex_arctata_MOR_465_WI_B113_HC 50Carex_davisii_MOR_592_DE_B240_HC Carex_castanea_MOR_1281_NFLD_B876_HC Carex_debilis_debilis_MOR_1280_NFLD_B875_HC 0 Carex_epapillosa_MOR_620_UT_B268_RM 24 85Carex_nova_MOR_434_CO_B081_RM 43 Carex_chalciolepis_MOR_1524_CO_B1115_RM 29 Carex_bella_MOR_1523_CO_B1114_RM 46Carex_heteroneura_MOR_659_NV_B307_RM Carex_pelocarpa_OR_B1189_RM 4536Carex_pelocarpa_MOR_997_NV_B589_RM Carex_nelsonii_MOR_1634_MO_B1225_RM Carex_helleri_MOR_1492_CA_B1083_RM 1748 Carex_raynoldsii_MOR_1638_ID_B1229_RM 0 9 Carex_raynoldsii_MOR_986_CA_B578_RM 96Carex_projecta_MOR_978_MB_B570_OV 22 Carex_atrosquama_MOR_1522_MO_B1113_RM Carex_atratiformis_MOR_1877_NL_B1469_RM 96Carex_atratiformis_MOR_1553_AB_B1144_RM 0 59 Carex_gmelinii_MOR_1431_AK_B1022_RM 9059Carex_stevenii_MOR_1512_CO_B1103_RM 39 Carex_norvegica_MOR_1418_OR_B1009_RM 0 Carex_media_MOR_1574_NB_B1165_RM 0 Carex_sabulosa_MOR_1799_YT_B1390_RM 67Carex_heterostachya_MOR_1824_B1415_PD 1 Carex_albonigra_MOR_1423_AK_B1014_RM Carex_adelostoma_MOR_1422_AK_B1013_RM 88 0 Carex_buxbaumii_MOR_499_AK_B147_RM 0 23Carex_adelostoma_MOR_1421_AK_B1012_RM 85Carex_holostoma_MOR_1433_AK_B1024_RM 1 Carex_aboriginum_MOR_1640_ID_B1231_RM 100 Carex_serratodens_MOR_1467_OR_B1058_RM 35Carex_specuicola_MOR_1616_AZ_B1207_RM 35 59Carex_parryana_MOR_1436_AK_B1027_RM 61Carex_hallii_MOR_1793_MN_B1384_RM 65Carex_hallii_MOR_1556_MB_B1147_RM Carex_idahoa_MOR_1737_CA_B1328_RM Carex_pedunculata_MOR_880_MD_B540_CL Carex_baltzellii_FL_B138_PT 77 Carex_picta_MOR_893_GA_B553_PT 0 Carex_panicea_MOR_1708_ME_B1299_PN 99 Carex_vaginata_MOR_1776_YT_B1367_PN 98 Carex_hendersonii_MOR_1749_BC_B1340_LF 0 Carex_albursina_KY_B084_LF 95 Carex_blanda_MOR_1621_KS_B1212_LF 31 Carex_leptonervia_MOR_1196_MB_B790_LF Carex_striatula_MOR_1066_DE_B658_LF 94 47 58Carex_blanda_MOR_474_MD_B122_LF 7 56 Carex_gracilescens_MOR_661_KY_B309_LF 59 36 32Carex_radfordii_MOR_1240_SC_B835_LF Carex_kraliana_MOR_715_AR_B363_LF 0 Carex_purpurifera_MOR_1272_KY_B867_LF Carex_tetanica_MOR_1593_IA_B1184_PN 57 Carex_bicolor_MOR_1424_AK_B1015_BI 0 Carex_meadii_MOR_1544_MB_B1135_PN 6141 62 Carex_tetanica_MOR_1116_MB_B709_PN Carex_hassei_MOR_1669_CA_B1260_BI 4 8 64 0 4 8 Carex_garberi_MOR_1800_BC_B1391_BI 3 Carex_hassei_MOR_1516_CO_B1107_BI 1 Carex_aurea_MOR_501_CA_B149_BI

92Carex_livida_MOR_1212_NJ_B807_PN 2 Carex_laxa_MOR_1895_YT_B1487_PN 240 Carex_chapmanii_MOR_566_FL_B214_LF Carex_livida_MOR_1450_AK_B1041_PN 52 45Carex_biltmoreana_MOR_1870_NC_B1462_PN 3 Carex_woodii_MOR_1592_IA_B1183_PN 0 Carex_manhartii_NC_B866_LF 2358 Carex_manhartii_MOR_1563_GE_B1154_LF 20Carex_ormostachya_MOR_868_MI_B528_LF Carex_manhartii_MOR_1578_TN_B1169_LF Carex_hirtifolia_QC_B872_HT 96 Carex_hirtifolia_MOR_682_DE_B330_HT Carex_amplifolia_MOR_449_NV_B097_AN 0 Carex_atrofusca_MOR_1456_AK_B1047_AU 6 81 Carex_extensa_MOR_1655_VA_B1246_SS 7 Carex_distans_MOR_1908_Spain_B1500_SS Carex_petricosa_misandroides_MOR_1797_QC_B1388_AU Carex_cherokeensis_MOR_564_FL_B212_HC 99Carex_obispoensis_MOR_1599_CA_B1190_HC Carex_pendula_MOR_1395_WA_B986_RC 29 Carex_williamsii_MOR_1771_YT_B1362_CS 78 Carex_krausei_MOR_1441_AK_B1032_CS 99Carex_capillaris_MOR_1896_NT_B1488_CS

97 Carex_luzulina_MOR_817_OR_B477_AU Carex_luzulina_luzulina_MOR_1710_CA_B1301_AU 3198 99Carex_luzulina_ablata_MOR_1481_CA_B1072_AU 31 51Carex_lemmonii_MOR_1480_CA_B1071_AU Carex_luzulifolia_MOR_762_CA_B410_AU 62Carex_lemmonii_MOR_763_CA_B411_AU Carex_collinsii_MOR_561_DE_B209_CO Carex_caryophyllea_Ibirica_MOR_1865_B1457_MT 15Carex_fuliginosa_MOR_1429_AK_B1020_AU Carex_glaucescens_MOR_660_MS_B308_GC 55Carex_barrattii_MOR_482_AL_B130_LM 1 28Carex_joorii_AR_B368_GC Carex_nigra_MOR_1297_NFLD_B894_PC Carex_ramenskii_MOR_1241_AK_B836_PC Carex_scopulorum_prionophylla_MOR_1389_WA_B980_PC 28Carex_lyngbyei_MOR_819_OR_B479_PC 21Carex_aquatilis_dives_MOR_1430_AK_B1021_PC Carex_interrupta_MOR_1468_OR_B1059_PC 59Carex_sabulosa_MOR_1448_YT_B1039_RM 0Carex_bigelowii_bigelowii_MOR_1288_NFLD_B885_PC Carex_subspathacea_MOR_1449_AK_B1040_PC Carex_recta_MOR_1947_B1539_PC 0 Carex_salina_MOR_1755_QC_B1346_PC 0 Carex_scopulorum_scopulorum_MOR_1509_CO_B1100_PC Carex_obnupta_OR_B500_PC 26Carex_eleusinoides_MOR_1425_AK_B1016_PC 0 Carex_gynandra_MOR_698_DE_B346_PC 0 74 6 44Carex_mitchelliana_MOR_835_AL_B495_PC 0 88 Carex_crinita_brevicrinis_MOR_540_AR_B188_PC Carex_torta_MOR_1121_GA_B714_PC 0181 87Carex_torta_MOR_1122_PN_B715_PC 0Carex_lenticularis_limnophila_MOR_1898_AK_B1490_PC 0 Carex_barbarae_MOR_1251_CA_B846_PC 0 Carex_podocarpa_MOR_1734_BC_B1325_ST 2 0 Carex_emoryi_MOR_619_DE_B267_PC 0 Carex_salina_MOR_1302_NFLD_B899_PC 0Carex_aquatilis_aquatilis_MOR_1287_B884_PC Carex_ramenskii_MOR_1447_AK_B1038_PC Carex_paleacea_MOR_861_ME_B521_PC Carex_lenticularis_lipocarpa_MOR_746_CA_B394_PC Carex_vacillans_MOR_1691_ME_B1282_PC Carex_nudata_MOR_1242_CAs_B837_PC_2 0 10 44Carex_angustata_MOR_447_CA_B095_PC 51Carex_nudata_MOR_1242_CAs_B837_PC 45Carex_schottii_MOR_1772_CA_B1363_PC 1 Carex_senta_MOR_1687_AZ_B1278_PC Carex_stricta_MOR_1098_TX_B690_PC Carex_lenticularis_impressa_MOR_750_CA_B398_PC Carex_nigra_Austria_B512_PC 38Carex_aquatilis_substricta_MOR_1684_NB_B1275_PC Carex_endlichii_MOR_1897_AZ_B1489_PC 31 26 8521Carex_lenticularis_lenticularis_NFLD_B877_PC 28 Carex_lenticularis_dolia_MOR_1807_BC_B1398_PC Carex_edwardsiana_MOR_1944_TX_B1536_GR 44 Carex_nebrascensis_MOR_850_CA_B510_PC Carex_macrochaeta_MOR_1438_AK_B1029_LM Carex_haydeniana_MOR_1888_AB_B1480_OV 0 63 0 0Carex_spectabilis_MOR_1781_BC_B1372_ST_2 77 96Carex_spectabilis_MOR_1781_BC_B1372_ST Carex_microchaeta_microchaeta_MOR_1748_YT_B1339_ST 27Carex_microchaeta_nesophila_MOR_1726_AK_B1317_ST Carex_magellanica_MOR_1439_AK_B1030_LM 98Carex_limosa_MOR_769_AK_B417_LM 76 88 Carex_squarrosa_MOR_1083_AR_B675_SQ 4 Carex_typhina_MOR_1132_AR_B725_SQ 70Carex_shortiana_KY_B621_SH 10 93Carex_shortiana_MOR_1031_KN_B622_SH Carex_prasina_MOR_900_GA_B560_HC Carex_grayi_MOR_658_KN_B306_LU 45 Carex_frankii_MOR_673_AL_B321_SQ 99Carex_aureolensis_MOR_504_MS_B152_SQ Carex_halliana_MOR_1491_CA_B1082_PD Carex_intumescens_MOR_709_ME_B357_LU Carex_pumila_MOR_1869_NC_B1461_PD 54Carex_lurida_MD_B474_VC 7 56Carex_baileyi_MOR_485_KY_B133_VC 3 Carex_lurida_MOR_816_FL_B476_VC Carex_tuckermanii_MOR_1147_MI_B740_VC 2 52 68Carex_schweinitzii_MOR_1058_MI_B649_VC 17Carex_schweinitzii_MOR_1656_VA_B1247_VC Carex_exsiccata_MOR_1778_BC_B1369_VC 64 Carex_saxatilis_MOR_1023_CO_B614_VC 2 94Carex_vesicaria_MOR_1162_DE_B755_VC Carex_rostrata_AK_B596_VC 20Carex_utriculata_MOR_1181_AK_B774_VC 13 54 1 62Carex_membranacea_MOR_784_AK_B442_VC 92Carex_rotundata_MOR_1006_AK_B598_VC 81 Carex_ruthii_MOR_1008_NC_B600a_SL 5 Carex_louisianica_MOR_742_FL_B390_LU 3 26Carex_gigantea_MOR_651_FL_B299_LU 30 32Carex_lupulina_MOR_812_MD_B472_LU 95 88Carex_lupuliformis_MOR_745_FL_B393_LU Carex_lupulina_MI_B471_LU 7 Carex_retrorsa_MOR_1012_MI_B603_VC Carex_bullata_MOR_509_MA_B157_VC 4 Carex_hystericina_MOR_815_AR_B475_VC 24 89 94Carex_thurberi_MOR_1618_AZ_B1209_VC 61 65 Carex_thurberi_MOR_1899_AZ_B1491_VC 37Carex_pseudocyperus_MOR_1543_MB_B1134_VC 100Carex_comosa_MOR_560_CA_B208_VC Carex_pseudocyperus_MOR_981_B573_VC Carex_houghtoniana_MOR_1248_MB_B843_PD Carex_lacustris_MOR_725_MB_B373_PD 0 10 17Carex_hyalinolepis_MOR_690_TX_B338_PD 0 67Carex_melanostachya_MOR_1745_NE_B1336_PD 5 46Carex_melanostachya_MOR_1693_KN_B1284_PD Carex_lasiocarpa_MOR_731_AK_B379_PD 8182Carex_pellita_MOR_882_CA_B542_PD Carex_striata_MOR_1076_FL_B668_PD Carex_antherodes_MI_B106_CX 74Carex_atherodes_MOR_1651_BC_B1242_CX Carex_trichocarpa_ON_B728_CX 60 99Carex_trichocarpa_MOR_1133_DE_B726_CX 53Carex_laeviconica_MOR_1689_KS_B1280_CX 7 75Carex_sheldonii_MOR_1495_CA_B1086_CX Carex_hirta_MOR_681_PN_B329_CX Carex_elliottii_MOR_1718_FL_B1309_VC Carex_sylvatica_MOR_1392_WA_B983_HC 15 Carex_aperta_MOR_1644_BC_B1235_PC 91Carex_haydenii_ON_B878_PC 97 74Carex_haydenii_MOR_1890_MA_B1482_PC Carex_stylosa_MOR_1292_NFLD_B889_RM Carex_concinna_CO_B1090_CL 72 Carex_concinnoides_MOR_1720_CA_B1311_CL 94 Carex_richardsonii_MOR_1022_MD_B613_CL Carex_pensylvanica_WA_B987_AC 81Carex_serpenticola_MOR_1763_CA_B1354_AC 8 44 62Carex_tonsa_rugosperma_MOR_1157_MB_B750_AC 98Carex_tonsa_tonsa_MOR_1156_MB_B749_AC 11 Carex_umbellata_MB_B772_AC 71Carex_whitneyi_MOR_1154_CA_B747_LG 39 Carex_novae_angliae_MOR_795_ME_B453_AC 33 Carex_albicans_emmonsii_MOR_433_MD_B080_AC 85Carex_lucorum_austrolucorum_MOR_743_GA_B391_AC Carex_geophila_MOR_1500_CO_B1091_AC 17 53 Carex_reznicekii_MOR_1014_AL_B605_AC 84 75Carex_nigromarginata_MOR_855_AL_B515_AC 10 35 Carex_albicans_australis_MOR_436_MS_B083_AC 61Carex_turbinata_MOR_1679_AZ_B1270_AC 24 Carex_turbinata_MOR_1773_AZ_B1364_AC Carex_pityophila_MOR_1002_CO_B594_AC Carex_peckii_MOR_1427_AK_B1018_AC 6527 Carex_brevicaulis_MOR_1375_WA_B966_AC Carex_rossii_MOR_1624_BC_B1215_AC 7727 18Carex_inops_inops_MOR_1410_WA_B1001_AC 68Carex_brainerdii_MOR_494_CA_B142_AC Carex_globosa_MOR_654_CA_B302_AC 109 74 Carex_verrucosa_MOR_1175_FL_B768_GC 84Carex_communis_amplisquama_MOR_1560_SC_B1151_AC STA1817_Trichophorum_cespitosum 100 STA1816_Trichophorum_alpinum

0.009