Loss of a morph is associated with asymmetric character release in a radiation of woodland salamanders

Supporting Information for Loss of a morph is associated with asymmetric character release in a radiation of woodland salamanders Authors: Brian P. Waldron, Maggie M. Hantak, Emily F. Watts, Josef C. Uyeda, Alan R. Lemmon, Emily Moriarty Lemmon, Robert P. Guralnick, David C. Blackburn, Shawn R. Kuchta Corresponding authors: Brian P. Waldron, Maggie M. Hantak Email: [email protected]; [email protected] This PDF file includes: Supporting text Taxon sampling Anchored hybrid enrichment Phylogenomic analyses (Figure S1 – S2) Timetree estimation Color classification schemes Ancestral character reconstruction (Figure S2 – S5) Morphometrics Variation in phylogenetic PCA and PCA (Figure S6) Rates of evolution and evolutionary optima (Figure S7 – S10) SI References Other supporting materials for this manuscript include the following: Table S1 – Sample information Table S2 – Per-locus summary statistics Table S3 – Morphometric raw data and discrete color classifications Table S4 – Discrete character evolution model rankings Table S5 – Morphometric phylogenetic signal Table S6 – Phylogenetic PCA (pPCA) loadings Table S7 – Phenotypic rates, optima, and tip rates for 3-state and 2-state models Tree files: “plethodon-iqtree.tree” – IQ-Tree treefile “plethodon-wastral.tree” – wASTRAL treefile “plethodon-timetree-unpruned.tree” – MCMCTree timetree (unpruned) “plethodon-timetree-pruned.tree” – MCMCTree timetree (pruned) Supporting Information Text Taxon sampling Plethodon consists of 57 extant species across four major clades: 1) western Plethodon (N = 9 species; also assigned to the subgenus Hightonia); 2) the cinereus group (for clarity, we omit the genus name when referring to species groups throughout) (N = 10); 3) the wehrlei-websteri group, also sometimes referred to as the “wehrlei-welleri group” (Wiens et al., 2006) (N = 10); and 4) the glutinosus group (N = 28). As the names suggest, western Plethodon are found in western North America, whereas all other groups are found in eastern North America, comprising “eastern Plethodon” (subgenus Plethodon). We included samples from all extant species. Phylogenetic inference has been most challenging in eastern Plethodon (Fisher-Reid & Wiens, 2011; Highton et al., 2012; Kozak et al., 2006; Wiens et al., 2006), and we made an effort to sample multiple individuals per species across different localities (Supplementary Table S1). Within two species, we recognized phylogroups identified in recent work with the same samples and genetic data. Plethodon cinereus included five groups (“Groups 1 – 5”), which were subsampled here using 1 – 3 samples per group (Waldron et al., 2025). Plethodon kentucki included four groups (“Cumberland," “Kentucky," “Kanawha," “New”), subsampled here using 3 samples per group (Watts et al., 2024). For some other species, all samples were retained and separated into geographic clusters: Plethodon serratus (“Appalachia," “Missouri," “Louisiana," “Ouachita”) (C. E. Newman & Austin, 2015; Thesing et al., 2016); Plethodon websteri (“AL," “MS," “GA," “SC”) (Feist et al., 2019); Plethodon albagula (“Texas," “Ozark”) (Meacham et al., 2024). Some other species were not separated into multiple geographic groups a priori, but instead multiple geographic groups were recognized after a concatenated analysis of individuals in IQ-Tree (see below and main text): Plethodon metcalfi (“N," “S”); Plethodon shermani (“E," “W”); Plethodon glutinosus (“N," “S”); Plethodon mississippi (“E," “W”). We recognize all recently described or resurrected species of the P. wehrlei species complex: Plethodon dixi, P. jacksoni, and P. pauleyi (Felix et al., 2019; Kuchta et al., 2018, 2024). Anchored hybrid enrichment Genomic DNA was extracted from blood or tail tissue using Qiagen DNeasy blood and tissue kits (Qiagen Corp.). Samples were processed at the Florida State University Center for Anchored Phylogenomics using an anchored hybrid enrichment (AHE) protocol (Lemmon et al., 2012). Each sample was standardized to ~20 ng/μL and sonicated to an average fragment size of 150 – 300 bp using a Covaris E220 focused ultrasonicator. Library preparation was performed using a Biomex FXp liquidhandling robot (Beckman Coulter) following (Meyer & Kircher, 2010). Samples were indexed and enriched using an Agilent Custom SureSelect Kit with amphibian-specific probes (Heinicke et al., 2018). Samples were then pooled for sequencing on a PE150 lane of a HiSeq 2000 DNA sequencer (Illumina). Data were processed using scripts and methodology following (Booker et al., 2022; Prum et al., 2015; Pyron et al., 2016), except where noted. Briefly, overlapping reads were merged and assembled. We did not phase alleles for this study. Low-level contaminants were filtered, and we performed an initial assessment of orthology based on pairwise distances for each locus. We aligned sequences using MAFFT (Katoh & Standley, 2013), which were trimmed and masked to remove sites with excessive missing data (Pyron et al., 2016). Within 20 bp windows, all sites were masked if they contained fewer than 14 “good” sites (i.e. where the most common base character was present in >50% of samples). Sites with masked or missing bases in >50% of samples were removed (Pyron et al., 2016). We retained 282 AHE loci for this study. Sequence statistics per locus can be found in Supplementary Table S2, and the proportion of total missing data per sample is found in Supplementary Table S1. Phylogenomic analyses Supplementary Figure S1. Concatenated phylogeny of all samples of Plethodon estimated using IQTree. Outgroups have been pruned to improve visualization. Node support represents bootstrap support; unlabeled nodes have support values >0.95. Sample names can be matched with updated species assignments (e.g. within the P. wehrlei species complex) and phylogroup assignments used for species tree estimation in Supplementary Table S1. Supplementary Figure S2. Species tree of Plethodon estimated using wASTRAL. Outgroups have been pruned to improve visualization. Node support represents local posterior probabilities; unlabeled nodes have support values >0.95. Branch lengths represent coalescent units + 2 * substitution rate, with external branches set to 1. Samples were assigned to species or phylogroups based on concatenated analysis of individuals (Supplementary Table S1). Timetree estimation. We estimated a timetree using the program PAML 4.10.6 (Yang, 2007). We initially attempted Bayesian analysis with starBEAST3 (Douglas et al., 2022), using a partitioned analysis of the 20 longest loci with minimal missing data (fewer than 10% of samples with completely missing data) that were more “clocklike” (coefficient of variation in root-to-tip distance less than the median value across loci) (Stiller et al., 2024); however, this analysis had ESS <100 for several parameters (typically population sizes, tree heights, and tree distances) after a total of 400,000 iterations across two independent chains, suggesting the analysis would require fewer loci, simpler models, or much longer runs to converge. Therefore, we estimated divergence times using MCMCTree. For this analysis, the species tree topology inferred using wASTRAL was fixed, and for each species or phylogroup—including separate tips from polyphyletic species—we selected the individual with the least missing data as a representative sample. We first obtained a rough estimate of the overall substitution rate across loci using BASEML, treating loci as partitions. The root node was fixed at 40 Mya, a date estimated for the split between eastern and western Plethodon in previous analyses (Shen et al. 2016; see below), and we assumed a GTR+ Γ model for each locus. The estimated substitution rate was 5.335 x 10-3 substitutions per 10 Ma, which was subsequently used to parameterize a broad gamma-Dirichlet distribution of locus rates (rgene_gamma = 1 382.40921). Next, we estimated the branch lengths as well as the gradient and Hessian of likelihood surface (usedata = 3). Finally, we used the estimated branch lengths and a fossil calibration of the root node to obtain divergence dates (usedata = 2). Few fossils are available within Plethodon, but we were able to constrain the root to be at least 25 Mya based a late Oligocene fossil from Montana consistent with western Plethodon (Tihen & Wake, 1981; Wake, 2017; Zheng et al., 2011). Including this same fossil calibration, Shen et al. (2016) used 50 loci to estimate divergence dates for Plethodontidae, with mean divergences between eastern and western Plethodon ranging from 37.1 – 45.3 Mya across four analyses. We used these values to set a skew-normal distribution on the root of Plethodon which included these values in the 95% the prior probability [SN(4.0, 0.2377331, 0.7183491)]. We used a birth-death model with a sampling proportion of 0.9 (i.e. assuming most species have been sampled). MCMC chains were set to collect samples every 100 iterations for a total of 1,000 samples, following a burn-in of 10,000 iterations. Chains were evaluated using Tracer V1.7.2 (Rambaut et al., 2018) to ensure convergence and ESS >200. For downstream comparative analyses that required species to be represented by a single tip, polyphyletic or paraphyletic species were reduced to the unit that we inferred to be the best representative of that species based on geography and topology in our estimated phylogenies: 1) the Texas isolate of P. albagula; 2) the northern (N) group of P. glutinosus; 3) the southern (S) sample of P. metcalfi; 4) the eastern (E) sample of P. mississippi; and 5) the eastern (E) sample of P. shermani from the Wayah isolate. In general, we prioritized groups that were less likely to occur at a contact zone with other species. Color morph classification schemes Species were classified into color morph categories based on species accounts (AmphibiaWeb, 2024; Petranka, 1998) and supplemented with expert opinion (see acknowledgements) and photographs from AmphibiaWeb (AmphibiaWeb, 2024) or iNaturalist (INaturalist, 2024). Many species had straightforward color morph classifications, but two areas of the phylogeny presented challenges that we addressed by exploring multiple classifications. First, eastern large-bodied Plethodon (the glutinosus group and the wehrlei species complex) generally lack a stripe, yet their patterning is distinct from other unstriped species. Plethodon yonahlossee, P. petraeus, and P. ouachitae are exceptions, each with a red dorsum (a possibly polymorphic feature for P. ouachitae), but their stripe is conspicuously different in width, pattern, and hue than any other species, and may have a different developmental basis or functional role. We tested classifications in which 1) most members of the glutinosus group and wehrlei complex were assigned to a fourth category consistent with eastern large-bodied Plethodon (“other”) with the exception of the three striped or polymorphic species listed above; or 2) all members of these clades were all classified as “other”. Second, western Plethodon classifications were complicated by an ontogenetic change observed in P. neomexicanus, P. asupak, P. stormi, and P. elongatus, in which some or all individuals are striped as juveniles, but the stripe gradually dulls in adulthood to be indistinguishable from an unstriped morph. The degree to which the stripe dulls varies among individuals and species. In previous work, P. neomexicanus was considered unstriped, while P. elongatus was considered striped, and the remaining two species were not sampled (Fisher-Reid & Wiens, 2015). Ontogenetic change is usually not considered polymorphism, and species are typically classified based on their adult morphology (Huxley, 1955); however, because there is little data regarding individual/population variation and the duration of the stripe into adulthood, we tested four alternative classifications based on photographs available on iNaturalist (INaturalist, 2024) and AmphibiaWeb (AmphibiaWeb, 2024) and correspondence with other scientists (see Acknowledgements): Plethodon neomexicanus was always considered unstriped, while 1) P. asupak and P. stormi were considered unstriped, and P. elongatus striped; or these three species were all considered 2) unstriped; 3) striped; or 4) polymorphic. In total, we tested 8 classification schemes. We were interested in the way in which these different classifications affected ancestral state reconstructions and estimates of evolutionary rates and optima. Most of our color classifications matched those of Fisher-Reid and Wiens (2015). However, we considered P. hubrichti unstriped because its golden stripe better resembles a dense concentration of iridophores rather than a red stripe. We also assigned P. dunni as polymorphic due to the presence of unstriped individuals and populations, once considered a separate species (P. gordoni) (Feder et al., 1978). We categorized P. petraeus as either striped or “other," depending on the classification scheme. Finally, species not included in Fisher-Reid and Wiens (2015) included P. sherando (polymorphic), newly described species of the “P. wehrlei complex” (all “other”), and P. asupak and P. stormi (varied across classification schemes). Although we consider the glutinosus group and the P. wehrlei complex to represent a distinct, large-bodied adaptive zone than those occupied by striped/unstriped species, we tested whether our results were robust to this decision. We created two additional color classifications that represent a nested subset of the classifications above. First, we used a 3-state classification scheme in which all large-bodied species of eastern Plethodon (“other”) that lack a dorsal stripe (i.e. excepting Plethodon yonahlossee, P. petraeus, and P. ouachitae) were lumped with our primary unstriped group. This scheme tested whether downstream results were robust to assuming that most large-bodied species represented examples of the unstriped morph. Within this 3-state scenario, we applied the same set of four schemes testing variation in assignment of species of western Plethodon as listed above. Secondly, we used a 2state classification scheme, which matched the 3-state scheme, but the dorsal stripe was treated as a presence/absence trait, thus lumping striped and polymorphic species. This scheme facilitated analyses focused exclusively on gains or losses of the dorsal stripe, but at the cost of modeling polymorphism as a separate character state. For the 2-state scenario, we also tested schemes varying in assignment of some western Plethodon, although only schemes in which each species was polymorphic or striped were redundant; therefore, three alternative schemes were tested for the 2-state scenario. Ancestral character reconstruction We tested 12 models of discrete character evolution for each color morph classification scheme. These models tested multiple hypotheses regarding the directionality of color morph evolution, while also accounting for transitions to and from the large-bodied color states (“other”), which were held constant across models (Fig. 2 in main text). Models were fit using ‘fitMk’ in ‘phytools’ (Revell, 2024). Model selection results for four-state color classifications are found in Supplementary Table S4a. Although ancestral character reconstructions for eastern Plethodon were generally consistent across schemes, the root state and the states within western Plethodon were highly variable (Supplementary Fig. S3), suggesting sensitivity to the color classifications within these groups. Supplementary Figure S3. Ancestral character reconstruction of color morph state using stochastic character mapping (SCM) for eight color classification schemes (A – H; scheme E is the same as Figures 1 and 3a in the main text). Schemes A – D considered all members of the glutinosus group and wehrlei species complex to be a separate state (“other”), while E – H allowed some species to be striped (S) or polymorphic (S+U); schemes further varied in the states of P. asupak, P. stormi, and P. elongatus. For each scheme, 1,000 SCMs were performed across models of discrete character evolution in proportion to their AIC weights. Ancestral reconstructions for 3-state color morph classifications involved the same models as the 4-state models (Fig. 2 in main text), but the “other” category was dropped from transition matrices. For all color classifications, a simple equal-rates model had the lowest AIC, while only symmetrical rates models had comparable scores (ΔAIC < 2.0; Supplementary Table S4b). Unlike our 4-state models, explicit polymorphism models were in all cases poorer fits to the data than those allowing transitions directly between striped and unstriped states; this resulted from large-bodied “striped” species nested within a clade considered unstriped in the three-state classification (Supplementary Fig. S4). Other results were generally consistent with those of 4-state classifications, where the ancestor of eastern Plethodon was most likely polymorphic (PP = 0.58 – 0.62), while the root and the ancestor of western Plethodon had low certainty for any state (Supplementary Fig. S4). For the 2-state classifications in which the stripe was treated as a binary presence/absence character, we compared four models: all-rates-different (ARD), equal rates (EQR), directional transitions only from striped to unstriped (DR1), and directional transitions only from unstriped to striped. Simple equal-rates models had the lowest AIC scores and were favored over directional models (ΔAIC > 2.0), but in all cases were indistinguishable from all-rates-different rates models (ΔAIC < 2.0; Supplementary Table S4c). There was greater uncertainty for the ancestor of eastern Plethodon in the two-state model, and the state of the root remained unresolved (Supplementary Fig. S5). Taken together, our results suggest that uncertainty in the ancestral state of Plethodon results primarily from uncertainty in ancestral character reconstruction, and to a smaller degree for only some nodes, color morph classification decisions. Supplementary Figure S4. 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