Contrasting demographic histories of two species in ...

Contrasting demographic histories of two species in the lichen-forming fungal genus Xanthomendoza (Teloschistaceae, Ascomycota) Author(s): Steven D. Leavitt , H. Thorsten Lumbsch , and Larry L. St. Clair Source: The Bryologist, 116(4):337-349. 2013. Published By: The American Bryological and Lichenological Society, Inc. DOI: http://dx.doi.org/10.1639/0007-2745-116.4.337 URL: http://www.bioone.org/doi/full/10.1639/0007-2745-116.4.337

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Contrasting demographic histories of two species in the lichen-forming fungal genus Xanthomendoza (Teloschistaceae, Ascomycota) Steven D. Leavitt1,2,3,4, H. Thorsten Lumbsch3 and Larry L. St. Clair4 2

Committee on Evolutionary Biology, University of Chicago, 1025 E. 57th Street, Chicago, IL 60637, U.S.A.; 3 Science & Education, The Field Museum, 1400 S. Lake Shore Drive, Chicago, IL 60605, U.S.A.; 4 Department of Biology and M. L. Bean Life Science Museum, Brigham Young University, Provo, UT 84602, U.S.A.

ABSTRACT. While the distribution and ranges of arctic plants were greatly affected by the advance and retreat of ice sheets, the impact of glacial and interglacial cycles on lichenized fungi remains largely unexplored. In this study we examine the impact of Pleistocene climatic changes on two closely related Xanthomendoza (Teloschistaceae, Ascomycota) species with distinct distribution patterns and reproductive strategies. We selected X. borealis, which occurs in polar regions of both hemispheres, and the corticolous X. montana, which is restricted to montane shrublands in western North America. We analyzed the complete nuclear ribosomal internal transcribed spacer region (ITS) to confirm the monophyly and relative ages of X. borealis and X. montana. We estimated molecular diversity and population demographics statistics, mismatch distributions, and Bayesian skyline plots for both species. Our data indicate that X. montana experienced a Late Pleistocene population expansion. We suggest that major shifts in vegetation types as a result of Pleistocene climate change had a substantial impact on distribution patterns and the demographic history of X. montana. In contrast, results from this study indicate that the demographic history of X. borealis is consistent with long-term stability, although low genetic variability in the ITS marker for X. borealis limits overall confidence in this inference. We propose that X. borealis has been able to maintain a stable population size across climatic shifts, likely through effective dispersal to suitable habitats and suggests that climatic conditions during Pleistocene glacial cycles were not inherently unfavorable or restrictive for some high altitude/latitude lichen-forming fungal species. Investigating mating systems for these two Xanthomendoza species may provide important insights about the factors affecting population demographics and reproduction in lichen-forming fungi in general. KEYWORDS. Bayesian skyline plot, climate change, mismatch distribution, North America, polar, refugia, shrublands.

¤ Distributional ranges of many species have been dramatically influenced by cyclical climatic fluctuations throughout the Pleistocene (Abbott et al. 2000; Harpending et al. 1998; Knowles 2000; Moyle et al. 2009). During glacial cycles, the survival of many species found at high altitudes and/or latitudes depended on migration to lower elevations or latitudes ahead of advancing ice sheets, and surviving in glacial refugia (Abbott et al. 2000; Anderson et al. 2010; Frenzel & Troll 1952; Provan & Bennett 2008; Stewart et al. 2010). In some cases, species may have persisted 1

Corresponding author’s e-mail: [email protected] DOI: 10.1639/0007-2745-116.4.337

The Bryologist 116(4), pp. 337–349 Published online: November 7, 2013 Copyright E2013 by The American Bryological and Lichenological Society, Inc.

¤

¤ in situ during glacial periods in so-called nunataks (e.g., Jørgensen et al. 2012; Scho¨nswetter et al. 2005) or in peripheral refugia (e.g., Holderegger & ThielEgenter 2009; Scho¨nswetter et al. 2004), only to recolonize suitable habitats at higher altitudes and latitudes during interglacial periods. The basic Expansion–Contraction (EC) model of Provan & Bennett (2008) provides a valuable framework for testing the demography of species throughout glacial and interglacial cycles. Major climatic changes are predicted to occur worldwide and because polar ecosystems are particularly vulnerable they are predicted to be subject to substantial changes (Bitz et al. 2012; Post et al. 2009). A 0007-2745/13/$1.45/0

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Figure 1. Geographic distribution of Xanthomendoza borealis and X. montana. Filled triangles represent the global distribution of X. borealis based on specimens verified by Lindblom & Søchting (2008); while open circles represent the global distribution of X. montana based on data available from the Consortium of North American Lichen Herbaria (http://lichenportal.org/).

better understanding and documentation of the past response of species to major climate shifts, such as glacial and interglacial periods during the Pleistocene, can provide insights into their potential response to currently forecast climate-related changes. Lichens form an ecologically important and conspicuous component of polar ecosystems and often exhibit interesting distribution patterns that are rarely found in vascular plants (Geml et al. 2010; Pe´rezOrtega et al. 2012; Thomson 1995). In some cases, it has been suggested that lichens are particularly sensitive to climatic fluctuations (Bjerke 2011; Cornelissen et al. 2001; Leavitt & St. Clair 2011). However, recent evidence suggests that some arctic lichens are able to track their potential niche through effective longdistance dispersal (Ferna´ndez-Mendoza & Printzen 2013; Geml et al. 2010). While the distribution and ranges of arctic plants were greatly affected by the advance and retreat of ice sheets (Abbott & Brochmann 2003; Abbott et al. 2000; Scho¨nswetter et al. 2005), the impact of glacial and interglacial cycles on lichens remains largely unexplored. Climate during the Pleistocene was not necessarily unfavorable for some lichen-forming fungal species (Ferna´ndez-Mendoza & Printzen 2013; Geml et al. 2010; Leavitt et al. 2012a). For example, high levels of genetic diversity and efficient long-distance dispersal in the arctic lichen-forming fungal species Flavocetraria cucullata and F. nivalis indicate that these species were able to effectively track suitable habitat throughout the

Pleistocene (Geml et al. 2010). It was initially suggested that survival of arctic species depended on migration southward ahead of advancing ice sheets, into unglaciated regions (Davis & Shaw 2001). However, mounting evidence indicates that some regions of the Arctic and Subarctic in Beringia (northwestern America and eastern Siberia) were not glaciated during Pleistocene glaciations (Abbott et al. 2000), and these served as important refugia for arctic plants (Beatty & Provan 2010; Breen et al. 2012). Putative evidence of glacial refugia in high latitude forests has also been identified for the lichenized fungus Cavernularia hultenii (Printzen et al. 2003), further supporting the potential importance of high latitude refugia for lichens (also see Leavitt et al. 2012a). In order to assess the impact of major climatic fluctuations on lichen-forming fungi, we evaluated demographic patterns for two closely related species with contrasting distribution patterns within the genus Xanthomendoza (Teloschistaceae). We selected X. borealis, which occurs in polar regions of both hemispheres (Lindblom & Søchting 2008) and X. montana, which is restricted to montane shrublands in western North America (Lindblom 1997, Fig. 1). In the Northern Hemisphere, X. borealis is widespread, though uncommon, in arctic regions and also extends southwards into boreal zones in central Scandinavia in Europe and British Columbia in North America (Lindblom & Søchting 2008). In the Southern Hemisphere X. borealis is widespread and abundant

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in continental Antarctica but appears to be absent from maritime Antarctica (Lindblom & Søchting 2008; Pannewitz et al. 2006). Xanthomendoza borealis commonly grows on rock surfaces that are often somewhat enriched by guano; and in Antarctica it is very abundant on moss cushions in sites that are eutrophied by penguin rookeries (Lindblom & Søchting 2008; Pannewitz et al. 2006). In contrast, X. montana occurs in dry, open, nutrient-rich habitats in montane to temperate areas of western North America (Lindblom 1997). This species is commonly found on the bark and twigs of phorophytes, including the genera Populus, Quercus and Artemisia, although it may also occur on a variety of conifer species, as well as Salix and Fraxinus spp. (Lindblom 1997). In addition to distinct distribution patterns, X. borealis and X. montana also exhibit contrasting reproductive strategies. Xanthomendoza montana always bears numerous ascomata, characteristic fungal fruiting bodies producing ascospores. Ascospores are dispersed independent of the photosynthesizing partner (photobiont) and require re-acquisition of the appropriate photobiont partner in order to re-establish the lichenized condition. In contrast, X. borealis commonly propagates asexually by means of vegetative diaspores (soredia), although it may rarely produce mature pycnidia with conidia (‘‘spermatia’’) (Lindblom & Søchting 2008). Poelt (1963) hypothesized that lichenized fungi reproducing asexually (via soredia and isidia) are potentially more successful in pioneering formerly glaciated areas than sexually reproducing lichen fungi. In contrast, Nimis & Martellos (2003) argued that general ecological conditions largely determined the distribution of holarctic lichens, rather than distribution strategy alone. In this study, we explore the impact of climatic fluctuations during the Pleistocene on two Xanthomendoza species (X. borealis and X. montana) with distinct distribution patterns and reproductive strategies. Major climatic changes during the Pleistocene, including the last glacial maximum (LGM; 19,000– 22,000 BP; Yokoyama et al. 2000), represent the most recent and dramatic series of habitat changes since the Cretaceous. An improved understanding and documentation of how lichens responded to major climatic change during the Pleistocene may provide essential insights into how they may respond to future natural climate variability as well as the potential impact of anthropogenic warming (Geml et al. 2012; Geml et al. 2010; Pearson & Dawson 2003). Specifically, we were interested in seeing if the demographic history of a lichen-forming fungal species with a bipolar distribution (X. borealis) would fit an EC model. We compared

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the demographic history of X. borealis with a closely related species (X. montana) restricted to montane shrubland habitats in western North America. MATERIALS AND METHODS Taxon sampling. In this study Xanthomendoza borealis was represented by a total of 42 sequences retrieved from GenBank, 26 specimens from Antarctica and 16 from polar regions in the Northern Hemisphere (Greenland, Norway and Russia). Xanthomendoza montana was represented by a total of 71 specimens collected throughout its known distribution in western North America. In order to examine the monophyly of X. borealis and X. montana we obtained sequence data from an additional 46 Xanthomendoza specimens (Supplementary Table S1), representing 11 of the 21 species listed for the genus in Index Fungorum (http:// www.indexfungorum.org/). DNA extraction and sequencing. Total genomic DNA was extracted from a small thallus section of each X. montana specimen using the PrepEase DNA Isolation Kit (USB, Cleveland, Ohio, USA), following the ‘plant leaf extraction’ protocol. We then amplified the complete internal transcribed spacer region (ITS1, 5.8S, ITS2; ,530 bp) using primers ITS1f (White et al. 1990) and ITS4a (Larena et al. 1999). We used ReadyTo-Go PCR Beads (GE Healthcare) for all PCR reactions following the manufacturer’s instructions. Cycling parameters for amplifying the ITS marker followed Crespo et al. (2007). PCR products were quantified on 1% agarose gel with ethidium bromide and cleaned using ExoSAP-IT (USB, Cleveland, Ohio, USA), following the manufacturer’s instructions. Complementary strands were sequenced from cleaned PCR products using the same primers used for the initial amplifications. Sequencing reactions were performed using BigDye v3.1 (Applied Biosystems, Foster City, CA, USA). Products were then run on an ABI 3730 automated sequencer according to established protocols (Applied Biosystems) at the Pritzker Laboratory for Molecular Systematics at the Field Museum, Chicago, IL, U.S.A. Multiple sequence alignments and tests for recombination. We assembled and edited sequences using the program Sequencher v4.10 (Gene Codes Corporation, Ann Arbor, MI). Sequence identity was inferred using a ‘megaBLAST’ search in GenBank (Wheeler et al. 2006). Sequences from the complete Xanthomendoza dataset (159 sequences) were aligned using the program MAFFT v6, implementing the GINS-I alignment algorithm, ‘200PAM / K52’ scoring matrix, and with an offset value of 0.0, with the remaining parameters set to default values. Sequences

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representing both X. borealis and X. montana were re-aligned independently for subsequent intraspecific population demographic analyses. For both speciesspecific alignments, sequences were aligned using the GINS-I alignment algorithm, ‘1PAM / K52’ scoring matrix, with an offset value of 0.4, with the remaining parameters set to default values. We tested for recombination events using the methods implemented in the Recombination Detection Program (RDP4; Heath et al. 2006; Martin et al. 2005a; Martin et al. 2005b). Maximum likelihood phylogenetic reconstruction. In order to assess the monophyly of X. borealis and X. montana and identify potential infraspecific substructure or phylogeographic patterns we used the program RAxML v7.3.2 (Stamatakis 2006; Stamatakis et al. 2008) to reconstruct a maximum likelihood (ML) gene tree from the ITS alignment of all sampled Xanthomendoza specimens. We used the GTRGAMMA model, which includes a parameter (C) for rate heterogeneity among sites but chose not to include a parameter for estimating the proportion of invariable sites (Stamatakis 2006; Stamatakis et al. 2008). A search combining 200 separate maximum likelihood searches (to find the optimal tree) and 1000 pseudoreplicates to evaluate bootstrap support for each node was conducted. Bayesian phylogenetic reconstruction. We also analyzed the complete Xanthomendoza data set in the program BEAST 1.7.4 (Drummond & Rambaut 2007) in order to assess the relative time to the most recent common ancestor (TMRCA) of extant ITS haplotypes in both Xanthomendoza borealis and X. montana. We used a relaxed clock model (uncorrelated lognormal), with a Yule process tree model prior, and models of ITS sequence evolution were selected with the program jModeltest v0.1, using the Akaike information criterion (AIC) (Posada 2008). Branch rates were drawn from a lognormal distribution and the exploratory analyses indicated that there were no significant differences in topology or branch lengths estimated under an exponential distribution. Two independent analyses were run for 100 million generations and parameter values were sampled every 4000 generations. The output from each analysis was visualized using Tracer version 1.5 (Rambaut & Drummond 2003) to assess convergence and effective sampling size (ESS). We also assessed convergence by comparing summarized tree topologies from separate runs. Based on these results, the first 25 million generations from each run were discarded as burn-in, and the remaining samples were summarized as a maximum clade credibility tree with mean divergence times and highest probability density (HPD) intervals of relative age estimates using the program TreeAnnotator version 1.7.4 (Rambault & Drummond 2009).

Haplotype network reconstruction. Traditional phylogenetic algorithms, including maximum likelihood, have been shown to be suitable for reconstructing genealogies from closely related, highly similar haplotype sequence data and may outperform widespread ‘network’ construction methods (Salzburger et al. 2011). A ML phylogenetic tree was reconstructed using RAxML v7.3.2 for both species-specific alignments representing X. borealis and X. montana. A haplotype genealogy was generated using Haploviewer version 1.0 (Salzburger et al. 2011). Molecular diversity, population demographics statistics, and mismatch distributions. We used the program DnaSP v4.50 (Librado & Rozas 2009) to calculate estimates of genetic diversity (including number of haplotypes, h; haplotypic diversity, Hd; number of segregating sites, S; and nucleotide diversity, p) using the ITS sequence data for both X. borealis and X. montana. To examine whether X. borealis and X. montana populations are at equilibrium, we calculated Tajima’s D (Tajima 1989) and Fu’s F (Fu 1997) statistics for each species. Under the assumption of neutrality, negative values are expected in populations that have undergone recent expansion because rare alleles are more numerous than expected; while positive values occur if rare alleles are eliminated from populations due to genetic bottlenecks or diversifying selection (Tajima 1989). Fu’s F statistic is especially effective in detecting significant changes in population size when using small sample sizes (Fu 1997; RamosOnsins & Rozas 2002). These statistics were calculated in DnaSP, and significance was determined using the coalescent process implemented in DnaSP (10,000 replicates). Mismatch frequency histograms were also plotted for each species in DnaSP to infer changes in population size. A smooth unimodal curve suggests either population expansion or spatial range expansion, whereas a multimodal curve represents population stability (Harpending et al. 1998). To assess the fit of the observed data in the mismatch plots we used the raggedness index (R) (Harpending 1994) estimated from 10,000 coalescent simulations in DnaSP. Bayesian skyline analyses. Although Tajima’s D, Fu’s F and mismatch distributions can provide insights into whether or not populations have undergone changes in population size, they do not provide information about the shape of population growth over time. Therefore, we assessed changes in speciesspecific demographic histories over time using Bayesian skyline plot (BSP) analysis (Drummond et al. 2005) in BEAST v1.7.4 (Drummond & Rambaut 2007). BSP models population size based on a wide range of demographic histories, and if a molecular clock rate is

Leavitt et al.: Demography of Xanthomendoza spp.

known for the locus in question, the model can be used to put demographic events into a historical context (Drummond et al. 2005). The Bayesian skyline model uses standard Markov chain Monte Carlo (MCMC) sampling procedures to estimate a posterior distribution of effective population size through time from gene sequences, given a model of sequence evolution. The Bayesian skyline model and other demographic inference methods assume panmixia (Donnelly & Tavare 1995; Ho & Shapiro 2011)—i.e., the absence of population structure. This assumption may be violated in X. borealis, which has a bipolar distribution and commonly produces asexual diaspores. However, reproductive strategies in some groups of lichenforming fungi traditionally considered to reproduce vegetatively are more complex than previously recognized (Buschbom & Barker 2006; Leavitt et al. 2012a; Leavitt et al. 2011; Lindblom & Ekman 2006); and we assume that some genetic exchange may occur (or has occurred) in X. borealis. Similarly, in this study we identified a number of shared haplotypes between Northern and Southern Hemisphere populations of X. borealis, suggesting some degree of connection between disjunct populations. With the absence of relevant fossil evidence for the genus Xanthomendoza, we used a rate of molecular evolution for the ITS marker (2.43 3 1029 substitutions/site/year) recently reported for the lichen-forming genus Melanelixia (Parmeliaceae, Lecanoromyctes; Leavitt et al. 2012a) to estimate the TMRCA for all clades. Although estimated ITS substitution rates do not exist for any members of Teloschistaceae, this estimated substitution rate is similar to other estimates of ITS substitution rates for both lichen-forming fungi (2.38 3 1029 s/s/yr; Oropogon, Parmeliaceae, Lecanorales; Leavitt et al. 2012c) and non-lichenized fungi (2.52 3 1029 s/s/y, Erysiphales, Takamatsu & Matsuda 2004). Because systematic rate heterogeneity is not expected in intraspecific data, we used a strict molecular clock. Two independent analyses were run for 50 million Monte-Carlo-Markov-Chain generations, sampling parameter values every 1000 generations, using the Bayesian Skyline tree model allowing five discrete changes in population size with linear growth between population size change events. A UPGMA generated tree was used as the starting point. We used the GTR+G+I model of nucleotide substitution without partitioning the ITS1, 5.8S, and ITS2 regions. For each species (X. borealis and X. montana), we combined two independent runs and all ESS were .200. We used Tracer v1.5.1 to analyze combined runs for each species and generate skyline plots.

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RESULTS Phylogenetic reconstructions. The complete Xanthomendoza ITS data matrix consisted of 159 sequences and 570 aligned nucleotide position characters (Supplementary online Table S1; TreeBase ID: 14794). The X. borealis dataset included 42 sequences and 512 aligned nucleotide position characters; and the X. montana dataset consisted of 71 sequences and 529 aligned characters. RDP4 detected no evidence of recombination in the ITS marker. Well-supported relationships were identical in the ITS topologies estimated using both ML and Bayesian (BEAST) analyses, and the Bayesian topology is presented in Fig. 2 (the complete ML topology is shown in Supplementary Fig. S1). Both X. borealis and X. montana were recovered as monophyletic with strong statistical support (bootstrap support [BS] . 90%; posterior probabilities [PP]) .0.95) in both analyses (Fig. 2). A majority of the other traditional species were also recovered as monophyletic, with the exception of X. hasseana which was recovered in two separate well-supported lineages; and X. oregana and X. poeltii which were recovered in a single well-supported clade (Fig. 2; Supplementary Fig. S1). Well-supported clades corresponding to allopatric populations suggesting the potential for reproductively isolated groups were not recovered in either X. borealis or X. montana. In the BEAST analyses, the estimated relative ages to TMRCA for ITS haplotypes were highly similar for both X. borealis and X. montana, although with slightly older estimates for X. montana (Fig. 2). The halplotype genealogies for X. borealis and X. montana are shown in Fig. 3. Two X. borealis haplotypes are shared between populations in the Northern and Southern Hemispheres. The general star-like shape of the X. montana network indicates population expansion for this species (Fig. 3). Population demographic histories. Genetic diversity indices (Hd, S, and p) for both X. borealis and X. montana are summarized in Table 1. The apotheciate species X. montana showed greater nucleotide and haplotype diversities than the sorediate X. borealis. Significant negative Tajima’s D and Fu’s F values were detected in X. montana but not in X. borealis, suggesting demographic growth for X. montana versus stability for X. borealis (Table 1). Likewise, the mismatch distribution showed a distinct multimodal distribution with a significant R value for X. borealis indicating population stability, while X. montana showed a relatively unimodal pattern with a nonsignificant raggedness value consistent with demographic or spatial range expansion (Fig. 4A & B; Table 1).

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Figure 2. Cartoon representations of the ITS topology obtained using a Bayesian analysis of 159 Xanthomendoza specimens using the program BEAST. Bars indicate the 95% highest posterior density interval (HPD) for relative age of the most recent common ancestor at each node; values at each node indicate posterior probabilities (PP) from the Bayesian BEAST analysis and non-parametric-bootstrap support (BS) values from a ML analysis. Only PP values . 0.50 and BS values . 50% and are indicated.

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Figure 3. Haplotype networks showing genealogical relationships among ITS haplotypes within X. borealis (3A) and X. montana (3B). Sizes of circles are proportional to the relative abundance of each sampled haplotype and numbers within each circle indicate the total number of specimens per haplotype. Small filled circles represent unsampled haplotypes, and lines between haplotypes represent one mutational step.

The effective population sizes and demographic trends estimated by the Bayesian skyline plot (BSP) analyses for X. montana are shown in Figure 4C. The BSP for X. montana indicated population size increases during the Pleistocene that began approximately 50 Ka, based on the ITS substitution rate of 2.43 3 1029 substitutions/site/year used in this study. The BSP for X. borealis did not extend beyond the LGM and is not shown. DISCUSSION The ecological and evolutionary responses of lichens to major climatic fluctuations during the Pleistocene remain largely unknown with only limited

exceptions (Ferna´ndez-Mendoza & Printzen 2013; Geml et al. 2012; Geml et al. 2010; Leavitt et al. 2012a; Printzen et al. 2003). In this study, we show that the bipolar species X. borealis exhibits a history consistent with long-term stability, while X. montana, a montane shrubland species restricted to western North America, has experienced a recent (Late Pleistocene) population expansion. Drift-mutation equilibrium statistics, mismatch analysis, haplotype network reconstruction, and a Bayesian demographic reconstruction for X. montana all yielded results consistent with a recent population expansion. In contrast, results for X. borealis based on the same analyses indicate a stable demographic history without any evidence of demographic expansion (or

Table 1. Estimates of genetic diversity and drift-mutation equilibrium statistics for the circumpolar species Xanthomendoza borealis and X. montana. N 5 sample size; H 5 number of haplotypes; Hd 5 haplotypic diversity; S 5 number of segregating (polymorphic) sites; p 5 nucleotide diversity; Tajima’s D; Fu’s F statistic; and raggedness index (R). Bolded values indicate significant Tajima’s D, Fu’s F statistic, and R values. Species

N

h

Hd

S

p

Tajima’s D

Fu’s F

R

X. borealis (512 bp) X. montana (529 bp)

42 71

12 30

0.588 0.876

5 38

0.00222 0.00474

20.09177 22.24152

20.893 222.626

0.09096 0.11891

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Figure 4. Mismatch distribution plots for Xanthomendoza borealis and X. montana (4A & 4B); and a Bayesian skyline plot for X. montana (4C). The solid black line represents the median value for the log of the population size (log Ne) and the dashed lines represent the upper and lower 95% credibility intervals. Bayesian skyline plot for X. borealis did not extend beyond the LGM and is not shown.

contraction) following the LGM. However, the inferred demographic history of X. borealis may be biased due to the reduced power of statistical analyses based on the limited number of segregating sites in X. borealis (5

sites) (Ramos-Onsins & Rozas 2002). Results and discussion for X. borealis therefore should be taken with caution and are intended only as hypothesisgenerating findings. A broader understanding of the past response of species to major climate shifts, such as glacial and interglacial periods during the Pleistocene, can provide valuable insights into their potential response to future climate change. Below we discuss various scenarios that may explain the demographic patterns observed for X. borealis and X. montana in this study. Researchers have proposed that the contemporary distribution and abundance of some common holarctic lichens may also be the result of recent range expansions after the LGM (Calvelo et al. 2005; Nimis 1993; Otte et al. 2001; Poelt 1963; Seaward 1995; Thell 1989). However, it has recently been shown that climate during the Pleistocene was not inherently unfavorable or restrictive for some common lichen-forming fungal species (Ferna´ndez-Mendoza & Printzen 2013; Leavitt et al. 2012a; Leavitt et al. 2013). For example, in two Melanohalea (Parmeliaceae) species that commonly cooccur with X. montana in western North America, M. subolivacea with apothecia and M. elegantula with vegetative diaspores, population expansions were estimated to significantly predate the LGM (Leavitt et al. 2012a). In this study, we provide evidence supporting a recent population expansion for X. montana, which commonly occurs in montane shrubland ecosystems in western North America. Pleistocene glacial-interglacial cycles had a significant impact on vascular plant communities in western North America (Coats et al. 2008; Osborn & Bevis 2001; Pierce 2003; Thompson & Anderson 2000); and in some cases vascular plant species responded to climate change by altitudinal adjustments of as much as 1200 m (Coats et al. 2008). Disturbances may have promoted the expansion of montane shrublands in western North America during the Late Pleistocene (Romme et al. 2009), resulting in the observed pattern of demographic expansion in X. montana. Interestingly, two Melanohalea species that commonly co-occur with X. montana in montane shrublands in western North America also appear to have experienced demographic expansion during the Pleistocene, although the timing of the population expansions in the Melanohalea species predates our estimate for X. montana (Leavitt et al. 2012a). We hypothesize that the late Pleistocene expansion of X. montana was likely due to disturbances resulting in major shifts in vegetation in western North America. While our current understanding of climate change on shrubland ecosystems is limited, montane shrubland habitats have been forecast to experience a moderate

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decline over the next century (Friggens et al. 2012). We predict a similar decline in the geographic distribution of X. montana as it responds to the predicted reduction in montane shrubland ecosystems in western North America. In contrast to the recent population expansion for X. montana, our data support long-term population stability for X. borealis, suggesting that this species has been able to effectively persist throughout glacial/ interglacial cycles without significant changes in population size. This conclusion is supported in part by this species contemporary distribution in extreme habitats in Polar Regions in both hemispheres (Lindblom & Søchting 2008) and shared haplotypes between disjunct populations in the Northern and Southern Hemispheres (Fig. 3). Whether the putative long-term persistence of X. borealis has been the result of effective dispersal into suitable habitats at lower latitudes or in situ persistence in nunataks remains uncertain (Jørgensen et al. 2012). Some arctic-alpine lichens have recently been shown to migrate over large distances in response to climatic fluctuations (Geml et al. 2010; Geml et al. 2012), although the frequency of trans-equatorial dispersal remains less clear (Ferna´ndez-Mendoza et al. 2011; Geml et al. 2012). While the extent of suitable nunatak habitat available to X. borealis during Pleistocene glacial periods is unknown, one would expect a substantial increase in population size during interglacial periods as additional suitable habitat became available. Therefore, the apparent stability in X. borealis population size is likely due to its ability to rapidly track suitable habitats during periods of climatic fluctuations, rather than simply in situ persistence in nunataks. However, because of limited statistical power using the ITS marker additional data will be required to corroborate the demographic history for X. borealis with confidence. Substrate availability and preference may play an important role in the different demographic histories observed for X. borealis and X. montana. Xanthomendoza borealis often occurs on eutrophicated rock substrates and moss cushions in continental Antarctica (Lindblom & Søchting 2008), which likely remain available, at least to some extent, even in habitats that are substantially impacted by glacial cycles. These eutrophicated rock nunataks may help maintain relatively constant population size in X. borealis during glacial cycles. In contrast, X. montana, is found on bark and twigs of a wide range of phorophytes, and vascular plant communities have been shown to experience major glacial-related changes in western North America (Coats et al. 2008; Osborn & Bevis 2001; Pierce 2003; Thompson & Anderson 2000). The limitations

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for re-establishing suitable woody substrates for X. montana would have been problematic when compared to the relatively short time frame for the exposure of suitable rock substrates for X. borealis. Different demographic histories between related sexually and vegetatively reproducing lineages have recently been documented for some lichen-forming fungi (Melanohalea; Leavitt et al. 2012a). In this study, we also provide evidence showing differing demographic histories between closely related Xanthomendoza species with contrasting reproductive patterns. Whether these differences are due to reproductive strategy-dependent fitness advantages, availability of the appropriate photosynthetic partner, differences in dispersal capacity, or other factors remains unknown. In lichen-forming ascomycetes, factors that induce sexual reproduction are largely unknown; however, as a general observation, the infrequent production of ascomata (no or only a few ascomata) has been connected with heterothallism (Honegger & Zippler 2007; Honegger et al. 2004; Kroken & Taylor 2001; Scherrer et al. 2005; Seymour et al. 2005; Zoller et al. 1999). In contrast, species that consistently produce ascomata can be either homothallic or heterothallic (Honegger & Zippler 2007; Honegger et al. 2004; Scherrer et al. 2005). We speculate that differences in self-compatibility versus self-incompatibility may provide a potential mechanism for explaining the observed rapid response to climate change demonstrated by X. montana. A comparative evolutionary history of mating-type loci and mating systems in Xanthomendoza merits further investigation and may provide important insights into factors affecting population demographics for both X. borealis and X. montana. Some caution must be taken with the results from our BSP analyses. Due to the possible limitations of using genetic data from the ribosomal tandem repeat (biased gene conversion in concerted evolution of ribosomal DNA), potential violations of the assumption of panmixia in lineages reproducing largely by vegetative diaspores (X. borealis), and a potentially biased ITS substitution rate the BSP analyses may misrepresent demographic histories in Xanthomendoza. The selection of genetic loci for inferring demographic histories is not always straightforward (reviewed in Ho & Shapiro 2011). Mitochondrial markers have been the locus of choice in skyline-plot analyses of animal populations (Buckley et al. 2010; Gompert et al. 2008; Ho & Shapiro 2011; Kumar et al. 2011). However, the ITS region is among the most variable commonly used markers in lichenized ascomycetes and has a higher mutation rate than standard mitochondrial loci (Bruns et al. 1991; Burt et al. 1996;

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Leavitt et al. 2012a; Schoch et al. 2012). Previous studies have confirmed the utility of variable ribosomal markers (i.e., ITS and IGS) for species- and population-level studies in Teloschistaceae (Lindblom 2009; Lindblom & Ekman 2006, 2007; Vondra´k et al. 2009). While we are aware of the potential limitations associated with using ribosomal markers to infer demographic histories, we consider this a good ‘‘first pass’’ marker with which to investigate population demographics in lichenized fungi. In this study, we used a substitution rate estimated from a distantly related lichen-forming fungal genus, Melanohalea (Parmeliaceae, Leavitt et al. 2012a), to assess the timing of population expansion in Xanthomendoza. While this estimated substitution rate is similar to other rates estimated for the ITS region in both lichen-forming fungi (Leavitt et al. 2012b,c) and non-lichenized fungi (Takamatsu & Matsuda 2004); variation within the same order of magnitude may substantially influence our interpretation of the factors driving population dynamics in Xanthomendoza. While our data provide strong evidence supporting a recent demographic expansion of X. montana, the precise timing of this expansion remains less certain. Although it is likely that population expansion in X. montana occurred during the late Pleistocene, whether the expansion actually predated the LGM (estimated at ca. 50 Ka in this study; Fig. 4) is uncertain. Ultimately, taxon-specific rates will be required to more accurately determine the specific timing of the population expansion for X. montana. In conclusion, population demographic studies of lichen-forming fungi potentially provide important insights into how species respond to major climatic change. In the case of X. montana, our data provide additional evidence that major shifts in vegetation types as a result of climate change will likely have a substantial impact on lichen distribution patterns and demographic histories in the future. Although it is somewhat surprising that the genetic structure of X. borealis did not contain a signature of demographic expansion consistent with Pleistocene glacial retreat, our results provide evidence that climatic change during Pleistocene glacial cycles was not inherently unfavorable or restrictive for some high altitude/ latitude lichen-forming fungal species. Future research investigating landscape-level gene flow in both X. borealis and X. montana will be important to effectively assessing their response to future climatic changes. ACKNOWLEDGMENTS We thank Griffin Briem, Mike Felix, Daniel Leavitt, and Hailey Leavitt for assistance in the field; and Matthew Nelsen for valuable discussion

concerning this research project. This study was supported by the USDA Forest Service, the Negaunee Foundation, and the National Science Foundation (DEB-0949147, awarded to H. T. L. and Theodore L. Esslinger).

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Supplementary documents online: Table S1. Collection information for all Xanthomendoza specimens included in the present study. Figure S1. Maximum likelihood ITS gene tree of the 159 sampled Xanthomendoza specimens. Bootstrap support indicated at nodes.