Climate-driven range expansion via long-distance larval dispersal

Climate-driven range expansion via long-distance larval dispersal | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Climate-driven range expansion via long-distance larval dispersal Cataixa López, Benjamin N. Daniels, Evan B Freel, Andy Lee, Jean M. Davidson, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4670567/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Climate-driven warming and changes in major ocean currents enable poleward transport and range expansions of many marine species. Here, we report the population genetic structure for the gastropod Kelletia kelletii , a commercial fisheries species and subtidal predator with top-down food web effects, whose populations have recently undergone climate-driven northward range expansion. We genotyped 598 adults from 13 locations across the species’ historical and expanded range ( ∼ 800 km) using reduced representation genomic sequencing (RAD-seq). Analyses of 40,747 SNPs show evidence for long-distance larval dispersal of K. kelletii larvae from a central historical range site (Point Loma, CA) hundreds of km into the expanded northern range (Big Creek, CA), which seems most likely to result from transport during an El Niño Southern Oscillation (ENSO) event rather than consistent on-going gene flow. Furthermore, despite smaller geographic distances among some sampled expanded-range populations, their genetic divergence exceeds that among the historical range sampled populations, suggesting multiple origins of the expanded-range populations. Given the frequency and magnitude of ENSO events are predicted to increase with climate change, understanding the factors driving changes in population connectivity is crucial for establishing effective management strategies to ensure the persistence of this and other economically and ecologically important species. Marine and Freshwater Ecology El Niño Southern Oscillation (ENSO) RADseq larval dispersal colonization event Kelletia kelletii Figures Figure 1 Figure 2 Figure 3 Introduction Human-induced ocean warming is causing alterations in species distributions, abundances, and phenology according to their thermal tolerance and ability to adapt (Harley et al. 2006 , Poloczanska et al. 2013 , Bernardi et al. 2024 ). More suitable conditions created by ocean warming have enabled many species with tropical affinities to successfully disperse poleward and establish populations beyond their historical range limit (Vergés et al. 2014 , Spies et al. 2020 ). Coupled with ocean warming, changes in major ocean currents and increased frequency of extreme oceanographic events, such as marine heatwaves and El Niño Southern Oscillation (ENSO) events (Yeh et al. 2009 , Cai et al. 2015 ), are increasing the frequency and magnitude of range expansions. This phenomenon is causing a reorganization of marine biota (Bindoff et al. 2007 , Lonhart et al. 2019 , Sanford et al. 2019 ), altering the structure and dynamics of community interactions among resident species (Gilman et al. 2010 , Gehrels et al. 2016 , Marzloff et al. 2016 , Wainright et al. 2021 ). By the end of the 20th century, the northeast Pacific Ocean had risen 0.8°C above pre-1950 historical levels (Roemmich 1992 ). In the past two decades, this region has experienced the combined effects of increasing temperatures and frequencies of anomalous oceanographic events, with 2022 being the warmest year on record (Chao et al. 2017 , Harvey et al. 2023 ). Consequently, many species across different taxa are undergoing shifts in their population distribution and abundance, with a general trend of poleward displacement (Cavole et al. 2016 , Molinos et al. 2018 , Osland et al. 2021 ). Some of these population expansions are associated with episodic anomalously warm oceanographic events (Sorte 2001 , Lluch-Belda et al. 2005 , Yamada et al. 2021 ). One example is the subtropical red crab Pleuroncodes planipes , where adults are sporadically found in central locations of California due to anomalous advection but without evidence of reproduction (Cimino et al. 2021 ). In contrast, several species have been able to establish stable populations that are reproducing beyond their historical distribution range (Goddard et al. 2016 , Spies et al. 2020 ), which could then act as a source of larvae for future expansions. Such alterations in population dynamics are leading to widespread concern about the future of ecosystem structure and function, and the indirect impacts on regional economies when these variations involve commercially fished species (Gilman et al. 2010 , Pinsky et al. 2018 , Young et al. 2019 , Spies et al. 2020 ). Kellet’s whelk (Buccinoidea: Kelletia kelletii ) is a subtidal gastropod whose populations have undergone a considerable poleward expansion along the west coast of North America (Herrlinger TJ 1981 , Zacherl et al. 2003 ). The historical northern range limit of Kellet's whelk was Point Conception, a widely recognized oceanographic and biogeographic border between warm-temperate and cool-temperate species (Ricketts et al. 1985 , Hohenlohe 2004 , Broitman et al. 2008 , Pelc et al. 2009 ). However, in 1980, five adult Kellet’s whelk (≥ 60 mm) were found in central California (3 in Monterey Bay and 2 in Big Creek), far north of their historical range, presumably due to ocean warming (Herrlinger TJ 1981 ). Kellet’s whelk is an ideal candidate for exploring the mechanism of poleward range expansion because it has high dispersal potential, with pelagic larval durations of up to 60 days (Romero et al. 2012 ). Furthermore, the extremely low population genetic structure throughout the species’ range at neutral loci (White et al. 2010 , Selkoe et al. 2010 ) also makes it a challenge for traditional population genetic inference, like many marine species. The first detections of range expansions were ~ 300 km beyond the species’ historical northern range limit (Herrlinger TJ 1981 ), and subsequent population surveys found irregular size-frequency distributions that suggest only occasionally successful recruitment (Zacherl et al. 2003 , Palmer 2016 ). These observations beg the question of whether the range expansion was the result of periodic long-distance dispersal events rather than a consistent march northward by an expanding population. Additionally, are these marginal populations maintained by long-distance larval recruitment, perhaps during unusual or periodic (ENSO) oceanographic events, or are they maintained by local recruitment of larvae spawned from within the species’ expanded range (Zacherl et al. 2003 , Lluch-Belda et al. 2005 , Cimino et al. 2021 )? Examining the range expansion in Kellet’s whelk not only presents an intriguing scientific question on the origin of novel populations but also carries broader ecological and economic implications. Kellet’s whelk is a subtidal predator and scavenger with top-down food web effects in kelp forests that also supports the second-largest commercial molluscan fishery in California (Rosenthal R. J. 1971, Schmitt 1987 , Aseltine-Neilson et al. 2006 , Halpern et al. 2006 , CDFW 2024 ). Kellet’s whelk is also prey to numerous species (Limbaugh 1955 , Rosenthal R.J. 1971, 1974), such as sea otters (Lonhart 2001 ), which are more abundant in central California than in its historical range to the south. Recently, fisheries harvest rates of Kellet’s whelk have started to rise in the species’ expanded range in central California (CDFW 2024 ). These studies suggest that the species plays a functional role in kelp forest ecosystems and that its range expansion affects ecological and socioeconomic community dynamics in central California. For all these reasons, understanding how the newly expanded and historical populations are structured is essential for establishing effective and sustainable management strategies for Kellet’s whelk and associated communities in the face of climate change. Furthermore, because Kellet’s whelk shares habitat and several key life history traits with many other coastal marine species in California (Allen et al. 2006 , Froese & Pauly 2011), the results of this study may help predict future expansion by other ecologically and economically important species in the region. Here, we studied the genetic structure of populations of Kellet’s whelk by analyzing reduced-representation genomic sequencing libraries (ezRAD; Toonen et al. 2013 ) using an equimolar pooled approach (Pool-seq; Schlötterer et al. 2014 ). Using this approach, we analyzed thousands of variable nucleotides (SNP loci) from 598 individuals sampled across 13 sites throughout the species’ historical and expanded range, spanning ~ 800 km, to quantify population genetic structure and relationships among geographic sites to test hypotheses regarding the poleward dispersal of K. kelletii into the newly expanded range. Material and Methods Sample collection, DNA extraction, and pooling Foot tissue from 46 K. kelletii adults (> 60 mm shell length; Rosenthal 1970 –23 individuals in 2015 and 23 individuals in 2016 – were sampled non-lethally from each of 13 subtidal locations (~ 15 m depth) across the species’ historical and expanded range (Fig. 1). Collected tissue samples were then frozen on dry ice or liquid nitrogen for transport to the California Polytechnic State University (San Luis Obispo, CA) and stored at -80 ℃ until processed for DNA extraction. DNA extraction was performed using an optimized version of the ‘salting-out’ protocol developed by Li et al. ( 2011 ) and modified by Daniels et al. ( 2023a ), where the full extraction protocol is detailed. Briefly, 30 mg of tissue was lysed with proteinase K and RNase A in a warm water bath. Subsequently, DNA was separated from proteins, which precipitated in the presence of ammonium acetate by centrifugation, and was then purified from the supernatant via ethanol washes. Finally, precipitated DNA was resuspended in Tris-EDTA (1xTE) buffer and stored at -20 ºC until further analyses. DNA quality was assessed visually using a 1% agarose gel in Tris-Acetic Acid-EDTA (TAE) buffer, GelRed (Biotum, Inc) gel stain, and referenced to the 200–10,000 bp Hyperladder I (Bioline, Meridian Bioscience). Because 91.3% of all extractions produced high molecular weight bands (> 10 kb) with faint smears from degraded DNA, all specimens were included in the study. Extractions were quantified using the AccuClear Ultra High Sensitivity dsDNA quantification kit (Biotium, Inc) with 3 standards and measured using a SpectraMax M2 microplate reader (Molecular Devices, LLC). Finally, an equimolar amount of DNA from each of the 46 individuals collected at each location was pooled by the collection site (population), ensuring that each library had the same number of individuals. In total, 598 individuals belonging to 13 populations spanning ~ 800 km were included in the analysis. Library preparation and sequencing Equimolar pooled ezRAD (Toonen et al. 2013 ) libraries were generated following the detailed protocol of Knapp et al. (2016) for all 13 populations. Briefly, genomic DNA was digested using the isoschizomer restriction enzymes Mbo I and Sau 3AI (New England Biolabs, Ipswich, MA). Digestions were performed in a total volume of 50 µl, containing 25 µl of dsDNA (~ 1 µg), 5 µl of NEB Cutsmart Buffer (provided with restriction enzymes), 18 µl of HPLC grade water, 1 µl Mbo I (10 units), and 1 µl Sau3 AI (10 units) under the following thermocycler profile: 37 ºC for 18 h, then deactivation at 65 ºC for 20 min. After digestion, samples were cleaned using Mag-Bind TotalPure NGS (Omega Bio-Tek) beads at a 1:1.18 (DNA:beads) ratio to remove fragments < 200 bp (Norcross, GA). Libraries were prepared for sequencing using the KAPA Hyper Prep DNA kit (Roche Sequencing and Life Science) following a modified version of the manufacturer protocol (see Knapp et al. 2016). Quality control by a Bioanalyzer and sequencing of the libraries on one lane of an Illumina HiSeq2500 were performed in the DNA Technologies and Expression Analysis Core Laboratory at the University of California (Davis, CA). Data filtering and SNPs calling Libraries were initially trimmed to remove low-quality bases and adapters using dDocent v.2.9.4 (Puritz et al. 2014), obtaining an average of 16,640,463 reads per sample. The population of Monterey had the lowest number of reads, with 4,439,406, while Yellow Banks had the highest number, with 45,795,618 reads. The same pipeline was used to align the reads using BWA (mem algorithm) to the K. kelletii reference genome, which contains 2,107,417,620 base pairs (2.1 Gb) in 46,654 contigs and a complete BUSCO score of 84.1% (Daniels et al. 2023b ). SNPs were identified using FreeBayes (Garrison & Marth 2012 ) implemented in dDocent, by calling variants from merged bam files produced by the pipeline. The TotalRawSNPs.vcf file contained 18,327,457 shared SNPs, which was further filtered through VCFtools v 0.1.16 (Danecek et al. 2011 ) using the following parameters: max-missing 0.75, maf 0.05, minQ30, and min-meanDP20. Downstream analyses only included loci with 30x coverage as recommended and widely used for reliable SNPs calling with RADseq data (Bentley et al. 2008 , Rivera-Colón & Catchen 2021 ) while also avoiding an overrepresentation of loci with higher quality scores (Li 2014 ). Population genetic analyses The final vcf filtered file produced was imported to TASSEL v. 5 (Bradbury et al. 2007 ) to explore population similarities via Principal Component Analysis (PCA) and to AssessPool ( github.com/ToBoDev/assessPool ), a bioinformatic program designed to analyze and visualize pool-seq data (Freel 2024 ). To calculate population genetic differentiation between sites based on pairwise estimates of F ST , AssesPool uses PoPoolation2, which also calculates pairwise significance ( p- values) using Fisher’s Exact Test (Kofler et al. 2011 ). We also compared the matrix of our pairwise estimates of genetic differentiation to those obtained by White et al. ( 2010 ), where the authors analyzed between 50 and 92 individuals per population from the Southern California Bight using 9 microsatellite DNA loci. For the populations shared between both studies (ANN, COJ, ISV, JAL and YEL, Fig. 1), we compared F ST values using a Mantel test in the vegan R package with 9999 permutations to test for significantly correlated results (v. 2.5–7; Oksanen et al. 2020 ). Results Our ezRAD libraries covered an average of 19% of the Kellet’s whelk reference genome, with Yellow Banks (40.13%) and Monterey (8.9%) being the populations with the highest and lowest genomic coverage, respectively. After filtering with VCFtools, a total of 46,737 shared SNPs were retained, of which 46,310 were biallelic and 427 multiallelic SNPs. Due to the low number of multiallelic SNPs (0.9%) and the insensitivity of these findings to their inclusion or exclusion, they were retained for all analyses. Genetic structure ( F ST ) between pairwise populations was low in general, ranging from 0.013 between Anacapa and Isla Vista to 0.028 between Naples and Point Loma (Fig. 2). The 8 populations from the Southern California Bight (SCB) had consistently lower values of F ST for all comparisons, ranging from 0.013 to 0.017 (Fig. 2), while populations within the expanded range showed higher levels of differentiation (i.e. F ST MON vs. BIC = 0.020, BIC vs. JAL = 0.014, and MON vs. JAL = 0.017). Despite the moderately low values, all pairwise comparisons of F ST were significant (p-value < 0.01), showing low but significant population genetic structure in Kellet’s whelk. Comparing the population genetic structure recovered here to the same 5 populations from the SCB previously reported by White et al. ( 2010 ), we found a positive and significant correlation (r = 0.55, p = 0.05) between the pool-seq SNP and individual-based microsatellite results, consistent with isolation by oceanographic distance. The results showed significant population structure throughout the range of Kellet’s whelk, with slightly greater differentiation within the expanded range than in the historical range and least differentiation within the Southern California Bight (SCB). We found moderately high genetic diversity, but comparing the 46,737 SNPs via PCA in TASSEL, we found moderately low genetic differentiation among Kellet’s whelk populations, where our PCA explained a total of 27% of the variance (Fig. 3). Populations located in the SCB were genetically most similar and distinct from the rest of the range-wide samples (Fig. 3), including the population from Jalama (JAL), which is geographically closest (~ 15km) to the SCB, but on the other side of Pt. Conception (Fig. 1). Notably, the two populations that are geographically highly proximate but on either side of Pt. Conception, Jalama (JAL), and Cojo (COJ), are highly differentiated, whereas the two most genetically similar populations among all 13 analyzed are Big Creek (BIC), in the expanded range, and Point Loma (POL), located at ~ 550 km apart into the historical range. Discussion Complicated geography and oceanographic features of the SCB lead to complex current patterns, with internal eddies limiting exchange or promoting high dispersal between distant sites (Mitarai et al. 2009 , Hyde & Vetter 2009 , Alberto et al. 2011 ). In fact, there is no correlation between pairwise genetic differentiation or frequency of larval exchange of the Kellet’s whelk populations and the Euclidean distances among sites in the SCB (White et al. 2010 ). Instead, nearly 50% of the observed variation in population genetic structure was explained by the frequency of larval exchange predicted by ocean currents (White et al. 2010 ). Likewise, kelp bed size (likely a habitat proxy for Kellet’s whelk population size) was a significant predictor of genetic diversity and population differentiation of Kellet’s whelk (Selkoe et al. 2010 ). Dispersal into and out of the SCB is limited relative to along the open coastline, with an offshore California current towards the south and inshore countercurrent to the north (Fig. 1), with considerable seasonal and inter-annual (ENSO) variability (Hobday 2000 , Mitarai et al. 2009 , Watson et al. 2010 ). In addition, coastal pollution was found to be a significant barrier to larval dispersal both within and across the SCB for the bat star Patiria miniata (Puritz & Toonen 2011 ). These studies highlight factors other than geographic distance driving population genetic structure in Kellet’s whelk. Analysis of Kellet’s whelk’s population genetic structure across both the species’ historical and expanded range using genomic loci allows us to test hypotheses about the observed range expansion. For example, among the expanded range samples, Jalama (JAL) is located closest to the historical northern range boundary, only ~ 15 km north of Cojo (COJ) in the SCB. Despite their geographical proximity, these two sites straddle the well-known physiological and biogeographic barrier of Point Conception (Broitman et al. 2008 , Hyde & Vetter 2009 , Selkoe et al. 2010 , Alberto et al. 2011 ), and are among the most genetically divergent of our comparisons ( F st = 0.021). Limited gene flow between these sites is also consistent with observed dramatic differences in abundance and size frequency distributions of individuals in the recently expanded population (JAL), compared to individuals from the historical range across Point Conception (COJ) (Zacherl et al. 2003 ). This study and our data collectively indicate that Kellet’s whelk’s range expansion was not a march northward from the leading edge of the historical range (COJ) into the expanded range (JAL). Decreased genetic diversity and increased pairwise differentiation of expanded range populations due to multiple successive founder events are consistent with climate-driven range expansion (Robalo et al. 2020 ). We see mixed support for this prediction in terms of increased differentiation among each of the three sites in the expanded range relative to the historical range, and no evidence of reduced genetic diversity among samples of 46 adults from each of these populations. Instead, we find relatively low population differentiation ( F ST = 0.013) between Big Creek (BIC, one of the northernmost expanded range sites) and Point Loma (POL, one of the southernmost historical range sites), consistent with migration between these locations (presumably, from POL to BIC). Furthermore, these two geographically isolated populations are genetically most similar in terms of shared SNPs in the PCA analysis and are highly divergent from other sampled sites (Fig. 3). With thousands of polymorphic SNPs shared by 46 adults per population, it is unlikely that a founder event from the introduction of just a few individuals from Point Loma (POL) to Big Creek (BIC), for example, by human-mediated transport, could explain the genetic similarity. Given that these locations are ~ 660 km apart and separated by many other sampled populations, this similarity is most consistent with range expansion through larval transport, possibly associated with an ENSO event (Zacherl et al. 2003 ). During these ENSO events, reduced thermal barrier to larval dispersal, combined with alterations in the main ocean currents, facilitate dispersal further north beyond Point Conception (Sorte 2001 , Lluch-Belda et al. 2005 , Yamada et al. 2021 ). The ENSO dispersal hypothesis is also supported by results of a length-age model for Kellet’s whelk (Palmer et al. 2018 , White et al. 2022 ), which suggests that the individuals first found in Monterey (Herrlinger TJ 1981 ) were spawned between 1969 and 1974, coincident with the 1972-73 ENSO event, which was one of the major ENSO events during the 20th century (NOAA 2018 ). The finding that the populations of Monterey (MON) and Isla de Todos Santos (ITS) are roughly equally divergent from the rest of the populations suggests a possible link between these populations. MON and ITS also show a clear divergence from one another, yet it is noteworthy that these two populations also showed the highest amount of missing data (Figure S1), which may confound RAD-seq results (Arnold et al. 2013 , Huang & Knowles 2016 , Shafer et al. 2017 , Hemstrom et al. 2024 ). To test whether our results were sensitive to such effects, we looked for a correlation between the amount of missing data per comparison and the corresponding pairwise F ST value and did not find any (Figure S1). Furthermore, performing the analyses with varying cutoffs for missing data ranging from 0 to 50% does change the relative position of these populations in the PCA but does not alter our inferences about the overall population structure (Figure S2). The only two populations greatly affected by the amount of missing data were Monterey (MON) and Isla de Todos Santos (ITS), which generally remain genetically distinct from all other sampled populations, but the relative amount of divergence between these two varies (Figure S1). Thus, our geographically proximate samples from within the expanded range show moderate population differentiation and are each genetically more similar to some sites within the historical range than they are to one another. These results are more consistent with multiple long-distance colonization of these newly range-expanded populations than a slow poleward march of an expanding population. Alternatively, selection could drive population differentiation irrespective of dispersal, similar to patterns identified for the intertidal crab Petrolisthes cinctipes along the northern California coastline (Toonen & Grosberg 2011 ). Previous work showed that Kellet’s whelk may be capable of adapting to the colder environment by altering their metabolic rates (Vasquez et al. 2019 , Lee et al. 2024 ) and increasing the concentration of proteins involved in energy metabolism and oxidative stress (Vasquez et al. 2019 , Daniels et al. 2023b , Lee et al. 2024 ). Adaptation to cold temperatures may help explain the persistence of individuals in the extended range, but the mechanism by which whelks colonized these northern range expanded sites remains unknown. Our finding that MON and ITS populations are genetically closer to one another than any others but still show clear population differentiation may be a result of long-distance dispersal followed by selection to survive in colder environments. In support of this hypothesis, Lee et al. ( 2024 ) found Kellet’s whelk in the expanded range to be upregulating triosephosphate isomerase (TPI), an essential enzyme for cold stress response. Nevertheless, whether these divergence patterns are driven by a response to selection, genetic drift, or a combination of both mechanisms requires additional studies. Conclusions & Implications Most marine animal species have a biphasic life cycle in which dispersal occurs primarily through the pelagic larval phase (Thorson 1950 , Kinlan & Gaines 2003 , Weersing & Toonen 2009 , Burgess et al. 2016 ). Larval dispersal kernels are generally leptokurtic, in which most successful recruits remain relatively close (10s to ~ 100 km) to the spawning site but with a long tail of some individuals that can be transported much longer distances (Kot et al. 1996 , Strathmann et al. 2002 , Siegel et al. 2008 , D’Aloia et al. 2015 ). Poleward range expansions have been studied for decades in terrestrial organisms, which generally follow a stepping-stone pattern, in which most dispersal occurs relatively near the parents to form reproductive populations that seed further expansions (Ibrahim et al. 1996 , Morales 2002 , Thomas 2010 , Saura et al. 2014 , Robalo et al. 2020 ). This process would result in a continuous slow-and-steady population range expansion through multiple successive founder events, because long-distance dispersers are unlikely to find mates, even if they survive and grow to reproductive maturity. The predictable consequences of such a process include reduced genetic diversity and high differentiation of populations in the expanded portions of the range relative to in the historical range (Robalo et al. 2020 ). Contrary to such predictions, the first observations of Kellet’s whelk in the species’ expanded range was ~ 300 km beyond its historical northern range limit (Herrlinger TJ 1981 ). Further, observations of irregular size-frequency distributions in the expanded range suggest that recruitment has been episodic (Zacherl et al. 2003 , Palmer et al. 2018 ). In support of these early observations, our results here show both high genetic diversity and minimal population genetic structure ( F ST ≈ 0.01 to 0.03) of Kellet’s whelk along its entire geographical distribution range. The greatest genetic divergences are seen among the newly expanded populations and some portions of the historical range, but those differences are roughly equivalent to the full range of population differentiation observed among sites within the historical range (Fig. 2). Further, each of these divergent expanded-range samples are more similar to a site within the historical range than to any geographically proximate location. In particular, the genetic similarity of Point Loma (POL) deep in the historical range to Big Creek (BIC) in the recently expanded range provides compelling evidence of long-distance larval dispersal. Overall, the observed patterns are more consistent with long-distance dispersal from central range origins, likely associated with an ENSO event, than with progressive northward population expansion due to ocean warming. Our findings have implications not only for Kellet’s whelk but likely for many other ecologically and economically co-distributed species in California that share similar dispersal characteristics and life history traits, such as the spiny lobster ( Palinurus interruptus ) and California sheephead ( Semicossuphus pulcher ) (Allen et al. 2006 , Selkoe et al. 2010 , Froese & Pauly 2011). The frequency and amplitude of ENSO events are predicted to increase under climate change (Power et al. 2013 , Cai et al. 2015 ), which will likely result in more frequent northward expansions and changes in biogeographic species ranges similar to Kellet’s whelk. Studies such as this one, focused on understanding and identifying the factors altering marine population dynamics, are essential to establishing effective management and conservation measurements that ensure the health of marine ecosystems and the services they provide to human populations. Declarations Acknowledgments Cataixa López thanks the University of La Laguna and the Spanish Ministry of Universities for the Margarita Salas postdoctoral fellowship, granted by Order UNI/551/2021 and funded by Next Generation European Union Funds. We thank members of the ToBo Lab, especially Mykle Hoban and Evan Freel, for sharing their expertise and advice during data analyses. We thank Paul Anderson at the Bioinformatic Research Group at California Polytechnic State University for helping with the Kellet’s whelk genome assembly. We thank members of the Center for Applied Biotechnology Lab at California Polytechnic State University, including Jenna Nurge, Olivia Sleeper, Jaden Hansen, Anabel Sanchez, Gabriella Richardson, Hanna Jaynes, Tyler Weipert, Alyssa Queen, Kathryn Hutchinson, Olivia Watt, Jordan Reichhardt, Chanel De Smet, and Alli Clark for extracting Kellet’s whelk DNA. This study was supported by the National Science Foundation under grant #OCE-1924604 to C. White, M. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4670567","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":321441150,"identity":"2b4f8e23-5925-4920-8e34-f4e966a67ef3","order_by":0,"name":"Cataixa López","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9UlEQVRIiWNgGAWjYLCCBAYGGTDjAxCzsRNUzwzWwgNiMs4AaWEmRgsDVAszD0IAN+BvP3/ww8M2Ox5+6ebDn21+bZPnY2Zg/PAxB7cWiTPJzBIJZ5J5JOccSzDO7btt2MbMwCw5cxtuLQYMyQwSCRXMPAY3cgySc3tuMwK1sDHz4tPC/5j5R4JBPVBL/ofDlj237QlrkUhmA9pyGGQLYzPDj9uJBLVI3HhsZpFw5jjIL8aMvQ23k9uYGZvx+oW/P/HxzZ9t1XLAEHv84cef27bz25sPfviIRwuSfUDM2AZiMTYQox6qheEPkYpHwSgYBaNgRAEAATdL06i9sTUAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-6877-9466","institution":"Hawai‘i Institute of Marine Biology, University of Hawai‘i at Mānoa, Moku o Lo‘e, Kāne‘ohe, HI, 96744, USA","correspondingAuthor":true,"prefix":"","firstName":"Cataixa","middleName":"","lastName":"López","suffix":""},{"id":321444725,"identity":"7f7c56a3-e4b9-4840-b41e-0337a04a68ee","order_by":1,"name":"Benjamin N. 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Expanded range populations: Monterey (MON), Big Creek (BIC), and Jalama (JAL). Historical range populations: Cojo (COJ), Naples (NAP), Isla Vista (ISV), Yellow Banks (YEL), Anacapa (ANN), Point Dume (POD), Palos Verdes (PAV), Dana Point (DAP), Point Loma (POL) and Isla de Todos Santos (ITS). Main ocean currents within the Southern California Bight are also shown.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-4670567/v1/f417e72fdcd4beb5d71298a0.png"},{"id":59596432,"identity":"59a63cf2-9d46-4e4d-9377-96dd576a6d57","added_by":"auto","created_at":"2024-07-03 15:57:30","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":239293,"visible":true,"origin":"","legend":"\u003cp\u003eHeat map representing and including \u003cem\u003eF\u003c/em\u003e\u003csub\u003e\u003cem\u003eST\u003c/em\u003e\u003c/sub\u003e values generated by Popoolation2 (Kofler et al. 2011). All pairwise p-values were p-value \u0026lt; 0.01 and thus significant (*). Expanded range populations: Monterey (MON), Big Creek (BIC), and Jalama (JAL). Historical range populations: Cojo (COJ), Naples (NAP), Isla Vista (ISV), Yellow Banks (YEL), Anacapa (ANN), Point Dume (POD), Palos Verdes (PAV), Dana Point (DAP), Point Loma (POL) and Isla de Todos Santos (ITS).\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4670567/v1/370a12af24716bba22bee059.png"},{"id":59595827,"identity":"0ed1bc57-e983-467e-b99e-cdaf838a59f2","added_by":"auto","created_at":"2024-07-03 15:49:30","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":174951,"visible":true,"origin":"","legend":"\u003cp\u003ePrincipal component analysis (PCA) showing the first two axes (explaining 24% of variation) of the genetic differentiation among the Kellet’s whelk populations in the expanded and historical distribution range. Expanded range populations: Monterey (MON), Big Creek (BIC), and Jalama (JAL). Historical range populations: Cojo (COJ), Naples (NAP), Isla Vista (ISV), Yellow Banks (YEL), Anacapa (ANN), Point Dume (POD), Palos Verdes (PAV), Dana Point (DAP), Point Loma (POL) and Isla de Todos Santos (ITS).\u003c/p\u003e","description":"","filename":"Figure3PCA30x.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4670567/v1/46a0349911c420091c1b6ca2.jpg"},{"id":59597548,"identity":"4388b2e5-daad-41dd-a259-62921848720e","added_by":"auto","created_at":"2024-07-03 16:13:30","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":973099,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4670567/v1/d09c11f1-788f-44f9-be5f-58544117690b.pdf"},{"id":59597019,"identity":"529a2bd3-bb49-4d0a-92b2-21226815d4a9","added_by":"auto","created_at":"2024-07-03 16:05:30","extension":"jpg","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":427307,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eS1. \u003c/strong\u003eRelationship between the average amount of missing data per population pair and their corresponding \u003cem\u003eF\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e value (R² = 0.01, p-value = 0.38)\u003c/p\u003e","description":"","filename":"FigureS1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4670567/v1/9798cda7c1b5ededf1424ba7.jpg"},{"id":59595823,"identity":"0cbba3cc-5a2b-4352-ba06-9f6a00362b71","added_by":"auto","created_at":"2024-07-03 15:49:30","extension":"jpg","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":189213,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eS2. \u003c/strong\u003ePrincipal component analysis (PCA) showing the first two axes (explaining 23.3% of variation) of the genetic differentiation among the Kellet’s whelk populations in the expanded and historical distribution range when allowing 50% of missing data.\u003c/p\u003e","description":"","filename":"FigureS2PCA50x.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4670567/v1/0d3784ead19e0355f53e663e.jpg"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eClimate-driven range expansion via long-distance larval dispersal\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eHuman-induced ocean warming is causing alterations in species distributions, abundances, and phenology according to their thermal tolerance and ability to adapt (Harley et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2006\u003c/span\u003e, Poloczanska et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2013\u003c/span\u003e, Bernardi et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). More suitable conditions created by ocean warming have enabled many species with tropical affinities to successfully disperse poleward and establish populations beyond their historical range limit (Verg\u0026eacute;s et al. \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2014\u003c/span\u003e, Spies et al. \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Coupled with ocean warming, changes in major ocean currents and increased frequency of extreme oceanographic events, such as marine heatwaves and El Ni\u0026ntilde;o Southern Oscillation (ENSO) events (Yeh et al. \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e2009\u003c/span\u003e, Cai et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), are increasing the frequency and magnitude of range expansions. This phenomenon is causing a reorganization of marine biota (Bindoff et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2007\u003c/span\u003e, Lonhart et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2019\u003c/span\u003e, Sanford et al. \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), altering the structure and dynamics of community interactions among resident species (Gilman et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2010\u003c/span\u003e, Gehrels et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2016\u003c/span\u003e, Marzloff et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2016\u003c/span\u003e, Wainright et al. \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBy the end of the 20th century, the northeast Pacific Ocean had risen 0.8\u0026deg;C above pre-1950 historical levels (Roemmich \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e1992\u003c/span\u003e). In the past two decades, this region has experienced the combined effects of increasing temperatures and frequencies of anomalous oceanographic events, with 2022 being the warmest year on record (Chao et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2017\u003c/span\u003e, Harvey et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Consequently, many species across different taxa are undergoing shifts in their population distribution and abundance, with a general trend of poleward displacement (Cavole et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2016\u003c/span\u003e, Molinos et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2018\u003c/span\u003e, Osland et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Some of these population expansions are associated with episodic anomalously warm oceanographic events (Sorte \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2001\u003c/span\u003e, Lluch-Belda et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2005\u003c/span\u003e, Yamada et al. \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). One example is the subtropical red crab \u003cem\u003ePleuroncodes planipes\u003c/em\u003e, where adults are sporadically found in central locations of California due to anomalous advection but without evidence of reproduction (Cimino et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In contrast, several species have been able to establish stable populations that are reproducing beyond their historical distribution range (Goddard et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2016\u003c/span\u003e, Spies et al. \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), which could then act as a source of larvae for future expansions. Such alterations in population dynamics are leading to widespread concern about the future of ecosystem structure and function, and the indirect impacts on regional economies when these variations involve commercially fished species (Gilman et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2010\u003c/span\u003e, Pinsky et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2018\u003c/span\u003e, Young et al. \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e2019\u003c/span\u003e, Spies et al. \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eKellet\u0026rsquo;s whelk (Buccinoidea: \u003cem\u003eKelletia kelletii\u003c/em\u003e) is a subtidal gastropod whose populations have undergone a considerable poleward expansion along the west coast of North America (Herrlinger TJ \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e1981\u003c/span\u003e, Zacherl et al. \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). The historical northern range limit of Kellet's whelk was Point Conception, a widely recognized oceanographic and biogeographic border between warm-temperate and cool-temperate species (Ricketts et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e1985\u003c/span\u003e, Hohenlohe \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2004\u003c/span\u003e, Broitman et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2008\u003c/span\u003e, Pelc et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). However, in 1980, five adult Kellet\u0026rsquo;s whelk (\u0026ge;\u0026thinsp;60 mm) were found in central California (3 in Monterey Bay and 2 in Big Creek), far north of their historical range, presumably due to ocean warming (Herrlinger TJ \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e1981\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eKellet\u0026rsquo;s whelk is an ideal candidate for exploring the mechanism of poleward range expansion because it has high dispersal potential, with pelagic larval durations of up to 60 days (Romero et al. \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Furthermore, the extremely low population genetic structure throughout the species\u0026rsquo; range at neutral loci (White et al. \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2010\u003c/span\u003e, Selkoe et al. \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) also makes it a challenge for traditional population genetic inference, like many marine species. The first detections of range expansions were ~\u0026thinsp;300 km beyond the species\u0026rsquo; historical northern range limit (Herrlinger TJ \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e1981\u003c/span\u003e), and subsequent population surveys found irregular size-frequency distributions that suggest only occasionally successful recruitment (Zacherl et al. \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2003\u003c/span\u003e, Palmer \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). These observations beg the question of whether the range expansion was the result of periodic long-distance dispersal events rather than a consistent march northward by an expanding population. Additionally, are these marginal populations maintained by long-distance larval recruitment, perhaps during unusual or periodic (ENSO) oceanographic events, or are they maintained by local recruitment of larvae spawned from within the species\u0026rsquo; expanded range (Zacherl et al. \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2003\u003c/span\u003e, Lluch-Belda et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2005\u003c/span\u003e, Cimino et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)?\u003c/p\u003e \u003cp\u003eExamining the range expansion in Kellet\u0026rsquo;s whelk not only presents an intriguing scientific question on the origin of novel populations but also carries broader ecological and economic implications. Kellet\u0026rsquo;s whelk is a subtidal predator and scavenger with top-down food web effects in kelp forests that also supports the second-largest commercial molluscan fishery in California (Rosenthal R. J. 1971, Schmitt \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e1987\u003c/span\u003e, Aseltine-Neilson et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2006\u003c/span\u003e, Halpern et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2006\u003c/span\u003e, CDFW \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Kellet\u0026rsquo;s whelk is also prey to numerous species (Limbaugh \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e1955\u003c/span\u003e, Rosenthal R.J. 1971, 1974), such as sea otters (Lonhart \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2001\u003c/span\u003e), which are more abundant in central California than in its historical range to the south. Recently, fisheries harvest rates of Kellet\u0026rsquo;s whelk have started to rise in the species\u0026rsquo; expanded range in central California (CDFW \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). These studies suggest that the species plays a functional role in kelp forest ecosystems and that its range expansion affects ecological and socioeconomic community dynamics in central California. For all these reasons, understanding how the newly expanded and historical populations are structured is essential for establishing effective and sustainable management strategies for Kellet\u0026rsquo;s whelk and associated communities in the face of climate change. Furthermore, because Kellet\u0026rsquo;s whelk shares habitat and several key life history traits with many other coastal marine species in California (Allen et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2006\u003c/span\u003e, Froese \u0026amp; Pauly 2011), the results of this study may help predict future expansion by other ecologically and economically important species in the region.\u003c/p\u003e \u003cp\u003eHere, we studied the genetic structure of populations of Kellet\u0026rsquo;s whelk by analyzing reduced-representation genomic sequencing libraries (ezRAD; Toonen et al. \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) using an equimolar pooled approach (Pool-seq; Schl\u0026ouml;tterer et al. \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Using this approach, we analyzed thousands of variable nucleotides (SNP loci) from 598 individuals sampled across 13 sites throughout the species\u0026rsquo; historical and expanded range, spanning\u0026thinsp;~\u0026thinsp;800 km, to quantify population genetic structure and relationships among geographic sites to test hypotheses regarding the poleward dispersal of \u003cem\u003eK. kelletii\u003c/em\u003e into the newly expanded range.\u003c/p\u003e"},{"header":"Material and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSample collection, DNA extraction, and pooling\u003c/h2\u003e \u003cp\u003eFoot tissue from 46 \u003cem\u003eK. kelletii\u003c/em\u003e adults (\u0026gt;\u0026thinsp;60 mm shell length; Rosenthal \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e1970\u003c/span\u003e\u0026ndash;23 individuals in 2015 and 23 individuals in 2016 \u0026ndash; were sampled non-lethally from each of 13 subtidal locations (~\u0026thinsp;15 m depth) across the species\u0026rsquo; historical and expanded range (Fig.\u0026nbsp;1). Collected tissue samples were then frozen on dry ice or liquid nitrogen for transport to the California Polytechnic State University (San Luis Obispo, CA) and stored at -80 ℃ until processed for DNA extraction.\u003c/p\u003e \u003cp\u003eDNA extraction was performed using an optimized version of the \u0026lsquo;salting-out\u0026rsquo; protocol developed by Li et al. (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) and modified by Daniels et al. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2023a\u003c/span\u003e), where the full extraction protocol is detailed. Briefly, 30 mg of tissue was lysed with proteinase K and RNase A in a warm water bath. Subsequently, DNA was separated from proteins, which precipitated in the presence of ammonium acetate by centrifugation, and was then purified from the supernatant via ethanol washes. Finally, precipitated DNA was resuspended in Tris-EDTA (1xTE) buffer and stored at -20 \u0026ordm;C until further analyses.\u003c/p\u003e \u003cp\u003eDNA quality was assessed visually using a 1% agarose gel in Tris-Acetic Acid-EDTA (TAE) buffer, GelRed (Biotum, Inc) gel stain, and referenced to the 200\u0026ndash;10,000 bp Hyperladder I (Bioline, Meridian Bioscience). Because 91.3% of all extractions produced high molecular weight bands (\u0026gt;\u0026thinsp;10 kb) with faint smears from degraded DNA, all specimens were included in the study. Extractions were quantified using the AccuClear Ultra High Sensitivity dsDNA quantification kit (Biotium, Inc) with 3 standards and measured using a SpectraMax M2 microplate reader (Molecular Devices, LLC). Finally, an equimolar amount of DNA from each of the 46 individuals collected at each location was pooled by the collection site (population), ensuring that each library had the same number of individuals. In total, 598 individuals belonging to 13 populations spanning\u0026thinsp;~\u0026thinsp;800 km were included in the analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eLibrary preparation and sequencing\u003c/h2\u003e \u003cp\u003eEquimolar pooled ezRAD (Toonen et al. \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) libraries were generated following the detailed protocol of Knapp et al. (2016) for all 13 populations. Briefly, genomic DNA was digested using the isoschizomer restriction enzymes \u003cem\u003eMbo\u003c/em\u003eI and \u003cem\u003eSau\u003c/em\u003e3AI (New England Biolabs, Ipswich, MA). Digestions were performed in a total volume of 50 \u0026micro;l, containing 25 \u0026micro;l of dsDNA (~\u0026thinsp;1 \u0026micro;g), 5 \u0026micro;l of NEB Cutsmart Buffer (provided with restriction enzymes), 18 \u0026micro;l of HPLC grade water, 1 \u0026micro;l \u003cem\u003eMbo\u003c/em\u003eI (10 units), and 1 \u0026micro;l \u003cem\u003eSau3\u003c/em\u003eAI (10 units) under the following thermocycler profile: 37 \u0026ordm;C for 18 h, then deactivation at 65 \u0026ordm;C for 20 min. After digestion, samples were cleaned using Mag-Bind TotalPure NGS (Omega Bio-Tek) beads at a 1:1.18 (DNA:beads) ratio to remove fragments\u0026thinsp;\u0026lt;\u0026thinsp;200 bp (Norcross, GA). Libraries were prepared for sequencing using the KAPA Hyper Prep DNA kit (Roche Sequencing and Life Science) following a modified version of the manufacturer protocol (see Knapp et al. 2016). Quality control by a Bioanalyzer and sequencing of the libraries on one lane of an Illumina HiSeq2500 were performed in the DNA Technologies and Expression Analysis Core Laboratory at the University of California (Davis, CA).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eData filtering and SNPs calling\u003c/h2\u003e \u003cp\u003eLibraries were initially trimmed to remove low-quality bases and adapters using dDocent v.2.9.4 (Puritz et al. 2014), obtaining an average of 16,640,463 reads per sample. The population of Monterey had the lowest number of reads, with 4,439,406, while Yellow Banks had the highest number, with 45,795,618 reads. The same pipeline was used to align the reads using BWA (mem algorithm) to the \u003cem\u003eK. kelletii\u003c/em\u003e reference genome, which contains 2,107,417,620 base pairs (2.1 Gb) in 46,654 contigs and a complete BUSCO score of 84.1% (Daniels et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2023b\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSNPs were identified using FreeBayes (Garrison \u0026amp; Marth \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) implemented in dDocent, by calling variants from merged bam files produced by the pipeline. The TotalRawSNPs.vcf file contained 18,327,457 shared SNPs, which was further filtered through VCFtools v 0.1.16 (Danecek et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) using the following parameters: max-missing 0.75, maf 0.05, minQ30, and min-meanDP20. Downstream analyses only included loci with 30x coverage as recommended and widely used for reliable SNPs calling with RADseq data (Bentley et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2008\u003c/span\u003e, Rivera-Col\u0026oacute;n \u0026amp; Catchen \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) while also avoiding an overrepresentation of loci with higher quality scores (Li \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003ePopulation genetic analyses\u003c/h2\u003e \u003cp\u003eThe final vcf filtered file produced was imported to TASSEL v. 5 (Bradbury et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) to explore population similarities via Principal Component Analysis (PCA) and to AssessPool (\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003egithub.com/ToBoDev/assessPool\u003c/span\u003e), a bioinformatic program designed to analyze and visualize pool-seq data (Freel \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). To calculate population genetic differentiation between sites based on pairwise estimates of \u003cem\u003eF\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e, AssesPool uses PoPoolation2, which also calculates pairwise significance (\u003cem\u003ep-\u003c/em\u003evalues) using Fisher\u0026rsquo;s Exact Test (Kofler et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). We also compared the matrix of our pairwise estimates of genetic differentiation to those obtained by White et al. (\u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), where the authors analyzed between 50 and 92 individuals per population from the Southern California Bight using 9 microsatellite DNA loci. For the populations shared between both studies (ANN, COJ, ISV, JAL and YEL, Fig.\u0026nbsp;1), we compared \u003cem\u003eF\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e values using a Mantel test in the vegan R package with 9999 permutations to test for significantly correlated results (v. 2.5\u0026ndash;7; Oksanen et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eOur ezRAD libraries covered an average of 19% of the Kellet\u0026rsquo;s whelk reference genome, with Yellow Banks (40.13%) and Monterey (8.9%) being the populations with the highest and lowest genomic coverage, respectively. After filtering with VCFtools, a total of 46,737 shared SNPs were retained, of which 46,310 were biallelic and 427 multiallelic SNPs. Due to the low number of multiallelic SNPs (0.9%) and the insensitivity of these findings to their inclusion or exclusion, they were retained for all analyses.\u003c/p\u003e \u003cp\u003eGenetic structure (\u003cem\u003eF\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e) between pairwise populations was low in general, ranging from 0.013 between Anacapa and Isla Vista to 0.028 between Naples and Point Loma (Fig.\u0026nbsp;2). The 8 populations from the Southern California Bight (SCB) had consistently lower values of \u003cem\u003eF\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e for all comparisons, ranging from 0.013 to 0.017 (Fig.\u0026nbsp;2), while populations within the expanded range showed higher levels of differentiation (i.e. \u003cem\u003eF\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e MON vs. BIC\u0026thinsp;=\u0026thinsp;0.020, BIC vs. JAL\u0026thinsp;=\u0026thinsp;0.014, and MON vs. JAL\u0026thinsp;=\u0026thinsp;0.017). Despite the moderately low values, all pairwise comparisons of \u003cem\u003eF\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e were significant (p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.01), showing low but significant population genetic structure in Kellet\u0026rsquo;s whelk. Comparing the population genetic structure recovered here to the same 5 populations from the SCB previously reported by White et al. (\u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), we found a positive and significant correlation (r\u0026thinsp;=\u0026thinsp;0.55, p\u0026thinsp;=\u0026thinsp;0.05) between the pool-seq SNP and individual-based microsatellite results, consistent with isolation by oceanographic distance.\u003c/p\u003e \u003cp\u003eThe results showed significant population structure throughout the range of Kellet\u0026rsquo;s whelk, with slightly greater differentiation within the expanded range than in the historical range and least differentiation within the Southern California Bight (SCB). We found moderately high genetic diversity, but comparing the 46,737 SNPs via PCA in TASSEL, we found moderately low genetic differentiation among Kellet\u0026rsquo;s whelk populations, where our PCA explained a total of 27% of the variance (Fig.\u0026nbsp;3). Populations located in the SCB were genetically most similar and distinct from the rest of the range-wide samples (Fig.\u0026nbsp;3), including the population from Jalama (JAL), which is geographically closest (~\u0026thinsp;15km) to the SCB, but on the other side of Pt. Conception (Fig.\u0026nbsp;1). Notably, the two populations that are geographically highly proximate but on either side of Pt. Conception, Jalama (JAL), and Cojo (COJ), are highly differentiated, whereas the two most genetically similar populations among all 13 analyzed are Big Creek (BIC), in the expanded range, and Point Loma (POL), located at ~\u0026thinsp;550 km apart into the historical range.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eComplicated geography and oceanographic features of the SCB lead to complex current patterns, with internal eddies limiting exchange or promoting high dispersal between distant sites (Mitarai et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2009\u003c/span\u003e, Hyde \u0026amp; Vetter \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2009\u003c/span\u003e, Alberto et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). In fact, there is no correlation between pairwise genetic differentiation or frequency of larval exchange of the Kellet\u0026rsquo;s whelk populations and the Euclidean distances among sites in the SCB (White et al. \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Instead, nearly 50% of the observed variation in population genetic structure was explained by the frequency of larval exchange predicted by ocean currents (White et al. \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Likewise, kelp bed size (likely a habitat proxy for Kellet\u0026rsquo;s whelk population size) was a significant predictor of genetic diversity and population differentiation of Kellet\u0026rsquo;s whelk (Selkoe et al. \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Dispersal into and out of the SCB is limited relative to along the open coastline, with an offshore California current towards the south and inshore countercurrent to the north (Fig.\u0026nbsp;1), with considerable seasonal and inter-annual (ENSO) variability (Hobday \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2000\u003c/span\u003e, Mitarai et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2009\u003c/span\u003e, Watson et al. \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). In addition, coastal pollution was found to be a significant barrier to larval dispersal both within and across the SCB for the bat star \u003cem\u003ePatiria miniata\u003c/em\u003e (Puritz \u0026amp; Toonen \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). These studies highlight factors other than geographic distance driving population genetic structure in Kellet\u0026rsquo;s whelk.\u003c/p\u003e \u003cp\u003eAnalysis of Kellet\u0026rsquo;s whelk\u0026rsquo;s population genetic structure across both the species\u0026rsquo; historical and expanded range using genomic loci allows us to test hypotheses about the observed range expansion. For example, among the expanded range samples, Jalama (JAL) is located closest to the historical northern range boundary, only\u0026thinsp;~\u0026thinsp;15 km north of Cojo (COJ) in the SCB. Despite their geographical proximity, these two sites straddle the well-known physiological and biogeographic barrier of Point Conception (Broitman et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2008\u003c/span\u003e, Hyde \u0026amp; Vetter \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2009\u003c/span\u003e, Selkoe et al. \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2010\u003c/span\u003e, Alberto et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), and are among the most genetically divergent of our comparisons (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e\u003cspan type=\"ItalicSmallCaps\" class=\"ItalicSmallCaps\" name=\"Emphasis\"\u003est\u003c/span\u003e\u003c/sub\u003e = 0.021). Limited gene flow between these sites is also consistent with observed dramatic differences in abundance and size frequency distributions of individuals in the recently expanded population (JAL), compared to individuals from the historical range across Point Conception (COJ) (Zacherl et al. \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). This study and our data collectively indicate that Kellet\u0026rsquo;s whelk\u0026rsquo;s range expansion was not a march northward from the leading edge of the historical range (COJ) into the expanded range (JAL).\u003c/p\u003e \u003cp\u003eDecreased genetic diversity and increased pairwise differentiation of expanded range populations due to multiple successive founder events are consistent with climate-driven range expansion (Robalo et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). We see mixed support for this prediction in terms of increased differentiation among each of the three sites in the expanded range relative to the historical range, and no evidence of reduced genetic diversity among samples of 46 adults from each of these populations. Instead, we find relatively low population differentiation (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e\u003cem\u003eST\u003c/em\u003e\u003c/sub\u003e = 0.013) between Big Creek (BIC, one of the northernmost expanded range sites) and Point Loma (POL, one of the southernmost historical range sites), consistent with migration between these locations (presumably, from POL to BIC). Furthermore, these two geographically isolated populations are genetically most similar in terms of shared SNPs in the PCA analysis and are highly divergent from other sampled sites (Fig.\u0026nbsp;3). With thousands of polymorphic SNPs shared by 46 adults per population, it is unlikely that a founder event from the introduction of just a few individuals from Point Loma (POL) to Big Creek (BIC), for example, by human-mediated transport, could explain the genetic similarity. Given that these locations are ~\u0026thinsp;660 km apart and separated by many other sampled populations, this similarity is most consistent with range expansion through larval transport, possibly associated with an ENSO event (Zacherl et al. \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). During these ENSO events, reduced thermal barrier to larval dispersal, combined with alterations in the main ocean currents, facilitate dispersal further north beyond Point Conception (Sorte \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2001\u003c/span\u003e, Lluch-Belda et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2005\u003c/span\u003e, Yamada et al. \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The ENSO dispersal hypothesis is also supported by results of a length-age model for Kellet\u0026rsquo;s whelk (Palmer et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2018\u003c/span\u003e, White et al. \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), which suggests that the individuals first found in Monterey (Herrlinger TJ \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e1981\u003c/span\u003e) were spawned between 1969 and 1974, coincident with the 1972-73 ENSO event, which was one of the major ENSO events during the 20th century (NOAA \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe finding that the populations of Monterey (MON) and Isla de Todos Santos (ITS) are roughly equally divergent from the rest of the populations suggests a possible link between these populations. MON and ITS also show a clear divergence from one another, yet it is noteworthy that these two populations also showed the highest amount of missing data (Figure S1), which may confound RAD-seq results (Arnold et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2013\u003c/span\u003e, Huang \u0026amp; Knowles \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2016\u003c/span\u003e, Shafer et al. \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2017\u003c/span\u003e, Hemstrom et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). To test whether our results were sensitive to such effects, we looked for a correlation between the amount of missing data per comparison and the corresponding pairwise \u003cem\u003eF\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e value and did not find any (Figure S1). Furthermore, performing the analyses with varying cutoffs for missing data ranging from 0 to 50% does change the relative position of these populations in the PCA but does not alter our inferences about the overall population structure (Figure S2). The only two populations greatly affected by the amount of missing data were Monterey (MON) and Isla de Todos Santos (ITS), which generally remain genetically distinct from all other sampled populations, but the relative amount of divergence between these two varies (Figure S1). Thus, our geographically proximate samples from within the expanded range show moderate population differentiation and are each genetically more similar to some sites within the historical range than they are to one another. These results are more consistent with multiple long-distance colonization of these newly range-expanded populations than a slow poleward march of an expanding population.\u003c/p\u003e \u003cp\u003eAlternatively, selection could drive population differentiation irrespective of dispersal, similar to patterns identified for the intertidal crab \u003cem\u003ePetrolisthes cinctipes\u003c/em\u003e along the northern California coastline (Toonen \u0026amp; Grosberg \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Previous work showed that Kellet\u0026rsquo;s whelk may be capable of adapting to the colder environment by altering their metabolic rates (Vasquez et al. \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2019\u003c/span\u003e, Lee et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) and increasing the concentration of proteins involved in energy metabolism and oxidative stress (Vasquez et al. \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2019\u003c/span\u003e, Daniels et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2023b\u003c/span\u003e, Lee et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Adaptation to cold temperatures may help explain the persistence of individuals in the extended range, but the mechanism by which whelks colonized these northern range expanded sites remains unknown. Our finding that MON and ITS populations are genetically closer to one another than any others but still show clear population differentiation may be a result of long-distance dispersal followed by selection to survive in colder environments. In support of this hypothesis, Lee et al. (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) found Kellet\u0026rsquo;s whelk in the expanded range to be upregulating triosephosphate isomerase (TPI), an essential enzyme for cold stress response. Nevertheless, whether these divergence patterns are driven by a response to selection, genetic drift, or a combination of both mechanisms requires additional studies.\u003c/p\u003e"},{"header":"Conclusions \u0026 Implications","content":"\u003cp\u003eMost marine animal species have a biphasic life cycle in which dispersal occurs primarily through the pelagic larval phase (Thorson \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e1950\u003c/span\u003e, Kinlan \u0026amp; Gaines \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2003\u003c/span\u003e, Weersing \u0026amp; Toonen \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2009\u003c/span\u003e, Burgess et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Larval dispersal kernels are generally leptokurtic, in which most successful recruits remain relatively close (10s to ~\u0026thinsp;100 km) to the spawning site but with a long tail of some individuals that can be transported much longer distances (Kot et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e1996\u003c/span\u003e, Strathmann et al. \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2002\u003c/span\u003e, Siegel et al. \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2008\u003c/span\u003e, D\u0026rsquo;Aloia et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Poleward range expansions have been studied for decades in terrestrial organisms, which generally follow a stepping-stone pattern, in which most dispersal occurs relatively near the parents to form reproductive populations that seed further expansions (Ibrahim et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e1996\u003c/span\u003e, Morales \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2002\u003c/span\u003e, Thomas \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2010\u003c/span\u003e, Saura et al. \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2014\u003c/span\u003e, Robalo et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This process would result in a continuous slow-and-steady population range expansion through multiple successive founder events, because long-distance dispersers are unlikely to find mates, even if they survive and grow to reproductive maturity. The predictable consequences of such a process include reduced genetic diversity and high differentiation of populations in the expanded portions of the range relative to in the historical range (Robalo et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eContrary to such predictions, the first observations of Kellet\u0026rsquo;s whelk in the species\u0026rsquo; expanded range was ~\u0026thinsp;300 km beyond its historical northern range limit (Herrlinger TJ \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e1981\u003c/span\u003e). Further, observations of irregular size-frequency distributions in the expanded range suggest that recruitment has been episodic (Zacherl et al. \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2003\u003c/span\u003e, Palmer et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). In support of these early observations, our results here show both high genetic diversity and minimal population genetic structure (\u003cem\u003eF\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e \u0026asymp; 0.01 to 0.03) of Kellet\u0026rsquo;s whelk along its entire geographical distribution range. The greatest genetic divergences are seen among the newly expanded populations and some portions of the historical range, but those differences are roughly equivalent to the full range of population differentiation observed among sites within the historical range (Fig.\u0026nbsp;2). Further, each of these divergent expanded-range samples are more similar to a site within the historical range than to any geographically proximate location. In particular, the genetic similarity of Point Loma (POL) deep in the historical range to Big Creek (BIC) in the recently expanded range provides compelling evidence of long-distance larval dispersal. Overall, the observed patterns are more consistent with long-distance dispersal from central range origins, likely associated with an ENSO event, than with progressive northward population expansion due to ocean warming.\u003c/p\u003e \u003cp\u003eOur findings have implications not only for Kellet\u0026rsquo;s whelk but likely for many other ecologically and economically co-distributed species in California that share similar dispersal characteristics and life history traits, such as the spiny lobster (\u003cem\u003ePalinurus interruptus\u003c/em\u003e) and California sheephead (\u003cem\u003eSemicossuphus pulcher\u003c/em\u003e) (Allen et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2006\u003c/span\u003e, Selkoe et al. \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2010\u003c/span\u003e, Froese \u0026amp; Pauly 2011). The frequency and amplitude of ENSO events are predicted to increase under climate change (Power et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2013\u003c/span\u003e, Cai et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), which will likely result in more frequent northward expansions and changes in biogeographic species ranges similar to Kellet\u0026rsquo;s whelk. Studies such as this one, focused on understanding and identifying the factors altering marine population dynamics, are essential to establishing effective management and conservation measurements that ensure the health of marine ecosystems and the services they provide to human populations.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCataixa L\u0026oacute;pez thanks the University of La Laguna and the Spanish Ministry of Universities for the Margarita Salas postdoctoral fellowship, granted by Order UNI/551/2021 and funded by Next Generation European Union Funds. We thank members of the ToBo Lab, especially Mykle Hoban and Evan Freel, for sharing their expertise and advice during data analyses. We thank Paul Anderson at the Bioinformatic Research Group at California Polytechnic State University for helping with the Kellet\u0026rsquo;s whelk genome assembly. We thank members of the Center for Applied Biotechnology Lab at California Polytechnic State University, including Jenna Nurge, Olivia Sleeper, Jaden Hansen, Anabel Sanchez, Gabriella Richardson, Hanna Jaynes, Tyler Weipert, Alyssa Queen, Kathryn Hutchinson, Olivia Watt, Jordan Reichhardt, Chanel De Smet, and Alli Clark for extracting Kellet\u0026rsquo;s whelk DNA. This study was supported by the National Science Foundation under grant #OCE-1924604 to C. White, M. Christie \u0026amp; R. Toonen.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAlberto F, Raimondi PT, Reed DC, Watson JR, Siegel DA, Mitarai S, Coelho N, Serr\u0026atilde;o EA (2011) Isolation by oceanographic distance explains genetic structure for \u003cem\u003eMacrocystis pyrifera\u003c/em\u003e in the Santa Barbara Channel. 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ICES J Mar Sci 76:93\u0026ndash;103\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZacherl D, Gaines SD, Lonhart SI (2003) The Limits to Biogeographical Distributions: Insights from the Northward Range Extension of the Marine Snail, Kelletia kelletii (Forbes, 1852). J Biogeogr 30:913\u0026ndash;924\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"University of Hawaii at Manoa","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"El Niño Southern Oscillation (ENSO), RADseq, larval dispersal, colonization event, Kelletia kelletii","lastPublishedDoi":"10.21203/rs.3.rs-4670567/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4670567/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eClimate-driven warming and changes in major ocean currents enable poleward transport and range expansions of many marine species. Here, we report the population genetic structure for the gastropod \u003cem\u003eKelletia kelletii\u003c/em\u003e, a commercial fisheries species and subtidal predator with top-down food web effects, whose populations have recently undergone climate-driven northward range expansion. We genotyped 598 adults from 13 locations across the species\u0026rsquo; historical and expanded range (\u003cb\u003e\u0026sim;\u003c/b\u003e800 km) using reduced representation genomic sequencing (RAD-seq). Analyses of 40,747 SNPs show evidence for long-distance larval dispersal of \u003cem\u003eK. kelletii\u003c/em\u003e larvae from a central historical range site (Point Loma, CA) hundreds of km into the expanded northern range (Big Creek, CA), which seems most likely to result from transport during an El Ni\u0026ntilde;o Southern Oscillation (ENSO) event rather than consistent on-going gene flow. Furthermore, despite smaller geographic distances among some sampled expanded-range populations, their genetic divergence exceeds that among the historical range sampled populations, suggesting multiple origins of the expanded-range populations. Given the frequency and magnitude of ENSO events are predicted to increase with climate change, understanding the factors driving changes in population connectivity is crucial for establishing effective management strategies to ensure the persistence of this and other economically and ecologically important species.\u003c/p\u003e","manuscriptTitle":"Climate-driven range expansion via long-distance larval dispersal","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-03 15:49:25","doi":"10.21203/rs.3.rs-4670567/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"658ad003-5322-4f9d-8d26-4ebcf84ca335","owner":[],"postedDate":"July 3rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":33983689,"name":"Marine and Freshwater Ecology"}],"tags":[],"updatedAt":"2024-07-03T15:49:25+00:00","versionOfRecord":[],"versionCreatedAt":"2024-07-03 15:49:25","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4670567","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4670567","identity":"rs-4670567","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}