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Article

A Comparative Phylogeographic Approach to Facilitate Recovery of an Imperiled Freshwater Mussel (Bivalvia: Unionida: Potamilus inflatus)

by
Chase H. Smith
1,2,* and
Nathan A. Johnson
3
1
Biology Department, Baylor University, Waco, TX 76798, USA
2
Department of Integrative Biology, University of Texas, Austin, TX 78712, USA
3
U.S. Geological Survey, Wetland and Aquatic Research Center, 7920 NW 71st Street, Gainesville, FL 32653, USA
*
Author to whom correspondence should be addressed.
Diversity 2020, 12(7), 281; https://doi.org/10.3390/d12070281
Submission received: 3 June 2020 / Revised: 30 June 2020 / Accepted: 10 July 2020 / Published: 17 July 2020
(This article belongs to the Special Issue Freshwater Mollusk Conservation)
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Abstract

:
North American freshwaters are among the world’s most threatened ecosystems, and freshwater mussels are among the most imperiled inhabiting these systems. A critical aspect of conservation biology is delineating patterns of genetic diversity, which can be difficult when a taxon has been extirpated from a significant portion of its historical range. In such cases, evaluating conservation and recovery options may benefit by using surrogate species as proxies when assessing overall patterns of genetic diversity. Here, we integrate the premise of surrogate species into a comparative phylogeographic framework to hypothesize genetic relationships between extant and extirpated populations of Potamilus inflatus by characterizing genetic structure in co-distributed congeners with similar life histories and dispersal capabilities. Our mitochondrial and nuclear sequence data exhibited variable patterns of genetic divergence between Potamilus spp. native to the Mobile and Pascagoula + Pearl + Pontchartrain (PPP) provinces. However, hierarchical Approximate Bayesian Computation indicated that the diversification between Mobile and PPP clades was synchronous and represents a genetic signature of a common history of vicariance. Recent fluctuations in sea-level appear to have caused Potamilus spp. in the PPP to form a single genetic cluster, providing justification for using individuals from the Amite River as a source of brood stock to re-establish extirpated populations of P. inflatus. Future studies utilizing eDNA and genome-wide molecular data are essential to better understand the distribution of P. inflatus and establish robust recovery plans. Given the imperilment status of freshwater mussels globally, our study represents a useful methodology for predicting relationships among extant and extirpated populations of imperiled species.

Graphical Abstract

1. Introduction

Due to anthropogenic alterations to the environment, the world is losing species at rates comparable to mass extinctions during major transitions of geological time periods [1,2]. North American freshwaters are among the world’s most threatened ecosystems [3], and freshwater mussels (Bivalvia: Unionida) are among the most imperiled groups of organisms inhabiting these systems with 65% of all recognized species considered to be of conservation concern [4,5,6]. Several inherent biological characters (e.g., limited locomotive capabilities in many species, extreme sensitivity to pollutants, obligate parasitism, and filter feeding) have disproportionately impacted mussels in anthropogenically dominated landscapes [7,8,9], leading to extensive population decline of both common and rare species [4,6,10]. Given these declines, establishing robust species-specific status assessments is essential toward future implementation of effective conservation and recovery strategies for these highly imperiled organisms [6,11].
One critical aspect of conservation biology is delineating patterns of genetic diversity across geographic ranges of species [12]. In general, freshwater organisms have unique biogeographic constraints as they are restricted by both terrestrial and marine barriers. Thus, dispersal between watersheds is primarily limited to connectivity of freshwaters during rare geologic events and often leaves unique genetic signatures [13,14]. Comparative phylogeographic approaches offer options for understanding the effects of geological processes on observed genetic diversity in co-distributed taxa with similar dispersal capabilities and life histories [15,16]. Multiple studies have used comparative phylogeography to resolve the evolutionary history of aquatic taxa in the southeastern United States and showed concordance in phylogeographic clustering across co-distributed taxa [17,18,19]. However, these examples have concentrated on relatively common species, and determining relationships among populations of imperiled species can be problematic when taxa have been extirpated from a significant portion of their historical range. The use of surrogate species (e.g., common species with similar life history characteristics used as proxies for imperiled species) is increasingly being used in conservation practices [20], but this methodology has not been explored in many freshwater taxa [21]. Studies focused on freshwater mussels have compared genetic structure among common and rare species [22,23,24,25,26]; however, no study has used resolved phylogeographic patterns among co-distributed congeners to make inferences regarding the hypothetical relationship between extant and extirpated populations. Here, we explore the use of comparative phylogeography for hypothesizing relationships among extant and extirpated populations of an imperiled freshwater mussel species by characterizing genetic structure in co-distributed taxa with analogous dispersal capabilities and life histories.
The genus Potamilus is a highly specialized group of freshwater mussels consisting of ten currently recognized species [27,28], including P. fragilis and P. leptodon (formerly Leptodea), which were added to the genus in a recent phylogenomic study [28]. All species in this genus have similar life history characteristics, including brooding phenology and reproductive timing, early maturation, high fecundity, parasitic growth during encystment, and specialized infection of Aplodinotus grunniens [28,29]. One species in this genus, Potamilus inflatus, is listed as threatened under the United States Endangered Species Act (ESA) [30] and was historically distributed throughout the Mobile, Pearl, and Lake Pontchartrain drainages [31,32]. Systematic habitat destruction has extirpated the species from much of its historical range and extant populations are restricted to the Tombigbee and Black Warrior rivers in the Mobile Basin, and a 40 km-long stretch of the Amite River in the Lake Pontchartrain drainage [33,34]. Concomitant to extirpation throughout large portions of the Lake Pontchartrain drainage, P. inflatus is believed to be extirpated from the entire Pearl River system [33,35]. Only two live individuals (MMNS13211; [36]) and three dead shells have ever been collected in the Pearl River system [37] despite extensive surveys throughout the basin [38,39]. Further, a mill spill in 2011 led to extensive fish and mussel kills (estimated total of 591,561 fish and mussels) throughout the presumptive range of P. inflatus in the Pearl River, however, no specimens of P. inflatus were salvaged [40,41].
Understanding genetic diversity across populations of P. inflatus is critical to determine threats to extant populations and establish effective recovery strategies to re-establish the species throughout its historical range, especially considering a previous assessment identified significant intra-specific variation between extant populations [42]. This problem is of the upmost importance given the threatened status of P. inflatus under the ESA and the possibility of recovery if viable populations are re-established in historically occupied areas where the species has been considered extirpated [35]. To facilitate conservation and recovery, we use phylogeographic techniques to evaluate range-wide genetic diversity within P. inflatus and sympatric congeners P. fragilis and P. purpuratus using multi-locus sequence data. Next, we integrate the premise of surrogate species into a comparative phylogeographic framework to hypothesize genetic relationships between extant and extirpated populations of P. inflatus by characterizing genetic structure in co-distributed congeners with similar life histories to better inform conservation and recovery planning.

2. Materials and Methods

2.1. Taxon Sampling

We examined genetic diversity from co-distributed members of Potamilus native to the Mobile, Pascagoula, Pearl, and Pontchartrain drainages (Table 1; Figure 1). A total of 103 individuals were examined in this study (Table 1), and more details on the specimens and collections are available on ScienceBase (https://doi.org/10.5066/P9Q3CFL5) and Johnson and Smith (Under Review). Mantle tissue clips from vouchered individuals in public museums were used to extract genomic DNA using the Qiagen PureGene DNA extraction kit with the standard extraction protocol (Qiagen, Hilden, Germany). We amplified and sequenced two mitochondrial (mtDNA) loci commonly used in freshwater mussel phylogenetic studies: a partial portion of cytochrome c oxidase subunit 1 (CO1) and NADH dehydrogenase subunit 1 (ND1). For all P. inflatus and a subset of P. fragilis and P. purpuratus, we sequenced three nuclear (nDNA) loci: the commonly used internal transcribed spacer 1 (ITS1), and two protein-coding loci fem-1 homolog C (FEM1) and UbiA prenyltransferase domain-containing protein 1 (UbiA). A subset of individuals representing the geographic range of P. fragilis and P. purpuratus were chosen for the additional nDNA loci due to the high prevalence of multiple copies at ITS1 and low genetic diversity at FEM1 and UbiA (Table 1; Figure 1). We utilized two recently developed primer sets from Johnson and Smith (Under Review) to amplify FEM1 and UbiA based on data generated in phylogenetic studies using the recently developed anchored hybrid enrichment probe set Unioverse [28,43,44]. Primers for all loci and thermal cycling conditions are reported in Table 2.
PCRs were conducted using a 25 µL mixture of the following: molecular grade water (9.5 µL), MyTaqTM Red Mix (12.5 µL; Bioline), primers (1.0 µL each) and DNA template (100 ng). Products were sent to Molecular Cloning Laboratories (McLAB, South San Francisco, CA, USA) for bi-directional sequencing on an ABI 3730. Geneious v 10.2.3 was used to assemble contigs and edit chromatograms [45], and sequences were aligned in Mesquite v 3.31 [46] using MAFFT v 7.311 [47]. Loci were aligned independently using the L-INS-i method in MAFFT and translated into amino acids to ensure absence of stop codons and gaps. Incomplete codons at each terminal end were removed. The total number of individuals included for each locus are as follows: CO1-102, ND1-103, FEM1-29, UBiA-29, and ITS1-31. Novel GenBank accessions for this study were as follows: CO1: MT662002–MT662099; FEM1: MT669773–MT669799; ITS1: MT661766–MT661792; ND1: MT669647–MT669745; and UbiA: MT669746–MT669772 (Table 1).

2.2. Phylogenetic Analyses

Phylogenetic reconstruction was performed on our five-locus molecular matrix consisting of 28 individuals and 3368 bp (CO1 = 657 bp; ND1 = 900 bp; FEM1 = 501 bp; UbiA = 765 bp; ITS1 = 545 bp) using IQ-TREE v 2.0-rc1 [48,49]. Both mtDNA and nDNA protein coding genes were partitioned by codon position. Partitions and substitution models for the analysis were determined by ModelFinder [50] using Bayesian inference criteria. We used 10 independent runs of an initial tree search and 1000 ultrafast bootstrap replicates (BS) for nodal support [51].
Coalescent-based approaches have been repeatably criticized to delimit populations and not species [52], including in freshwater mussels [53,54,55]. Here, we use the Bayesian coalescent-based model STACEY [56] in BEAST v 2.6.2 [57] to define genetic clusters in our molecular dataset for downstream analysis. STACEY allows for the inclusion of individuals with missing data, so we included all available data for the 5 loci in the analysis. Potamilus spp. were binned by drainage of capture, and we allowed the model to freely assign drainages to appropriate clusters. A substitution model for each locus alignment was determined using ModelFinder, a strict molecular clock was set at 1.0 for CO1, and clock rates for the four additional loci were estimated by STACEY. The Epi Tree prior was used as the species tree prior with a collapse height of 0.0001. Our analyses executed 109 generations and logged every 5000 trees with an initial 10% burn-in. Effective sample size (ESS) was ensured using Tracer v 1.7 [57], and the most likely number of clusters was calculated by SpeciesDelimitationAnalyser (SpeciesDA) v 1.8.0 [56] with a collapse height of 0.0001, a 1.0 simcutoff, and an initial 10% burn-in (2000 trees).
To estimate divergence times among well-supported clusters, we used the Bayesian coalescent-based model *BEAST [58] in BEAST. We chose a coalescent approach to account for concatenation methods, which typically overestimate the divergence times across species trees [59,60]. Similar to STACEY, *BEAST allows for the inclusion of individuals with missing data and all available data for the five loci were included in the analysis. For each species, individuals were grouped based on the most likely clusters resolved by STACEY: (1) Mobile; and (2) Pascagoula + Pearl + Pontchartrain (herein referred to as PPP). A strict molecular clock and an HKY model of nucleotide evolution was fit to each locus to better match priors for comparative phylogeographic analyses (see below). The substitution rate for CO1 was set to 2.56 × 10−9 ± 0.6 × 10−9 substitutions per site per year [61], and substitution rates were estimated for the four additional loci. Yule process was used as the species tree prior paired with a piecewise linear and constant root population size model. The analysis was run for 1.5*109 MCMC generations sampling every 5000 generations and a 10% burn-in. Effective sample size (ESS) was ensured using Tracer v 1.7 [57], and a maximum clade credibility tree was created using TreeAnnotator v 2.5 [57].

2.3. Phylogeographic Analyses

To visualize genetic divergence with respect to geographic distribution, we created a median joining haplotype network [62] for each of the three Potamilus spp. independently in PopART 1.7 [63] with the default epsilon value set at 0. Additionally, an analysis of molecular variance (AMOVA) was conducted for each species independently in PopART to further evaluate the geographic distribution of genetic diversity. Each analysis was performed on a concatenated alignment of CO1 and ND1, and missing data in both PopART analyses was handled using complete deletion. To further assess genetic variation within Potamilus spp. with regard to geography, we calculated DNA sequence divergence between clusters of Potamilus spp. using uncorrected pairwise genetic distances in MEGAX [64]. Partial deletion was used to handle missing data in MEGAX calculations. For haplotype networks, species were grouped by drainage and groups for all other analyses were as follows: P. fragilis from the Mobile and Pearl + Pontchartrain, P. inflatus from the Mobile and Pontchartrain, and P. purpuratus from the Mobile and PPP.

2.4. Comparative Phylogeography

We tested for simultaneous divergence between clusters of Potamilus spp. defined by STACEY under a hierarchical Approximate Bayesian Computation (hABC) approach as implemented in the PyMsBayes package [65]. Specifically, we tested if divergence between Mobile and PPP clusters of P. fragilis, P. inflatus, and P. purpuratus was synchronous. PyMsBayes implements a modified version of msBayes [66] that specifies a Dirichlet-process prior (dpp) to compare fit of empirical data to simulated data under user-informed priors [14]. We used dpp-msbayes to test for synchronous divergence between Mobile and PPP clusters of Potamilus spp. using alignments from all available loci. We used results from our *BEAST divergence time analysis to guide prior selection for dpp-msbayes as follows: the concentration parameter [1000, 0.00141] in which there was prior probability for one, two, or three divergence events, population size (θ) [1, 0.0005], and divergence times (τ) [1, 0.01]. To allow dpp-msbayes to freely explore different divergence scenarios, we allowed the model to estimate independent parameters for each species (θ parameter = 012) and the number of divergence events (τ classes = 0). Transition-transversion rate of the HKY substitution model was estimated for each alignment independently using IQ-TREE. Our dpp-msbayes run performed a total of 107 simulations with 10,000 standardizing samples and reported every 20,000 simulations. We retained the 1000 simulations with the best fit to empirical data to estimate posterior probability (PP) values for each divergence scenario. To measure support for the number of divergence events, Bayes factors were measured using twice the difference of −ln likelihood [67].

3. Results

Molecular Analyses

Five partitions and substitution models were determined by ModelFinder for phylogenetic reconstruction in IQ-TREE: TN + F + I for mtDNA codon 1 and nDNA codon 3, TN + F + I for mtDNA codon 2 and nDNA codon 2, K3Pu + F + G4 for mtDNA codon 3, F81 + F for nDNA codon 1, and K2P + I for ITS1. All species-level relationships had full support (BS = 100) and the only two major nodes that were not strongly supported (i.e., BS ≥ 95) were the PPP clade of P. fragilis (BS = 94) and the Mobile clade of P. purpuratus (BS = 92; Figure S1). All three taxa were resolved as monophyletic with P. inflatus, the sister to P. fragilis and P. purpuratus, aligning with findings in a previous phylogenetic study [28].
Substitution models determined by ModelFinder for locus alignments in the STACEY analysis were: HKY + I for CO1, HKY + I for ND1, JC for FEM1, F81 + I for UbiA, and K2P + I (=K80 + I) for ITS1. Convergence of the analysis was supported by all parameters having ESS values > 200, and all nodes were strongly supported (PP ≥ 95). SpeciesDA supported six clusters (54%): (1) P. inflatus from the Mobile, (2) P. inflatus from the Pontchartrain, (3) P. fragilis from the Mobile, (4) P. fragilis from the Pearl + Pontchartrain, (5) P. purpuratus from the Mobile, and (6) P. purpuratus from the PPP (Figure S2). The second most likely clustering scenario supported seven clusters (18.5%), with the Pearl population of P. purpuratus recognized as a distinct cluster.
The topological reconstruction from *BEAST was congruent with IQ-TREE and STACEY topologies, and all nodes were strongly supported (Figure 2A). Mobile and PPP clusters of Potamilus spp. were resolved as monophyletic with full support (PP = 100; Figure 2A). Convergence of the analysis was supported by all parameters having ESS values > 200. Divergence estimates differed slightly among Mobile and PPP clusters of Potamilus spp. The split between clusters of P. inflatus was estimated to have occurred ~2.13 Mya (95% CI 0.28–3.92 Mya; Figure 2A), and the splits between clusters within P. fragilis and P. purpuratus were estimated to have occurred more recently: ~1.35 Mya (95% CI 0.54–2.27 Mya) and ~0.72 Mya (95% CI 0.27–1.39 Mya), respectively (Figure 2A).
Mean uncorrected p-distances between Mobile and PPP clusters for all species were larger than 1% and are reported in Table 3. Distance values were larger in P. inflatus (2.33%) when compared to P. fragilis (1.11%) and P. purpuratus (1.31%). Haplotype networks were concordant with phylogenetic analyses and showed clear separation between the Mobile and PPP groupings of all three Potamilus spp. (Figure 3). However, within the PPP province there was haplotype sharing between drainages in P. fragilis and P. purpuratus (Figure 3). AMOVAs indicated the majority of molecular variation was distributed between Mobile and PPP groups for all Potamilus spp. (Table 3). Molecular variance was higher within P. fragilis (19.1%) than P. inflatus (1.1%) and P. purpuratus (3.7%).
The dpp-msbayes analysis supported synchronous divergence between clusters of Potamilus spp. (Figure 2B–D). Support for a single divergence event was 55.7 PP, with the next best supported scenario of two divergence events (P. inflatus and P. purpuratus equal, and P. fragilis subsequently diverged independently) at 15.7 PP (Figure 2C,D). Similarly, Bayes factors indicated positive support for one divergence event (2lnBF = 1.7), and negative support for two (2lnBF = −0.74) and three (2lnBF = −2.19) divergence events (Figure 2B). The overlap of confidence intervals for divergence estimates in the *BEAST analysis and dpp-msbayes further supports evidence of synchronous divergence between Potamilus spp. (Figure 2A).

4. Discussion

Accurate evaluations of genetic diversity are a critical component in developing effective conservation and recovery strategies. The specific goal of our study was to characterize range-wide genetic variation of P. inflatus. Given the overall rarity of the species and plausible extirpation from multiple river systems, estimating genetic relationships across the historical range of P. inflatus is completely dependent on understanding the genetic composition of closely related and co-distributed species with similar dispersal capabilities and life histories. Our comparative phylogeographic approach integrated the premise of surrogate species to predict relationships among extant and extirpated populations. Although the use of comparative phylogeography has been used to characterize genetic diversity in common and rare species within freshwater mussels [22,23,24,25,26], the use of surrogate species within a comparative phylogeographic framework to hypothesize relationships among extant and extirpated populations of imperiled species is a novel approach. Below, we discuss the evolutionary forces driving congruent patterns of genetic divergence within Potamilus spp., and how our findings may impact future conservation and recovery efforts for P. inflatus.

4.1. Patterns of Genetic Variation in Potamilus Species

Large-scale environmental change has substantial effects on communities of species and associated microbiota [14,72,73]. This is certainly the case in mussels and their hosts, as biogeographical processes are a driver of faunal structure and genetic diversity [28,29,53,74,75,76]. Given biogeography is a critical driver of genetic variation, identifying faunal provinces is the first step toward understanding specific patterns of phylogeography [77]. Multiple attempts have been made to classify North American mussel fauna into biogeographic provinces [78,79,80,81,82], and understanding the processes that have driven faunal shifts across these regions has been integral toward understanding the evolution of the group [28,74,83]. In the case of the Mobile and PPP provinces, the drainages have been linked in hierarchical classifications of mussel diversity based on species composition [79]. Prior to our study, however, these relationships have not been tested in a molecular context. Our molecular analyses align with the hypothetical historical connection between the Mobile and PPP, as our phylogenetic and coalescent-based species delimitation analyses strongly supported Potamilus spp. in these biogeographic provinces as distinct clines. These results align with other mussel species showing genetic distinctiveness across these drainages [53,69,83,84], as well as other aquatic species [85,86,87,88,89,90].
The geological connection between the Mobile and PPP drainages has been hypothesized by numerous authors (reviewed by [91]) and a vicariance event between the two systems has likely driven the observed genetic differentiation in Potamilus spp. If a vicariance event was the causation of molecular diversification for all the species, we would expect to see similar patterns of divergence across Potamilus spp. Results from our molecular analyses, however, deviated from these expected patterns of genetic drift and showed varying levels of sequence divergence (Table 3). Specifically, genetic distance values between populations of P. inflatus were larger than those in P. fragilis and P. purpuratus (Table 3). However, it is an unrealistic expectation to assume that rates of evolution are identical between species, especially across geographically isolated populations [18,92,93]. Variable rates of molecular diversification within Potamilus spp. could be indicative of a variety of confounding variables, such as differing population demographics (e.g., population size, age structure), evolutionary processes (e.g., mutation rate, genetic drift, selection), or species-specific traits (e.g., habitat preferences) rather than multiple hypothetical vicariance events. To address this issue, we used a hABC approach to explicitly test whether divergence between Mobile and PPP populations of Potamilus spp. occurred synchronously. Our results suggest that the divergence between Potamilus spp. in the Mobile and PPP occurred simultaneously and further support previously described biogeographic provinces [79]. The causative event driving genetic differentiation between these groupings is uncertain, but additional molecular investigations in other freshwater mussels, as well as host fishes, may further elucidate the timing and patterns of faunal exchange between these two provinces.
Despite extensive geographic range within the PPP, our molecular data showed no diagnostic divergence between drainages within the province (Figure 3; Table 3). Limited genetic diversity was suspected within P. inflatus given there is only one extant population; however, the more common and wide-ranging species, P. fragilis and P. purpuratus, both showed haplotype sharing between drainages and no evidence of drainage specific structuring within the PPP (Figure 3A,C; Table 3). A signal for incomplete lineage sorting at nDNA loci is expected due to the effective population size being nearly four times that of mtDNA loci [94,95]; however, incomplete lineage sorting of mtDNA loci likely indicates relatively recent gene flow between populations. Approximately 18 Kya during the last glacial lowstand; geological evidence suggests the PPP drainages were connected [91,96], permitting gene flow to occur. Subsequent sea level rise from deglaciation began to form modern fluvial systems in the PPP [96], causing genetic isolation among contemporary populations of Potamilus spp. Given the hypothetical mtDNA mutation rates of freshwater mussels [61,97], it is an unrealistic expectation that mtDNA markers would become fixed across these drainages, and using more rapidly evolving markers (genotype-by-sequencing, whole genome resequencing) would be necessary to delineate fine-scale genomic differentiation among Potamilus spp. inhabiting these drainages or test for ongoing gene flow. However, only one extant population of P. inflatus occurs within the PPP (Amite River—Pontchartrain drainage) and it is a realistic expectation that the presumed extirpated populations of P. inflatus in the Pontchartrain and Pearl drainages would be most closely related to members of the Amite River given the patterns of genetic diversity seen in P. fragilis and P. purpuratus.

4.2. Implications on Conservation

Numerous practices have been proposed for delineating population units using genetic data for conservation and management [98,99,100,101,102], and in particular, ESA listed species have been partitioned into distinct population segments (DPSs), evolutionary significant units (ESUs), or management units (MUs) to facilitate recovery practices [101,102,103,104]. However, under the ESA, DPSs only apply to vertebrate species [103] and formal recognition of population units remains rare in freshwater mussels [105]. This is particularly concerning because information regarding population units is often required to facilitate conservation and recovery efforts [106]. In the case of P. inflatus, we observed high levels of molecular divergence at mtDNA loci. Formal recognition of ESUs are diagnosed based on reciprocal monophyly [104] and significant differences in allele frequencies at both mtDNA and nDNA loci [107]. Although individuals from the Amite River and Mobile drainage show evidence of fixation at mtDNA markers, we saw no evidence of fixation at nDNA loci, which would rule out the recognition of the two populations as ESUs. However, it is an unrealistic expectation that the nuclear loci used in this study would diagnose population units within species, and assessments with more rapidly evolving nuclear data (e.g., microsatellites, genome-wide SNPs) would facilitate delineation of ESUs. Nonetheless, molecular data from this study paired with available distributional information [34,35] provide ample evidence for the delineation of the Amite River and Mobile drainage populations of P. inflatus as two distinct MUs [102,104,107]. The designation of these MUs ensures the protection of irreplaceable genetic variation, and in particular, emphasizes conservation needs in the highly susceptible Amite River given its limited geographical distribution [34] and presumed extirpation of populations from adjacent systems that were hypothetically closely related based on our comparative phylogeographic approach. Future long-term monitoring efforts will be useful to identify specific population characteristics such as abundance, age-class structure, dispersal capabilities, and reproductive timing within these MUs and may lead to fine-scale delineation of population units.
Captive propagation of freshwater mussels is a critical component of recovery planning for many species [106,108] and likely the only viable option for re-establishing extirpated populations of P. inflatus [35], especially in the Pearl River drainage. Our assessment provides defensible justification for natural resource managers to use individuals from the Amite River rather than the Mobile drainage as a source of brood stock for recovery efforts for P. inflatus that include translocation or captive propagation in the Pearl and Pontchartrain drainages. Based on the likely scenario that extant populations of P. inflatus are restricted to the Amite River and Mobile drainage, possible re-establishment sites include historically occupied reaches in the Bogue Chitto, Comite, Pearl, and Tangipahoa rivers.

5. Conclusions

Our study revealed congruent patterns of molecular diversification within a group of freshwater mussels with analogous life history traits and dispersal capabilities. Our findings suggest synchronous diversification between Potamilus spp. in the Mobile and PPP, which advances knowledge regarding the drivers of molecular diversification and biogeography of freshwater mussels in these provinces. Patterns of genetic variation in Potamilus spp. recovered by our comparative phylogeographic approach provided defensible justification for the use of the Amite River brood stock for re-establishing P. inflatus in PPP drainages. This finding provides direction for natural resource managers to develop appropriate recovery practices that may include captive propagation and translocation. Although a useful tool, without proper guidance and planning efforts, introduction of captive raised or translocated individuals has the potential to harm existing populations or nontarget species [109,110]. Recovery planning would greatly benefit from robust distributional information for P. inflatus, and future efforts utilizing both eDNA sampling and traditional surveys would help resolve whether the species is truly extirpated from select drainages. We also encourage further evaluations using fine-scale genomic markers and detailed genetic management planning to characterize genetic diversity of brood stock and captively bred individuals in efforts to maximize genetic diversity in augmented or re-establish populations.
Given the imperilment status of freshwater mussel species globally [111], our study represents a useful methodology for hypothesizing the genetic relationships of extant and extirpated populations of imperiled species to facilitate recovery planning. The use of mtDNA may be limited on a regional scale in most species; however, comparative phylogeographic approaches incorporating more rapidly evolving genome-wide markers introduces a more robust methodology for evaluating population dynamics within drainages and even at a local scale using surrogate species. As the understanding of phylogenetic relationships and life history characteristics continues to improve, utilizing comparative phylogeographic methodologies is a promising tool toward effective species recovery and long-term viability of freshwater mussels.

Supplementary Materials

The following figures are available online at https://www.mdpi.com/1424-2818/12/7/281/s1, Figure S1: Maximum likelihood (IQ-TREE) phylogenetic reconstruction based on a concatenated alignment of CO1, ND1, ITS1, FEM1, and UbiA. Values above branches represent ultrafast bootstrap support and information on taxon labels can be found in Table 1., Figure S2: Bayesian inference (STACEY) phylogenetic reconstruction based on a concatenated alignment of CO1, ND1, ITS1, FEM1, and UbiA. Terminals are collapsed to represent the best number of clusters (n = 6): Mobile and Pascagoula + Pearl + Pontchartrain (PPP) populations of Potamilus fragilis, P. inflatus, P. purpuratus. All branches were strongly supported by posterior probability being greater than or equal to 99.

Author Contributions

Conceptualization, C.H.S. and N.A.J.; methodology, C.H.S.; validation, C.H.S. and N.A.J.; formal analysis, C.H.S.; investigation, C.H.S.; resources, C.H.S. and N.A.J.; data curation, C.H.S. and N.A.J.; writing—original draft preparation, C.H.S.; writing—review and editing, N.A.J.; visualization, C.H.S. and N.A.J.; supervision, N.A.J.; project administration, N.A.J.; funding acquisition, N.A.J. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the U.S. Fish and Wildlife Service and the U.S. Geological Survey.

Acknowledgments

The authors wish to thank Caitlin Beaver for assistance in the laboratory; John Pfeiffer for supplying unpublished data; Matt Cannister for help with SceinceBase; along with Carla Atkinson, Michael Buntin, Matthew Duplessis, Jeff Garner, Paul Johnson, and Kevin Kocot for assistance with collections. Special thanks to Jeff Powell for help obtaining funding, which was provided to Nathan A. Johnson by the U.S. Fish and Wildlife Service and U.S. Geological Survey. Specimens utilized in this study were either from museum collections or collected under the U.S. Fish and Wildlife Service permit TE 697819-4. This work was authored as part of the Contributor’s official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law. This is an Open Access article that has been identified as being free of known restrictions under copyright law, including all related and neighboring rights (https://creativecommons.org/publicdomain/mark/1.0/). You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Collection locations for Potamilus fragilis (red), P. inflatus (green), and P. purpuratus (yellow) in the Amite (Pontchartrain), Mobile, Pascagoula, and Pearl River drainages.
Figure 1. Collection locations for Potamilus fragilis (red), P. inflatus (green), and P. purpuratus (yellow) in the Amite (Pontchartrain), Mobile, Pascagoula, and Pearl River drainages.
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Diversity 12 00281 g002 550
Figure 2. Summary of synchronous diversification analyses performed in *BEAST and Dpp-msbayes. (A) Phylogenetic reconstruction with divergence time scaled in million years before present; node bars represent the 95% confidence intervals. Values above branches represent estimated divergence time. Epoch abbreviations are as follows: Mc—Miocene, Pc—Pliocene, and Ps—Pleistocene. All nodes were strongly supported with posterior probability greater than 97. (B) Bayes Factor support for the number of divergence events generated by Dpp-msbayes. (C,D) The two most likely divergence scenarios between Potamilus species in the Mobile and PPP provinces resolved by Dpp-msbayes with posterior probability (PP) support of each scenario. Units on the y-axis are divergence times in million years before present.
Figure 2. Summary of synchronous diversification analyses performed in *BEAST and Dpp-msbayes. (A) Phylogenetic reconstruction with divergence time scaled in million years before present; node bars represent the 95% confidence intervals. Values above branches represent estimated divergence time. Epoch abbreviations are as follows: Mc—Miocene, Pc—Pliocene, and Ps—Pleistocene. All nodes were strongly supported with posterior probability greater than 97. (B) Bayes Factor support for the number of divergence events generated by Dpp-msbayes. (C,D) The two most likely divergence scenarios between Potamilus species in the Mobile and PPP provinces resolved by Dpp-msbayes with posterior probability (PP) support of each scenario. Units on the y-axis are divergence times in million years before present.
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Figure 3. Haplotype networks based on a concatenated alignment of CO1 and ND1 for Potamilus fragilis (A), P. inflatus (B), and P. purpuratus (C). Each circle represents a unique haplotype and size is relative to the number of individuals. Black circles represent unsampled haplotypes and individual tick marks indicate nucleotide substitutions. Specimens are grouped by drainage of capture: Mobile, Pascagoula, Pearl, and Pontchartrain.
Figure 3. Haplotype networks based on a concatenated alignment of CO1 and ND1 for Potamilus fragilis (A), P. inflatus (B), and P. purpuratus (C). Each circle represents a unique haplotype and size is relative to the number of individuals. Black circles represent unsampled haplotypes and individual tick marks indicate nucleotide substitutions. Specimens are grouped by drainage of capture: Mobile, Pascagoula, Pearl, and Pontchartrain.
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Table
Table 1. Molecular material examined in this study. Museum abbreviations are as follows: UA—Alabama Museum of Natural History; UF—Florida Museum. GenBank or SRA accession numbers are provided for each locus, and missing values were not used in phylogenetic analyses.
Table 1. Molecular material examined in this study. Museum abbreviations are as follows: UA—Alabama Museum of Natural History; UF—Florida Museum. GenBank or SRA accession numbers are provided for each locus, and missing values were not used in phylogenetic analyses.
TaxonIDDrainageSourceCO1ND1ITS1FEM1UbiA
Potamilus fragilisLfraAla001MobileUF438237MT662019MT669665MT661766MT669798MT669771
Potamilus fragilisLfraAmi040PontchartrainUF439330MT662020MT669666MT661773MT669778MT669751
Potamilus fragilisLfraAmi041PontchartrainUF439352MT662021MT669667
Potamilus fragilisLfraAmi042PontchartrainUF439352MT662022MT669668
Potamilus fragilisLfraPrl043PearlUF439332MT662023MT669669
Potamilus fragilisLfraPrl044PearlUF439332MT662024MT669670MT661780MT669785MT669758
Potamilus fragilisLfraPrl045PearlUF439365MT662025MT669671
Potamilus fragilisLfraPrl046PearlUF439343MT662026MT669672
Potamilus fragilisLfraPrl047PearlUF439343MT662027MT669673
Potamilus fragilisLfraPrl048PearlUF439343MT662028MT669674
Potamilus fragilisLfraAmi057PontchartrainUF439529MT662029MT669675
Potamilus fragilisLfraAmi058PontchartrainUF439529MT662030MT669676
Potamilus fragilisLfraAmi059PontchartrainUF439529MT662031MT669677
Potamilus fragilisLfraMob063MobileUF439528MT662033MT669679
Potamilus fragilisLfraMob064MobileUF439528MT662032MT669678
Potamilus fragilisLfraMob065MobileUncatologedMT662034MT669680MT661792MT669797MT669770
Potamilus inflatusPinfMob001MobileUF439131MT662002MT669647MT661768MT669773MT669746
Potamilus inflatusPinfMob002MobileUF439131MK044952MK045103MK036203MT669774MT669747
Potamilus inflatusPinfMob003MobileUF439131MT662003MT669648MT661769MT669775MT669748
Potamilus inflatusPinfMob004MobileUF439131MK044953MK045104MK036204SRR10579071SRR10579071
Potamilus inflatusPinfMob005MobileUF439131MT662004MT669649MT661770MT669776MT669749
Potamilus inflatusPinfMob006MobileUF439131MT662005MT669650MT661771MT669777MT669750
Potamilus inflatusPinfAmi010PontchartrainUF439530MT662006MT669651MT661774MT669779MT669752
Potamilus inflatusPinfAmi011PontchartrainUF439530MT662007MT669652MT661775MT669780MT669753
Potamilus inflatusPinfAmi012PontchartrainUF439531MT662008MT669653MT661776MT669781MT669754
Potamilus inflatusPinfAmi013PontchartrainUF439532MT662009MT669654MT661777MT669782MT669755
Potamilus inflatusPinfAmi014PontchartrainUF439532MT662010MT669655MT661778MT669783MT669756
Potamilus inflatusPinfAmi015PontchartrainUF439533MT662011MT669656MT661779MT669784MT669757
Potamilus inflatusPinfMob019MobileUF439514MT662012MT669657MT661783MT669788MT669761
Potamilus inflatusPinfMob020MobileUF439514MT662013MT669658MT661784MT669789MT669762
Potamilus inflatusPinfMob021MobileUF439514MT662014MT669659MT661785MT669790MT669763
Potamilus inflatusPinfMob022MobileUF439514MT662015MT669660MT661786MT669791MT669764
Potamilus inflatusPinfMob023MobileUF439514MT662016MT669661MT661787MT669792MT669765
Potamilus inflatusPinfMob017MobileUF439513MT662017MT669662MT661788MT669793MT669766
Potamilus inflatusPinfMob018MobileUF439513MT662018MT669663MT661789MT669794MT669767
Potamilus inflatusPinfMob016MobileUA2696 MT669664MT661781MT669786MT669759
Potamilus purpuratusPpurPas001PascagoulaUF438434MT662035MT669681
Potamilus purpuratusPpurPrl022PearlUF439145MT662036MT669682
Potamilus purpuratusPpurPrl023PearlUF439145MK044960MK045111MK036211MT669799MT669772
Potamilus purpuratusPpurPrl024PearlUF439145MK044961MK045112MK036212
Potamilus purpuratusPpurPrl025PearlUF439145MT662037MT669683
Potamilus purpuratusPpurPrl026PearlUF439145MT662038MT669684MT661767
Potamilus purpuratusPpurAmi038PontchartrainUF439452MT662039MT669685
Potamilus purpuratusPpurAmi039PontchartrainUF439452MT662040MT669686
Potamilus purpuratusPpurAmi040PontchartrainUF439452MT662041MT669687
Potamilus purpuratusPpurAmi041PontchartrainUF439452MT662042MT669688
Potamilus purpuratusPpurAmi042PontchartrainUF439452MT662043MT669689
Potamilus purpuratusPpurAmi043PontchartrainUF439453MT662044MT669690
Potamilus purpuratusPpurAmi044PontchartrainUF439453MT662045MT669691
Potamilus purpuratusPpurAmi045PontchartrainUF439453MT662046MT669692MT661772SRR10579081SRR10579081
Potamilus purpuratusPpurAmi046PontchartrainUF439453MT662047MT669693
Potamilus purpuratusPpurAmi047PontchartrainUF439453MT662048MT669694
Potamilus purpuratusPpurAmi048PontchartrainUF439454MT662049MT669695
Potamilus purpuratusPpurAmi049PontchartrainUF439454MT662050MT669696
Potamilus purpuratusPpurAmi050PontchartrainUF439454MT662051MT669697
Potamilus purpuratusPpurAmi051PontchartrainUF439454MT662052MT669698
Potamilus purpuratusPpurPrl052PearlUF439456MT662053MT669699
Potamilus purpuratusPpurPrl053PearlUF439456MT662054MT669700
Potamilus purpuratusPpurPrl054PearlUF439457MT662055MT669701
Potamilus purpuratusPpurPrl055PearlUF439457MT662056MT669702
Potamilus purpuratusPpurPrl056PearlUF439457MT662057MT669703
Potamilus purpuratusPpurPrl057PearlUF439457MT662058MT669704
Potamilus purpuratusPpurPrl058PearlUF439457MT662059MT669705
Potamilus purpuratusPpurPrl059PearlUF439456MT662060MT669706
Potamilus purpuratusPpurPrl060PearlUF439456MT662061MT669707
Potamilus purpuratusPpurPrl061PearlUF439456MT662062MT669708
Potamilus purpuratusPpurPrl062PearlUF439456MT662063MT669709
Potamilus purpuratusPpurPrl063PearlUF439456MT662064MT669710
Potamilus purpuratusPpurPrl064PearlUF439458MT662065MT669711
Potamilus purpuratusPpurPrl065PearlUF439459MT662066MT669712
Potamilus purpuratusPpurPrl066PearlUF439459MT662067MT669713
Potamilus purpuratusPpurPrl067PearlUF439459MT662068MT669714
Potamilus purpuratusPpurPrl068PearlUF439459MT662069MT669715
Potamilus purpuratusPpurPrl069PearlUF439459MT662070MT669716
Potamilus purpuratusPpurMob081MobileUA62MT662071MT669717
Potamilus purpuratusPpurMob082MobileUA2469MT662072MT669718
Potamilus purpuratusPpurMob083MobileUA2510MT662073MT669719
Potamilus purpuratusPpurMob084MobileUA2562MT662074MT669720
Potamilus purpuratusPpurMob085MobileUA2740MT662075MT669721MT661782MT669787MT669760
Potamilus purpuratusPpurMob086MobileUA3100MT662076MT669722
Potamilus purpuratusPpurMob087MobileUA3123MT662077MT669723
Potamilus purpuratusPpurMob088MobileUA3205MT662078MT669724
Potamilus purpuratusPpurMob089MobileUA3417MT662079MT669725
Potamilus purpuratusPpurMob090MobileUA3482MT662080MT669726
Potamilus purpuratusPpurPas097PascagoulaUF439510MT662081MT669727
Potamilus purpuratusPpurPas098PascagoulaUF439510MT662082MT669728
Potamilus purpuratusPpurPas099PascagoulaUF439510MT662083MT669729
Potamilus purpuratusPpurPas100PascagoulaUF439510MT662084MT669730
Potamilus purpuratusPpurPas101PascagoulaUF439510MT662085MT669731MT661790MT669795MT669768
Potamilus purpuratusPpurPas102PascagoulaUF439510MT662086MT669732
Potamilus purpuratusPpurPas103PascagoulaUF439510MT662087MT669733
Potamilus purpuratusPpurMob107MobileUF439527MT662088MT669734MT661791MT669796MT669769
Potamilus purpuratusPpurMob108MobileUF439527MT662089MT669735
Potamilus purpuratusPpurMob109MobileUF439527MT662090MT669736
Potamilus purpuratusPpurMob110MobileUF439527MT662091MT669737
Potamilus purpuratusPpurMob111MobileUF439527MT662092MT669738
Potamilus purpuratusPpurMob112MobileUF439527MT662093MT669739
Potamilus purpuratusPpurMob113MobileUF439527MT662094MT669740
Potamilus purpuratusPpurMob114MobileUF439527MT662095MT669741
Potamilus purpuratusPpurMob115MobileUF439527MT662096MT669742
Potamilus purpuratusPpurMob116MobileUF439527MT662097MT669743
Potamilus purpuratusPpurMob117MobileUF439527MT662098MT669744
Potamilus purpuratusPpurMob118MobileUF439527MT662099MT669745
Table
Table 2. Primers used for PCR and cycling conditions used in this study.
Table 2. Primers used for PCR and cycling conditions used in this study.
LocusPrimersSourceConditions
CO1F: 5′-GTTCCACAAATCATAAGGATATTGG-3′[68][69]
R: 5′-TACACCTCAGGGTGACCAAAAAACCA-3′
ND1F: 5′-TGGCAGAAAAGTGCATCAGATTAAAGC-3′[70][70]
R: 5′-CCTGCTTGGAAGGCAAGTGTACT-3′
ITS1F: 5′-AAAAAGCTTCCGTAGGTGAACCTGCG-3′[71][71]
R: 5′-AGCTTGCTGCGTTCTTCATCG-3′
FEM1F: 5′- GTRATGGAGTATCGCAGTGT-3′[44][44]
R: 5′-ACRCTYTTCCTGTTAACATC-3′
UbiAF: 5′- TTTACTCCTGTTGCACTTGGGA-3′[44][44]
R: 5′-AGCATCTGTCATGAAGACTCCAAC-3′
Table
Table 3. Summary of analysis of molecular variance (AMOVA) analyses in PopArt. Sample sizes for each taxon from the Mobile drainage and Pascagoula + Pearl + Pontchartrain (PPP) are reported. All values for each comparison were found to be significant (α < 0.0001).
Table 3. Summary of analysis of molecular variance (AMOVA) analyses in PopArt. Sample sizes for each taxon from the Mobile drainage and Pascagoula + Pearl + Pontchartrain (PPP) are reported. All values for each comparison were found to be significant (α < 0.0001).
TaxonN MobileN PPPAMOVA betweenAMOVA withinDistance between (Uncorrected p)
Potamilus fragilis41280.9%19.1%1.11%
Potamilus inflatus13698.9%1.1%2.33%
Potamilus purpuratus224596.3%3.7%1.31%

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Smith, C.H.; Johnson, N.A. A Comparative Phylogeographic Approach to Facilitate Recovery of an Imperiled Freshwater Mussel (Bivalvia: Unionida: Potamilus inflatus). Diversity 2020, 12, 281. https://doi.org/10.3390/d12070281

AMA Style

Smith CH, Johnson NA. A Comparative Phylogeographic Approach to Facilitate Recovery of an Imperiled Freshwater Mussel (Bivalvia: Unionida: Potamilus inflatus). Diversity. 2020; 12(7):281. https://doi.org/10.3390/d12070281

Chicago/Turabian Style

Smith, Chase H., and Nathan A. Johnson. 2020. "A Comparative Phylogeographic Approach to Facilitate Recovery of an Imperiled Freshwater Mussel (Bivalvia: Unionida: Potamilus inflatus)" Diversity 12, no. 7: 281. https://doi.org/10.3390/d12070281

APA Style

Smith, C. H., & Johnson, N. A. (2020). A Comparative Phylogeographic Approach to Facilitate Recovery of an Imperiled Freshwater Mussel (Bivalvia: Unionida: Potamilus inflatus). Diversity, 12(7), 281. https://doi.org/10.3390/d12070281

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