Cochlearia) with Emphasis on Icelandic Populations

Genetic structure of diploid (2n = 12, 14) Scurvygrasses (Cochlearia) with emphasis on Icelandic populations

Luka Natassja Olsen

MSc Thesis Centre for Ecology and Evolutionary Synthesis, Department of Biosciences UNIVERSITY OF OSLO September 2015

© Luka Natassja Olsen 2015 Genetic structure of diploid (2n = 12, 14) Scurvygrasses (Cochlearia) with emphasis on Icelandic populations Luka N. Olsen http://www.duo.uio.no/ Cover art: Sondre Strøm Linde Print: University Print Central, University of Oslo

Spoonwort doth warm, and also doth dry, In the Scurvy 'tis a great Remedy, It sends out all corrupt humors by sweat With this your mouth gargel often, and wet. This plant which deserves so much of your praise The Apothecaries use six several wayes, It's Spirit, Syrup, Water procures health, So doth its Salt conserve, and the Herb itself.

'Six several ways' (of using the treasured Spoonwort (Cochlearia) as a remedy of scurvy), as cited by Lorenz (1953)

Forord

En stor takk til min hovedveileder Anne, for møter med kaffe, te og klemmer. Takk for laboratoriehjelp og utregninger, takk for utallige rettinger og tilbakemeldinger på utkast, og for svar på en myriade av spørsmål. Takk til medveileder Inger, for all nomenklaturisk og taksonomisk eksperthjelp i Cochlearia-feltet. I tillegg, takk for at du ble med Anne og meg ut i felt på Island som vår private sjåfør – til tross for at det skulle vise seg å innebære risikable turer over hraun for å krafse Cochlearia ut av klippesprekker! Takk til medveileder Charlotte, for at du hjalp til med gamle Islandske floraer på Tøyen. Takk til Marie, for at du viste vei for meg innenfor RAD-seq, STACKS og alt! Jeg er glad vi rakk å bli kjent før du ble ferdig med din oppgave. Takk til resten av Annes gruppe også, for koselige tirsdagsmøter.

Takk til Sigríður og Ingrid Johansen, for at dere oversatte gamle Islandske floraer for meg. Takk til Paul Grini, for at du tok deg tid til å diskutere epigenetikk. Thank you, Robin, for all your thoughts, and for pushing me into trying bioinformatic gymnastics. Thank you, Annie, for feedback on my writing. Many thanks to Terezie Mandáková and Martin Lysák, for letting me stay in Brno. And to Terezie especially, for all help with the chromosome counts, both at the Mazaryk University in Czeck Republik, and here at UiO.

En spesielt stor takk til Stine, Tonje og Mathilde, for at jeg fikk være en brøkdel av den fantastiske firkløveren vår. Det er usikkert om jeg ville likt meg så godt gjennom studiene om det ikke hadde vært for dere. Nå som den dårlige studentsamvittigheten omsider fordufter håper jeg at vi kan finne på noe utenfor lesesalen igjen. Takk også, til alle de fine samboerne mine, Åsa, Sverre, Veronika og Linnea, for at det ofte har vært klemmer å få og middag i kjøleskapet når jeg kommer sent hjem. Takk til familien min, spesielt Ronja, for alle oppmuntrende ord, og for at du tvinger meg til å ta kaffepauser selv når jeg tror jeg ikke trenger det. Sist, men ikke minst, takk til Sondre, for at du laget forside for meg, og for at du alltid synes jeg er den flinkeste i verden – uansett hva det er jeg foretar meg.

Index

Abstract ...... 9 1 Introduction ...... 11 1.1 Taxonomical treatment of Cochlearia in Iceland...... 13 1.2 Research aims and questions ...... 15 2 Materials and methods ...... 16 2.1 Plant material ...... 16 2.2 Chromosome counting ...... 17 2.3 Morphometry ...... 19 2.4 DNA extraction ...... 21 2.5 RAD-sequencing ...... 21 Processing the raw RAD-seq reads ...... 23 Population structure analysis ...... 25 Tree and network analyses ...... 25 PCA analyses ...... 26 Maps ...... 26 3 Results ...... 27 3.1 Chromosome counting ...... 27 3.2 Morphometry ...... 28 3.3 RAD-sequencing ...... 32 Population structure analysis ...... 32 Tree and network analysis ...... 33 Bayesian phylogeny ...... 35 PCA analysis ...... 36 4 Discussion ...... 39 4.1 Do Icelandic plants with different chromosome number or ecology constitute different genetic clusters? ...... 39 4.2 How is the evolutionary relationship between the Icelandic plants and other diploid Cochlearia species? ...... 43 4.3 How can the results from this study be guiding for taxonomical decisions in Flora Nordica? ...... 44 References ...... 47 Appendix ...... 52

Abstract

Section Cochlearia (Brassicaceae) includes highly polymorphic species complexes with regard to ploidal level, ecological adaptation and distribution. Low levels of chloroplast DNA divergence suggest that taxa most likely have diversified relatively recently, and that speciation is still ongoing. This has led to conflicting taxonomic treatments. The European Cochlearia displays a range of ploidal levels, from diploid to decaploid. Diploid species with chromosome number 2n = 12 dominate in southwestern Europe, whereas the arctic Cochlearia is diploid with 2n = 14. In Iceland, diploid plants of both basic numbers (2n =12, 14) are found. Whereas the 2n = 12 plants are found only in beach cliffs along the Icelandic coast, the 2n = 14 plants are found in two different habitats: In snowbeds on inland mountains, and along the western coast of Iceland. There is still no agreement as to which taxa the Icelandic plants belong. It has been suggested that the 2n = 14 plants belong either to the arctic diploid C. groenlandica (2n = 14) or constitute a subspecies of the tetraploid C. officinalis (2n = 24). The 2n = 12 plants have been related either to C. groenlandica or to the southwestern European diploid C. pyrenaica (2n = 12). In this study, single nucleotide polymorphisms (SNPs) derived from RAD-sequencing were applied to study whether the Icelandic Cochlearia plants constitute genetic clusters in accordance with chromosome number or ecology. Additionally, to investigate their evolutionary relation to other Cochlearia species, Icelandic plants were compared to recognized diploid species in Svalbard (C. groenlandica) and southwestern Europe (C. pyrenaica and C. aestuaria). Analyses of SNP data showed that Icelandic plants cluster according to ecology, and not according to chromosome number. Furthermore, the genetic variation among the Icelandic populations display a geographic pattern, where plants sampled in closely located sites are more similar irrespective of chromosome number. Icelandic plants do not cluster with southwestern European plants, but alpine (2n = 14) plants on Iceland consistently group with C. groenlandica in Svalbard. Based on the results from this study, it is suggested to refer alpine Icelandic plants to C. groenlandica. The Icelandic coastal plants show no clear genetic or morphological separation between plants with different chromosome number (2n = 12, 14), and they should therefore be referred to the same taxon. However, because the relation to C. officinalis (2n = 24) was not addressed in this study, it is not decided which taxon they should be referred to.

1 Introduction

[Cochlearia] has always proved to me to be one of the most intractable boreal genera […] Habit, pods and leaves afford the characters hitherto made use of; and all are equally fallacious, as far as affording permanent distinctions (Hooker 1861, p. 317).

The genus Cochlearia L. is part of the mustard family (Brassicaceae) and is widely distributed in Europe and the circumpolar region. The genus comprises two sections: Cochlearia and Glaucocochlearia O.E. Schulz (Koch et al. 1996). The focus of this study will be on a selection of diploid taxa within the section Cochlearia.

Section Cochlearia is known as a notoriously difficult group when it comes to taxonomic delimitations (Saunte 1955, Gill 1965, Hultén 1971, Gill 1971a, 1971b, 1973, 1978, Nordal 1988, Nordal and Laane 1990, Nordal and Stabbetorp 1990, Koch et al. 1996, 1999). The opening quote of Hooker, on his observation of morphological traits more than 150 years ago, is still applicable today. The section as a whole appears to be quite young, possibly with a post or late glacial origin (Koch et al. 1996, Koch 2012). There is obviously ongoing speciation within this group, and considerable chromosome evolution has taken place without corresponding morphological differentiation (Koch et al. 1996). Two basic diploid series exist, based on haploid numbers x = 6 and x = 7. The x = 6 series is suggested to be the most basal, and it is found from south temperate to north boreal Europe, while the x = 7 series is widespread in arctic regions (Gill 1971a, 1973, Nordal and Laane 1990, Koch et al. 1996). The geographically disjunct distribution of the 2n = 12 plants: in Iceland, Scotland and southwestern Europe, seen today, are possibly relicts of a formerly wider distribution (Koch et al. 1996). Koch et al. (1996) suggested that during the Pleistocene, Cochlearia plants similar to the extant 2n = 12 species (C. pyrenaica DC. or C. aestuaria (J.Lloyd) Heywood) survived in refugia south of the glaciers in southwestern Europe. As the glaciers retreated, the diploids spread northwards from the refugia, underwent chromosomal changes and diversified. Cytological studies have shown that the circumpolar 2n = 14 (x = 7) most likely derived from 2n = 12 (x = 6) by primary tetrasomy (doubling of one chromosome set; Gill 1971a, 1973, Nordal and Laane 1990). Tetrasomy is suggested to create potential for greater variation (Nordal and Laane 1990), and it is speculated that the x = 7 series evolved in western Europe,

11 possibly on Iceland, and subsequently colonized the circumpolar and arctic region (Svalbard, Greenland, North America and Siberia; Nordal and Laane 1990, Koch et al. 1996).

Large cytological variation is present in the section Cochlearia, ranging from diploids to decaploids (Saunte 1955, Gill 1965, 1973, Nordal et al. 1986, Nordal and Laane 1990). Crossing experiments across the chromosome levels have resulted in fully or partially fertile hybrids (Crane and Gairdner 1923, Gill 1971a, 1973, 1975, Fearn 1977, Koch et al. 1996, Pegtel 1999). Taxa recognition based on morphology without knowing the ploidal level or geographic origin can be very difficult, if not impossible, as individuals of the same taxon may present large variation in morphology dependent on their habitat. Particularly the level of soil nitrogen, light conditions and stress factors (e.g. salinity) are likely to influence the phenotype, such as size, erect versus prostrate habit, leaf shape and development of stem leaves (Elkington 1984, Nordal et al. 1986, Nordal and Stabbetorp 1990, Pegtel 1999). Accordingly, environmental influences must be accounted for when morphological traits are given taxonomic weight. On the other hand, separate evolutionary entities that are morphologically similar might be mistakenly included into the same taxon if morphological divergence has not happened at the same speed as genetic divergence and reproductive isolation (Shaw 2000, Chan et al. 2002, Whittall et al. 2004, Duminil and Di Michele 2009).

Determination of species’ boundaries of recently diverged lineages is a general problem in organism groups because populations may not have been isolated long enough to accumulate significant differences in the traits considered (Shaffer and Thomson 2007, Escobar García et al. 2009, Lega et al. 2012, Slovák et al. 2012, Dick et al. 2014). Different species concepts often focus on particular properties of the diverging populations, e.g. diagnosable morphological traits, internal reproductive isolation, restricted gene flow or monophyly (cf. Medrano et al. 2014). However, the evolutionary changes that lead to such properties through speciation do not necessarily occur at the same time or in a regular order (De Queiroz 2005, 2007). Consequently, delimitation of taxa may vary among authors depending on which traits they focus on, and which species concept and methods they use. The treatment of diverging lineages might therefore often result in incompatible taxonomical treatments (De Queiroz 2005, 2007). In an attempt to unify the different more or less incompatible species concepts, De Queiroz (2005) recognized that all concepts are based on a general understanding of species as a separately evolving metapopulation lineage, and considered this to be the only necessary property. As an example, if two metapopulations (each consisting of several subpopulations) diverge with regard to one or several properties, this is according to De 12

Queiroz sufficient to postulate that they are different species. Consequently, properties such as reproductive isolation and ecological differentiation are not needed to delimit species, but can be used as evidence for species boundaries and to determine the degree of separation. In addition, these properties can be used as descriptions of the separation (e.g. reproductively isolated species or ecologically differentiated species). As mentioned, Cochlearia is of a young age and consists of species characterized by high phenotypic plasticity, introgression and ongoing differentiation. The degree of separation between units, however, is still unknown.

1.1 Taxonomical treatment of Cochlearia in Iceland

For the genus Cochlearia, Iceland is of particular interest since it is the only area where plants with different diploid chromosome counts co-occur (2n = 12, 14) (Gill 1971a, Nordal and Laane 1990, Koch et al. 1996, Koch et al. 1998). The plants are distributed along the entire coast of Iceland, and have in addition a scattered distribution on inland mountains. Chromosome numbers have, so far, only been obtained on a limited number of populations (Appendix, Table A1).Two ecologically differentiated Cochlearia forms exist in Iceland. A dwarfed “alpine” form with a chromosome number of 2n = 14 is found in late snow beds on inland mountains, whereas a larger “coastal” form is found in beach cliffs along the coast. Both diploid chromosome numbers are, so far, reported for the coastal plants, but 2n = 12 plants are reported only from a restricted part of the southern coast of Iceland (except that Gill referred to an unpublished observation of 2n = 12 plants in northwestern Iceland; Gill 1971a). On the other hand, 2n = 14 plants are reported from the west-coast of Iceland (Saunte 1955, Gill 1971a, Löve 1975, Nordal and Laane 1990).

Icelandic populations of Cochlearia have been treated very differently both with regards to taxonomy and nomenclature through the years, varying greatly depending on the author (Appendix, Table A2). In the second edition of Flóra Íslands (Stefánsson 1924, first edition from 1901, not seen), all Icelandic plants were referred to one species, C. officinalis L., and were subdivided into three varieties, var. groenlandica (L.) Gelert., var. oblongifolia (DC.) Gelert., and var. arctica (Schlecht.) Gelert. The mountain form was referred to var. groenlandica, whereas the coastal forms were referred to var. oblongifolia and var. arctica based on differentiation in leaf and fruit forms (Stefánsson 1924). This delimitation was upheld in the third edition (Stefánsson 1948). In Íslenzkar Jurtir, Löve (1945) referred all

Cochlearia populations to one species, C. officinalis without subspecific taxa. In Flora Europaea (Tutin et al. 1964), two species were referred to Iceland: C. fenestrata R.Br. and C. groenlandica L., with C. fenestrata probably representing the coastal plants, and C. groenlandica the alpine form. The paragraph on these taxa concludes: “There has been much confusion between the two taxa, consequently their distribution is uncertain” (Tutin et al. 1964). Pobedimova (1969) revised the circumpolar plants in the genus. She reported C. groenlandica from the northeastern Iceland and C. islandica Pobed. all along the coast, except the southern part of Iceland. Additionally, Pobedimova (1970) reported C. anglica L. in the northwest, close to Snæfellsnes. In Icelandic Excursion Flora, (Löve 1970) referred the Icelandic plants to C. groenlandica ssp. islandica (Pobed.) Á. Löve. Later, however, he referred the Icelandic taxa to two genera, Cochlearia based on x = 6, and Cochleariopsis based on x = 7 (Löve 1983). He reported two taxa from Iceland: Cochlearia pyrenaica (2n = 12), and Cochleariopsis groenlandica (L.) Löve & Löve ssp. islandica (Pobed.) Löve & Löve (2n = 14). This has not been accepted in any later treatments (Elven 2011), as the morphological differences are ignorable and the chromosome difference probably is a result of tetrasomy (Gill 1971a, Nordal and Laane 1990). In Flowering plants and ferns of Iceland, Kristinsson (1986) referred all the Icelandic plants to C. officinalis. He also mentioned the unclear origin of the mountain plants, and suggested that they might belong to a species distinct from the coastal plants (Kristinsson 1986). The treatment of the Icelandic plants as C. officinalis is upheld in the third edition (Kristinsson 2010). Nordal and Laane (1990) chose not to group the Icelandic plants with C. officinalis, based on experiments that showed significant differences in flower and seed size as well as differences in mode of reproduction (Icelandic plants were supposed to be self-compatible, whereas C. officinalis proved to be obligate outcrossers). Instead, Nordal and Laane (1990) grouped the Icelandic plants together and referred them to C. groenlandica based on morphology, chromosome number and reproductive biology. They further suggested that the ecologically and morphologically differentiated alpine and coastal plants on Iceland might deserve subspecific recognition.

Few molecular studies have been conducted on the Icelandic Cochlearia plants, and it is so far unclear whether they belong to the same genetic cluster, or whether they represent two or more separate genetic clusters corresponding to chromosome number and/or habitat. In a study on chloroplast divergence in section Cochlearia, Koch et al. (1996) included European diploid (2n = 12) C. pyrenaica and C. aestuaria, distributed in southwestern Europe as well as Icelandic plants from a 2n = 12 coastal population and four 2n = 14 populations (sample

14 location is known for only one population, which is a coastal population), all referred to by the authors as C. groenlandica. All the 2n = 12 diploid plants turned out to have a distinct chloroplast (cpDNA) type (B) and grouped together irrespective of geographic origin. The four Icelandic 2n = 14 populations had another cpDNA type (F), and grouped with C. officinalis individuals from northern Scandinavia, which also had this cpDNA type (Koch et al. 1996). Isoenzyme studies grouped the Icelandic 2n = 12 plants with C. pyrenaica, while Icelandic 2n = 14 plants were grouped with C. aestuaria (Koch et al. 1998).

1.2 Research aims and questions

Given the partly contradictory information on cytological, ecological, molecular and morphological data observed in Icelandic Cochlearia, the aim of this thesis is to further investigate evolutionary relationships and taxonomic status of these plants. Restriction site Associated DNA Sequencing (RAD-seq) will be used to detect possible genetic structure among Icelandic populations. RAD-seq is a method that makes it possible to create a reduced representation of the genome by sequencing fragments of nucleotides next to restriction enzyme cutting sites and searching these for molecular markers such as single-nucleotide polymorphisms (SNPs). This can be done for multiple individuals and populations simultaneously (Baird et al. 2008). RAD-seq can be performed de novo, without the need of a reference genome, which makes it suitable for studies on non-model species. Chromosome count information will be obtained from several populations, and results from a small pilot study on morphological leaf traits will be compared to the molecular and cytological results.

Specifically, the following research questions will be addressed:

 Do Icelandic plants with different chromosome number (2n = 12/14) or ecology (coastal/alpine) constitute different genetic clusters?

 How is the evolutionary relationship between the Icelandic plants and other diploid Cochlearia species, specifically: C. groenlandica (Svalbard), C. aestuaria (Spain), and C. pyrenaica (Spain, France)?

 How can the results from this study be guiding for taxonomical decisions in Flora Nordica?

2 Materials and methods

2.1 Plant material

Plant material was mainly sampled in Iceland during one week in August 2014. Leaf samples were collected from ten individuals per population, twelve populations in total (abbreviation of locality names are used throughout the thesis according to Fig. 1; Appendix Table A3). Ten of the sampled populations were located close to the sea and considered as representatives of the ‘coastal’ ecotype, while two populations were sampled on inland mountains at 920-1030 m.a.s.l. representing the ‘alpine’ ecotype. Sampling localities were chosen based on previous publication of chromosome numbers (Saunte 1955, Gill 1971a, Löve 1975, Nordal and Laane 1990, Koch et al. 1998, Appendix Table A1), or from locality records from a database at the Icelandic Institute of Natural History (IINH).

In the field, healthy green leaves were harvested and dried instantly on silica gel for subsequent DNA extraction. Seeds were collected when present and later germinated in a phytotron at the University of Oslo, Department of Biosciences. From most populations (except for populations STK, HVA, DJU and HAF) living specimens were additionally sampled and cultivated in the phytotron. Herbarium vouchers were made from field collected specimens for all populations and will be deposited at the Natural History Museum, University of Oslo (Appendix, Table A3). For cytological studies, flower buds were harvested in the field or in the phytotron.

Additional material sampled by collaborators was obtained from three Icelandic populations (either as seeds, silica dried material or both, Fig. 1), and from Svalbard, France and Spain (Appendix Tables A3, A4).

Seeds were subjected to stratification before sowing. Five layers of paper tissue were placed in a petri dish and covered by filter paper. Using a syringe, 5 ml water was added before 14 healthy seeds were evenly distributed in the petri dish. The seeds were covered by filter paper and sprinkled with 2 ml water. Petri dishes were sealed with Parafilm before being placed in a cold room at 4 °C for approximately three weeks. Seeds were sown in standard soil (S-jord) in the phytotron with conditions of 18 h day at18 °C and 6 h night at 10 °C. As most Cochlearia species are biennial or perennial (Gill 1971a) and do not flower until the second (biennial) and subsequent seasons (perennial), plants were allowed to develop leaf rosette for about 2.5

16 months before they were moved to simulated winter conditions: 10 h day and a temperature of less than 9 °C for 1.5 month and then moved back to summer conditions to induce flowering. As not all plants flowered after the first induced winter, they were exposed to winter conditions for further 1.5 months. During the second induced summer, conditions were changed to speed up the flowering process: 18 h day at 20 °C and 6 h night at 18 °C.

Figure 1: Map of Iceland with indication of locations from where 15 populations of Cochlearia were sampled; abbreviated names in brackets are used throughout the study. Inserted map in top left corner shows the distribution of Cochlearia in Iceland (map from Kristinsson 2010). For further locality information, see Appendix Table A3.

2.2 Chromosome counting

From plants in the field or the phytotron, we collected whole inflorescences containing buds which were early in their development (the biggest bud in the inflorescence was yellow). Chromosome counts were obtained from altogether 12 Icelandic populations. From most populations only one individual per population was counted, except for population BAE from

17 which four individuals were counted. Population HJO was not included as no flowers were available in the field, planted seeds did not sprout, and the live plant in the phytotron did not flower. Seeds of populations HFN and LAT were not available. Inflorescences were placed in freshly prepared Carnoy’s fixative I (3 parts ethanol, 1 part glacial acetic acid), which was changed once before the inflorescences were transferred into tubes with 70 % ethanol and kept in the freezer for long-time storage. This material was later used for chromosome counts done either together with collaborators at Masaryk University in Brno, Czech Republic, or at the University of Oslo. Chromosome slide preparation was performed following parts of a protocol originally developed for chromosome painting (Lysak and Mandáková 2013). Counted individuals did not necessarily correspond to those included in the RAD-seq library.

Floral material was first rinsed with distilled water for 10 min before suitable parts of the inflorescence were selected and washed twice in 1 x citrate buffer (Appendix Table A5) for 5 min while shaking on an orbital shaker. The 1 x citrate buffer was removed and the tissue submerged in ~1 ml pectolytic enzyme mixture (Appendix Table A6 a, b) at 37 °C for 3 h. The enzyme mixture was replaced by 1 x citrate buffer and the digested material kept on ice until use. A single flower bud was placed on a FisherBrand Superfrost plus microscope slide (Fischer Scientific, Pittsburg, USA) using a Pasteur pipette together with 20 µl 60% acetic acid. The bud was disintegrated to break the cells using a dissection needle, and placed on a heating block (50 °C) for 2 min. During this step the cell suspension was spread by circular stirring of the 60% acetic acid droplet using a needle that was held horizontally (without touching the slide). The chromosomes were fixed in 100 µl Carnoy’s fixative I (pipetted as four drops around the suspension drop and lastly one in the middle). The fluid was discarded by tilting the slide and quickly dried for two seconds using a hair dryer. The slide was quality checked in a light microscope with phase contrast before applying 20 µl DAPI (4',6- diamidino-2-phenylindole; Appendix Table A7), and covered with a coverslip. For each individual, multiple microscope slides were prepared and examined. In Masaryk University, Brno, the search for clear nucleus spreads was done in an Olympus BX-61 epifluorescence microscope and CoolCube CCD Camera (Metasystem) and pictures were processed in Adobe Photoshop CS2 (Adobe Systems). Chromosome counts of three of the populations (STR, HNF and SUR) were determined in Oslo using both a light microscope with phase contrast and a Zeiss Axioplan Imaging2 epifluorescence microscope system equipped with Nomarski optics, epifluorescence attachment and the software Zeiss AxioVision 4.8. After chromosome counting, the slides were stored in a dust free box at 4 °C.

2.3 Morphometry

After several months (depending on whether plants were grown from seeds or collected as live plants) of exposure to the same conditions in the phytotron, five leaves from four individuals per population (10 populations in total) were sampled. For population DYR, ING, BAE, OLF, material included in the morphometric analyses were collected both from plants sampled in the field (and subsequently cultivated in the phytotron) and from plants grown from seeds in the phytoptron. For population STK, HVA, DJU and HAF, only material sampled from plants germinated from seeds were included, as live plants were not sampled in the field. For the alpine populations EIR and GIL, only material from live plants sampled in the field were included, as seeds were not available or did not germinate. Only three individuals from the EIR population were available for morphometric analyses. The two populations HJO and STR were excluded from the morphometric analyses as phytotron material was available from only one plant. Population SUR was excluded since all individuals presumably suffered from a virus causing sickly plants with crippled leaves. Populations HFN and LAT were only available as silica-dried field material and were neither included in the morphometric analyses.

Because only few individuals were flowering in several of the populations, flower traits were not used in morphometric analyses. Instead, leaf traits previously recognized by Nordal and Laane (1990) as informative, were used: Maximum leaf length (L), maximum leaf width (W) and leaf base angle (Fig. 2). Maximum leaf length was measured as the vertical line drawn from the leaf tip (apex) to the attachment of the leaf stem. Apex was considered the part of the lamina farthest removed from the point of attachment of the leaf to the stem. Maximum leaf width was the distance between the leftmost and rightmost points in the horizontal line measured 90° on the vertical leaf length line. The measurements were used to calculate leaf surface area (L x W) and leaf ratio (W/L). Leaf base angle was measured as the angle degrees between the lines drawn from the point of attachment along the lower margins of the leaf. Leaf surface area gives information about leaf size, while leaf ratio and leaf base angle give information about leaf shape. The average of an individual’s five leaves was calculated. Differences in morphological traits were investigated using the following statistical analyses: Levenes (1960), Shapiro and Wilk (1965), Kruskal Wallis (1952) and the Mann-Whitney U test (1947), as well as box plots. These tests were generated in EXCEL using the REAL STATISTICS RESOURCE PACK software (Release 4.3, copyright (2013-2015) Charles Zaiont www.real-statistics.com).

Figure 2: Illustration roughly depicting how measurements were made in leaf morphometric analyses of Cochlearia plants from Iceland. Examples of two leaves with very different size and shape are shown.

Tests for critical requirements of homoscedasticity (Levenes test) and normality (Shapiro and Wilk) for parametric analysis were performed. Because of the rejection of these requirements, subsequent analyses were done using non-parametric tests: Kruskal-Wallis and Mann-

Whitney U tests for two independent samples. The Kruskal-Wallis test was used to test for significant differences in the population samples in respect to leaf surface area, ratio and base angle. The Mann-Whitney U test was used to test for significant values of the mentioned traits between two groups (according to habitat, chromosome number or chromosome number within or between habitat). To test which of the populations that were significantly different, Dunn’s test for multiple comparisons (Dunn 1964) was performed using the DUNN.TEST 1.2.4 (Dinno 2015) package in R. To visualize potential trends or patterns when combining the effect of the the three morphological variables (leaf surface area, leaf ratio and leaf base angle), a Principle Component Analysis (PCA) biplot was created in R using the VEGAN 2.3-0 (Oksanen et al. 2013) package. PCA identifies the ordination axes that correspond to the greatest variability in the data set by reducing multidimensional data into lower dimensions while still retaining most of the information (Sparks et al. 1999). To include the different variables into the same analysis, normalization of the data was done by calculating the mean and standard deviation of each variable (leaf surface area, ratio and angle) separately. Each observation (Xi) was converted into a corresponding Z score, preserving the shape of the original data: Mean (µ) was set to 0 and standard deviation to 1: Zi=(Xi-µ)/s.

2.4 DNA extraction

DNA was extracted from approximately 30 mg dried leaf samples using the E.Z.N.A. SP plant DNA kit (Omega bio-tek, Norcross, USA) and the protocol issued by the manufacturers with minor modifications. The dried samples were crushed by adding two 3 mm tungsten carbide beads (Qiagen, Venlo, Netherlands) to a 2 ml Eppendorf tube containing the leaf sample, disrupting them for 2 min at 20 Hz in a TissueLyser II, Retsch MMo1 (Retsch, Castleford, UK). The remaining protocol was followed without any modifications until the elution steps at the end, where most samples were eluted in 100 µl elution buffer run once through the binding column or in two steps with 50 µl elution buffer at a time. Individuals with considerably less starting material than 30 mg were first eluted in 50 µl elution buffer, and then once again using the first eluate to increase the final concentration of the extracted DNA. DNA LoBind tubes (Eppendorf, Hamburg, Germany) were used for prolonged storage. Quantification and quality check of the extracted DNA was performed using both NanoDrop ND-1000 V3.10 Spectrophometer (Thermo scientific, USA) and Qubit dsDNA BR assay kit (Life Technologies, Carlsbad, California, USA) with a Qubit fluorometer (Life Technologies).

2.5 RAD-sequencing

RAD-seq uses a restriction enzyme to cut DNA from each individual, producing sticky-ended fragments. The sticky-end fragments are ligated to adapters that contain a matching sticky-end and a barcode. Barcodes are used in subsequent analyses to recognize individuals (Davey and Blaxter 2010, Davey et al. 2011).

A single-digest RAD-seq library was prepared using single digest, double barcoding and size selection with magnetic beads according to a protocol adapted from Baird et al. (2008) and modified by Ovidiu Paun and Clemens Pachschwöll (University of Vienna). Further modification was done based on a protocol developed by Robin Cristofari (University of Oslo): The sub-libraries were kept separate throughout the procedure (i.e. pooling of sub- libraries was not done until after qPCR). The library comprised of 82 samples (79 individuals and three replicate samples) individuals separated into seven sub-libraries: six sub-libraries each with 12 individuals and one sub library with ten individuals. Each individual was marked by a unique double barcode combination (Appendix, Table A8), where seven P2 adapters indicated sub-libraries and 12 P1 adapters indicated individuals within sub-libraries. The barcodes had at least three nucleotide differences between each other. Isolated genomic DNA

21 was cleaned with NucleoSpin gDNA Clean-up (Macherey-Nagel, Düren, Germany). Quantification and quality check of the cleaned DNA was done using both a NanoDrop ND- 1000 V3.10 Spectrophometer and a Qubit Fluorometer. Based on quantification values each sample was diluted to ensure that the same amount of DNA (250 ng) was included from each individual (i.e. normalization): x µl DNA and 44-x µl Milli-Q water. Genomic DNA was digested with restriction enzyme PstI-HF (CTGCA/G) (NEB, New England Biolabs, UK) at 37 °C for about 2 h. Since PstI-HF cannot be heat activated, the samples were cleaned with SPRI (i.e. solid phase reversible immobilization; SPRI, Beckman Coulter, Indiana, USA) with no selection (1.8x) to remove the enzyme after restriction digestion. The samples were quantified using Qubit and normalized to a volume of 30 µl. Ligation of P1 adapters was done by adding 1.25 µl 100 nM P1 adapter, 1 µl 100 mM rATP (Promega, Fitchburg, USA), 1 µl NEB Buffer 2, 3.25 µl Milli-Q water, 3 µl 10x SmartCutBuffer and 0.5 µl 200 000 U T4 ligase (NEB) to each sample before incubating at 16 °C over night in a PCR machine without heated lid. The samples were heat treated for 10 minutes at 65 °C to inactivate the enzyme, pooled into seven sub-libraries and randomly sonicated (stochastic shearing) using nine cycles (2 °C, 30 sec on and 30 sec off) on a Bioruptor Plus (Diagenode, Denville, US) to obtain an optimal size of 300-600 bp. The shared samples were cleaned using a MinElute Reaction Cleanup Kit (Qiagen) eluting in 15 µl elution buffer, and subsequently SPRI size selection was performed on both the left (0.7x) and right (0.55x) side. To polish the ends of the fragments, the Quick Blunting Kit (NEB) was used; 2.5 µl Buffer, 2.5 µl 100 mM dNTP and 1.0 µl enzyme was added to 19 µl DNA per sub-library and incubated for 30 min at room temperature. Next, the samples were cleaned with MinElute Reaction Cleanup Kit, before dATP/adenine (Fermentas) overhangs were attached to the 3’ end of the fragments by adding 2 µl (15U) Klenow Exo (NEB), 1 µl 100 mM dATP and 2 µl NEB Buffer to 15 µl DNA per sub-library before incubation at 37 °C for 30 min. Once again the samples were cleaned using MinElute Reaction Cleanup Kit. P2 adapters were ligated to the DNA fragments by adding 5 µl 2 µM P2 Adapter, 1 µl 199 mM rATP, 3 µl NEB Buffer 2, 0.5 µl T4 ligase to 20 µl DNA solution with subsequent incubation at room temperature for 30 min. A new purification was done using MinElute Reaction Cleanup Kit (Qiagen) as well as left side size selection (0.65x) with SPRI. The sub-libraries were amplified using PCR. PCR amplification was done as seven reactions each containing 12.5 μl Phusion Polymerase remix (NEB), 1 μl Solexa primer (10 µM), 7.5 μl water and 4 μl sub-library template (DNA), with the following cycling conditions; 30 sec at 98 °C, followed by 18 cycles [10 sec 98 °C, 30 sec 65 °C, 30 sec 72 °C], 5 min at 72 °C, and incubation at 4 °C. The resulting products were run on a 2% TBE gel for

30 min to verify successful amplification. The sub-libraries were cleaned with MinElute Reaction Cleanup Kit (Qiagen) and left side SPRI size selection (0.65x). The sub-libraries were quantified using Qubit, and run on an Agilent 2100 Bioanalyzer (Agilent technologies, Santa Clara, USA) with a High sensitivity DNA Assay Kit (Agilent) to verify that the overall size range and quantity of the sub-libraries were optimal. The concentration of each sub- library was measured with qPCR assay (KAPA Library Quantification Kits cat no KK4824, KAPA biosystems, Massachusetts, USA), using a qPCR cycler (Lightcycler 96, Roche, Basel, Switzerland) ensuring that equal amounts of each sub-library were included in the final RAD- seq library before it was sequenced using paired-end sequencing (125 bp) in one Illumina HiSeq2500 lane at the Norwegian Sequencing Centre (NCS).

Processing the raw RAD-seq reads

A total number of 348,745,226 paired-end Illumina sequence reads (120 bp in length) were returned from the sequencing lab and processed with STACKS version 1.29, using high- throughput computation resources at the University of Oslo. STACKS is a pipeline program used to build loci and identify SNPs (Catchen et al. 2011, Catchen et al. 2013). In STACKS, the program PROCESS_RADTAGS.PL was used to sort individuals according to barcodes (demultiplexing; Appendix Table A8) and to filter reads to improve quality (clean/remove low quality reads), resulting in 196,579,422 retained forwards reads. In addition to the individuals included in the current RAD-seq library, ten diploid individuals (C. aestuaria and C. pyrenaica from population AST, PYR1, PYR2, PYR3, PYR4, see Appendix Table A4) were included from a RAD-seq library produced in a previous study (Brandrud 2014). Both forward and remainder forward reads were merged and used in the analysis, trimmed to 100 bp to match the additional sequences. Next DENOVO.MAP.PL was used to execute three STACKS component programs: unique stacks (USTACKS), catalog stacks (CSTACKS) and search stacks (SSTACKS). The USTACKS program aligns sequence reads into matching stacks and uses these to build loci and call SNPs using maximum likelihood. CSTACKS builds a catalog by creating sets of consensus loci and merges alleles accordingly. SSTACKS allows us to search among stacks created by USTACKS, matching each sample against the catalog. Severel runs with different settings were performed to see which combination maximized the number of reliable loci with the chosen filters. Resulting files were loaded into a MySQL database with LOAD RADTAGS.PL and compared: Only allowing loci with one to nine SNPs, and only counting SNPs that appeared in at least 80% of the individuals. Settings used in the end were

23 m (minimum number of identical, raw reads required to create a stack) = 2, M (number of mismatches allowed between loci when processing a single individual) = 2, n (number of mismatches allowed between loci when building the catalog) = 1.

A high number of unique loci in the processed RAD-seq library raised suspicion about contamination. The genome of any Cochlearia species has not yet been sequenced, but as the genus is a relative of the model plant species Arabidopsis thaliana, the sequence reads were aligned to the A. thaliana reference genome using the National Centre for Biotechnology Information (NCBI). When aligning reads to the A. thaliana reference genome, alignment rates were somewhat low: < 30 % of the tested reads aligned more than once to the reference genome; approximately 10 % aligned once and the rest did not align at all. Blasting of the data revealed that around 77 % of the reads were indeed from bacteria and fungi; some of them known endophytes of Arabidopsis. The probability of a read stemming from bacteria or fungi decreased steeply with the increasing number of scored reads; almost all reads scored in at least 10 samples had Brassicaceae like BLAST-hits. To remove bacterial reads from the final files used in the data analysis, strict filter settings in the STACKS program POPULATIONS were implemented: Retaining only loci that were present in minimum 0.75-0.8 % of the individuals in a population. Furthermore, only loci that were present in 0.75-0.85 % of the populations were kept. Additionally, filtered reads were blasted to check for remaining bacterial DNA, and no contamination was observed. Individuals were linked to their respective populations using POPULATIONS, and the following format output files were chosen: STRUCTURE, VCF and PHYLIP. For more information about the settings used to produce the different output files, see Appendix Table A9.

Because of the focus of this study (diploid Cochlearia), and potential complications arising when mixing numbers in the analyses, six tetraploid individuals (originally included in the RAD-seq library) were excluded from further analyses. Additionally, ten diploid individuals from a previously produced RAD-seq library (Brandrud 2014) were included, resulting in a total number of 83 individuals in addition to the three replicates. Replicates were excluded in the final results.

Initial data analyses, showed that two samples (in population HFN and LAT) were most probably switched in the lab during DNA extraction, as the sample tubes had identical numbers. In the analyses, one individual in the HFN population always grouped with the LAT

24 population and vice versa. Based on these results a decision was made to switch the samples back to their suspected true populations.

Population structure analysis

Population structure was investigated with the program STRUCTURE (Pritchard et al. 2000). STRUCTURE is based on the Hardy-Weinberg (HW) assumption, and uses Bayesian clustering to find the optimal number of groups (= K) that the dataset can be divided into, and then assigns individuals to these groups. For the analysis, the STRUCTURE output file was used (containing 1500 SNPs for 83 individuals). Since we are dealing with closely related species and populations, the admixture model was used, assuming that individuals may originate from more than one group. Correlated frequencies were chosen, allowing allele frequencies in the different populations to be quite similar (Falush et al. 2007). The dataset was run for each K from K = 1 to K = 10 using 1 000 000 iterations and burn‐in of 100 000, through the

Lifeportal at the University of Oslo. Results were summarized in STRUCTURE HARVESTER (Earl and von Holdt 2012) and CLUMPAK (Kopelman et al. 2015). After the evaluation of the likelihood graphs and graphs of DeltaK produced by the Evanno method (Evanno et al. 2005), the data was visualized in DISTRUCT (Rosenberg 2004).

Tree and network analyses

SPLITSTREE v4.13.1 (Huson and Bryant 2006) can be used to infer various phylogenetic trees and networks based on for instance SNPs, sequences or a distance matrix. A neighbor-joining network based on the PHYLIP file (containing 1500 SNPs) for 83 individuals was made using uncorrected_P as SNP data distance. The network was performed with each end node representing an individual.

A Bayesian tree was created using a PHYLIP file, (containing 2482 SNPs for 83 individuals represented as 24 populations), with each end node representing a population. This PHYLIP file was converted to a NEXUS file using ALIVIEW v1.17.1 (Larsson 2014). Selecting the best- fit model of nucleotide substitution was done by the use of JMODELTEST 2.1.7 (Darriba et al. 2012), where number of substitution schemes was set to 3, rate variation to G (gamma) without variable sites and calculation for base tree for likelihood set to Fixed Bionj-JC. Otherwise default settings were used. Based on the result of this test, the F81+G substitution model was used when running a Bayesian inference phylogenetic analysis using the MCMC

25 method in MRBAYES v3.2.5 (Ronquist and Huelsenbeck 2003). MRBAYES was programmed to perform two parallel runs using four heated chains. Each run had number of generations set to 1.000.000, sampling every 100th generation and giving diagnostics every 1000th generation. To test if the Markov Chain converged, the standard deviation of split frequencies was monitored to make sure it fell below 0.01 when comparing the two independent runs. The p output files were opened in TRACER (Baldwin et al. 1995) to check the run performed in

MRBAYES: confirming the converged chains and deciding the burnin. Next, the t output file was opened in TREEANNOTATOR v1.8.2 (Rambaut and Drummond 2011, available at: http://beast.bio.ed.ac.uk/treeannotator). TREEANNOTATOR was used to create a majority rule consensus tree using a burnin percentage of 10 Posterior probability was set to 0.9, and PP- values below were not shown. The resulting tree was visualized in FIGTREE v1.4.2 (Rambaut 2014, available at: http://tree.bio.ed.ac.uk/software/figtree/) and edited in ADOBE ILLUSTRATOR CS4.

PAUP* v4.0b10 (Swofford 2001) was used to perform a phylogenetic analysis, producing a most parsimonious tree based on the same NEXUS file as used in MRBAYES. The following settings were used: Heuristic search, 1000 replications saving 20 trees per replicate, tree bisection reconnection (TBR) as branch swapping and 1000 replications for the bootstrap analysis. The majority rule bootstrap consensus tree was visualized in FIGTREE, and bootstrap values from this tree were added to the Bayesian tree using ILLUSTRATOR CS4.

PCA analyses

PCA analyses were performed based on RAD-seq data using the VCF output file (containing 3246 SNPs for 83 individuals). PCA was performed in R using the ADEGENET package version 1.4.2 (Jombart 2008, Jombart and Ahmed 2011) with default parameters, without removing any outliers, and missing data was set to max 25 %. The data was plotted using the GGPLOT2 package (Wickham 2009).

Maps

Maps were made based on GPS coordinates sampled in the field (Appendix Table A3) using QGis-OSGeo4W-2.4.0-1 (QGIS Developmental Team, 2009. QGIS Geographic Information

System. Open Source Geospatial Foundation. http://qgis.osgeo.org), and modified in ADOBE ILLUSTRATOR CS4.

3 Results

3.1 Chromosome counting

Chromosome counts were done on inflorescences sampled from 12 Icelandic populations. Four populations (EIR, GIL, HAF, STK) had a chromosome number of 2n = 14 and eight populations (DJU, STR, DYR, HVA, ING, BAE, OLF and SUR) had a chromosome number of 2n = 12. Photos of nuclei were taken for nine of the populations (Fig.3). Both alpine populations, EIR and GIL, had 14 chromosomes. Among the coastal populations, two (STK and HAF) had 14 chromosomes, and the remaining eight had 12 chromosomes.

Figure 3: Map of Iceland with 15 sampled Cochlearia populations indicated (for further locality information, see Appendix Table A3). Inserted map in top left corner shows the distribution of Cochlearia in Iceland (map from Kristinsson 2010). Different symbols (squares or triangles) indicate chromosome number of the 12 populations for which chromosome numbers were counted. For nine of these populations pictures displaying nuclei with visible chromosomes are shown. Populations with unknown chromosome number are indicated by a circle. Populations are further colored according to geographical areas, which are referred to throughout the results and discussion.

3.2 Morphometry

There were significant differences in leaf traits among the 10 measured populations (Kruskal Wallis test, leaf surface area, p = 0.0031; leaf ratio: p = 0.0049; leaf base angle: p = 0.0003, Fig. 4 a, b and c). Dunn’s post hoc test (multiple comparisons) indicated that there was a significant difference in leaf surface area when comparing the alpine population EIR and the two coastal populations DYR (p = 0.03) and ING (p = 0.05). There was also a significant difference in leaf surface area when comparing the other alpine population GIL with DYR (p = 0.007) and ING (p = 0.01). There was further a significant difference in leaf ratio when comparing EIR with DYR (p = 0.02) and OLF (p = 0.05) and when comparing GIL with DYR (p = 0.01) and OLF (p = 0.03). Lastly, there was a significant difference in leaf base angle when comparing EIR with DYR (p = 0.01), OLF (p = 0.03) and ING (p = 0.02) and when comparing GIL with DYR (p = 0.004), OLF (p = 0.01) and ING (p = 0.04). Thus, the leaves of alpine populations were overall smaller in leaf surface area, ratio and angle than coastal populations, and significantly so in the cases mentioned above. For selected examples of leaf morphology, see Appendix Fig. A1. Mann Whitney test showed a significant difference between the alpine and coastal populations in leaf surface area (p = 0.0001, Fig. 5 a), leaf ratio (p = 0.0001, Fig. 5 e) and leaf base angle (p<0.0001, Fig. 5 i). Furthermore, there was a significant difference between the coastal and alpine populations when including only populations with chromosome number 2n = 14: Leaf surface area (p = 0.01, Fig. 5 b), leaf ratio (p = 0.001, Fig. 5 f) and leaf angle (p = 0.001, Fig. 5 j). Mann-Whitney test showed a significant difference between the 2n = 14 and 2n = 12 plants in leaf surface area (p = 0.0002, Fig. 5 c), leaf ratio (p = 0.0002, Fig. 5 g) and leaf angle (p = 0.003, Fig. 5 k). However, there was no significant difference between coastal populations with 2n = 14 and 2n = 12 when comparing leaf surface area (Fig. 5 d) or leaf base angle (Fig. 5 l), but there was a significant difference in leaf ratio (p = 0.03; Fig. 5 h).

a) Leaf surface area 12 10

6 Cm2 4 2 0 EIR GIL STK HAF DYR ING HVA DJU BAE OLF Population

b) Leaf ratio (W/L) 250% 200% 150% 100% 50% 0% EIR GIL STK HAF DYR ING HVA DJU BAE OLF Population

c) Leaf base angle 300 250 200 150 100 50 0 EIR GIL STK HAF DYR ING HVA DJU BAE OLF Population

Figure 4: Boxplots illustrating differences in leaf morphological traits among 10 Icelandic Cochlearia populations (names abbreviated according to Appendix Table A3): a) Leaf surface area, b) Leaf ratio (width/length) and c) Leaf base angle. The average of 5 leaves from an individual was calculated. Populations with 2n = 14 are colored grey and populations with 2n = 12 are white. N = 4 (except EIR with N = 3). For further explanation of the boxplot, see Appendix Fig. A2.

a) Leaf surface area e) Leaf ratio (W/L) i) Leaf base angle 12 250% 300 10 200% 250

8 200 150% 6 150 * Cm2 100% 4 * * 100 2 50% 50 0 0% 0 Coastal Alpine Coastal Alpine Coastal Alpine

b) Leaf surface area f) Leaf ratio (W/L) j) Leaf base angle 8 150% 250 200 6 100% * 150 * 4 * Cm2 50% 100 2 50 0 0% 0 Coastal Alpine Coastal Alpine Coastal Alpine 2n=14 2n=14 2n=14 2n=14 2n=14 2n=14

c) Leaf surface area g) Leaf ratio (W/L) k) Leaf base angle 12 250% 300 10 200% 250 * * * 200 8 150% 6 150

Cm2 100% 4 100 50% 2 50 0 0% 0 2n=12 2n=14 2n=12 2n=14 2n=12 2n=14

l) d) Leaf surface area h) Leaf ratio (W/L) Leaf base angle 12 250% 300 10 200% 250 200 8 150% * 150 6 100% Cm2 4 100 50% 2 50 0 0% 0 Coastal Coastal Coastal Coastal Coastal Coastal 2n=12 2n=14 2n=12 2n=14 2n=12 2n=14

Figure 5: Boxplots illustrating differences in leaf traits between 10 Icelandic Cochlearia populations (names abbreviated according to Appendix Table A3) grouped according to habitat (coastal in blue and alpine in beige) or chromosome number (2n = 12 in white and 2n = 14 in grey) or a combination of habitat and chromosome number: a-d) Leaf surface area, e-h) Leaf ratio (width/length) and i-l) Leaf base angle. Asterisk indicates significant differences between the two groups. For explanation of the boxplot, see Appendix Fig. A2.

The PCA analysis (Fig. 6) showed a separation of populations according to habitat along the first principal axis (PC1; explaining 75.4 % of the variation) and the second principal axis (PC2; explaining 15.4% of the total variation). As indicated in the PCA plot by the direction of arrows from origo, above mean and increased value of leaf surface area, leaf ratio and leaf base angle were correlated with PC1, with points close to the extremity of the arrow indicating higher values. The alpine populations (EIR and GIL) constituted a dense group at the left side of the plot, away from the direction of the arrows, indicating low values of leaf surface area, leaf ratio and leaf base angle. The coastal populations were more scattered, showing overall higher variation along both PC1 and PC2. Some individuals from populations OLF, ING and DYR had highest values along PC1, indicating high values of the three morphological traits.

Figure 6: Biplot resulting from the PCA analysis of leaf morphological traits (leaf surface area, leaf ratio and leaf base angle) from 10 Icelandic Cochlearia populations (names abbreviated according to Appendix Table A3). Each point represents the mean score from five of leaves from one individual plant. The direction of the arrows from origo indicate above mean and increased values for the morphological traits. Points close to the extremity of the arrow indicate higher values. Populations with 2n = 14 are illustrated as squares, and populations with 2n = 12 as triangles. N = 4 (except for EIR, N = 3).

3.3 RAD-sequencing

Sequencing of the paired-end RAD-seq library from 82 Cochlearia individuals/replicates yielded a total number of 348,745,226 sequence reads. After barcode sorting and filtering by the use of PROCESS_RADTAGS in STACKS, 196,579,422 forwards reads were retained.

Population structure analysis

When using STRUCTURE HARVESTER to select number of genetic clusters from the STRUCTURE analysis, K = 3 had the highest and K = 5 the second highest delta K value (Appendix Fig. A3). K = 5 had, however, a higher value than K = 3 in the likelihood of K graph (Appendix, Fig. A4). These results were checked and confirmed in CLUMPAK (not shown). Both K = 3 and K = 5 were visualized using DISTRUCT.

When three genetic clusters were selected (K = 3), the Icelandic populations were assigned to two of these clusters, the orange and the blue (Fig. 7). Coastal populations from southern Iceland (DYR, HJO, ING and SUR) assigned to the orange cluster together with two of the most southerly located populations along the eastern coast (DJU and HVA, Fig. 1). The alpine 2n = 14 populations (EIR and GIL) assigned to the blue cluster together with populations from Svalbard (HOP, TJU, LOM and FLA), except for one individual from GIL that was admixed between the blue and the orange cluster. The remaining populations (all coastal), showed varying degree of admixture between these two clusters. The coastal 2n = 14 populations (STK and HAF) showed a higher percentage assignment to the blue cluster than they did to the 2n = 12 populations (OLF, BAE, STR), and two populations of unknown chromosome number (LAT and HFN), and vice versa. Southwestern European populations were assigned to a cluster of their own (yellow). Two of the C. pyrenaica populations (PYR2 and PYR4; consisting of one individual each) showed, however, some minor admixture with the orange and blue clusters.

When five genetic clusters were selected (K = 5), the Icelandic populations showed further geographical clustering (Fig. 8). The large non-admixed orange cluster from the previous plot (K = 3) were here split into one cluster constituting the southern populations (blue) and one cluster constituting the eastern populations (pink). The two northeastern populations (HFN and STR) were now admixed between three clusters, assigning mainly to the eastern (pink) cluster, but additionally to the alpine/Svalbard (brown) cluster and to the southern (blue)

32 cluster. The coastal populations from western and northern Iceland were assigned mainly to the green cluster, which contained populations with different chromosome numbers (STK and HAF with 2n = 14; OLF and BAE with 2n = 12, and LAT with unknown chromosome number). The three latter populations displayed admixture with the southern (blue) cluster. The admixed individual in the alpine GIL population shared also genes with the southern populations. The southwestern European populations still constituted a cluster of their own (purple).

Figure 7: STRUCTURE analysis of 83 Cochlearia individuals, based on 1500 SNPs obtained from RAD-seq data. Each vertical bar represents an individual. Populations are separated by vertical black lines and names abbreviated according to Appendix Table A3 and A4. The number of colors depict the number of genetic clusters (K = 3).

Figure 8: STRUCTURE analysis of 83 Cochlearia individuals, based on 1500 SNPs obtained from RAD-seq data. Each vertical bar represents an individual. Populations are separated by vertical black lines, and names abbreviated according to Appendix Table A3 and A4. The number of colors represents the number of genetic clusters (K = 5). Populations are ordered according to geographical area, as depicted in the white boxes below.

Tree and network analysis

In the neighbor-joining network performed by SPLITSTREE, all individuals (except the outlier individual in the alpine GIL population) were grouped according to populations (Fig. 9), displaying the same geographical structure as was found in the Structure and PCA analyses.

There was a clear split separating southwestern European populations from the Svalbard and Icelandic populations. The Svalbard and Icelandic alpine populations were also separated from the Icelandic coastal populations by a clear split. A minor diagonal split further divided the eastern Icelandic populations from the western, southern and northern populations.

Figure 9: Neighbor-joining network performed in SPLITSTREE for 83 Cochlearia individuals based on 1500 SNPs obtained from RAD-seq data and using the uncorrected_P distance measure. Different symbols (squares or triangles) indicate chromosome number. Individuals with unknown chromosome number are indicated by a circle. Populations are further colored according to geographical areas, and names abbreviated according to Appendix Table A3 and A4.

Bayesian phylogeny

The topology of the Bayesian majority-rule consensus tree was consistent with the single most-parsimonious tree (length = 1423) that was found (Fig. 10, the most-parsimonious tree not shown). When rooted with the southwestern European population AST, the Icelandic alpine and Svalbard populations constituted a well-supported monophyletic group where the alpine populations (brown) were sister group to the Svalbard populations (orange), which again constituted a well-supported sister group to the coastal Icelandic populations. Within the Icelandic coastal populations, the eastern populations (pink) were sister group to a clade consisting of southern (light blue), northern (grey) and western (green) populations. Bootstrap values supporting the S-N-W-clade as monophyletic were, however, low (61), and further relationships within this clade were generally with low support.

Figure 10: Bayesian majority-rule consensus tree for 24 Cochlearia populations (names abbreviated according to Appendix Table A3 and A4) based on 2482 SNPs obtained from RAD-seq data. Posterior probability values are shown in black above branches. Bootstrap values from the parsimony bootstrap analysis are shown in grey below branches. Color coding of populations is as follows: Spanish = dark blue, French = purple, Svalbard = orange; Icelandic regions: alpine = brown, eastern = pink, southern = light blue, western = green, northern = grey.

PCA analysis

In the PCA analysis, PC1 explained 17.7 % of the total variation and separated first of all the Icelandic alpine and Svalbard populations from the Icelandic coastal and southwestern European populations (Fig. 11). PC2 explained 10.6 % of the variation and separated the Icelandic and Svalbard populations from the southwestern European populations. The variation explained along the two first axes thus correspond to the two major splits in the neighbor net (Fig. 9). Among the Icelandic coastal populations, populations from southern Iceland (colored bluish) grouped together at the left side of the plot. The two southeastern Icelandic populations (HVA and DJU, pinkish) grouped closely together, whereas the two northeastern populations (HFN and STR, purplish) were placed somewhat closer to the western populations (greenish), corresponding to the admixture patterns observed in the STRUCTURE analysis. Among the western populations, the two 2n = 14 populations (HAF and STK) grouped together (at the top of the plot), while OLF was placed closer to the northern population BAE (both 2n = 12). Except for the outlier individual from the GIL population, the Icelandic alpine populations constituted a dense group (brownish), which were separated from the Svalbard populations along PC2.

PC3, which explained 7.3 % of the variation further separated the Icelandic eastern populations from the remaining Icelandic populations (Fig. 12), corresponding to the minor split in the neighbor net. The two most southeastern populations, DJU and HVA grouped at low values along PC3, whereas the two northeastern populations, HFN and STR, had somewhat higher values along this axis. At the other end of PC3, the southwestern European populations had somewhat higher values than the remaining Icelandic populations. Among these populations, the southern Icelandic populations and the two 2n = 14 western populations, HAF and STK, displayed the highest values, whereas the alpine (and Svalbard) populations had intermediate values along this axis.

Figure 11: PCA of 83 Cochlearia individuals based on 3246 SNPs obtained fra RAD-seq data. Different symbols (squares or triangles) indicate chromosome number. Individuals with unknown chromosome number are indicated by a circle. Populations are further colored according to geographical areas, and names abbreviated according to Appendix Table A3 and A4. Polygons indicate larger geographic regions: southwestern Europe, Iceland and Svalbard.

Figure 12: PCA of 83 Cochlearia individuals (Appenddix Table A3), based on 3246 SNPs obtained from RAD- seq data. Different symbols (squares or triangles) indicate chromosome number. Populations with unknown chromosome number are indicated by a circle. Populations are further colored according to geographical areas, and names abbreviated according to Appendix Table A3 and A4. Polygons indicate larger geographic regions: southwestern Europe, Iceland and Svalbard.

4 Discussion

4.1 Do Icelandic plants with different chromosome number or ecology constitute different genetic clusters?

Most of the sampled Cochlearia populations in this study turned out to have a chromosome number of 2n = 12. This chromosome number, which has previously been reported mainly from a few populations along the southern coast of Iceland (Gill 1971a, Nordal and Laane 1990), Fig.13; Appendix, Table A1), thus seems to be much more common in Iceland than previously thought. Only two of the coastal populations sampled as part of this study have a chromosome number of 2n = 14, and both are located in southwestern Iceland. Previous reports of coastal 2n = 14 plants, have been from the northwestern and southwestern part of Iceland. The two alpine populations both have 2n = 14, corresponding to a previous count reported for one of these, the EIR population (Nordal and Laane 1990, Koch et al. 1996).

In western Iceland, population from HAF (2n = 14) was sampled close to a site (Grindavíkurbjarg) where 2n = 12 plants have previously been reported (Löve 1975), while the population from OLF (2n = 12) was sampled close to a site (Stapi) where 2n = 14 plants have previously been reported (Gill 1971a). This indicates that chromosome number may vary between geographically close sites, and possibly even within a site. In the only population of this study from which more than one individual were counted (BAE), all four individuals had a chromosome number of 2n = 12.

Based on analyses of the RAD-seq data, there is no clear genetic separation between Cochlearia plants with different chromosome numbers. The 2n = 14 coastal populations from STK and HAF are, thus, part of genetic clusters that are more similar to coastal 2n = 12 plants than they are to alpine 2n = 14 plants. Among the coastal populations the genetic variation is clearly geographically structured, with geographically adjacent populations being genetically more similar disregarding chromosome number. The coastal 2n = 12 populations from southern and southeastern part of Iceland form distinct genetic clusters. Additionally, in sites where admixture between both chromosome numbers are found (BAE in the north; HFN and STR in the northeast; OLF and LAT in the west) there is apparent genetic admixture between coastal populations. To find admixture among plants with different chromosome numbers is not surprising, as Cochlearia is known to hybridize across ploidal levels with no or slightly

39 reduced fertility in F1 and F2 generations (Saunte 1955, Gill 1973, Elkington 1984, Nordal et al. 1986, Nordal and Laane 1990, Nordal and Stabbetorp 1990, Nordal and Laane 1996, Pegtel 1999). Gill (1971a) performed successful crosses between plants with 12 and 14 chromosomes. He did, however, not cross Icelandic plants of different chromosome numbers as his cultivated Icelandic 2n = 12 plants died before crosses were made (Gill 1971a).

In the results from the STRUCTURE analysis, alpine 2n = 14 plants show no genetic admixture with, or influence from, coastal Icelandic populations (except for one individual in the GIL population). The lack of ongoing gene flow between alpine and coastal populations is

Figure 13: Map with new and previously published chromosome numbers of Cochlearia populations in Iceland (see Appendix, Table A1, A3). Small map indicate distribution of Cochlearia in Iceland (map from Kristinsson 2010). Different symbols (squares or triangles) indicate chromosome number of populations for which these have been counted. Olsen (2015) refers to the current study.

40 possibly a result of the topography where mountains may function as barriers, limiting the contact between plants in the two habitats to infrequent long distance dispersal events. Plants from the two alpine populations are genetically similar, which can be a result of small population size (Cieślak et al. 2007) and self-fertilization (Nordal and Laane 1990). Additionally, little genetic variation between the alpine populations might indicate that these populations are young and recently separated. To summarize, rather than being distinguished according to chromosome number, molecular data sort the the Icelandic Cochlearia plants according to ecology, i.e. whether they grow along the coast in beach cliffs or in late snowbeds in the alpine inland regions.

Alpine and coastal habitat differs in several ways. The harsh conditions in alpine habitats may be a challenge to the plants, particularly since Cochlearia has no dormancy phase in the winter. Accordingly, vegetative rosettes must endure extreme temperatures and wind, as well as long lasting snow cover (Gill 2008) and short growing season (Nordal and Laane 1990). Coastal plants, on the other hand, must adapt to, and withstand high salt concentrations and coastal waves (Pegtel 1999). Whereas alpine plants delay germination to after snow melting, coastal plants have seeds that must tolerate high salt concentrations (Pegtel 1999) and that germinate quickly after seed set before they are swept away into the sea water (Pegtel 1999, Gill 2008). Differentiation according to coastal versus alpine habitat is well studied in other plants (Turesson 1922, Lowry et al. 2008, Lowry 2012, Moore et al. 2014). Within Cochlearia, a similar disjunct coastal-alpine distribution pattern is seen in the ecotypically differentiated C. officinalis in Norway (Nordal and Laane 1996, Brandrud 2014). The coastal C. officinalis populations are genetically similar, displaying high amounts of gene flow over large geographical distances, while the inland spring ecotype has more limited dispersal, a patchy distribution and genetically more distinct populations (Brandrud 2014).

In support of the results from molecular analyses, there are also morphological differences between the Icelandic alpine and coastal plants in the field and the phytotron. Differences observed in the field were especially evident with regard to overall plant size, leaf size and degree of succulence (pers. obs.). The differences in size were less pronounced between plants that were cultivated under the same conditions in the phytotron, but differences in leaf shape and size between alpine and coastal populations were still retained both in pairwise population comparisons (Dunn’s test) and when all populations were grouped according to habitat (Mann-Whitney test). The observed morphological traits correspond to what (Nordal and Laane 1990) reported: Alpine plants have small lanceolate leaves and coastal plants have

41 large cordate/reniform leaves. The fact that differences persist when plants are grown under the same conditions indicate underlying genetic factors (Nordal and Laane 1990). Additionally, the overall boosted growth in the phytotron indicate that environmental factors may limit the size of wild populations (Nordal and Stabbetorp 1990, Pegtel 1999, Gill 2008).

The underlying genetic mechanisms of the differences observed in leaf morphology are not identified in this study. The smaller leaves of alpine plants might be a result of genetic adaptation to the more severe habitat and shorter growing season that they are exposed to. However, considering the fact that the morphological comparisons are based on material partly sampled as live plants in the field (the case for all alpine plants) and partly germinated from seeds, some of the morphological variation might be remnants of plastic responses to the habitat in which the live plants were sampled (Nordal et al. 1986, Nordal and Laane 1990, Nordal and Stabbetorp 1990). Thus, it cannot be ruled out that some of the observed variation might be a result of plasticity and/or epigenetics. Epigenetic variation can be especially important for populations with low genetic diversity as a source of phenotypic variation (Kalisz and Purugganan 2004, Richards 2008, Yi et al. 2010, Medrano et al. 2014). Pinpointing sources of phenotypic variation would demand a solid and well-replicated experimental design, controlling for ecological interactions and epigenetic variation (Bossdorf et al. 2008).

When comparing the leaf morphology of the 2n = 12 coastal plants to the 2n = 14 coastal plants (as two groups), no significant differences in leaf area or leaf base angle were found, but coastal 2n = 14 plants had significantly narrower leaves than the 2n = 12 plants. However, no significant differences in leaf shape or form were seen in pairwise comparisons of the coastal populations, which corresponds to the results by Nordal and Laane (1990) who found no significant morphological differences between coastal populations of the two different chromosome numbers. It should also be noted that leaf morphology is known to be a highly variable and uncertain comparative trait in Cochlearia. Petiole length, and length and width of lamina are not optimal traits for taxonomical delimitation (Pegtel 1999). Leaf base angle, flower and fruit and seed characteristics are less biased by environmental factors and are considered as more reliable traits that can be used taxonomically to distinguish species (Nordal and Laane 1990, Nordal and Stabbetorp 1990, Koch et al. 1996, Pegtel 1999). Petal length and seed size have, thus, been used to morphologically differentiate between the alpine and coastal plants in Iceland (Nordal and Laane 1990). In this study, flower traits were not

42 measured as too few individuals within each population flowered in the field or in the phytotron.

In conclusion, there is no indication that Icelandic Cochlearia plants form genetic clusters according to chromosome number. Rather both molecular and morphological results indicate that Cochlearia populations on Iceland can be divided into two groups corresponding to ecology (coastal and alpine).

4.2 How is the evolutionary relationship between the Icelandic plants and other diploid Cochlearia species?

Icelandic alpine Cochlearia plants (2n = 14) are genetically, ecologically and morphologically separated from the geographically relatively close coastal plants (2n = 12, 14). On the other hand, the alpine plants consistently group with C. groenlandica (2n = 14) from Svalbard, despite being separated by 1950 km Arctic Ocean. This might be due to lineage separation. Individuals belonging to the same species are commonly closely related despite large geographic separation, whereas individuals belonging to two different species would be different even when they are closely located (Duminil and Di Michele 2009, Medrano et al. 2014).

Svalbard plants were not included in the morphological analysis in this study, but previous analyses show that the tundra plants in Svalbard are morphologically very similar to the Icelandic alpine plants (Nordal and Laane 1990). The late snow bed habitats where the Icelandic alpine plants are found, have much in common with the habitat (arctic tundra) in which the arctic Cochlearia plants are growing in Svalbard. Because of the high latitude, the environmental conditions on Svalbard are severe, even during the summer. Here plants are exposed to stress, such as low nutrient and water availability, short growing season, unstable weather conditions and permafrost (Zmudczyńska-Skarbek et al. 2013).

The observed genetic, morphological, ecological and cytological similarity between the Icelandic alpine and the Svalbard populations suggests that they share a common evolutionary history. This study cannot determine whether the alpine plants in Iceland initially dispersed from Svalbard, or some other part of the Arctic (this would require additional samples from other parts of the Arctic, e.g. Greenland). The disjunct distribution might possibly be explained as a result of recent separation through long distance dispersal. Cochlearia seeds have no specialized dispersal adaptations and probably spread mainly over short distances 43

(Quinn et al. 1994), but Nordal et al. (1986) suggested that seeds can be spread by sea currents or that they may be transported by birds. Furthermore, the dispersal of seeds to Iceland in general has been heavily discussed in the tabula rasa versus glacial survival debate, which influenced the study of North Atlantic biogeography for several decades (Löve and Löve 1963, Nordal 1987). Supporters of the tabula rasa theory have suggested dispersal of diaspores with or without adaptations to long dispersal (such as hairs and wings), to occur with strong winds carrying diaspores across sea-ice in winter (Brochmann and Steen 1999, Ægisdóttir and Þórhallsdóttir 2004), as ice rafted debris (Buckland and Dugmore 1991), or with aerial transport, ocean currents and migrating birds (Nordal 1987, Johansen and Hytteborn 2001, Alsos et al. 2007). Even though one or more such long distance dispersals of Cochlearia between Iceland and the arctic adjacent regions (Greenland and Svalbard) seem reasonable, it seems a less likely mechanism for sustained gene flow between Icelandic and arctic populations.

Coastal 2n = 12 plants in Iceland have previously been referred to C. pyrenaica (Löve 1975). However, a close relationship between the Icelandic 2n = 12 plants and the southwestern European diploid Cochlearia (C. aestuaria and C. pyrenaica) is not supported in this study, as these two groups are genetically clearly separated in all analyses. Plants within the southwestern European cluster group together according to country of origin rather than species. Cires et al. (2011) also observed a geographically structured genetic variation among populations of western European C. pyrenaica, but further analyses including a much larger sampling are needed to investigate the evolutionary history of the European mainland diploid Cochlearia taxa.

4.3 How can the results from this study be guiding for taxonomical decisions in Flora Nordica?

To answer this question, one needs to consider whether the alpine and coastal plants in Iceland constitute different species. This is highly dependent on the species concept used. As an example, the classic biological species concept of Mayr (1942) requires internal reproductive barriers to recognize a species as “good”. Hence, Mayr would probably disapprove of most existing Cochlearia species, as they are known to hybridize freely across ploidal levels (Gill 1971a). However, according to De Queiroz’s unified species concept, the clear genetic, morphological and ecological separation between Icelandic alpine and coastal

44 plants observed in this study is sufficient to hypothesize that we are dealing with two different species (De Queiroz 2005, Medrano et al. 2014). The degree of separation, however, is not clear. Previous studies have shown almost no reproductive barriers between Icelandic 2n = 14 plants and other Cochlearia taxa with similar or dissimilar chromosome number (Gill 1971a). This might indicate that Icelandic plants of different habitats or chromosome numbers are probably not reproductively isolated yet. The molecular analyses in this study show genetic similarities and probably introgression between coastal plants independent of chromosome number. Determining potential internal reproductive barriers between Icelandic alpine and coastal plants demands experimental crossings. If they are not yet reproductively isolated, the geographic isolation of coastal and alpine populations can certainly stimulate further population divergence and possible species formation (Rieseberg et al. 2004). Despite the lack of internal reproductive barriers, factors such as habitat differentiation, flowering and pollinator isolation, as well as short seed dispersal can function as external barriers of gene flow (Clausen et al. 1947, Linhart and Grant 1996, Buerkle et al. 2000, Eckstein et al. 2006).

The morphometric analyses were limited in several aspects and to be able to make thorough taxonomic recommendations, it would be desirable to include more reliable flower and fruit traits and to do morphological comparison on material from the southwestern European and arctic diploids (Greenland, Siberia and North America). In both morphological and molecular studies, a more balanced population sample (with more 2n = 14 populations from both habitats), more samples per population and comparison with the tetraploid C. officinalis would be of great interest.

Based on the results of this study some preliminary recommendations can, however, be made for the publication of Brassicaceae for Flora Nordica (Bjorå and Nordal in prep.). From the discussion above it seems clear that Cochlearia in Iceland should not be separated into different taxa according to chromosome number. Certainly, there is no support for the suggestion made by Löve (1983) to divide Icelandic plants into two genera (Cochlearia and Cochleariopsis), based on different basic chromosome numbers, x = 6 and x = 7. Instead, both molecular and morphological data suggest that Icelandic Cochlearia populations might be divided corresponding to ecology (coastal and alpine). Furthermore, alpine populations are morphologically and genetically more similar to populations of C. groenlandica in Svalbard, than to coastal populations in Iceland. For the Icelandic 2n = 14 plants, several epithets have been used (Appendix, Table A2). In the Flora of North America, Al-Shehbaz and Koch (1993), reduced C. arctica, C. oblongifolia and C. fenestrata to one species, namely C.

45 groenlandica. The reference to the other species epithets is accordingly not relevant. Only C. groenlandica is an accurate name for the Icelandic alpine plants.

No separation between coastal 2n = 12 and 2n = 14 plants was found in this study, and morphologically they cannot be separated Thus, it is obvious that the coastal 2n = 12 and 2n =14 have to be accepted in the same taxon. Their close relation is obviously due to initial autotetrasomy (Gill 1971a), with possibly subsequent introgression. The Icelandic 2n = 12 coastal plants have previously been referred to C. pyrenaica (Löve 1975). The molecular analyses in this study, however, indicate that Icelandic coastal plants are genetically separated from southwestern European C. aestuaria and C. pyrenaica. Pobedimova (1970) referred northwestern Icelandic plants to C. anglica (2n = 48), without taking chromosome number into consideration. In a study on estuary populations along the western coast of Europe, C. aestuaria was recognized in south Europe (2n = 12), C. officinalis ssp. norvegica Nordal and Stabbetorp (2n =24) in fjord bottoms along the Norwegian coast and C. anglica in northwestern Europe (2n = 48) (Nordal and Laane 1996). There is no evidence that C. anglica occurs in Iceland.

Thus, two species epithets remain possible for the Icelandic coastal plants: Referring them either to the tetraploid C. officinalis, as consistently done by (Kristinsson 1986, 2010); or to the (probably diploid) C. islandica described by Pobedimova (1969) in northeastern Iceland. It is possible, that the coastal plants (2n = 12, 14) should be referred to a subspecies of C. officinalis (2n = 24), despite the different ploidal level. The relation between C. officinalis, and Icelandic coastal plants is potentially due to autopolyploidy (2n = 12 to 2n = 24, Gill 1973). There are quite a few examples were autopolyploidal populations are grouped with their parental species (e.g. Parnassia palustris: Borgen and Hultgård 2003, Leucanthemum vulgare and Campanula rotundifolia: Lid and Lid 2005) but see Soltis et al. (2007). Material from C. officinalis (in Scandinavia) was not included in the molecular study, and the relationship between Icelandic coastal plants (2n = 12, 14) and C. officinalis cannot be addressed in this thesis. If reproductive compatibility is considered, the Icelandic coastal plants might be justified as a separate taxon. In such a case, the epithet islandica might be considered.

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Appendix

Table A1: Previously published chromosome numbers of Cochlearia in Iceland.

Taxon used by Chromosome Locality Reference author number C. groenlandica L. 14 Naustvik, Heykjatjordur (Reykjarfirdi) (Saunte, 1955) C. groenlandica L. 14 Naustvik, Arnesstrond (Saunte 1955) C. groenlandica L. 14 Unknown (Löve and Löve 1956) C. groenlandica L. 14 Stokkseyri, Arnessýsla (Gill 1971a) C. groenlandica L. 14 Stapi, Snafellnes (Gill, 1971a) Cochlearia 12 Ingolfshöfdi, Austur-Skaftafellssvala (Gill, 1971a) C. pyrenaica DC. 12 Grindavikurbjarg (close to Grindavik), Gullbrusýsla (old sysla) (Löve 1975) C. groenlandica L. 12 Ingòlfshöfði, Austre-Skaftafellssýsla (Nordal and Laane 1990) C. groenlandica L. 12 Hnuta, S of Djupivogur (Nordal and Laane, 1990) C. groenlandica L. 14 Hnefill, N of Eiriksstadir (Nordal and Laane, 1990) C. groenlandica L. 14 Blönduos, Austur-Hunavatnssysla (Nordal and Laane, 1990) C. groenlandica L. 12 Unknown (Koch et al. 1996, 1998) C. groenlandica L. 14 Stokkseyri, Arnessýsla (Koch et al. 1996, 1998) C. groenlandica L. 14 Unknown (Koch et al. 1996, 1998) C. groenlandica L. 14 Unknown (Koch et al. 1996, 1998)

Table A2: A survey of names (epithets), used for Icelandic Cochlearia through times. Information based on Bjorå and Nordal (in prep.)

Species epithet Author Year of publication Origin of type Ploidal level officinalis Linneaus 1753 Scandinavia Tetraploid (2n = 24) groenlandica Linneaus 1753 Greenland Diploid (2n = 14) anglica Linneaus 1759 Scandinavia Octoploid (2n = 48) fenestrata R. Brown 1819 N America Diploid (2n = 14) arctica Schlectendal 1821 Siberia Diploid (2n = 14) oblongifolia De Candolle 1821 N America Diploid (2n = 14) pyrenaica De Candolle 1821 S Europe Diploid (2n = 12) islandica Pobedimova 1968 Iceland Diploid (2n = 12 or 14)

Table A3: Collection data of Cochlearia in Iceland. RAD-seq indicate the number of individuals included in the RAD-seq library. Bold numbers indicate replicated individuals within the population. 2n indicate the number of chromosomes counted in this study and number in brackets gives number of counted individuals. Collectors: IN: I. Nordal, AKB: A. K. Brysting, LNO: L. N. Olsen, PW: P. Wasowicz.

Name Locality Ecotype Longitude DD Latitude DD Collector Collection date RAD-seq 2n Voucher

STO Stokkseyri, Arnessýsla Beach cliff -21.07519444 63.83858333 IN, AKB & LNO 11.08.2014 6 14 (#1) L.N. Olsen LO.14-1 (Herb, O)

DYR Dyrhòleya, Vestar-Skaftafelssýsla Beach cliff -19.13027778 63.40191667 IN, AKB & LNO 12.08.2014 5 12 (#1) L.N. Olsen LO.14-2 (Herb, O)

HJO Hjörleifshöfði, Vestar-Skaftafelssýsla Beach cliff -18.76527778 63.42030556 IN, AKB & LNO 12.08.2014 4 L.N. Olsen LO.14-3 (Herb, O)

ING Ingòlfshöfði, Austre-Skaftafellssýsla Beach cliff -16.63777778 63.80400000 IN, AKB & LNO 13.08.2014 5 12 (#1) L.N. Olsen LO.14-4 (Herb, O)

HVA Hvalnes, Austre-Skaftafellssýsla Beach cliff -14.54455556 64.40327778 IN, AKB & LNO 13.08.2014 5 12 (#1) L.N. Olsen LO.14-5 (Herb, O)

DJU Djùpivogur, Suður-Mùlasýsla Beach cliff -14.27983333 64.65666667 IN, AKB & LNO 13.08.2014 5 12 (#1) L.N. Olsen LO.14-6 (Herb, O)

EIR Eirìkstaðir, Norður-Mùlasýsla Tundra -15.47175000 65.14344444 IN, AKB & LNO 14.08.2014 4 14 (#1) L.N. Olsen LO.14-7 (Herb, O)

STR Strandhòfnur, Norður-Mùlasýsla Beach cliff -14.64700000 65.90400000 IN, AKB & LNO 14.08.2014 6 12 (#1) L.N. Olsen LO.14-8 (Herb, O)

GIL Gilsbakkifjall, Skagafjarðarssýsla Tundra -18.96622222 65.37027778 IN, AKB & LNO 15.08.2014 4 14 (#1) L.N. Olsen LO.14-9 (Herb, O)

Bær á Höfðaströnd, BAE Beach cliff -19.43600000 65.93000000 IN, AKB & LNO 15.08.2014 5 12 (#4) L.N. Olsen LO.14-10 (Herb, O) Skagafjarðarssýsla Òlafsvikurenni, Snæfells- og OLA Beach cliff -23.76588889 64.90272222 IN, AKB & LNO 16.08.2014 5 12 (#1) L.N. Olsen LO.14-11 (Herb, O) Hnappadalssýsla

HAF Hafnir, Gullbringusýsla Beach cliff -22.68669444 63.93591667 IN, AKB & LNO 17.08.2014 5 14 (#1) L.N. Olsen LO.14-12 (Herb, O)

SUR Surtsey, Vestmannaeyjar Beach cliff -20.59340000 63.30010000 PW 2014 3 12 (#1) P. Wasowicz 06160714A (Herb, O)

HFN Hafnarhólmi, Norður-Múlasýsla -13.75475000 65.54207000 PW 2014 3

LAT Látrabjarg, Vestur-Barðastrandarsýsla -24.53071000 65.50150000 PW 2014 3

Table A4: Collection data of Cochlearia species from populations in Spain, France and on Svalbard. 2n indicate chromosome numbers known from a previous master study (Brandrud 2014). Chromosome numbers in brackets are not confirmed, but assumed since Cochlearia plants reported on Svalbard have been 2n = 14 (Nordal and Laane 1990). P. B. Eidesen, AL: A. Launes, JH: J. Homet , JAFP: J. A. F. Prieto, AKB: A. K. Brysting.

Name 2n Species Country Locality Ecotype Longitude DD Latitude DD Collector Collection date Collection ID RAD-seq

FLA (14) C. groenlandica L. Norway Svalbard, Flatøyrdalen, Widjefjorden 17.72845840 79.59123031 PBE 24.07.2010 CG.10 2

Hillside/ HOP (14) C. groenlandica L. Norway Svalbard, Hopen 25.45779300 76.68975750 AL 30.07.2011 Coch.gro2 4 Beach cliff TJU (14) C.groenlandica L. Norway Svalbard, Edgeøya, Tjuvfjorden Beach 9.522053843 77.50555088 PBE 04.07.2013 Tjuvfjorden_3 1

LOM (14) C.groenlandica L. Norway Svalbard, Ny-Friesland, Lomfjord Beach 17.72845840 79.59123031 PBE 06.07.2013 Lomfjord_1 1

C. aestuaria AES1 12 Spain Aestuarias, Ribadesella Spring -4.93583000 43.46222000 AKB 04.07.2013 AB13-2 5 (Lloyd) Heywood Asturias, between Villar de Vildas PYR1 12 C. pyrenaica DC. Spain Estuary -5.66472000 43.07861000 JH & JAFP pyrenaica25.1 1 and La Pornacal Asturias, Ascent to Puerto de 1 PYR2 12 C.pyrenaica DC. Spain Spring -5.76666000 43.03333000 JH & JAFP pyrenaica5.1 Somiedo Haute-Garonne, between Oô and Lac PYR3 12 C. pyrenaica DC. France Spring 0.500000000 42.76666000 JH & JAFP pyrenaica50.1 1 d'Oô Haute-Garonne, between Oô and Lac PYR3 12 C. pyrenaica DC. France Spring 0.500000000 42.76666000 JH & JAFP pyrenaica55.1 1 d'Oô Hautes-Pyrénées, Col du Tourmalet, PYR42 12 C. pyrenaica DC. France Spring 0.116660000 42.90000000 JH & JAFP pyrenaica77.1 1 west face

1 Representative vouchers were deposited at the Herbarium FCO (FCO numbers: 32169–32173) 2 Material included in Cires et al. 2011 54

Table A5: 10 x citrate buffer solution. The buffer was diluted with distilled water to 1 x working solution and used for preparing inflorescences for chromosome counts.

10 x citrate buffer* 40 ml 100 mM citric acid 60 ml 100 mM trisodium citrate *Adjusted to pH 4.8 and stored at 4 °C.

Table A6: Pectolytic enzyme mixture used for preparing inflorescences for chromosome counts. The 1% enzyme stock solutions were prepared in 1 x citrate buffer.

Pectolytic enzyme mixture

1 % pectolyase (Aspergillus japonicus) 3 ml stock solution 1 % cellulase (Aspergillus niger) stock 3 ml solution 1 % cytohelicase (Helix pomatia) stock 3 ml solution 1 x citrate buffer 1 ml Total volume 10 ml

Table A7: DAPI staining buffer solution applied to chromosome preparations before visualizing nuclei in an epifluorescence microscope.

DAPI staining buffer

2.5 µg/ml DAPI 10 µl

0.01 % Tween-20 1 µl

5 % DMSO 50 µl

1 % PBS, pH 7.5 100 µl

Milli-Q H20 839 µl Total volume 1 ml

Table A8: Unique barcode combinations of barcode 1 (P1) and barcode 2 (P2) was used to lable individual samples in the RAD-seq library. Barcodes were used in subsequent analyses to recognize individuals. For explanation of names, see table A3.

Name Barcode1 Barcode2 Name Barcode1 Barcode2

BAE-10 AGTCAC GACT HOP-3 ACCTGA GACT

BAE-4 ACCTGA TCGG HOP-4 TCGATA ACTT

BAE-5 GATGCG TGAC HOP-5 CACGGT CAAGT

BAE-6 ACCTGA TGAC HVA-2 CACGGT CTGA

BAE-9 CGTTAG CTGA HVA-3 AGTCAC CTGA

DJU-1 TCGATA TCGG HVA-4 ACCTGA CTGA

DJU-10 TTACTC CTGA HVA-5 ACCTGA ACTT

DJU-2 GCACTA ACTT HVA-9 CACGGT TCGG

DJU-4 ATGGAC CTGA ING-2 CACGGT TGAC

DJU-6 TCGATA CTGA ING-3 GATGCG CTGA

DYR-1 TGCACT GACT ING-5 CACGGT ACTT

DYR-10 TCGATA CAAGT ING-7 GTATCG GACT

DYR-2 GATGCG TCGG ING-8 ATGGAC ACTT

DYR-5 CACGGT GACT LAT-B AGTCAC TCGG

DYR-7 GCACTA GACT LAT-D TTACTC ATCCGT

EIR-1 CGTTAG TCGG LAT-E CAGTCT ATCCGT

EIR-2 ATGGAC ATCCGT LOM-1 TCGATA GACT

EIR-3 TTACTC TCGG OLF-2 CAGTCT CTGA

EIR-6 CGTTAG TGAC OLF-4 GCACTA CTGA

FLA-1 GCACTA ATCCGT OLF-7 CAGTCT TGAC

FLA-2 GCACTA TCGG OLF-9 TGCACT CTGA

OLF-9- GIL-3 CACGGT ATCCGT CAGTCT ACTT replikat GIL-4 GCACTA TGAC STK-2 AGTCAC ACTT

STK-2- GIL-7 GTATCG CAAGT ATGGAC GACT replikat GIL-9 TGCACT TCGG STK-3 TTACTC TGAC

HAF-1 CAGTCT TCGG STK-6 GATGCG ACTT

HAF-2 TTACTC ACTT STK-8 GATGCG GACT

HAF-6 TGCACT TGAC STK-9 CGTTAG ACTT

HAF-7 GATGCG ATCCGT STR-1 AGTCAC TGAC

HAF-8 ATGGAC TGAC STR-10 TCGATA TGAC

HFN-A GTATCG ATCCGT STR-5 TGCACT ACTT

HFN-B TCGATA ATCCGT STR-6 GTATCG TCGG

HFN-C CGTTAG ATCCGT STR-9 ACCTGA ATCCGT

STR-9- HJO-5 ATGGAC TCGG AGTCAC ATCCGT replikat HJO-3 GTATCG ACTT SUR-B AGTCAC CAAGT

HJO-4 TTACTC GACT SUR-D CGTTAG GACT

HJO-5 TGCACT ATCCGT SUR-E GTATCG CTGA

HOP-1 GTATCG TGAC TJU-3 CAGTCT GACT

Table A9: Settings applied when running POPULATIONS to filter the processed reads in STACKS. No. SNPs: Number of SNPs present after filters was applied in the different output files produced. –r: minimum percentage of individuals in a population required to process a locus for that population; -p: minimum number of populations in which a locus must be present to process a locus; –write_single_snp restricts data analysis to only the first SNP per locus. Total number of individuals: 83. Total number of populations: 24.

POPULATION settings in STACKS --write_single_snp -r -p Output file No. SNPs yes 0.8 18 phylip 2482 yes 0.8 70 phylip 1500 yes 0.8 70 structure 1500 yes 0.75 18 vcf 3246

Figure A1: A selection of leaf variation from 10 populations represented by one individual each: The plant displaying the largest leaves within a population was selected, and five leaves were sampled per individual. For explanation of names, see table A3. (s) depict leaves from plants grown from seeds, (l) depict leaves from plants brought from the field.

Figure A2: Box plot explanation.

Figure A3: Delta K values as calculated in STRUCTURE HARVESTER, for the STRUCTURE run (K = 1 to K = 10) for 83 Cochlearia individuals based on 2482 SNPs obtained from RAD-seq data.

Figure A4: Likelihood of K values as calculated in STRUCTURE HARVESTER, for the STRUCTURE run (K = 1 to K = 10) for 83 Cochlearia individuals based on 2482 SNPs obtained from RAD-seq data.