ZooKeys | | 58: 9 I] 20 (2023) A peer-reviewed open-access journal doi: 10.3897/zookeys.1 158.94152 RESEARCH ARTICLE #ZooKey S https:/ / ZOO keys. pensoft.net Launched to accelerate biodiversity research Using genomics, morphometrics, and environmental niche modeling to test the validity of a narrow-range endemic snail, Patera nantahala (Gastropoda, Polygyridae) Nathan V. Whelan'”, Ellen E. Strong’, Nicholas S. Gladstone’, Jason W. Mays* I Southeast Conservation Genetics Lab, Warm Springs Fish Technology Center, US Fish and Wildlife Service, 203 Swingle Hall, Auburn, Alabama, 36849, USA 2 School of Fisheries, Aquaculture, and Aquatic Sciences, College of Agriculture, Auburn University, 203 Swingle Hall, Auburn, Alabama, 36849, USA 3 Department of Invertebrate Zoology, National Museum of Natural History, Smithsonian Institution, PO Box 37012, MRC 163, Washington, DC 20013, USA 4 Asheville Ecological Services Field Office, United States Fish and Wildlife Service, 160 Zillicoa ST, Asheville, NC 28801, USA Corresponding author: Nathan V. Whelan (nathan_whelan@fws.gov) Academic editor: Martin Haase | Received 27 August 2022 | Accepted 13 March 2023 | Published 20 April 2023 https://z0obank.org/6D 1EA64A-63CB-4C77-82DB-F64FC2352291 Citation: Whelan NV, Strong EE, Gladstone NS, Mays JW (2023) Using genomics, morphometrics, and environmental niche modeling to test the validity of a narrow-range endemic snail, Patera nantahala (Gastropoda, Polygyridae). ZooKeys 1158: 91-120. https://doi.org/10.3897/zookeys.1158.94152 Abstract Terrestrial gastropods are among the most imperiled groups of organisms on Earth. Many species have a complex taxonomic history, often including poorly defined subspecies, most of which have not been the focus of modern systematics research. Genomic tools, geometric morphometrics, and environmental niche modeling were used to assess the taxonomic status of Patera clarkii nantahala (Clench & Banks, 1932), a subspecies of high conservation concern with a restricted range of approximately 3.3 km? in North Carolina, USA. A genome-scale dataset was generated that included individuals with morphologies matching P c. nantahala, Pc. clarkii, and one individual with an intermediate form between P c. nanta- hala and Pc. clarkii that was initially hypothesized as a potential hybrid. Mitochondrial phylogenetics, nuclear species tree inference, and phylogenetic networks were used to assess relationships and gene flow. Differences in shell shape via geometric morphometrics and whether the environmental niches of the two subspecies were significantly different were also examined. Molecular analyses indicated an absence of gene flow among lineages of P clarkii sensu lato. Analyses rejected our hypothesis that the intermediate Copyright Nathan V.Whelan et al. This is an open access article distributed under the terms of the CCO Public Domain Dedication. 92 Nathan V. Whelan et al. / ZooKeys 1158: 91-120 (2023) shelled form represented a hybrid, but instead indicated that it was a distinct lineage. Environmental niche models indicated significant differences in environmental niche between P c. clarkii and P c. nanta- hala, and geometric morphometrics indicated that P c. nantahala had a significantly different shell shape. Given multiple lines of evidence, species-level recognition of P nantahala is warranted. Keywords 3RAD, generalized linear model, Maxent, morphology, Noonday Globe Snail, phylogenetic network, species tree, taxonomy Introduction Many conservation and environmental policies rely on functional units like species or subspecies (Primack 2014; Coates et al. 2018). For example, the U.S. Endangered Species Act defines species and subspecies as entities that can be listed as threatened or endangered. ‘Therefore, applied conservation requires an informed taxonomy that ac- curately reflects diversity so conservation targets are not overlooked or overemphasized. In other words, modern systematics is essential for positive conservation outcomes. Even though systematists debate the best approach for delineating species (Stankowski and Ravinet 2021), the definition of a species as a distinct evolutionary lineage is implicit in most species concepts (Mayden 1997; De Queiroz 2007). The taxonomic rank of subspecies, however, has been controversial. Unambiguous criteria for recognizing subspecies do not exist. Nevertheless, many systematists consider sub- species to be geographically distinct populations, often with distinct morphologies, that interbreed with other populations of the same species at contact zones (Patten 2015; Taylor et al. 2017). Under this definition, the defining characteristic of subspe- cies versus species is the ability of subspecies to routinely interbreed with other mem- bers of its species. Therefore, one would expect signatures of recent, or ongoing, gene flow between subspecies of the same species. If no such signature exists, then the two subspecies would be better considered as two distinct species. The number of subspecies per species varies considerably among taxonomic groups. Generally, terrestrial snail groups exhibiting greater conchological complexity and larger ranges contain more subspecies (Pall-Gergely et al. 2019). This bias in use of subspecies implies that the number of subspecies may not always reflect actual ter- restrial snail diversity. In the case of morphologically variable species with large ranges and discontinuous habitats, recognized subspecies may warrant species-level recogni- tion. Given that few genome-scale studies have focused on terrestrial snails (but see Razkin et al. 2016; Phillips et al. 2020; Bober et al. 2021; Bamberger et al. 2022), the implicit hypothesis that gene flow occurs among subspecies has not been adequately tested in most cases. One terrestrial snail species that warrants closer scrutiny to assess the validity of subspecies and inform conservation is Patera clarkii (I Lea, 1858). Currently, two subspecies are recognized: Patera c. clarkii and Patera c. nantahala (Clench & Banks, Systematics of Patera nantahala 93 1932), the latter of which is a federally listed subspecies under the U.S. Endangered Species Act (Greenwalt 1978). Patera c. clarkii is distributed in the southern Appalachi- an Mountains in northwestern Georgia, western North Carolina, and eastern Tennes- see, USA (Fig. 1; Pilsbry 1940). Patera c. nantahala, the Noonday Globe Snail, inhabits a much smaller range, occupying approximately 3.3 km’ on the southeast slope, facing northwest, of the Nantahala Gorge in North Carolina (Fig. 1; Clench and Banks 1932; Van Devender 1984). Clench and Banks (1932) originally described P c. nantahala as a distinct species in the genus Polygyra Say, 1818, but Pilsbry (1940) recognized nantahala at the rank of subspecies, within Mesodon clarkii, based on shell morphol- ogy. Emberton (1991) elevated Patera Albers, 1850 from Mesodon Férussac, 1821 and included P clarkii in Patera. Emberton (1995) appeared to consider P c. nantahala a valid subspecies when briefly discussing the listing status of polygyrids under the U.S. Endangered Species Act, but subspecies were not included in his list of species. Perez et al. (2014) was the first molecular phylogenetic study to infer that Patera species in the subgenus Patera, which includes Patera clarkii (Emberton 1995), are monophyletic. However, no molecular study has assessed the status of P c. nantahala. oo —— An owe ck creation fe ’ ge fea. a r Tatt % / : to ais eget Norris, ee a in Si take x % ae aay f _ Morristown Pa Pe yf NG aye ; a Sia ae . ie Sp Dougla pe: us al Yaa ese Manhattan Knoxville aer = it a WS ir x Park i gg soph 5876 it ce 25 fa eal + = 7 5s “> £ > heal 3 ata _benoir N petites Ce (hen ; f b Morganton Hickoy . zip ye y 16 i 4 Pe Pye ee a 7 su ' a4 f «eT | Chatlilhoachee : om " he é National Forest oT oe 2 r 2 rnft k ul t 4 ( rae RO are Patera clarkii from other studies Patera nantahala collected for this study Patera aff. clarkii clade 1, included in phylogenetic analyses Patera aff. clarkii clade 2, included in phylogenetic analyses ow % i ea Figure |. Map of records used for environmental niche modeling and phylogenetic analyses. Inset: Re- cords collected here and included in molecular analyses. Only samples collected from locations in the inset were used for 3RAD analyses. Top right: photograph of P nantahala in its natural habitat. Photograph by Gary Peeples (USFWS). 94 Nathan V. Whelan et al. / ZooKeys 1158: 91-120 (2023) Aside from morphological and range information from the original species de- scription and museum records, little is known about P c. nantahala. Based on the type specimens, P c. nantahala has a larger shell diameter and a more depressed spire in relation to overall shell size (Fig. 2) than P c. clarkii. Patera c. nantahala also has a smaller parietal tooth and a less pronounced denticle on the baso-palatal wall of the aperture. Patera c. nantahala inhabits heavily forested calcareous rocks that receive little daylight because of the Nantahala Gorge’s slope and position (Fig. 1), making its habitat unique from that of geographically proximate locations where Pc. clarkii is found. Patera c. nantahala was listed as threatened under the U.S. En- dangered Species Act because of its extremely restricted range and concerns about potential habitat destruction from a proposed highway project (Greenwalt 1978). Currently, there are no plans to move forward with the highway project (Mays 2021), but P c. nantahala relies on moist, shaded habitats that could be damaged by impacts to forest canopy such as wildfire, invasive species, and drought. For ex- ample, Pc. nantahala appeared to decrease in abundance after a prolonged drought in 2007-2009 (Mays 2021). Objective morphological and phylogenetic analyses are needed to evaluate tax- onomic hypotheses (Nekola and Horsak 2022). However, with so few data avail- able, the taxonomic status of P c. nantahala remains untested and its phylogenetic placement uncertain. Here, we generated mitochondrial and nuclear genomic data- sets for P c. clarkii, P c. nantahala, an intermediate form, and the outgroup P perigrapta (Pilsbry, 1894) to assess relationships among lineages and to test for evi- dence of gene flow. We also investigated morphological and environmental niche overlap between putative P clarkii subspecies. Molecular results, in combination with habitat and morphological information, form the basis for proposed taxo- nomic revisions that better reflect diversity in Patera and will result in improved conservation focus. eg Figure 2. Photographs of type specimens A holotype of Patera nantahala, MCZ 86429 B syntype of Patera clarkiit, MCZ 93923. Scale bar: 1 cm. Systematics of Patera nantahala 95 Materials and methods Taxon sampling and morphological documentation Patera c. clarkii, Pc. nantahala, and P perigrapta were collected from eastern North Carolina in the Nantahala National Forest (Table 1; Figs 1, 3, 4). Collections in- cluded one individual with a morphology intermediate between the type specimens of Pc. clarkii and P c. nantahala that we initially hypothesized was a hybrid be- tween the two putative subspecies (Fig. 4D; individual “P aff. clarkii 008”). Sam- pling locations were chosen strategically as likely contact zones, making the taxon sampling of this study well-suited to test the taxonomic status of the two subspe- cies. Individuals were placed in 95% ethanol in the field. A ~ 3 mm‘% tissue clip was taken from each individual for DNA extraction, and some shells had to be cracked to access the tissue. All shells were photographed. The shell vouchers for all sequenced individuals have been deposited at the National Museum of Natural History (Table 1). Table I. Collection localities, molecular data accession numbers, and museum catalog numbers of indi- viduals collected in this study. Individual Collection Location GPS Coordinates USNM GenBank ## (COI, H3, 28S) SRA ## HHT Patera aff. clarkii 001 Winding Stairs next to 35.285, -83.668 1522402 OQ617117, OQ628057, SRX19664328 Queens Creek OQ628452 Patera aff. clarkii 002 Winding Stairs next to 35.285, -83.668 1522403 OQ617115, OQ628064, SRX19664327 Queens Creek OQ628453 Patera aff. clarkii 003 Winding Stairs next to 35.285, -83.668 1522404 0Q617116, OQ628063, SRX19664326 Queens Creek OQ628454 Patera aff. clarkii 004 Adjacent to Wesser Creek 35.334, -83.654 1522405 OQ617118, OQ628065, SRX19664325 and Nantahala River OQ628455 Patera aff. clarkii005 Adjacent to Handpole 35.281, -83.682 1522406 OQ617119, OQ628058, SRX19664324 Branch OQ628456 Patera aff. clarkii006 Adjacent to Handpole 35.281, -83.682 1522407 , OQ628059, SRX19664323 Branch OQ628457 Patera aff. clarkii007 Adjacent to Handpole 35.281, -83.682 1522408 OQ617120, OQ628060, SRX19664322 Branch OQ628458 Patera nantahala 001 Southeast Cliff of 35.308, -83.644 1522409 OQ617122, OQ628062, SRX19664333 Nantahala Gorge OQ628460 Patera nantahala 002 Southeast Cliff of 35.308, -83.644 1522410 0Q617123, OQ628056, SRX19664332 Nantahala Gorge OQ628461 Patera nantahala 003 Northeast corner of 35.336, -83.620 1522411 O0Q617124, OQ628055, SRX19664329 Nantahala Gorge OQ628462 Patera perigrapta 001 Winding Stairs next to 35.285, -83.668 1522398 OQ617112,OQ628052, SRX19664334 Queens Creek OQ628463 Patera perigrapta 002 Adjacent to Wesser Creek = 35.333, -83.587 1522399 OQ617114, OQ628053, SRX19664330 OQ628464 Patera perigrapta 003 Wayah Road, Nantahala = 35.257, -83.656 1522400 OQ617113, OQ628054, OQ628465 Patera aff. clarkii 008 Adjacent to Wesser Creek — 35.333, -83.587 1522401 0Q617121, OQ628061, SRX19664331 0Q628459 96 Nathan V. Whelan et al. / ZooKeys 1158: 91-120 (2023) Figure 3. Shell morphology of Patera aff. clarkii from Clade 1 A P aff. clarkii 001, USNM 1522402 B P aff. clarkii 002, USNM 1522403 C P aff. clarkii 003, USNM 1522404 D P aff. clarkii 005, USNM 1522406 E P aff. clarkii 006, USNM 1522407 F P aff. clarkii 007, USNM 1522408. We also obtained loans of type material and other Patera clarkii ssp. lots from three major natural history collections: Harvard Museum of Comparative Zoology, the Academy of Natural Sciences Philadelphia, and the National Museum of Natural His- tory (Suppl. material 1). Subspecies identification was based on collector identification, Systematics of Patera nantahala D7 Figure 4. Shell morphology of P nantahala and P aff. clarkii from Clade 2 A P nantahala 001, USNM 1522409 B P nantahala 002, USNM 1522410 € P nantahala 003, USNM 1522411 D P aff. clarkii 008, USNM 1522401. location of collection, and comparisons to type material. Institutional abbreviations used in the text are: MCZ Harvard Museum of Comparative Zoology; ANSP Academy of Natural Sciences Philadelphia; USNM National Museum of Natural History. For mitochondrial analyses (see below), we obtained sequences of Patera and other Polygyridae from Perez et al. (2014: fig. 1). Sequences were obtained directly from the authors as the data were not available on GenBank. No other sequences for Patera were publicly available at the time of this study. Genetic data generation DNA was extracted from tissue clips with the Qiagen DNeasy Plant Mini Kit using a slight modification to incorporate a proteinase K tissue digestion step. A plant kit 98 Nathan V. Whelan et al. / ZooKeys 1158: 91-120 (2023) was used because it handles mucopolysaccharides in snail tissue better than standard animal kits (Whelan et al. 2019). DNA was quantified on a Qubit fluorometer. An aliquot was taken from each DNA extraction and diluted to 20 ng/uL. Three genes were targeted for Sanger sequencing: 1) mitochondrial cytochrome c oxidase I, 2) nuclear 28S rRNA, and 3) nuclear Histone H3. PCR amplification for COI used primers dgLCO-1490 (5° GGTCAACAAATCATAAAGAYATYGG 3’) and dgHCO-2198 (5°TAAACTTCAGGGTGACCAAARAAYCA 3’) (Meyer 2003). Reactions occurred in 25 pL volumes consisting of 5 wL 5x GoTag Flexi Buffer (Pro- mega), 2.5 uL MgCl, (25 mM), 1 uL of each primer (10 uM), 1 pL dNTP solu- tion (10 mM), 0.1 U GoTaq DNA polymerase (Promega), and 20 ng whole genomic DNA. PCR cycling used an initial denaturation at 94 °C for 2 min; 35 cycles of 94 °C for 30 s, 45 °C for 30 s, 72 °C for 1 min; and a final extension at 72 °C for 5 mins. PCR amplification for 28S used primers 28S-VI (5’ AAGGTAGCCAAATGCCTCATC-3’) and 28S-X (5’-GTGAATTCTGCTTCATCAATGTAGGAAGAGCC-3’) (Hillis and Dixon 1991). Reactions occurred in 25 pL volumes consisting of 5 pL GoTagq Flexi Buffer, 2.5 wL MgCl, (25 mM), 1 pL each primer (10 pM), 1 pL dNTPs (10 pM), 0.1 U GoTaq DNA polymerase, and 10 ng genomic DNA. PCR for 288 cycling used an initial denaturation at 94 °C for 2 min; 30 cycles of 94 °C for 30 s, 50 °C for 30 s, 72 °C for 30 s; and a final extension at 72 °C for 5 mins. PCR for H3 used primers H3F (5’°-ATGGCTCGTACCAAGCAGACVGC-3’) and H3R (5’-ATATCCTTRG- GCATR ATRGTGAC-3’) (Colgan et al. 1999), and the same reaction chemistry as 28S. H3 PCR cycling used initial denaturation at 94 °C for 2 min; 30 cycles of 94 °C for 30 s, 55 °C for 30 s, 72 °C for 30 s; and a final extension at 72 °C for 5 mins. Raw PCR products were purified using the New England Biolabs Monarch PCR & DNA cleanup kit following manufacturer's protocol. Cleaned PCR products were sent to GeneWiz for Sanger sequencing in both directions using the same primers as used in PCR reactions. After finding a lack of variation in nuclear genes (see results), we generated a ge- nome-scale dataset for two individuals of P perigrapta and all P clarkii sensu lato (s.1.) that we successfully Sanger sequenced. To do this, we used the “3RAD” restriction site associated DNA sequencing reduced representation sequencing approach (RAD-seq; Bayona- Vasquez et al. 2019). 3RAD has advantages over other RAD-seq approaches by reducing adapter-dimer formation, allowing incorporation of a random 8 bp Illumina i5 index for removing PCR duplicates during assembly, and using a sequencing strat- egy (2 x 150 paired-end) that results in 200 bp, or greater, contigs. The long contigs generated with 3RAD, compared to some other RADseq approaches (e.g., 2bRAD; Wang et al. 2012), are particularly useful for phylogenetics. We followed the original 3RAD protocol with slight modification (full protocol available from https://github. com/NathanWhelan/3RAD_protocols/). The digestion step used restriction enzymes Nhel, EcoRI, and Xbal. Patera libraries were combined with samples from other stud- ies that had unique barcodes, resulting in 192 libraries that were sequenced at the University of Oregon Genomics and Cell Characterization Core facility on an Illumina NovaSeq 6000 using an SP flow cell with 2 x 150 paired-end sequencing chemistry. Systematics of Patera nantahala 99 Molecular data analyses Raw Sanger sequencing chromatograms were visualized in Geneious Prime and checked for sequencing errors. For the two nuclear genes, sites with two chromatogram peaks of equal intensity on both the forward and reverse sequences were coded as heterozy- gous using standard IUPAC codes. Each gene was aligned with Clustal Omega 1.2.2 (Sievers et al. 2011). All 28S sequences were identical, so 28S was not used in phylo- genetic analyses. We inferred a COI mitochondrial gene tree and an H3 nuclear gene tree separately. First, the best-fit substitution models and partitions were identified with ModelFinder using the Bayesian information criterion (BIC) (Kalyaanamoorthy et al. 2017) as implemented in IQTREE 1.6.12 (Nguyen et al. 2015); codon posi- tions were used as starting blocks. Maximum likelihood tree inference was then done in IQTREE using best-fit models and partitions. Tree search used default parameters, except perturbation strength was set to 0.2 and number of unsuccessful steps to stop tree inference was set to 500. Support was measured with 1,000 ultrafast bootstrap replicates (Hoang et al. 2018). Average pairwise distances among P clarkii s.1. clades were calculated in MEGAX 10.2.6 (Kumar et al. 2019). An automatic species delimitation approach was used to generate species-level taxonomic hypotheses. For this, we used COI data with Assemble Species by Auto- matic Partitioning (ASAP; Puillandre et al. 2021). ASAP has improved performance and less subjectivity in choosing delimitation schemes than its predecessor, the widely used Automatic Barcode Gap Discovery method (ABGD; Puillandre et al. 2012). ASAP was chosen over other methods because ABGD was previously shown to work well compared to other methods on gastropods with low dispersal ability (Strong and Whelan 2019). We also chose to use ASAP because it is not based on the coalescent model, and methods that use the coalescent tend to over split species (Sukumaran and Knowles 2017; Strong and Whelan 2019). For ASAP, the COI dataset was trimmed of outgroups to only include P c. clarkii and P c. nantahala. First, the best fit model for the trimmed dataset was inferred with ModelFinder in IQ-TREE. Second, we cal- culated best-fit model maximum likelihood distances among individuals with PAUP* 4.0a build 169 (https://paup.phylosolutions.com) using model parameters inferred by ModelFinder. Finally, ASAP analyses were performed with the ASAP web server (https://bioinfo.mnhn.fr/abi/public/asap/) using maximum likelihood distances. Raw 3RAD sequence data were demultiplexed into individual libraries with the STACKS 2.53 script process_radtags (Rochette et al. 2019). One mismatch per bar- code was allowed. Reads that lacked restriction enzyme sites were discarded. After demultiplexing, PCR clones in each library were removed using the STACKS script clone_filter. PCR clones were identified with the random sequence i5 index used dur- ing library preparation. After demultiplexing and clone filtering, data were assembled using the STACKS denovo_map.pl pipeline. We first used the method described by Paris et al. (2017) to identify appropriate assembly parameters. ‘The best parameters for our data were deter- mined to be a minimum stack depth of three (-m 3), five mismatches allowed between 100 Nathan V. Whelan et al. / ZooKeys 1158: 91-120 (2023) stacks within individuals (-M 5), and five mismatches allowed between stacks among individuals (-n 5). Contigs were assembled by denovo_map using paired-end informa- tion. All other assembly parameters were set to default. After assembly, the STACKS program populations was used for final data filtering. To pass filters, loci had to be present in 100% of individuals, have a minimum minor allele frequency of 0.025, and have an observed heterozygosity frequency of no more than 0.5. These parameters were chosen to eliminate missing data and filter potential paralogs or sequencing errors. All SNPs per locus were retained. Processed data were output into various file formats by STACKS for downstream analyses. Some contigs, or RAD loci, did not have overlapping reads because the locus was longer than 300 bp, which STACKS represented as a string of Ns. These were re- moved prior to phylogenetic analyses with the custom script noGaps-nucleotides.sh. Maximum likelihood gene trees were inferred for each RAD locus with IQTREE. ModelFinder, as implemented in IQTREE, was used for substitution testing using the BIC; partition finding was not done because RAD loci are unlikely to be found only in exons. Tree inference and bootstrapping for RAD loci were the same as for Sanger sequenced genes. ASTRAL III (Zhang et al. 2018) and the RAD-loci nuclear gene trees were used to infer a species tree. This method uses the multispecies coalescent to resolve gene tree conflict and assumes that all gene tree discordance is a result of incomplete line- age sorting (Rannala and Yang 2003). Prior to using the inferred maximum likelihood trees of each gene for species tree inference, all branches with 10% ultrafast bootstrap support or less were collapsed with Newick Utilities Junier and Zdobnov 2010). Col- lapsed maximum likelihood trees for each gene and default parameters were used as ASTRAL input. Individuals were not assigned a priori taxon designations. Support was measured with local posterior probability (Sayyari and Mirarab 2016). Given that focal taxa were putative subspecies where some gene flow is expected, introgression is a potential cause of gene tree discordance (Maddison 1997). To test for a signal of introgression, we used the phylogenetic network method SNAQ (Solis-Le- mus and Ané 2016) implemented in PhyloNetworks (Solis-Lemus et al. 2017). Unlike implicit network approaches that visualize discordance (e.g., SplitsTree; Huson and Bryant 2006), networks inferred with SNAQ can represent explicit reticulation events and all nodes represent ancestors (Solis-Lemus and Ané 2016). SNAQ is also an ap- propriate method for the current taxon sampling as genome-wide markers, combined with a network approach, allows estimating gene flow across the evolutionary history of a lineage. Maximum likelihood trees used for ASTRAL input were used in SNAQ to calculate concordance factors, and the ASTRAL species tree was used as the starting tree. Five separate networks that allowed for 0-4 reticulations (4), respectively, were inferred with ten replicates each. The best-fitting number of reticulations was assessed by examining the log pseudolikelihood profile of /, following Solis-Lemus and Ané (2016). Inferred networks that conflicted with the outgroup position of P perigrapta were discarded, and we instead retained the network for each / with the highest log pseudolikelihood value that did not conflict with root position. Goodness-of-fit of Systematics of Patera nantahala 101 each network was also examined by plotting observed concordance factors versus ex- pected concordance factors for each network. The R package ggplot2 (Wickham 2009) was used for plotting. Morphological analyses All shell vouchers for molecular samples and most shells obtained from museum collec- tions were used to assess morphological similarity between P c. nantahalaand Pc. clarkii via geometric morphometrics (Suppl. material 1). We used a maximum of four shells per museum lot; shells with damage in areas important for assigning landmarks were also excluded. Shells were photographed in apertural view with the axis of coiling paral- lel to the camera sensor (Fig. 5). Photographs were taken on a Canon EOS 80D with a 100 mm f/2.8 macro lens. Photographs of a ruler at the same scale as the shell pho- tographs were also taken so we could test differences in shell size in addition to shape. We used tpsUtil version 1.82 (Rohlf 2021a) to convert photographs to tps file format. Photographs were reordered randomly to limit landmark placement biases sys- tematically affecting samples from the same lot. tpsDig2 version 2.32 (Rohlf 2021b) was used to place 12 landmarks on each shell (Fig. 5). Landmarks were chosen based on inferred ability to consistently place them in homologous positions. Geometric morphometric analyses were conducted in MorphoJ (Klingenberg 2011). First, a Procrustes fit was applied to the dataset to account for differences in shell size, Patera clarkii s.1. Patera nantahala Frequency hb ho L °4°0 -3.0 -2.0 -1.0 0.0. 1.0 Canonical variate 1 Figure 5. Landmarks used for geometric morphometrics and history of canonical variate scores. Shells are type specimens and points represent landmarks connected by wireframe that shows shape variation. Wire- frame graphs under CVA plots represent extremes and show shape changes associated with canonical variates. 102 Nathan V. Whelan et al. / ZooKeys 1158: 91-120 (2023) position, and image rotation. Correct landmark digitization and the presence of outliers were checked by eye for all samples using Mahalanobis distance (Klingenberg and Mon- teiro 2005), which was inferred by MorphoJ to be more appropriate than Squared Pro- crustes distance for our dataset. Incorrect digitization of landmarks was corrected via the “Swap Landmark” command when the deviation from the average of any two landmarks on the same shell clearly pointed at each other (see MorphoJ manual for more details). Differences in shape were measured using two statistical tests. First, a Procrustes ANOVA was performed to test for significant differences in shape between the two pu- tative subspecies. Then, a canonical variate analysis (CVA) was performed in Morpho] to visualize shape differences and further assess evidence for shape differences between Pc. clarkii and Pc. nantahala. For the CVA, a permutation test of pairwise distances between putative subspecies was performed to test for significance using 1,000 itera- tions per comparison. Wireframe graphs were plotted to visualize morphological vari- ation along the CVA axis. A Procrustes ANOVA was also performed to test for signifi- cant differences in centroid size, which is a measure of shell size. Environmental niche modeling Patera c. nantahala is an ideal taxon for examining the utility and accuracy of envi- ronmental niche models because its range is extremely restricted and well defined. We also wanted to quantify potential environmental niche overlap between P c. clarkii and P c. nantahala. First, we downloaded collection records of P clarkii from the Global Biodiversity Information Facility (GBIF) that had latitude and longitude information (GBlEorg 2022). One record of P c. clarkii from New Jersey was removed from the downloaded dataset (GBIEorg 2022) as P clarkii is not known to occur north of North Carolina (Hubricht 1985). A GBIF record of P c. nantahala from iNaturalist was also removed because the precise location was obscured reflecting the species’ threatened status. Records from Perez et al. (2014) and our own collections were added to those downloaded from GBIF (Fig. 1). Perez et al. (2014) did not provide latitude and lon- gitude, so we determined reported locations based on their descriptions and coordi- nates determined from Google Earth. To reduce potential biases associated with spatial autocorrelation of species records, we spatially rarefied locality records at a distance of 1 km with SDMtoolbox 2.0 (Brown et al. 2017) in ESRI ArcGIS Pro; 1 km was cho- sen given the small distance between P c. nantahala records. Continuous environmental variables that covered the spatial extent of collection records (Fig. 1) were downloaded from publicly available sources as raster files. Biocli- matic data from WorldClim (Fick and Hijmans 2017) were downloaded at 30 second resolution with the R package raster (Hijmans 2022). Erodibility and albedo raster files were downloaded from the USA Soils dataset (SSURGO; Soil Survey Staff 2022) via ESRI ArcGIS Living Atlas of the World at 30-meter resolution. Categorical soil map unit data were also downloaded from SSURGO to examine differences in habitat, but categorical data were not included in environmental niche models. Forest canopy cover (i.e., proportion of floor covered by vertical projection of tree crowns), forest canopy Systematics of Patera nantahala 103 base height (i.e., average height to the top of tree canopy), vegetation height (ie., vertically projected cover of live plants), and vegetation cover (i.e., average height of dominant vegetation) were downloaded at 30-meter resolution from LANDFIRE ver- sion LF 2016 Remap (LANDFIRE 2020). Elevation data were downloaded from The National Map at 1/3 arc-second resolution (U.S. Geological Survey 2020); elevation data at 1/3 arc-second resolution were only available as multiple raster files across the study extent, so raster files were combined in ESRI ArcGIS Pro using the “Mosaic to Layer” tool. Slope and aspect data were created from the elevation data in ArcGIS Pro using the “Slope” and “Aspect” tools, respectively. Environmental data used in niche modeling were chosen to represent potentially unique features of the Nantahala Gorge and its habitat (e.g., steep slope, soil type, vegetation, and limited sunlight). Environmental data raster files were trimmed to cover the area where samples were collected (Fig. 1) in ArcGIS Pro and bicubic resampling was used to ensure each raster had the same cell size of 0.0005. Data were resampled to a cell size of 0.0005 to balance processing speed and resolution of taxa whose records were sometimes barely more than 1 km apart. For data with the USGS version of USA Contiguous Albers Equal Area Conic as their native projection, we used ArcGIS pro to reproject to the World Geo- detic System 1984 projection. After data transformation, all data raster files were ex- ported from ArcGIS Pro as .tif files for use in R. Data points of “NA” were changed to “0” because some datasets (e.g., LANDFIRE) coded water bodies as NA, rather than 0. Raster files were loaded into R with the “raster” command of the package raster and stacked into a single variable. Correlation of the different environmental data lay- ers was assessed on P c. clarkii collection records with “raster.cor.matrix” and “raster. cor.plot” commands of the R package ENMTools (Warren et al. 2021). Correlated variables were determined with only the P c. clarkii dataset because there were con- siderably more records for P c. clarkii than P c. nantahala. We removed all but one of any given environmental layer that had high correlation with other layers (Pearson correlation coefficient > 0.70; see Table 2 for variables used in final datasets). To exam- ine effects of performing niche modeling using bioclimatic data such as temperature and precipitation versus geographical and biotic data such as elevation and vegetation cover, we created three datasets: 1) all variables; 2) only bioclimatic data; 3) biotic, geological, and geographic (Table 2). Environmental niche models, sometimes referred to as species distribution mod- els, of Pc. clarkii and P c. nantahala were generated with the R package ENMTools 1.0 (Warren et al. 2021). For each taxon, niche models were generated with all three datasets using Maxent and the generalized linear model (GLM) method in ENMTools. Relative contribution of variables to each model was determined by model-specific variable importance analysis with the command “enmtools.vip” and the “permute” method in ENMTools. Niche models and variable importance plots were plotted in R. We used the “identity.test” function of ENMTools to test whether the niche of each putative subspecies was significantly different. Tests were done with 100 replicates and 10,000 background points. The niche overlap metrics D (Schoener 1968) and I (War- ren et al. 2018) were used in significance tests with a critical value of 0.05. 104 Table 2. Data used for environmental niche modeling. Nathan V. Whelan et al. / ZooKeys 1158: 91-120 (2023) Data Source Environmental Layer Data type Characteristics WorldClim BIOI Bioclimatic Annual mean temperature WorldClim BIO2 Bioclimatic Mean diurnal range WorldClim BIO3 Bioclimatic Isothermality WorldClim BIO4 Bioclimatic Temperature seasonality WorldClim BIO7 Bioclimatic Temperature annual range WorldClim BIO8 Bioclimatic Mean temperature of wettest quarter WorldClim BIO9 Bioclimatic Mean temperature of driest quarter WorldClim BIO12 Bioclimatic Annual precipitation WorldClim BIO15 Bioclimatic Precipitation seasonality SSURGO erodibility Geological Susceptibility of soils to erosion SSURGO albedo Geological Reflective property of surface LANDFIRE LC20_CC_200 Biotic Forest canopy cover LANDFIRE LC20_CBH_200 Biotic Forest canopy base height LANDFIRE LC16_EVH_200 Biotic Existing vegetation height LANDFIRE LC16_EVC_200 Biotic Existing vegetation cover The National Map Elevation Geographical Elevation from sea level Calculated from Elevation Layer Slope Geographical Slope of surface Calculated from Elevation Layer Aspect Geographical Direction land faces Data and code availability All scripts are available from https://github.com/nathanwhelan/Patera. STACKS output, alignments, COI distance matrix, tree files, SNAQ input and output, shell photographs, and environmental data raster files are available on FigShare https://doi. org/10.6084/m9.figshare. 19638642. Demultiplexed and decloned 3RAD data are available from NCBI SRA BioProject PRJNA944142. Results Molecular analyses Sanger sequencing for all three genes was successful for three P perigrapta individu- als, six P c. clarkii, three P c. nantahala, and one potential hybrid individual with an intermediate morphology (i.e., P aff. clarkii 008; Fig. 4D; Table 1). We were able to successfully sequence nuclear genes, but not COI, for one additional P c. clarkii individual. For 3RAD sequencing, after demultiplexing and clone filtering, the num- ber of raw paired-end reads per individual ranged from 256,990 to 1,899,741 (aver- age = 1,018,463). After filtering, 2,905 loci were retained. Loci had an average length of 273 bp, and 74.8% of loci had overlapping read pairs. The number of SNPs per locus ranged from 1—41, with an average of 14 SNPs per locus. The COI tree had greater taxon sampling than other analyses because only COI data were available for Patera and related Polygyridae from previous studies. Generally, deep divergences were inferred within putative species and multiple species were not monophyletic (Fig. 6). This could be the result of misidentifications, taxonomy in need Systematics of Patera nantahala 105 383026A Mesodon normalis 100 437674A Mesodon normalis 100) oo; 3830164 Mesodon normalis 88 446510A Mesodon normalis 65 90) 97! 446679A Mesodon normalis 437710A Mesodon normalis 63 447118A Mesodon normalis 447145A Mesodon zaletus 84 437673A Mesodon zaletus 94| 99————_ 382970A Mesodon zaletus 94 L__._ 447247A Mesodon zaletus 437721A Mesodon zaletus tl 446565A Mesodon altivagus 83 446585A Fumonelix wheatleyi L_83 100;-— 447151A Mesodon thyroidus 100] 437699A Mesodon thyroidus 97 447199A Mesodon thyroidus — 437756A Mesodon clausus 67 eS 447126A Mesodon mitchellianus a 360273A Mesodon elevatus gal aap Se Appalachina sayana 7672A Appalachina chilhoweensis Lez}+}—____ 4377; A Appatetis sayana 7 437733A Songun sayana 42 85 434344A Patera perigrapta 448706A Patera perigrapta 382967A Patera perigrapta 382963A Patera perigrapta 434335A Patera perigrapta -— 437742A Patera pengrapta 78 Patera perigrapta 001 Patera perigrapta 002 Patera perigrapta 003 98 437677A Patera perigrapta 437669A Patera perigrapta 437662A Patera aff. clarkii 91). 437713A Patera aff. clarkii 99, Pelee aM ora ee atera aff. clarkii 83 98] ; Patera aff. clarkii 001 Clade 1 Patera aff. clarkii 004 n a ~ fe} Patera aff. clarkii 007 70! Patera aff. clarkii 005 99-——._ 437643A Patera aff. clarkii 44 7250A Patera aff. clarkii | Clade 4 86, Patera nantahala 0! Patera nantahala 003, Clade 3 Patera nantahala 0 Patera aff. clarkii 008 446639A Patera aff. eal Clade 2 447200A Patera sargentiana 0.08 448791A Patera sp. 66) 437676A Patera appressa 68 | 92, 437722A Patera appressa baby Patera laevior 99 474 A. Patera perigrapta aSv757A Patera appressa Figure 6. COI maximum likelihood tree. Branches are labelled with ultrafast bootstrap support. Clades within P clarkii s.|. are labelled with numbers referred to in the main text. Scale is in substitutions per site. of revision, or more likely both. One individual of “P perigrapta”, (447175A) that was sequenced by Perez et al. (2014), was placed sister to an individual of Patera appressa (Say, 1821), indicating that 447175A was most likely misidentified. Patera clarkii s.1. was recovered in four main clades on the COI tree, all of which had ultrafast bootstrap support greater than 90 (see labels on Fig. 6). All sequenced in- dividuals that we initially identified as P c. clarkii (i.e., excluding the possible hybrid), were in a clade with two individuals sequenced by Perez et al. (2014) that were col- lected from northern Georgia (Clade 1, Fig. 6). This clade was sister to two additional P c. clarkii individuals from Perez et al. (2014) that were also collected in northern Georgia (Clade 4, Fig. 6). Clade 3 contained three P c. nantahala individuals and was sister to Clades 1 and 4 (Fig. 6). The sister clade to all other P clarkii s.1. contained the individual that we initially hypothesized to be a hybrid (individual P aff. clarkii 008) and an individual from eastern Tennessee that was identified as P clarkii by Perez et al. (2014; Clade 2, Fig. 6). The “aff.” epithet is used hereafter because both “P c. clarkii” lineages resemble the type, but we are unable to determine which lineage, if either, is true P c. clarkii (see below). Relationships among the four clades within P clarkii s.l. had limited support on the COI gene tree. However, pairwise distances among P clarkii s.\. clades were high, ranging from 9.3%—12.5%. Automatic species delimita- tion analysis with ASAP indicated the presence of four putative species, corresponding to the four main clades of P clarkii s.1. on the COI tree (Fig. 6). In contrast to the COI tree, there was virtually no resolution on the H3 gene tree as no node had greater than 89% ultrafast bootstrap support (Fig. 7). Two P c. nanta- hala individuals had a private H3 allele and were sister to each other on a long branch 106 Nathan V. Whelan et al. / ZooKeys 1158: 91-120 (2023) | Patera perigrapta 002 89! Patera perigrapta 001 Patera perigrapta 003 63, Patera nantahala 003 Patera nantahala 002 0.001 85] Patera aff. clarkii 007 59| Patera nantahala 001 Patera aff. clarkii 008 45! Patera aff. clarkii 005 62 67| Patera aff. clarkii 001 Patera aff. clarkii 006 Patera aff. clarkii 002 73 89 Patera aff. clarkii 003 Patera aff. clarkii 004 Figure 7. H3 maximum likelihood tree. Branches are labelled with ultrafast bootstrap support. Scale is in substitutions per site. 0.48 Patera aff. clarkii 002 Patera aff. clarkii 003 10 Patera aff. clarkii 004 Patera aff. clarkii 006 Clade 1 0.45 Patera aff. clarkii 007 0.99 es Patera aff. clarkii 005 Patera aff. clarkii 001 Patera nantahala 003 1.0 1.0 10 Patera nantahala 002 | Clade 3 Patera nantahala 001 Patera aff. clarkii 008] Clade 2 10 Patera perigrapta 002 0.7 Patera perigrapta 001 Figure 8. ASTRAL species tree. Branches are labelled with local posterior probability. Clades are labelled with numbers referred to in the main text. Scale is in coalescent units. within a clade consisting of most P clarkii s.l. individuals. Two P c. clarkii individuals were sister to all other P clarkii s.l. All individuals that we sequenced had the same 28S sequence, including the three P perigrapta individuals that served as outgroups. Three P clarkii s.l. clades were resolved on the ASTRAL species tree, each hav- ing 100% local posterior probability (Fig. 8). The absence of a clade on the ASTRAL tree corresponding to Clade 4 on the COI tree was likely a result of the two Clade-4 individuals from Perez at al. (2014) not being available for genome-based ASTRAL analysis. ASTRAL clades were given designations 1, 2, and 3 to match those on the Systematics of Patera nantahala 107 COI tree and distinguish between the two P aff. c. clarkii lineages and P c. nantahala. The clade with the individual initially identified as a possible hybrid between P c. clarkii and P c. nantahala (i.e., individual P aff. clarkii 008) was placed in “Clade 2”, whereas other P c. clarkii were placed in “Clade 1”. Relationships among clades on the ASTRAL species tree were congruent with the COI mitochondrial gene tree (Figs 5, 8), albeit without individuals from Perez et al. (2014) on the ASTRAL tree. Analyses with SNAQ indicated that the data were tree-like as the zero-reticulation model and one-reticulation model had similar pseudo log-likelihood values (Suppl. material 2: fig. S1). Expected versus observed concordance factor plots were also similar between models with no obvious outliers on the zero-reticulation model compared to the one- reticulation model (Suppl. material 2: fig. S2). The reticulation event on the one- reticulation network had a gamma value of less than 3.5 (Suppl. material 2: fig. $3). Thus, SNAQ analyses rejected our hypothesis that individual P aff. clarkii 008 was a hybrid. SNAQ analyses also rejected recent or ongoing gene flow among P clarkii s.1. clades, including among P c. nantahala and the P aff. c. clarkii clades. Shell shape and size variation The final morphometric dataset had 21 individuals of P c. nantahalaand 77 Pc. clarkii (Suppl. material 1). We were unable to separate the P aff. c. clarkii lineages for geo- metric morphometrics because we only had sequence data for one individual from Clade 2 and geographic and morphological characters to distinguish the P aff. c. clarkii lineages have not been documented and may not exist. This likely resulted in a greater breadth of shape for P c. clarkii, thereby increasing the chance of shape overlap be- tween P c. clarkii and P c. nantahala. Geometric morphometrics confirmed what was mostly evident by eye. Procrustes ANOVA indicated a significant size and shape difference between P c. nantahala and Pc. clarkii (p < 0.0001; Table 3). Canonical variate analysis indicated that 100% of shell shape variation was explained by a single axis and there was no overlap between the two subspecies (Fig. 5; Table 3). Permutation tests indicated significant differences in shell shape between P c. clarkii and P c. nantahala (p < 0.0001). Patera c. nantahala had a wider shell and a more compressed spire height compared to overall width (Fig. 5). The parietal tooth in P c. nantahala did not protrude as far as in P c. clarkii (Fig. 5). Several qualitative morphological differences distinguish P c. nantahala from P c. clarkii. The denticle on the baso-palatal wall is much more prominent in P aff. c. clarkii Clade 1 individuals (Fig. 3) and slightly more prominent in the P aff. c. clarkii individual from Clade 2 (Fig. 4D) than in P c. nantahala (Figs 2, 4A—C). Furthermore, the parietal tooth covers a larger part of the aperture in both P aff. clarkii Clades 1 and 2 (Figs 3, 4D) compared to P c. nantahala (Figs 2A, 4A—C). In two of the three sampled P c. nantahala individuals, mantle pigmentation displayed a branch- ing pattern (Fig. 4A, B), versus a horizontal band in P c. clarkii clades when present (Figs 3A—D, F, 4D). However, the branching pattern does not appear to be diagnostic as it is not visible on the types (Fig. 2), nor on one individual we collected (Fig. 4C). 108 Nathan V. Whelan et al. / ZooKeys 1158: 91-120 (2023) Table 3. Results of geometric morphometric statistical tests. Procrustes ANOVA for Shape Effect Procrustes Sum Procrustesmean degrees of — Goodall’s F pF) Pillai’s —_p (Pillai’s of Squares squares freedom trace trace) Species 0.080648 0.004032 20 11.98 < 0.0001 0.76 < 0.0001 Residual 0.646333 0.000337 1920 Procrustes ANOVA for Centroid Size Effect Procrustes Sum Procrustesmean degrees of — Goodall’s F p (Ff) of Squares squares freedom Species 6.258875 6.258875 1 73.29 < 0.0001 Residual 8.19893 0.085398 96 Canonical Variate Analysis Eigenvalues % Variance Mahalanobis p (Mahalanobis Procrustes p (Procrustes distance distance) distance distance) between species between species 3.180948 100 4.302 <0.0001 0.0699 < 0.0001 Environmental niche models and niche overlap After removal of several suspect records, occurrence data consisted of nine records for Pc. nantahala and 79 for P c. clarkii. Spatial rarification of the data resulted in a reduced dataset with three records for P c. nantahala records and 46 for P c. clarkii (Suppl. material 1). Environmental niche models inferred with Maxent resulted in much greater pre- dicted suitable habitat for P c. nantahala compared to GLMs, whereas models for Pc. clarkii were similar regardless of modeling method (Fig. 9). The relative impor- tance of any given variable was highly dependent on the modeling approach (i.e., Max- ent vs. GLM), the variables included, and whether P c. nantahala or Pc. clarkii was being modeled (Suppl. material 2: figs S4—S15). Models inferred with only BioClim variables resulted in considerably greater predicted suitable habitat for P c. nantahala than models that used all environmental variables. Similarly, models that used all vari- ables appeared to be least likely to overpredict suitable habitat of P c. clarkii based on its known range (Fig. 9). Patera c. nantahala only occupied locations that were clas- sified on the SSURGO soil map units as “Inceptisols: Sylco-Cataska complex, 50 to 95 percent slopes, very rocky”. Inceptisols are characterized as being from humid and subhumid regions with subsurface soil layers lacking illuviated material and without an ochric epipedon (Soil Survey Staff 1999). Some records of P c. clarkii were also from locations classified as “Inceptisols: Sylco-Cataska complex, 50 to 95 percent slopes, very rocky”. However, these records were separated from P c. nantahala by at least one different soil type, and P c. clarkii also occupied other soil types, including ultisols (i.e., soils with low base saturation and kandic or argillic horizons, generally with a vegeta- tion of coniferous or hardwood forests) and entisols (i.e., soils with little or no evidence of layers). For more details on soil types see Soil Survey Staff (1999). Overlap comparisons indicated significant differences in niches of P c. clarkii and Pc. nantahala when using GLMs and datasets with non-bioclimatic variables (p < 0.05; Table 4). Although not statistically significant, D and I values were also low for GLMs Systematics of Patera nantahala 109 P. clarkii GLM, all variables P. clarkii GLM, biotic, geological, and geographic P. clarkii GLM, Bioclimatic a Suitability 0.75 0.50 Latitude 34.5 =84 =83 82 =i 3 82 =a P. nantahala GLM, biotic, geological, and geographic ioclimati Latitude -84 -83 -82 -81 P. clarkii Maxent; biotic, geological, and geographic P. clarkii Maxent, Bioclimatic P. clarkii Maxent, all variables o CG =] = S o -84 -83 -82 -81 -82 -81 -84 -83 -82 -31 P. nantahala Maxent, biotic, geological, and geographic P, nantahala Maxent, Bioclimatic P. nantahala Maxent, all variables a ~ Longitude =84 83 =B1 =81 Longitude a Longituds- Figure 9. Environmental niche models for P clarkii and P nantahala. Brighter colors indicate locations with greater niche suitability. Table 4. D and I environmental niche overlap metrics for GLM and Maxent based niche overlap tests. Bold values indicate models with significant niche differences between P clarkii and P nantahala at o = 0.05. Non-bioclimatic variables Bioclimatic variables All environmental variables GLM: D 0.013 0.033 0.001 GLM: I 0.089 0.166 0.026 Maxent: D 0.334 0.361 0.163 Maxent: I 0.627 0.659 0.371 with only bioclimatic variables (Table 4). Maxent models did not indicate significant differences (p > 0.05), except with the D statistic on the model that was generated with all environmental variables (Table 4). However, the GLM with only bioclimatic vari- ables and all Maxent models clearly overpredicted suitable habitat for P c. nantahala (Fig. 6), which is why we emphasize the significant results. The P c. clarkii records included in environmental niche modeling potentially include more than one species (i.e., the multiple molecular P c. aff. clarkii lineages from Clade 1, Clade 2, and Clade 4; Figs 3, 4D, 6), but inferred niche differences should be robust as inclusion of the multiple lineages from GBIF records of “P c. clarkii” is likely to increase and homog- enize predicted habitat of P c. clarkii, which would have resulted in overestimating niche overlap. 110 Nathan V. Whelan et al. / ZooKeys 1158: 91-120 (2023) Systematics Family Polygyridae Pilsbry, 1895 Subfamily Triodopsinae Pilsbry, 1940 Tribe Mesodontini Tryon, 1866 Genus Patera Albers, 1850 Helix (Patera) Albers, 1850: 96. Type species: Helix appressa Say, 1821, by subsequent designation (Pilsbry 1930: 326) [non Patera Lesson, 1839 (Cnidaria)]. Remarks. Patera is a junior homonym of Patera Lesson, 1839 (Cnidaria). However, Patera Lesson, 1839 has only been used in a few treatises during the 19" century and at the beginning of the 20" century, whereas Patera Albers, 1850 is in widespread use. As such, continued usage of the junior homonym is in the best interest of stability and the case should be referred to the International Commission on Zoological Nomenclature for a ruling under Art. 23.9.3 of the Code (ICZN 1999). Patera nantahala (Clench & Banks, 1932) Polygyra (Triodopsis) nantahala Clench & Banks, 1932: 17, pl. 2, figs 1-3, 5. Mesodon clarki nantahala—Pilsbry 1940: 731, fig. 440g; Chambers 1981: 55-59; Hu- bricht 1983: 13; Hubricht 1985: 44; Richardson 1986: 45. Patera clarki nantahalae {sic|—Emberton 1995: 72. Type material. Holotype: MCZ 86429. GS Banks leg., 27 August 1930. Paratypes: ANSP 153664 (4 spms), GS Banks leg., 25 August 1930; MCZ 82533 (1 spm), Clench, Archer & Rehder leg., 7 August 1931; MCZ 185877 (3 spms), Clench, Rehder & Archer leg., July 1931, ex. A Archer collection; USNM 408310 (3 spms), Clench, Rehder & Archer leg., 1931. Type locality. Blowing Springs, cliff ridges, Nantahala Gorge, Swain County, North Carolina. Other material examined. USNM 1522409, USNM 1522410: Adjacent to unnamed tributary of Nantahala River, southeast cliff of Nantahala Gorge, Swain County, North Carolina, 35.308, -83.644, GenBank: OQ617122, OQ628062, OQ628460, OQ617123, OQ628056, OQ628461, SRA: SRX19664333, SRX19664332; USNM 1522411: Adjacent to Pizza by the River, northeast corner of Nantahala Gorge, Swain County, North Carolina, 35.336, -83.620, GenBank: O0Q617124, OQ628055, OQ628462, SRA: SRX19664329 ANSP 171736: Blow- ing Springs, Swain County, North Carolina; ANSP 348077: Nantahala Gorge, Swain County, North Carolina, 35.40, 83.25; MCZ 94130: Blowing Springs, Nantahala Gorge, Swain County, North Carolina. Systematics of Patera nantahala 111 Diagnosis. Shell imperforate, subglobose, weakly translucent, with 5.5—5.75 whorls. Teleoconch sculpture of coarse, prosocline, axial striae. Spire low, dome- shaped, sutures weakly impressed. Aperture lunate, peristome white, with small basal notch. Slightly curved parietal tooth, moderate in size for the genus. Mantle pigmenta- tion of branching lines in at least some individuals. Distribution. Restricted to the eastern slope of the Nantahala Gorge in North Carolina, USA. Ecology. Little is known about the ecology of P nantahala. The species appears to prefer the moist, highly vegetated habitats that receive little sunlight, which are typical of the eastern slope of the Nantahala Gorge. Found only in habitats with soil characterized by the SSURGO soil map as “Inceptisols: Sylco-Cataska complex, 50 to 95 percent slopes, very rocky”. Conservation status. Federally threatened under the U.S. Endangered Species Act. Listed as threatened by the state of North Carolina. Available data indicate that P. nantahala is in one of the three “threatened” IUCN ranking categories, likely falling under “endangered”. Remarks. All sampled P nantahala individuals are more similar to the holotype and paratypes of P nantahala than to the types of P clarkii. Shell shape of P nantahala differs significantly from closely related lineages (Figs 2-5; Table 3). We are unable to comment on internal anatomical variation among P aff. clarkii lineages and P nan- tahala because we did not preserve specimens in a manner suitable for anatomical work. Emberton (1995) examined internal anatomy of Patera and found no differences among P clarkii, P perigrapta, and other species in the subgenus Patera (Patera), mak- ing it unlikely that anatomical investigations would yield diagnosable features among the lineages examined here. Discussion Our results demonstrate that P nantahala is a distinct species based on molecular, mor- phological, and ecological data. Recognition of P nantahala renders P clarkii polyphyl- etic, and our phylogenetic analyses indicate that unrecognized species diversity still exists within P clarkii s.l. Recognition of P nantahala at the rank of species is also consist- ent with the framework developed by Horsakova et al. (2019) for recognizing “cryptic” species in terrestrial snails, who argued that multiple lines of evidence including mito- chondrial and nuclear concordance, quantitative morphological differences, and ecology should support a taxonomic hypothesis before recognizing entities at the species level. In contrast, a better understanding of the geographic ranges of the P aff. clarkii lineages and establishing which lineage should be ascribed to P clarkii s.s. is needed before a new species can be described. Our results emphasize the need for genome-based analyses to understand diversity and conservation of North American terrestrial snails. From a conservation standpoint, the original listing decision under the Endangered Species Act treated P nantahala as a distinct entity. Thus, our results support continued protection. 112 Nathan V. Whelan et al. / ZooKeys 1158: 91-120 (2023) Species, morphological, and genetic diversity Both mitochondrial and 3RAD data are congruent and demonstrate that P nantahala is reciprocally monophyletic with respect to P aff. clarkii lineages. Mitochondrial di- vergence among P nantahala and P. aff. clarkii lineages exceeds 9%, and both SNAQ and mitochondrial analyses indicate a lack of recent nuclear introgression. Thus, P. nantahala is a distinct evolutionary lineage. The observed absence of recent gene flow is unlikely to be a result of sampling error as sampling locations for P clarkii and P. nantahala were in close proximity and within likely contact zones. Furthermore, if gene flow was currently occurring, we would not expect divergence patterns on the mitochondrial tree and ASTRAL species tree to be congru- ent and to match morphological differences. Although some may argue that additional sampling of P nantahala would be desirable prior to revising its status, this is not prefer- able given its conservation status. Destructive sampling of museum specimens is not a suitable alternative given the paucity of preserved specimens and because techniques for 3RAD with dry shell material are unproven. Furthermore, network-based approaches with genomic data are sufficiently sensitive to assess gene flow, even with one or two in- dividuals per species (Solis-Lemus and Ané 2016; Mao et al. 2018; Watson et al. 2020). The branching pattern inferred in phylogenetic analyses supports the presence of several unrecognized species. Analysis with ASAP indicated that Clades 1-4 on the COI tree were each a distinct species (Fig. 6). As noted above, ASAP is not based on the multispecies coalescent, but rather barcode gaps, which has been shown to be more conservative in splitting entities into hypothesized species than other automatic delimitation methods (Strong and Whelan 2019). Nevertheless, automatic species de- limitation methods can give incongruent results, and the best automatic approach for land snails, if there is one, is unclear (Sauer and Hausdorf 2011; Greve et al. 2012; Prévot et al. 2013; Bamberger et al. 2022). The absence of gene flow among Patera clarkii s.l. lineages inferred with SNAQ also corroborates ASAP results. Notably, SNAQ found no gene flow between individual “P. aff. clarkii 008” (i.e., Clade 2; Figs 6, 8) with other clades, therefore rejecting our initial hypothesis that individual “P aff. clarkii 008” was a hybrid between P clarkii and P. nantahala. However, we refrain from describing a new species pending additional work to determine its geographic range. Furthermore, we are unsure whether Clade 1, 2, 4, or an unsampled lineage, represents true P clarkii because phylogenetic analyses did not include individuals from the type locality Tuskee [sic, Tuskeegee] Cove, Chero- kee County [now Graham County], North Carolina. However, individuals sampled closest to the type locality were in Clade 1. Topotypic material of the other available species-group name currently in the synonymy of P clarkii is also needed (i.e., Polygyra clarkii var. bradleyi Vanatta 1912) prior to species descriptions. We note that P clarkit is the correct original spelling and should be preserved under Article 31.1.3 of the Code (ICZN, 1999) even though “P clarki” is more commonly used in the recent literature. Geometric morphometrics showed that P nantahala has a significantly different shell shape compared to closely related congeners. We were unable to unambiguously Systematics of Patera nantahala 113 assign museum records to one of the three Patera aff. clarkii lineages because distin- guishing shell features or geographic ranges have not been established. Future studies with more P clarkii s.1. sampling for molecular phylogenetics will be necessary to allow confident clade assignments that can be used in geometric morphometrics. However, truly cryptic species may exist within Patera. Hubricht (1983) claimed that P clarkii exists in the Nantahala Gorge and P nanta- hala exists outside the Nantahala Gorge. These conclusions were based on comparisons of shell morphology, but the exact shell features, aside from shell size, used to support these conclusions were not reported. Phylogenetic analyses, geometric morphomet- rics, and environmental modeling results reject Hubricht’s (1983, 1985) hypothesis that P nantahala is not a valid subspecies. Although we cannot completely rule out that future survey work will find overlap in the range of P clarkii and P nantahala, the absence of gene flow and high genetic divergence indicate that the two species are reproductively isolated. Our results add to a growing body of research that used genomic tools to better un- derstand terrestrial snail evolution (e.g., Razkin et al. 2016; Phillips et al. 2020; Bober et al. 2021; Bamberger et al. 2022). When used in conjunction with distributional, ecological, and morphological data, as done here, genomic data appear especially well- suited for resolving polygyrid relationships. Our conclusions about species diversity likely would have been different, and incorrect, if we had relied only on 28S and H3 for nuclear genetic data. For instance, the H3 tree indicated little genetic differentia- tion among P clarkii s.\. lineages (Fig. 7), and 28S was invariant across P perigrapta, P. nantahala and P. clarkii s.\. Prior to generating nuclear data via 3RAD sequencing, we thought gene flow among sampled P clarkii s.l. was possible, if not probable, based on the 28S and H3 data. In contrast, 3RAD data indicate that incomplete lineage sorting, rather than gene flow, is responsible for a lack of resolution in the 28S and H3 genes. ‘This finding is essential for future research on polygyrids, and we encourage future studies to employ genomic data for population- and species-level research. Environmental niche models The environmental niches of P nantahala and P clarkii are significantly different ac- cording to GLM analyses with non-bioclimatic data included, which appear to be the most accurate given environmental niche model plots and known ranges (Fig. 9). For example, predicted suitable habitat using GLMs appears reasonable and not over- predicted, particularly when all environmental variables were used. We hypothesize that niche models with non-bioclimatic variables are more accurate because of unique abiotic features of the southeastern slope of the Nantahala Gorge. Maxent models for P. nantahala predicted suitable habitat far outside the known species range and in loca- tions where only shells that match the morphology of P clarkii have been recorded. Thus, disagreement in the significance of environmental niche differences between GLM and Maxent analyses appears to be a result of Maxent making overpredictions in the suitable habitat of P nantahala (Fig. 9). 114 Nathan V. Whelan et al. / ZooKeys 1158: 91-120 (2023) Our results indicate the need to be cautious when using environmental niche modeling approaches for understudied, narrow-range endemics. Most analyses over- estimated the distribution of P nantahala (Fig. 9), and we do not think that suitable habitat inferred with Maxent represents true suitable habitat or an unrecognized, po- tential niche for P nantahala. Furthermore, models that used only bioclimatic data performed worse, especially with P nantahala (Fig. 9). We argue that overestimation of environmental niche is at least possible, if not likely, for any narrow range endemic, especially when relying entirely on bioclimatic data. Most environmental data used in niche modeling, particularly BioClim data, are likely not of adequate resolution for distinguishing the environmental niches of extreme narrow-range endemics. Our re- sults indicate that if environmental niche models are to be generated for narrow-range endemics, environmental data other than bioclimatic variables are essential. Environmental niche models that include data other than bioclimatic information can be useful for assessing the potential for narrow-range endemics to occupy other habitats, but they may not always be necessary to make inferences about terrestrial snail distributions and environmental niches. For example, even before running en- vironmental niche models, SSURGO soil classifications of collection sites made clear that P nantahala only inhabits a single, uncommon soil type, whereas P clarkii s.l. in- habits many different soil types. More broadly, our results indicate that Maxent models will tend to overpredict ranges for narrow-range endemics. These findings should be applicable to other terrestrial snails. Conclusions Morphological, ecological, and phylogenetic data support Patera nantahala as a valid species. We hypothesize that the ancestor of P nantahala invaded the Nantahala Gorge, or became isolated in the gorge, and subsequently underwent allopatric speciation, with the Nantahala Gorge and Nantahala River serving as dispersal barriers. Although the recognition of P nantahala is a step in the right direction, the systematics of Polygyridae requires comprehensive revision. Despite calls for increased study (Perez 2011; Perez et al. 2014), little progress has been made. Our results suggest that phylogenetically distinct lineages of polygyrids remain unrecognized. As such, species that may require conserva- tion attention are being overlooked. This could lead to a loss of diversity and evolution- ary potential before we know how many species of polygyrids exist. To improve poly- gyrid systematics, both increased sampling and genome-wide markers will be needed. Acknowledgements This work would not have been possible without the resources provided by Biodiver- sity Heritage Library. Frank Kohler and Philippe Bouchet answered questions we had about MolluscaBase records, which improved the manuscript. Thanks to Paul Callo- Systematics of Patera nantahala 115 mon (ANSP), Amanda Robinson (NMNH), and Jennifer Trimble (MCZ) for facilitat- ing museum loans. Two anonymous reviewers and M. Haase provided feedback that improved an earlier version of this work. 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The Open Database License (ODDbL) is a license agreement intended to allow users to freely share, modify, and use this Dataset while maintaining this same freedom for others, provided that the original source and author(s) are credited. Link: https://doi.org/10.3897/zookeys.1158.94152.suppl1 Supplementary material 2 Additional images Authors: Nathan V. Whelan, Ellen E. Strong, Nicholas S. Gladstone, Jason W. Mays Data type: figures (PDF file) Copyright notice: This dataset is made available under the Open Database License (http://opendatacommons.org/licenses/odbl/1.0/). The Open Database License (ODDbL) is a license agreement intended to allow users to freely share, modify, and use this Dataset while maintaining this same freedom for others, provided that the original source and author(s) are credited. Link: https://doi.org/10.3897/zookeys.1158.94152.suppl2