Genomic population structure of Striped Bass (Morone saxatilis) from the Gulf of St. Lawrence to Cape Fear River

Abstract Striped Bass, Morone saxatilis (Walbaum, 1792), is an anadromous fish species that supports fisheries throughout North America and is native to the North American Atlantic Coast. Due to long coastal migrations that span multiple jurisdictions, a detailed understanding of population genomics is required to untangle demographic patterns, understand local adaptation, and characterize population movements. This study used 1,256 single nucleotide polymorphism (SNP) loci to investigate genetic structure of 477 Striped Bass sampled from 15 locations spanning the North American Atlantic coast from the Gulf of St. Lawrence, Canada, to the Cape Fear River, United States. We found striking differences in neutral divergence among Canadian sites, which were isolated from each other and US populations, compared with US populations that were much less isolated. Our SNP dataset was able to assign 99% of Striped Bass back to six reporting groups, a 39% improvement over previous genetic markers. Using this method, we found (a) evidence of admixture within Saint John River, indicating that migrants from the United States and from Shubenacadie River occasionally spawn in the Saint John River; (b) Striped Bass collected in the Mira River, Cape Breton, Canada, were found to be of both Miramichi River and US origin; (c) juveniles in the newly restored Kennebec River population had small and nonsignificant differences from the Hudson River; and (d) tributaries within the Chesapeake Bay showed a mixture of homogeny and small differences among each other. This study introduces new hypotheses about the dynamic zoogeography of Striped Bass at its northern range and has important implications for the local and international management of this species.


| INTRODUC TI ON
The Striped Bass, Morone saxatilis (Walbaum, 1792), is a facultative anadromous and economically important fish with a native range extending along the Atlantic coast of North America from the St.
Lawrence River, Quebec, to the St John's River, Florida, as well as a native population in the Apalachicola-Chattahoochee-Flint river system in the Gulf of Mexico (Setzler et al., 1980;Wirgin, Currie, Roy, Maceda, & Waldman, 2005; Figure 1). Individuals from the Hudson River to the Roanoke River can move long distances, some moving 400-1000 km along the Atlantic Coast (Callihan, Harris, & Hightower, 2015;Kneebone, Hoffman, Dean, Fox, & Armstrong, 2014;Mather et al., 2010), and along with some Canadian populations are known to enter non-natal rivers (Grothues, Able, Carter, & Arienti, 2009;Kneebone et al., 2014;LeBlanc et al., 2018). Migratory populations within the United States are currently managed as two separate stocks: the Roanoke River, and all US populations north of the Roanoke River (Atlantic States Marine Fisheries Commission (ASMFC, 2019)). Populations south of the Roanoke River and Albemarle Sound are generally considered nonmigratory (Bjorgo, Isely, & Thomason, 2000), Striped Bass in the Gulf of St. Lawrence are thought to be isolated from the rest of the range (Rulifson & Dadswell, 1995), and it is unknown whether Bay of Fundy populations travel further than the Gulf of Maine (Department of Fisheries and Oceans (DFO), 2014). Striped Bass throughout its range experienced severe population declines from the 1960s to 1980s, leading to extensive temporary and permanent closures of commercial and recreational fisheries (Andrews, Dadswell, Buhariwalla, Linnansaari, & Curry, 2019;Carmichael, Haeseker, & Hightower, 1998;Richards & Rago, 1999). Multistate emergency management measures im- Effective management of a highly migratory species requires knowledge of the connectivity between populations and the seasonal mixing rates of multiorigin stocks in relation to spatial dynamics within the species range. Striped Bass populations have complex life histories and often exhibit multiple migratory components, or contingents (Andrews, Linnansaari, Curry, & Dadswell, 2017;Clark, 1968;Gahagan, Fox, & Secor, 2015;Secor, 1999;Secor, Rooker, Zlokovitz, & Zdanowicz, 2001), which appear tied to ontogenic development (Conroy, Piccoli, & Secor, 2015;Gahagan et al., 2015) and population size (Callihan, Godwin, & Buckel, 2014;Waldman, Dunning, Ross, & Mattson, 1990). Partial migration, where some individuals in a population are resident while others migrate, and contingent behaviors further complicate management of Striped Bass as harvest in coastal waters may be on mixed stocks from multiple populations and also from specific behavioral subsets of those populations. Coastal migrations can facilitate genetic exchange between populations because mixing away from natal rivers may lead to some individuals straying and spawning in non-natal rivers, an infrequent yet measurable occurrence (e.g., Gauthier et al., 2013;LeBlanc et al., 2018). In anadromous fishes, straying allows moving, expanding or contracting its range in response to environmental changes (Pess, Quinn, Gephard, & Saunders, 2014). Striped Bass inhabiting areas once covered by the Laurentide Ice Sheet, that is, the entirety of the Bay of Fundy and Gulf of St. Lawrence must have descended from southern migrants colonizing these rivers within the last 10,000 years as the glaciers retreated (Curry, 2007;Pielou, 1991).
Over the past five decades, Striped Bass stock discrimination has been attempted using many techniques producing inconsistent results when matching individuals to more than two reference populations (Waldman & Fabrizio, 1994;Waldman, Maceda, & Wirgin, 2012).The Chesapeake Bay is usually considered the primary source of migratory Striped Bass found along the North American Atlantic Coast, with the Hudson River occasionally providing large numbers and the Delaware and Roanoke Rivers previously considered to have a negligible contribution (Richards & Rago, 1999;Wirgin, Waldman, Maceda, Stabile, & Vecchio, 1997). Mixed-stock analyses have found that stock composition can vary dramatically.
Hudson River Striped Bass can contribute 14%-89% of coastal aggregations in different seasons and locations and from year to year (Fabrizio, 1987;Wirgin, Maceda, Waldman, & Crittenden, 1993). and nonsignificant differences from the Hudson River; and (d) tributaries within the Chesapeake Bay showed a mixture of homogeny and small differences among each other. This study introduces new hypotheses about the dynamic zoogeography of Striped Bass at its northern range and has important implications for the local and international management of this species.

K E Y W O R D S
aquatic ecology, candidate gene identification, ecology, population genetics, population genomics Existing mixed-stock methods are often unable to reliably differentiate Roanoke River and Chesapeake Bay individuals, and consequently, the Roanoke River population is often merged with the Chesapeake Bay in reference groups, making it difficult to track relative contribution of Roanoke River Striped Bass to the current coastal groups (Waldman & Fabrizio, 1994;Waldman et al., 2012).
The Delaware River is often not considered in coastal stocks, because the Delaware River population is small and was not expected to contribute to coastal aggregations in previous decades (Waldman & Fabrizio, 1994;Waldman et al., 2012); however, acoustic telemetry showed Delaware River Striped Bass make up 14%-20% of Striped Bass caught off the coast of Massachusetts (Kneebone et al., 2014).
A mixed-stock analysis that can reliably distinguish among stocks that exhibit varying degrees of mixing in the coastal environment could substantially improve Striped Bass management.
In addition to the ongoing attempts to characterize Striped Bass migration, the last decade has seen shifts in the existing range of several populations. Large-sized Striped Bass in the Roanoke River population, previously considered largely resident because few tagged fish have been caught outside the river, have been recently shown to migrate approximately 500-600 km to New Jersey (Callihan et al., 2015).
Striped Bass from the Miramichi River, which is considered the only spawning population in the Gulf of St. Lawrence (Robinson, Courtenay, Benfey, Maceda, & Wirgin, 2004), have been caught off the Labrador coast following a decade of strong population growth (Andrews, Dadswell, et al., 2019;DFO, 2018). These apparent range expansions have been attributed to increased ocean temperature (DFO, 2018), increased population size (Andrews, Dadswell, et al., 2019;Callihan et al., 2014), and an increase in the number of older, larger adults that are more likely to migrate longer distances (Callihan et al., 2014). These F I G U R E 1 On the left, a map showing the current range of Striped Bass along the North American Atlantic Coast. Potential additions to the range where Striped Bass have been reported in or may inhabit are marked in darker green. Sampling sites marked in numbered circles as follows and listed according to the location of the river mouth. (1) Bras d'Or Lake, Nova Scotia; (2) Mira River, Nova Scotia; (3) Shubenacadie River, Nova Scotia; (4) Saint John River, New Brunswick; (5) Kennebec River, Maine; (6) Hudson River, New York/New Jersey; (14) Roanoke River, North Carolina; and (15) Cape Fear River, North Carolina. On the right, a close up of Delaware River and Chesapeake Bay, with sampling locations marked as follows. (7) Delaware River, New Jersey/Delaware; (8) upper Chesapeake Bay, Maryland; (9) Potomac River, Maryland; (10) Rappahannock River, Virginia; (11) James River, Virginia; (12) Choptank River, Maryland; and (13) Nanticoke River, Maryland emerging migrations highlight the need to apply more sophisticated population discrimination tools to best inform management.
Several attempts have been made to use genetic markers in mixed-stock analysis of Atlantic Coast Striped Bass (Brown, Baltazar, & Hamilton, 2005;Gauthier et al., 2013;Wirgin, Waldman, et al., 1997), within the Bay of Fundy (Wirgin et al., 1995), and the Gulf of St. Lawrence (Robinson et al., 2004). Two studies have comprehensively investigated the genetic structure among the major migratory populations of the North American Atlantic Coast (Gauthier et al., 2013;Wirgin, Maceda, Tozer, Stabile, & Waldman, 2020). Previous studies have found consistent genetic differences among known Canadian populations (Bentzen & Paterson, 2008;Wirgin, Ong, et al., 1993), and lower but significant differences between regions such as the Hudson River and Chesapeake Bay (Gauthier et al., 2013;Wirgin, Waldman, et al., 1997); however, rivers in close proximity to each other, particularly the Chesapeake Bay and Delaware River, have had inconsistent results (see Brown et al., 2005). Most recently, Gauthier et al. (2013) and Wirgin et al. (2020) found very low but significant differences among rivers within the Chesapeake Bay using 14 and 8 microsatellites, respectively, but both were unable to assign a high number of individuals to a river of origin.
Genotyping by sequencing (GBS) can be used to construct large panels of single nucleotide polymorphisms (SNPs) throughout the genome of an individual organism (Narum, Buerkle, Davey, Miller, & Hohenlohe, 2013;Poland, Brown, Sorrells, & Jannink, 2012 While these outlier analyses are biased toward detection of single loci with strong signals of selection over more subtle polygenic adaptation (Rockman, 2012), they can serve as a starting point for identifying adaptive differences between populations. Moreover, inclusion of outlier loci in tests of population differentiation can disproportionately bias results (Allendorf & Seeb, 2000;Luikart, England, Tallmon, Jordan, & Tab erlet, 2003). Once identified, these loci can then be removed from analyses of genetic structure, migration, and effective population size, and examined separately to gain insights into adaptive selection that may be occurring in a population and highlight potential candidate genes for future studies.
In this work, we employ next-generation sequencing to examine the genetics of Striped Bass from 14 locations across the native range, from the Gulf of St. Lawrence to the southernmost edge of the migratory range in the Roanoke River ( Figure 1). We sample two locations (Hudson River and Delaware River) in two different years to assess temporal stability of populations. We include samples from six tributaries within the Chesapeake Bay to examine small-scale spatial differences. Also included are samples from the Cape Fear River, which has a supportive breeding program to maintain a Striped Bass population in-river, the recently restored Kennebec River, and from the Mira River on the northeastern coast of Nova Scotia, which is speculated to host a spawning aggregation of Striped Bass (Buhariwalla, 2018). We assess neutral genetic structure and characteristics of SNPs that show signs of selection, and we test the ability of our SNP dataset to assign Striped Bass back to their natal population.

| Sample collection
Fin clips and scales were taken from Striped Bass from multiple collections ( Table 1). Age of sampled individuals differed by location.
YOY juveniles were individuals less than 1 year old (<15 cm long).
Saint John juveniles were 1-4 years old and largely spawned in the year 2013. Ages for Saint John River juveniles were obtained from scales. Adults were sexually mature individuals aged 4 years and older. All adults collected were in spawning condition at time of sampling, except for Bras d'Or Lake, Mira River, and Shubenacadie River. Shubenacadie origin Striped Bass migrate to the Stewiacke-Shubenacadie systems from overwintering sites during the sampling period (DFO, 2014;Keyser, Broome, Bradford, Sanderson, & Redden, 2016). Adult bass caught during this period are assumed to be of Shubenacadie River origin for the purpose of population surveys (DFO, 2014). Putative Miramichi River origin Striped Bass were included using fin clips taken from Striped Bass caught in the Bras d'Or Lake, Cape Breton, that have previously been examined using microsatellites and found to match the Miramichi River population (Bentzen, Mcbride, & Paterson, 2014). These samples will hereafter be referred to as Bras d'Or-Miramichi individuals (Box 1).

| Laboratory
DNA was isolated using either NucleoMag ® 96 Tissue (Macherey-Nagel) kit on an epMotion 5075t (Cat. 5075000302), or the E.Z.N.A. Tissue DNA Kit (Omega Bio-Tek). Libraries containing 96 individuals each were prepared using a double-digest restrictionsite-associated DNA sequencing (ddRAD-seq or ddRAD) protocol developed by Poland et al. (2012) and modified as described in LeBlanc et al. (2018). Samples were randomized so that each lane contained individuals from multiple locations and sequenced using Illumina ® HiSeq™ 2,500 or Illumina ® HiSeq™ 4000 (San Diego) at Génome Québec Innovation Centre.

| Quality control and analysis
SNPs were demultiplexed and filtered using modified versions of Eric Normandeau's Stacks workflow scripts, available on github (https:// github.com/enorman deau/stacks_workflow, downloaded August 2016). Cutadapt v. 1.13 (Martin, 2011) was used to trim adapters from the raw sequences using a maximum error rate (e) of 0.2 and a minimum read length (m) of 50. FastQC v. 0.11.5 (Babraham Bioinformatics) was used to assess sequence quality before and after. Sequences were then trimmed to a uniform length of 85 bp and demultiplexed using the process radtags module of Stacks v. 1.46 (Catchen, Hohenlohe, Bassham, Amores, & Cresko, 2013) using the paired-end option -P. BWA version 0.7.15 (Li & Durbin, 2010) was used to align sequences to the Striped Bass genome (BioProject accession number PRJNA266827) using a minimum seed length (k) of 19, a maximum seed occurrence of 55, and no filtering on output alignment score, and otherwise default parameters. The stacks module pstacks identified reference aligned loci with a minimum depth (m) of 4 using the "snp" model type and an alpha of .1. Loci were assembled into a catalogue using cstacks, sstacks, and rxstacks with default settings, and unclear or unlikely haplotypes, as well as SNPs with a log likelihood <45, were pruned from the dataset. Using the populations module, SNPs were further filtered to remove all loci with a stack depth <5, with >20% missing data in any given location, and any loci not amplified in all locations. We examined the output of populations and removed loci with an Fis < −0.3 to eliminate possible paralogs, and used VCFTools 0.1.13 (Danecek et al., 2011) to remove any loci with a minor allele frequency <0.01, and plink v. 1.90 (Chang et al., 2015) was used to remove loci in linkage disequilibrium with each other.
Structure files created by Stacks were converted to the appropriate input files for downstream analyses using PGDSpider v.
2.1.1.0 (Lischer & Excoffier, 2012). Sibship analyses were carried out in Colony2 v. 2.0.6.5 (Jones & Wang, 2010) on each population separately to ensure individuals were not closely related. Full sibling pairs identified with a probability of >.5 were removed from subsequent analyses. Percent polymorphism of loci in each population was reported by the Stacks populations module, and expected and observed heterozygosity were calculated using the R package adegenet v. 2.1.1 (Jombart, 2008).
An initial pairwise F ST analysis was conducted in Arlequin v.
3.5.2.2 (Excoffier & Lischer, 2010), with significance assessed using 10,000 random permutation tests. Individuals caught in the Hudson River and Delaware River in 2012 and 2014 were grouped by location and year in order to assess whether the genetic profile of each location differed from year to year. After confirming no significant

| Constructing a neutral SNP panel and assessing adaptive selection
Outlier loci were removed prior to subsequent population genetic analyses, and a subset of outliers were examined separately.  (Foll & Gaggiotti, 2008) was run with 100,000 iterations, using a burn-in of 50,000, a thinning interval of 10, and a sample size of 5 K. Prior odds were set to 1,000 to minimize false positives while retaining power to detect outliers (Lotterhos & Whitlock, 2014). We also used the recently developed R package OutFLANK (Whitlock & Lotterhos, 2015) with Hmin >0.1 to identify an additional set of outliers. Unlike previous outlier tests like BayeScan, outFLANK uses distribution of allele frequencies across all loci to account for differences in genetic structure among populations (Whitlock & Lotterhos, 2015). Loci identified as outliers at a q-value ≤0.05 by either method were removed to create a dataset of putatively neutral loci for genetic structure analyses. Loci identified as outliers by both methods were mapped to one of 35,010 scaffolds contained in the published Striped Bass genome using the JBrowse genome browser (Skinner, Uzilov, Stein, Mungall, & Holmes, 2009) to identify associated genes showing signatures of selection, and allele frequencies were calculated in Arlequin to investigate divergence patterns across populations.  (Archer, Adams, & Schneiders, 2017), and corrected to account for multiple tests using the false discovery rate method detailed in Benjamini and Hochberg (1995). Chi-square tests have high power and low false-positive rates when used on large numbers of biallelic loci, as found in SNP datasets (Ryman et al., 2006).

| Connectivity of Striped Bass locations through population genetic structure
Isolation by distance (IBD) was assessed using mantel tests implemented in Arlequin v. 3.5.2.2 (Excoffier & Lischer, 2010 always been on the forefront of these changes and applying them to nonmodel organisms, often in natural settings. Many of these species had few genomic tools developed and many of the datasets were "messy" in comparison with zebrafish in laboratory settings, requiring innovated data analysis strategies. Louis has always embraced these situations as the variability is not a nuisance but rather fundamental to the way nature works. Highly duplicated genomes, traits controlled by many loci, panmictic or nearly panmictic species, are just a few of the messy systems that Louis has studied which have resulted in substantial insights about how selection, drift, migration, and mutation affect Earth's biodiversity. criterion. The K values with the lowest minimal cross-entropy value were considered most probable as the true number of ancestral populations (Frichot, Mathieu, Trouillon, Bouchard, & François, 2014).
Where the lowest entropy was unclear, clustering results for the lowest K values were manually inspected for informative grouping and consistency across repetitions. Population structure was also assessed using Discriminant Analysis of Principal Components (DAPC; Jombart, Devillard, & Balloux, 2010), implemented in the R package adegenet, using 1-20 assumed clusters (K). The number of putative clusters with the lowest Bayesian information criterion value was chosen to evaluate population groupings. Another DAPC analysis was conducted with samples taken from Canadian rivers excluded, using the same methods described above.

| Assessing the power of SNPs and reference pool for population assignment
We tested whether our SNP panel could accurately assign individuals to populations of origin using a leave-one-out protocol implemented in GeneClass2 v. 2.0 (Piry et al., 2004), using the Rannala & Mountain, 1997 Bayesian method (Rannala & Mountain, 1997).
Assignment success was compared to results from another genetic assignment algorithm implemented in the R package rubias, again using a leave-one-out protocol. Using this protocol, each individual is assigned to a region using a reference panel composed of all individuals except the one being tested.
We tested assignment success of all sample locations separately, as well as assignment to pooled groups according to previous population groupings used in Gauthier et al. (2013). In both cases, we considered an individual assigned to a population if the confidence score for assignment to that population was 80% or above.

| Filtering
The initial SNP catalogue contained 756,713 loci. After filtering for Ln Likelihood less than −40, the catalogue contained 670,167 loci.
After filtering out loci with stack depths of less than five, more than 20% missing data, more than two alleles, and loci present in fewer

| Outliers
Outlier analyses identified 35 total outlier loci: BayeScan identified 13 loci as possible outliers, compared to 25 loci found by outFLANK, and 3 loci were identified by both analyses. All 35 potential outliers were excluded from downstream genetic structure analyses, while the three loci identified by both approaches were examined further TA B L E 2 as putative adaptive loci. These three loci were located on three different scaffolds and were given names according to their scaffold number and base pair position on the scaffold (scaffold_bp). Locus 4437_41108 is located 41,108 base pairs into a large (77,288 bp) scaffold, Msax_4437, inside an intron of insulin-like growth factor 2b (igf2b). The remaining two outliers, 25891_222 and 27535_2519, were located on short (2,825 and 5,316 bp, respectively) scaffolds with no known genes.
Examination   Figure S1). Canadian Striped Bass formed three groups, and all US Striped Bass were assigned to a fourth group ( Figure 3; Table 4). This general pattern was seen when DAPC was run assuming five and six genetic groups ( Figure S2). Using LEA, the number of genetic clusters (K) with the lowest entropy across 10 runs was 6 ( Figure S1). We visualized clustering patterns for K values 4 through 7 to identify hierarchal clustering patterns as K increases ( Figure 4). In all simulations, Canadian Striped Bass clustered into the same three groups as in DAPC. North Carolina rivers separated into their own cluster at K = 5, while Kennebec River and Hudson River separated at K = 6, and at K = 7, the two rivers on the eastern coast of Chesapeake Bay (Nanticoke River and Choptank River) primarily belong to the seventh cluster ( Figure 4). The same clustering pattern was seen when US samples were analyzed separately from Canadian samples ( Figures S3 and S4). When LEA was run with balanced sampling numbers, the lowest entropy was K = 4 as seen in DAPC analyses. Canadian locations clustered into three regions, while all US Striped Bass were clustered together. Mean assignment per location remained high when K was increased to 6, with the same clustering pattern seen in the full dataset ( Figure S3).

| Assignment
Analyses were performed at two spatial resolutions to determine the geographic scale to which reliably natal assignments could be made. When individuals were compared to all 15 collection locations in GeneClass 2, 53% were assigned back to their collection location (

TA B L E 5 Self-assignment of Striped
Bass samples from 6 regions (proposed reporting groups) in GeneClass2 using 1,256 putatively neutral SNP loci. Individuals were considered to belong to a reporting group if they were assigned with a confidence score of 80% or more. Rows correspond to the location individuals were collected in, while columns correspond to assigned reporting group

| Genetic diversity
The lowest observed heterozygosity values seen in this study (0.26-0.28) were similar to observed heterozygosity seen in other anadromous fishes examined using SNP markers, such as Blueback Herring

| Outlier loci represent regions of major effect
Most ecologically relevant traits are thought to be polygenic, involving small allele frequency differences of many genes (Pavey et al., 2015;Yeaman, 2015). All three outliers identified in this study showed high allele frequency changes among populations (

Rivers near the Gulf of St. Lawrence (Bras d'Or-Miramichi and Mira
River), the Shubenacadie River, and the Saint John River were consistently, highly differentiated from each other and from US populations (F ST = 0.13-0.20). Phylogeographic theory predicts that populations founded after the last glacial retreat will show less intraspecific divergence than their southern counterparts (Bernatchez & Wilson, 1998). Unexpectedly high divergence in Canadian populations has been seen in other anadromous fishes along the North American Atlantic coast and has been attributed both to the circuitous coastline created by the Nova Scotia peninsula and to a complex hydrography within the Bay of Fundy that drives differentiation of native fish populations (Hasselman et al., 2013;King, Kalinowski, Schill, Spidle, & Lubinski, 2001;McConnell, Ruzzante, O'Reilly, Hamilton, & Wright, 1997). Variation in habitat is known to drive differentiation of anadromous fish species such as Atlantic Salmon (Bradbury et al., 2014) and Dolly Varden Char (Salvelinus malma; Bond, Crane, Larson, & Quinn, 2014). The Shubenacadie River, in particular, is the only tidal bore river wherein Striped Bass are known to successfully spawn (Rulifson & Dadswell, 1995), and the extreme environmental conditions that eggs and larvae must tolerate in this river may contribute to its increased population differentiation (Rulifson & Tull, 1999). Unexpectedly high genetic divergence in Canadian populations could also be the result of small initial colonization sizes driving changes in allele frequencies that persist to the present day (Excoffier & Ray, 2008).

Genetic similarity between the Mira River and Bras d'Or-
Miramichi Striped Bass indicates that these two groups have the same origin. It is likely that Striped Bass currently residing in the Mira River migrated from the Miramichi River at some point after the formation of suitable estuarine habitat and nursery areas some 500-800 years ago (Andrews, Dadswell, et al., 2019). While Striped Bass in the Mira River appear behaviorally distinct, demonstrating multiannual residency and spring upstream migration shown in an acoustic telemetry study in 2012-2015 (Andrews, Dadswell, et al., 2019;Buhariwalla, 2018), our data suggest that this potential spawn-  Hogans & Melvin, 1984), the Bay of Fundy (Broome, 2014;Rulifson & Dadswell, 1995), and along the US coast Richards & Rago, 1999;Waldman et al., 1990) have been externally tagged from the 1960s to the present day (Andrews, Dadswell, et al., 2019), only one of which has ever been caught on the far eastern shores of Nova Scotia Douglas et al., 2003).
This apparent isolation may be caused by a physical isolation of the Gulf of St. Lawrence before the Canso Strait opened postglacier retreat (Shaw & Courtney, 2002) and after the Canso Causeway was built in 1955 (Vilks, Schafer, & Walker, 1975), or influenced by a sharp temperature change between the two water bodies (Rulifson & Dadswell, 1995). A "genetic breakpoint" has been described in several other species along eastern Nova Scotia at ~45°N (close to the City of Halifax; Stanley et al., 2018). Increasing ocean temperatures are predicted to drive Striped Bass populations north, but this remains a poorly studied region.
The presence of a genetically distinct population of Striped Bass in the Saint John River following its suggested extirpation in the 1970s has been debated for over a decade (Andrews et al., 2017).
Two previous studies have found evidence of unique genotypes distinct from US and Shubenacadie River Striped Bass, and present in adults (Bentzen & Paterson, 2008) and juveniles (LeBlanc et al., 2018). A third study examined a mixture of 17 juveniles and 25 adults collected from the Saint John River in 2014 and found that all fish showed admixture between Shubenacadie River and US genotypes with no unique cluster (Wirgin et al., 2020). The 17 juveniles examined by Wirgin et al. (2020)  River before the population crash and no information about possible admixed individuals (Andrews et al., 2017). Larger Striped Bass are more likely to migrate and to travel far (Andrews, Dadswell, et al., 2019;Callihan et al., 2014;DFO, 2018), and as Striped Bass populations recover, there is an increase in the number of older, larger individuals making migrations (Callihan et al., 2014). We hypothesize that the admixed juveniles result from small numbers of local spawners making admixed offspring more prevalent, increased migration from recovering populations, and a climate-induced northward range shift.
Our study also investigates the current genetic profile of the recently restored Kennebec River population of Striped Bass. The Kennebec River is one of several rivers in Maine that likely once hosted a native population of Striped Bass (Little, 1995 Striped Bass found significant differences in minor length-frequency alleles from Chesapeake Bay Striped Bass (Waldman & Wirgin, 1994). Minor length-frequency differences were also seen among tributaries within the Chesapeake Bay , and microsatellite studies which found significant F ST values between the Delaware River and the Chesapeake Bay also found F ST values of the same magnitude among tributaries within the bay (Gauthier et al., 2013). Decades of observations of adult Striped Bass using the Chesapeake and Delaware Canal to transit between the Chesapeake and Delaware estuaries during spawning season (Kneebone et al., 2014;Koo & Wilson, 1972;Nichols & Miller, 1967)

| Assignment
Self-assignment tests were performed on the SNP panel generated in this study to assess its utility as a reference dataset for future mixed-stock analyses. Previous attempts to use genetic markers for mixed-stock analysis have met with limited success. Most recently, a study conducted self-assignment tests using GeneClass2 on 14 microsatellites and was able to assign 60% of Striped Bass from the Hudson River, Chesapeake Bay (including the Delaware River), North Carolina, and South Carolina to a region of origin (Gauthier et al., 2013). Our SNP panel showed the highest assignment success when overlapping populations were grouped into the same reporting groups used by Gauthier et al. (2013). We were able to assign 99% of Striped Bass to a region of origin with >80% confidence.
When individuals were assigned to river of origin (rather than region of origin), assignment success was much lower and individuals were misassigned to other rivers within the same region, reflecting the low genetic differentiation among these rivers. The assignment success rate seen within regions is likely an indication that rivers within a region are not demographically independent.
Statistical biases when using large panels of SNP loci have been identified in assignment tests that use simulated individuals to predict assignment accuracy of a set of loci (Anderson, Waples, & Kalinowski, 2008); however, the data in this present study indicate that self-assignment tests in the absence of simulations can result in misleadingly high confidence values. In light of emerging techniques allowing high-throughput genotyping of large numbers (>1,000) of loci (Ali et al., 2016), researchers looking to assess stock composition of increasingly closely related populations should interpret confidence scores with these issues in mind when choosing a geographic resolution in which to assign fish. In addition, admixed individuals seen in the Saint John River were assigned to one of their parent populations with high confidence, suggesting that assignment in both GeneClass2 and rubias is insensitive to the presence of admixed individuals. When performing mixed-stock analysis on locations with large numbers of hybrid individuals, assignment may be better conducted using a genetic clustering algorithm such as those found in LEA or STRUCTURE. Overall, our SNP panel constitutes a significant improvement over other genetic markers in assigning Striped Bass to regional areas along the Atlantic coast and will be invaluable to the development of a highly accurate and reliable genetic tool for mixed-stock analysis of the species across the central and northern portion of their range.

| CON CLUS ION
Striped Bass have been thought to exhibit a high degree of natal homing (Pess et al., 2014), but recent genetic and telemetry studies indicate the species expresses more variability in homing to their natal river (e.g., Callihan et al., 2015;Gahagan et al., 2015). Studies document skipped spawning and straying among populations (Gahagan et al., 2015;Kneebone et al., 2014). Low or nonexistent genetic structure among tributaries in the Chesapeake Bay and the connected Delaware River (see also Brown et al., 2005;Gauthier et al., 2013) suggests that straying or colonization among rivers in this region is common. Canadian populations at the northern range limit exhibited greater genetic isolation, but with evidence of hybrid-

ACK N OWLED G EM ENTS
We would like to thank Louis Bernatchez for the opportunity to contribute to this special issue (Box 1). We would like to acknowledge Paul

CO N FLI C T O F I NTE R E S T
None declared.

DATA AVA I L A B I L I T Y S TAT E M E N T
Raw sequencing data are available on the US National Center for