Temporal genetic similarity among year-classes of the pacific geoduck clam (Panopea generosa Gould 1850): a species exhibiting spatial genetic patchiness.
Article Type: Report
Subject: Clams (Genetic aspects)
Population genetics (Research)
Authors: Vadopalas, Brent
Leclair, Larry L.
Bentzen, Paul
Pub Date: 08/01/2012
Publication: Name: Journal of Shellfish Research Publisher: National Shellfisheries Association, Inc. Audience: Academic Format: Magazine/Journal Subject: Biological sciences; Zoology and wildlife conservation Copyright: COPYRIGHT 2012 National Shellfisheries Association, Inc. ISSN: 0730-8000
Issue: Date: August, 2012 Source Volume: 31 Source Issue: 3
Topic: Event Code: 310 Science & research
Product: Product Code: 0913030 Clams NAICS Code: 114112 Shellfish Fishing SIC Code: 0913 Shellfish
Geographic: Geographic Scope: United States Geographic Code: 1USA United States
Accession Number: 303011393
Full Text: ABSTRACT A previous study revealed genetic differences among collections of the commercially exploited geoduck clam (Panopea generosa) in Puget Sound, WA, but this heterogeneity did not follow an isolation-by-distance model. In this study, we investigated whether these differences were ephemeral or stable and tested predictions of the sweepstakes recruitment hypothesis, in which individuals show a high variance in reproductive success. We genotyped 11 allozyme and 7 microsatellite loci in 2,021 geoducks from 2 sites in Puget Sound and aged individuals by counting annuli in thin-section chondrophores under light microscopy. Genotypic data were then collated by year-class to test predictions of the sweepstakes recruitment hypothesis with allele count rarefaction, year-class relatedness, and 3 estimators of efective population size ([N.sub.e]) using temporal shifts in allele frequencies. Although estimates of [N.sub.e] were similar among year-classes, spatial shifts in allele frequencies and year-class strengths were detected among stations at 1 site, indicating that patchy settlement may be the result of an interaction between larval behavior during dispersal and hydrology.

KEY WORDS: geoduck, Panopea generosa, effective population size, sweepstakes recruitment, isolation by distance

INTRODUCTION

Many marine species are characterized by large, broadly distributed populations, high fecundities, and planktotrophic larvae with high dispersal potential. These attributes often lead to genetic homogeneity (Bohonak 1999), even on scales as large as hundreds of kilometers. Genetic variability among populations for many species generally follow patterns of isolation by distance (IBD), whereby populations in close geographical proximity are more similar than populations that are farther apart, and differentiation is detectable usually only over long distances (reviewed in Shaklee & Bentzen (1998) and Bradbury et al. (2008)). However, genetic differentiation in some species deviates from the IBD pattern, including limpets (Siphonaria jeanae (Johnson & Black 1984)), queen conch (Strombus gigas (Mitton et al. 1989)), blue crab (Calinectes sapidus (McMillen-Jackson et al. 1994)), giant clams (Tridacna gigas (Benzie & Williams 1995)), oysters (Crassostrea angulata (Michinina & Rebordinos 1997)), sea urchins (Strongylocentrotus franciscanus (Moberg & Burton 2000)), and abalone (Haliotis cracherodii (Hamm & Burton 2000)). In these cases, genetic and geographical distances are not correlated on either large (hundreds of kilometers) or small (tens of meters) spatial scales.

Estimates of spatial genetic differentiation can be confounded by temporal shifts (Jorde & Ryman 1995), because differences among year-classes or cohorts at a site can be as large or larger than differences among spatially distinct stocks (e.g., Laikre et al. 1998, Planes & Lenfant 2002). Temporal shifts in allele frequencies would be expected to produce heterozygote deficiencies in samples that include individuals from multiple year-classes or cohorts (Wahlund effect). Conversely, heterozygote deficiencies (and [F.sub.IS]) are expected to be absent or smaller within year-classes or cohorts than in the population as a whole.

One potential explanation for large intercohort genetic differences is the sweepstakes recruitment hypothesis (Hedgecock 1994), which proposes that temporal variation in allele frequencies of highly fecund marine organisms reflects a large variance in reproductive success among individuals within a spawning event. Under this hypothesis, cohorts in a population are dominated by the progeny of relatively few spawners. Consequently, genetic diversity and effective population size ([N.sub.e]) are reduced greatly relative to population census size. Sweepstakes recruitment can also generate spatial variation in allele frequencies when local aggregates of individuals differ in age structure or are derived from different spawning events. Thus, sweepstakes recruitment is expected to lead to temporal shifts in allele frequencies and to patchy or chaotic spatiotemporal structures, rather than to patterns of IBD. The sweepstakes recruitment hypothesis has been invoked to explain the complex patterns of differentiation in some marine invertebrates, such as those listed earlier, and investigators have suggested that studies of genetic stock structure should also consider temporal variability (Hedgecock 1994, Laikre et al. 1998, Heath et al. 2002); however, few studies have addressed the sweepstakes recruitment hypothesis specifically.

The geoduck clam (Panopea generosa Gould, 1850, formerly Panopea abrupta Conrad, 1849 (Vadopalas et al. 2010)) is the world's largest burrowing clam and is commercially harvested subtidally by scuba divers in the nearshore environment throughout Puget Sound, WA. Its high ex-vessel value, spurred by increasing international demand, makes it one of Washington's most lucrative and intensively managed fisheries. The geoduck clam exhibits several biological characteristics that suggest it might be subject to the effects of sweepstakes recruitment. It is extremely fecund, with a mean annual fecundity under laboratory conditions of more than 10 million eggs (Jonathan P. Davis, pets. comm.), and has a pelagic larval stage that lasts for about 6 wk. High fecundity and long larval duration are consistent with high variance in reproductive success under the sweepstakes recruitment hypothesis (Hedgecock 1994). In addition, geoduck clams are long-lived; the oldest specimen on record lived 168 y (Bureau et al. 2002). High fecundity, extensive longevity, and high larval dispersal capacity produce local populations that include numerous age classes, as evidenced by the age frequency data presented in Goodwin and Shaul (1984).

A molecular marker survey of geoduck clam populations in Puget Sound and southeast Alaska revealed a pattern of genetic variation that showed no evidence of IBD (Vadopalas et al. 2004). Significant allele frequency differences were not detected between most samples, but patchy differentiation was evident among some populations with both microsatellite (7) and allozyme (11) loci. Notably, allozyme and microsatellite allele frequencies for 1 location in Puget Sound (Freshwater Bay) differed significantly from other nearby locations in Puget Sound. In contrast, geoduck clams from southeast Alaska were genetically indistinguishable from Puget Sound populations.

[FIGURE 1 OMITTED]

Temporal variation in allele frequencies, however, can potentially explain the observed patchy genetic differentiation. This explanation embodies 2 predictions: first, different age classes should exhibit different allele frequencies. Second, local aggregates of geoduck clams should differ substantially in age-frequency composition, although the presence of multiple year-classes within samples would obscure allele frequency shifts associated with sweepstakes recruitment. If temporal variation is the product of sweepstakes recruitment, individual year-classes should show less genetic diversity and smaller [N.sub.e] relative to the whole population.

In this study, we tested these predictions with estimates of individual ages and a genetic analysis of geoduck clams from 2 spatially distinct Puget Sound locations (Fig. 1). We used an age analysis technique based on counts of annual growth bands read from thin sections of the shell to test whether the 2 locations differed in age frequency distribution. We estimated allozyme and microsatellite genotype frequencies to test the following predictions of the sweepstakes recruitment hypothesis: (1) allele frequencies vary significantly among year-classes, (2) heterozygote deficiencies within year-classes are small relative to deficiencies in samples of mixed year-classes, (3) genetic diversity is lower within year-classes than among year-classes, (4) [N.sub.e] is smaller within year-classes than in the total population, and (5) relatedness among individuals within year-classes is greater than relatedness among year-classes.

METHODS

Sampling

Projections based on geoduck clam age-frequency data (Goodwin & Shaul 1984) indicated that a sample size of 1,000 would produce approximately 30-50 individuals from each of the most highly abundant year-classes. A total of 2,021 geoduck clams were collected from the subtidal zone of 2 environmentally distinct and geographically separated sites in Puget Sound (Fig. 1). The sites had not been commercially harvested previously. Scuba divers used pressurized water jets to loosen the mixed sand and mud surrounding the geoduck clams before removing them from the substrate. Site 1 (Washington state management tract designation: Olympic View) in Puget Sound's Hood Canal is characterized by low outflow and high salinity stratification. Geoduck clams at this site were sampled from 2 stations separated by 530 m along approximately the same isobath. Site 2 (Washington state management tract designation: Dougall Point) in south Puget Sound is characterized by a moderate outflow and low salinity stratification. Here, geoduck clams were sampled from 5 stations along 2 depth strata. The stations were located an average of 130 m apart. Sample dates, sizes, coordinates, and depths for each site are given in Table 1.

Age Estimation

We counted growth bands, verified as annuli (Vadopalas et al. 2011), in the internal chondrophore (hinge plate) of the shell (Shaul & Goodwin 1982). This location was chosen because abrasion on exterior portions of the valves can obscure growth bands. A 3 x 2-cm dorsal region of the right valve, including the umbo and chondrophore, was removed from each clam using a 10-cm pneumatic cut-off wheel (DeVilbiss, Martin, MI). A minimum of three 2-mm thin sections were made along the dorsal ventral axis of the hinge plate using a slow-speed saw (Buehler, Lake Bluff, IL) mounted with a high-density diamond blade. Translucent thin sections were mounted on a slide and polished sequentially with 500 grit and 800 grit paper (Struers, Cleveland, OH). When increased resolution of the growth bands was needed, the sections were etched for 2 min with 1% HCl. Annulus counts over multiple sections were viewed independently by 3 age readers using a light microscope, and a final consensus was used to estimate the birth year of each specimen. Geoducks known to be 3 y and 4 y old were used in blind tests to verify age estimates of younger clams; verification that the growth bands represent annuli has been demonstrated indirectly in older clams (Shaul & Goodwin 1982).

Microsatellite and Allozyme Data Collection

Tissues were sampled from each individual for allozyme and microsatellite analyses as described in Vadopalas et al. (2004). DNA was extracted using DNeasy columns (Qiagen). Seven microsatellite loci (Pab3, Pab4, Pab5, Pab6, Pab7, Pab8, and Pab9) developed for P. generosa (Vadopalas & Bentzen 2000, Vadopalas et al. 2004) were amplified via single-locus PCRs in a PTC200 thermocycler (Bio-rad). Reactions were carried out in 384-well microtiter plates in 10 [micro]L volumes containing 10 mM Tris-HCl (pH 8.3), 50 mM KC1, 1.5 mM [MgCl.sub.2], 0.01 [micro]M BSA, 0.1% Triton-X100, 0.2 mM of each dNTP, 0.5 [micro]M of each primer, 0.5 U Taq DNA polymerase, and 25-100 ng genomic DNA. Cycling conditions were as follows: 95[degrees]C at 3 min; 5 cycles at 95[degrees]C for 30 sec, at 52[degrees]C for 30 sec, and at 72[degrees]C for 30 sec; 25 cycles at 90[degrees]C for 15 sec, at 52[degrees]C for 15 sect, at 72[degrees]C for 30 sec; and at 72[degrees]C for 40 min. Alleles were electrophoresed and scored on a MegaBACEI000 (GE Healthcare) capillary automated genotyper. Allozyme data from 11 loci were collected only from site 1 using the methods described in Vadopalas et al. (2004).

Statistical Analyses

Genepop v.3.3 (Raymond & Rousset 1995) was used to test for conformation to Hardy-Weinberg expectations (HWE) at each locus for each grouping with the Markov chain exact test method (Guo & Thompson 1992) for loci with 5 or more alleles. The Louis and Dempster (1987) enumeration method was used for the allozyme loci PEPA*, GAPDH*, and MDH*. The Bonferroni adjustment (Rice 1989) at initial alpha = 0.05 was used to control type I error in multiple tests. Genotypic linkage disequilibrium between loci was estimated using the algorithm described by Cockerham and Weir (1979). The genotypic log-likelihood (g)-based exact test (Goudet et al. 1996) was used to test for allele frequency differentiation used for all loci. To increase power, the allelic (genic) test as implemented in Genepop v.3.3 (Raymond & Rousset 1995) was used for the allozyme loci, because assumptions of HWE were not violated (see results). Unbiased estimators of single- and multilocus F statistics (Weir & Cockerham 1984) were computed using FSTAT (Goudet 1995), and [F.sub.ST] values were jackknifed over loci and bootstrapped to obtain the 95% confidence limits.

Global allele frequencies pooled over collections reported by Vadopalas et al. (2004) and the program Relatedness (Queller & Goodnight 1989) were used to estimate genetic relatedness (R) between pairs of individuals within each year-class for both sites, and within stations at site 2. Relatedness coefficients were jackknifed over year-classes, sites, and loci.

Effective population size ([N.sub.e]) was estimated from temporal allele frequencies in 3 ways: (1) the moment-based (MB) method (Waples 1989); (2) the Monte Carlo based [N.sub.e] estimator, MCLEEPS (MC) (Anderson et al. 2000); and (3) the likelihood approach, TM3 (LB) based on coalescence (Berthier et al. 2002). The MB estimator was used when sample sizes in consecutive year-classes were sufficiently large. A correction factor (C) was applied to account for overlapping generations (Jorde & Ryman 1995). Generation length (average age of parents) was estimated using geoduck clam life tables (Juan Valero, unpubl. data; Bradbury & Tagart 2000). The MC and LB methods depend on samples spaced in generational time intervals; therefore, year-classes used for these methods were about 1 generation apart. The assumption of discrete generations was knowingly violated and tended to underestimate the true [N.sub.e]. Estimates of [N.sub.e] produced using these methods yielded an average [N.sub.e] over the time period tested. To estimate [N.sub.e] per year-class using the MB method, we also explored the use of sample pairs consisting of a relatively young cohort and a pool of year-classes of reproductive age at that time.

Tests for reductions in allelic diversity within year-classes relative to the whole population (Launey & Hedgecock 2001) were conducted empirically using the rarefaction equations of Simberloff (1979) as implemented by John Brzustowski (http:// www2.biology.ualberta.ca/jbrzusto/rarefact.php) for each locus, using allele counts from a random sample of 96 specimens to seed the equations. We used POWSIM (Ryman & Palm 2006) to evaluate the statistical power to detect genetic heterogeneity. Simulations of n = 1,000 replicates included various combinations of [N.sub.e] and time since divergence to yield [F.sub.ST] values of 0.0025, 0.005, and 0.01. Default parameters were used for dememorizations, iterations, and batches. We used MICROCHECKER (Van Oosterhout et al. 2004) to estimate the combined frequencies of nonamplifying alleles.

RESULTS

Age Structure

Annuli counts made over multiple sections by independent age readers were in agreement. Sections that included the umbo were the only sections to show a ventral growth band for the first year of growth; thin sections that were anterior or posterior to the umbo occasionally missed this first annulus. Annuli for the first 4-10 y appeared as dark regions separated by more translucent areas, and were wide relative to annuli more dorsal to the umbo (Fig. 2). The appearance and width of the annuli shifted between the 4th and 10th growth band. The bands representing growth shifted from opaque to translucent, and bands representing periods of low growth became less translucent. The postshift growth bands were much narrower than those preceding them dorsally. The closer to the ventral margin of the hinge plate the growth bands occurred, the narrower they became. Ventral margins of the hinge plate with more than 50-60 growth bands required an increase from 400x to 600x magnification because the growth lines became densely packed and difficult to discern at the lower magnification. Age estimates based on growth band counts were consistent and accurate in blind tests of clams of known age (3 and 4 y old), thus validating annual growth band depositions in young geoduck clams.

[FIGURE 2 OMITTED]

Year-class distributions were substantially different between the 2 sites and among stations within site 2 (Figs. 3 and 4), and age frequencies did not follow distributions expected from previous Puget Sound age-frequency data sets (Goodwin & Shaul 1984). Significant year-class frequency deviations from expectations were noted at both sites. In particular, the 1978 year-class at site 1 comprised 24% of the sample, depressing the expected numbers in other well-represented year-classes to about 30 individuals. At site 2, the 1993 year-class comprised 8% of the sample, which also exceeded expectations based on previous age frequency data. Overall, there was a paucity of year-classes with sufficient specimens to enable highly robust comparisons of genetic differentiation and estimates of effective population size (Fig. 3). Selected year-classes represented by n > 18 individuals were included in the analyses; however, no well-represented year-classes were shared between sites. Therefore, an additional, less abundant year-class from site 2 (1992, n = 11) was included to enable an additional between-site comparison of a single year-class.

[FIGURE 3 OMITTED]

[FIGURE 4 OMITTED]

Genetic Variability

All the microsatellite and allozyme loci assayed were polymorphic. As expected, levels of genetic diversity exhibited by the microsatellites were greater than those observed at the allozyme loci. The average number of alleles per locus summed over all loci and year classes was 4.3 and 17.9 for allozymes and microsatellites, respectively (Tables 2, 3, and 4). No significant differences in mean observed heterozygosity appeared among year-classes for either marker set. Nor was there any significant linkage disequilibrium detected between pairs of allozyme or microsatellite loci, or between allozyme and microsatellite locus pairs.

Allozyme and microsatellite loci differed markedly in conformity to HWE. No significant deviations from HWE were detected for any allozyme locus in any collection (Table 2). On the other hand, significantly fewer heterozygotes than expected were detected for 6 microsatellite loci (P < 0.0001), likely a result of multiple nonamplifying alleles; MICROCHECKER combined null allele frequency estimates ranging from 0.06-0.34. Only Pab6 did not depart from HWE overall or in any year-class after Bonferroni correction. Overall, there were no significant reductions in deviations from HWE within year-classes relative to the whole population in either site 1 or site 2.

Year-Class Differentiation

Global [F.sub.ST] for site 1 year-classes was not significantly different from 0 using microsatellites (mean, -0.001; 95% CI, -0.002-0.001), allozymes (mean, -0.001; 95% CI, -0.006-0.006), or both marker combined (mean, -0.002; 95 % CI, -0.004-0.001). Likewise, global [F.sub.ST] values for site 2 year-classes and stations within site 2 were not significantly different from 0 (mean site 2 year-class [F.sub.ST] = 0.002; 95% CI, -0.001-0.006; station mean, 0.002; 95% CI, 0.0-0.004; site 2 station summary statistics are in Table 5). The overall [F.sub.ST] between random samples of 96 (microtiter plate capacity) individuals from sites 1 and 2 was 0.001, with a 95% CI of -0.001-0.003.

At site 1, we were unable to detect significant differences in pairwise genotypic and genic tests among any of the 9 year-classes detected with either allozymes (P = 0.238 0.999), microsatellites (P = 0.026-0.936, Bonferroni corrected alpha 0.05/36 = 0.0014), or with all 18 markers combined (P = 0.267-0.997). Likewise, at site 2 we detected no significant differences in pairwise genotypic tests using microsatellites among the 1991, 1992, 1993, 1994, and 1995 year-classes (P = 0.126-0.657). No differences were detected in the only 2 possible comparisons of between-site variation in microsatellite genotype frequencies within a single year-class: 1992 (P = 0.263) and 1994 (P = 0.739). Results of POWSIM analyses indicate that the probability of detecting an [F.sub.ST] of 0.005 was 85.4% for n = 30 and 100, and 76.6% for n = 20, 30, and 40 with the microsatellite loci used.

Relatedness

Mean relatedness coefficients for all year-classes at site 1 ranged from -0.0001-0.0094 (Table 6) and at site 2 they ranged from -0.0037 to -0.0004 (Table 7). At both locations, relatedness coefficients did not differ significantly from 0. The relatedness coefficients calculated for each station in site 2 ranged from -0.0054-0.0004, and were not significantly different from 0 (Table 7).

Effective Population Size

Because Pab4 and Pab8 had the highest variability (96 and 55 unique alleles, respectively) and high null allele frequencies, they were excluded from estimates of [N.sub.e] and rarefaction to avoid the potentially confounding effects of many low-frequency alleles. For site 1 samples, comparisons were made between the 1943 year-class and the 1981, 1982, and 1983 year-classes, a span of about 1 generation, using the MC and LB methods. The MB method (corrected as described in Jorde & Ryman (1995)) was used for the 1981, 1982, and 1983 year-classes. We were unable to estimate [N.sub.e] using the MC and LB methods for site 2 because no well-represented year-classes were separated by 1 generation or more. We applied the MB method to the 1991 to 1995 year-classes. Little evidence for a reduction in [N.sub.e] was found from any of the 3 methods used in this study. Estimates ranged from 84 (MB)-1,500 (LB), but effectively infinite upper confidence bounds were computed using all 3 methods.

Rarefaction

Rarefaction analysis correctly predicted the number of alleles in each year-class for all 5 of the microsatellite loci (Pab4 and Pab8 excluded, as noted earlier) with few exceptions. Overall, there was only scattered evidence for a reduction in allele number in a few select year-classes. The 1991 and 1992 year-classes from site 2, and the 1992 year-class from site 1, had allele counts below those predicted at 3 of the 5 loci (data not shown). These loci are among those with significant heterozygote deficits.

Mierospatial Variability in Year-Class Structure and Genetic Variation

No differences in year-class composition appeared between the 2 site 1 stations (t-test, P = 0.153), although the 2 stations did differ genetically (genotypic test, P = 0.0242). Significant differences in year-class composition were detected among the 5 site 2 stations (ANOVA, P = 0.036; Fig. 4). Four significant pairwise differences between stations in site 2 were detected after Bonferroni correction (P = 0.0003-0.00002; Table 8). These differences were evident at 4 of the 7 microsatellite loci.

DISCUSSION

The analyses presented here provide no evidence of temporal genetic variation or sweepstakes recruitment. For sweepstakes reproduction to affect genetic differentiation among geoduck clam populations, strong signals should be evident in temporal data sets. The requisite year-class frequency spikes that would provide support for the sweepstakes hypothesis were evident in our data, but we failed to find genetic differences among year-classes. Significant genetic heterogeneity is necessary to support the sweepstakes recruitment hypothesis as a biologically significant mechanism for producing the spatial differentiation previously observed in this species (Li & Hedgecock 1998). We also failed to detect significant increases in relatedness, or reductions in [N.sub.e] or allelic richness within year-classes that would be expected under the sweepstakes hypothesis.

Two other recognized methods for estimating [N.sub.e] from genetic data could not be used in this study. The heterozygote excess method (Pudovkin et al. 1996) produces reasonably narrow confidence intervals, but only when n is larger than 60 individuals and the number of genetic markers is larger than 20 (Luikart & Cornuet 1999). Likewise, the linkage disequilibrium method developed by Hill (1981) is imprecise with smaller numbers of loci.

Several explanations are possible for our failure to detect sweepstakes recruitment. First, the sample sizes from each year-class provided only a small amount of statistical power to detect genetic differences. David et al. (1997) found small but significant [F.sub.ST] values with just 9 polymorphic allozyme loci in a similar study of the hard clam Spisula ovalis. The difference in results might be explained by different longevities of S. ovalis and P. generosa, and differences in sample size. The sample of S. ovalis in the study of David et al. (1997) comprised 10 year-classes, and temporal comparisons were based on an average of 952 specimens for each year-class. In our study, samples of the longer lived geoduck clam were distributed over a greater number of year-classes, with smaller sample sizes per year-class. Nevertheless, no genetic differentiation was detected in pairwise comparisons of the highest frequency 1978 year-class from site 1 (n = 95), and 1993 year-class from site 2 (n = 76), with the rest of the individuals in the respective collections (data not shown). The high variability of the microsatellite loci may compensate to some degree for the loss of power associated with low sample size. However, no greater differentiation was detected with microsatellites than with allozymes in our data set, even though the resolution of intraspecific differentiation is generally greater for microsatellites than for allozymes (Estoup et al. 1998, Ross et al. 1999).

Li and Hedgecock (1998) found evidence for sweepstakes recruitment in populations of the oyster C. gigas in Puget Sound. The contrast with geoduck clams might be explained in 2 ways. First, more pronounced sweepstakes recruitment in C. gigas may be a consequence of its status as an exotic species, now naturalized in Puget Sound. Natural recruitment in this species is known to occur only in isolated localities within Puget Sound; the study site of Li and Hedgecock (1998), Dabob Bay, is one such locality. It seems likely that the oceanographic window of opportunity (cf. Hedgecock 1994) for successful reproduction is narrower in Dabob Bay than in C. gigas' natural range, and that genetic effects of sweepstakes recruitment might therefore be more readily detectable at this location. The evidence for C. gigas suggests that sweepstakes effects may be more evident near the edge of a species" natural range, because settlement success in these areas may be more variable than at the center of distribution. Thus, our failure to detect the effects of sweepstakes recruitment in Puget Sound's geoduck clams may be a consequence of sampling large aggregations at the center of the species' known geographical range.

The presence of many overlapping generations in aggregations of spawning geoduck clams may serve to maintain genetic variability and buffer against genetic drift in the population (Pearse & Anderson 2009). This may be the result of the presence of the same breeders in multiple spawns (Palstra et al. 2009), and the greater potential to realize relatively rare events (e.g., the intense recruitment pulse at site 1 in 1978) that can affect genetic structure (Selkoe et al. 2006, Selkoe et al. 2008). Domingues et al. (2011) observed similar temporal genetic homogeneity in the shore crab, Carcinus maenas. Thus, sweepstakes recruitment may occur in geoduck clams, but on finer temporal scales than was detectable in this study. Captive geoduck clams are known to spawn repeatedly in a single season, and the year-class samples in our study likely included individuals from several spawnings in a year. Each cohort from individual spawning events may indeed be produced by only a few parents, but taken as a whole, each year-class may form a representative sample of the entire population. In this scenario, the genetic signature of sweepstakes reproduction and recruitment may be obscured by temporal averaging over discrete spawning or settlement events that take place over the course of a year.

Although no evidence of sweepstakes recruitment was detected, year-class composition and allele frequencies differed on a subkilometer geographical scale at a site undisturbed by commercial harvest (site 2). Because we failed to find genetic evidence of sweepstakes recruitment, the surprisingly high variance in year-class frequency may, instead, be the result of other factors. High variance in year-class frequency is typical of many highly fecund marine fishes (Rickman et al. 2000), and may reflect susceptibility to variation in environmental conditions that influence recruitment (Portner et al. 2001). Environmental forcing of variation in geoduck clam age frequencies has been supported by back-calculating year-class strength (Valero et al. 2004). Although selection or variation in postsettlement survival, or both, might explain the genetic differences detected, the presumed selective neutrality of microsatellite and allozyme loci used in this study was supported previously using a test of the codistribution of heterozygosity and [F.sub.ST] (Beaumont & Nichols 1996, Vadopalas et al. 2004). In the long-lived bivalve clam Arctica islandica, large variation in recruitment was demonstrated but not correlated with an environmental variable (Lewis et al. 2001), although survival and settlement may occur only during rare oceanographic conditions. In addition, a strategy of gambling on rare successful spawning may be used by long-lived broadcast spawners to increase population growth, as evidenced in a stochastic matrix model developed for 7 long-lived bivalves (Ripley 1998). Such mass spawning-recruitment spikes may be required only once during an average life span to buffer the effects of genetic drift over multiple generations.

An alternative explanation for the genetic patchiness observed in geoducks (Vadopalas et al. 2004) is clustered larval dispersal. Under static water flow conditions in the laboratory, precompetent geoduck larvae form clusters of about 100 individuals using byssal threads and mucus (B. Vadopalas and J. Davis, unpubl, data). This behavior may both decrease dispersal in diffusive eddies (Scheltema 1986) and increase the drag coefficient of the aggregation, and thus dispersal, by advection. Competent larvae, as they leave the cluster, travel only short distances because pedal locomotion is unlikely to result in long-distance dispersal. Byssal drifting has been observed in bivalves (Sigurdsson et al. 1976), including geoduck clams (W. Shaul, April 7, 2007, CALFED, pers. comm.). If the larvae in a cluster were the progeny of only a few parents, then we would expect to observe increased relatedness within clusters. This predicted increase in relatedness within year-classes at the sampling level of our stations may have been obscured because multiple clusters may have been included in the samples. Even without a reduction in the effective number of breeders, clustered larval dispersal is still a viable explanation for the microgeographical differentiation noted in our study.

Observations from a separate study support both the clustered dispersal and the edge signal hypotheses. Using a remotely operated vehicle, we obtained 2 geoduck clams from the edge of an aggregation at 35 m (MLLW) near Hazel Point (Fig. 1). In stark contrast to the geoduck clams collected at site 1 (~10 m MLLW) about 5 km south of Hazel Point, these 2 specimens were small with disproportionately small viscera, and the valves were extremely thin. The 2 individuals had identical annuli counts, and an estimated birth year of 1951, a year with a relatively weak year-class at site 1 (frequency = 0.001). Based on the site 1 age frequency distribution, the probability that a random sample of 2 geoduck clams would yield this result is low (P < 0.01). Allele sharing between the 2 was close to 50% (r = 0.557), a highly unlikely finding for unrelated individuals (P < 0.001). Remarkably, these results strongly suggest that the 2 specimens were full siblings. Sweepstakes recruitment, selection, or both, are likely explanations of these results, especially given the likelihood that we sampled at the edge of their depth range in that vicinity. Finding 2 full siblings in such close proximity to one another would certainly depend on codispersing larvae.

Regardless of whether geoduck clam larvae codisperse, our age-class frequency distributions indicate that recruitment varies both among basins of Puget Sound and within the small area encompassed by site 2 (Fig. 4). The genetic variation we observed on microgeographical scales is similar to that observed previously among locations in Puget Sound (Vadopalas et al. 2004), but greater than that observed between populations in Puget Sound and southeast Alaska, a distance of about 1,000 km. Even though we were unable to detect temporal genetic variation, the general concordance of patchy age structure variation and patchy genetic variation suggests a link between the 2 phenomena. Thus, our results suggest that although larval dispersal is sufficient to ensure genetic homogeneity over broad geographical areas, complex but poorly understood heterogeneity in settlement provides a more likely explanation than sweepstakes recruitment for the genetic differentiation we observed over small geographical scales.

ACKNOWLEDGMENTS

We gratefully acknowledge the Washington Department of Fish and Wildlife dive team members Alex Bradbury, Robert Sizemore, Don Rothaus, and Michael Ulrich (a.k.a. The Fab Four), and Dave Palazzi and Doug Williams of the Washington Department of Natural Resources for assisting with the sample collecting. Jim Shaklee, Sewall Young, and Steve Phelps provided valuable advice and expertise. Jessica Raum, Elyse Cronin, and Heather Honeycut collected the age data. Cherril Bowman, Rebecca Colwell, Amilee Wilson, Cameron Duff, Bill Ingrain, Anne Marshall, Ken Obrien, Keith Sweeney, and Norman Switzler assisted with dissections, and C. J. Casson of the Seattle Aquarium graciously provided dissection facilities. We thank Ocean Eveningsong for constructing the sample location map. We gratefully thank Drs. Patrick O'Reilly, Carolyn Friedman, Lorenz Hauser, Fred Utter, and Dennis Hedgecock for illuminating and insightful discussions. We are indebted to Jordan Watson, Allen Pleus, Davy Lowry, and Robert Sizemore for valuable edits, and Drs. Stewart Grant and Kristina Straus for valuable suggestions and edits that greatly improved the manuscript. This work was funded in part by a grant from the Washington Sea Grant Program, University of Washington, pursuant to National Oceanic and Atmospheric Administration award no. NA76RG0119. The views expressed herein are those of the authors and do not necessarily reflect the views of NOAA or any of its sub-agencies. B. V. was additionally supported by the Roy Jensen Fellowship, School of Aquatic and Fishery Sciences, University of Washington.

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BRENT VADOPALAS, (1) * LARRY L. LECLAIR (2) AND PAUL BENTZEN (3)

(1) School of Aquatic and Fishery Sciences, University of Washington, 1122 NE Boat St., Box 355020, Seattle, WA 98105; (2) Washington Department of Fish and Wildife, 600 Capitol Way N., Olympia, WA 98501-1091; (3) Department of Biology, Dalhousie University, 1355 Oxford St., Halifax, Nova Scotia B3H 4J1

* Corresponding author. E-mail: brentv@uw.edu

DOI: 10.2983/035.031.0314
TABLE 1.
Collection dates, numbers of samples, depths, and locations for
site 1 and site 2 Panopea generosa collections.

                       Samples   Depth
            Date         (n)      (m)

Site 1
A        May and           930   -12.3
           June 2000
B        June 2000          79   -10.9

Site 2
A        March 2001        200    -5.2
B        March 2001        200    -6.1
C        March 2001        200    -9.8
D        March 2001        200    -6.7
E        March 2001        200    -9.8

                             Location

Site 1
A        47[degrees]40'58.92"N    122[degrees]44'51.66"W

B        47[degrees]40'41.76"N    122[degrees]44'53.16"W

Site 2
A        47[degrees]17'46.20"N    122[degrees]50'48.60"W
B        47[degrees]17'44.34"N    122[degrees]50'51.12"W
C        47[degrees]17'45.42"N    122[degrees]50'47.04"W
D        47[degrees]17'49.56"N    122[degrees]50'42.66"W
E        47[degrees]17'47.70" N   122[degrees]50'42.66"W

TABLE 2.
Panopea generosa, site 1 summary statistics for 11 allozyme loci
by individual year-class and summed over all year-classes.

Year-Class            ALAT *       MPI *      PEPA *      PGDH *

1994    4             2           7           3           1
        [H.sub.e]     0.245       0.748       0.503       0
        [H.sub.o]     0.286       0.636       0.455       0
        P             1           0.186       0.356      --
        [F.sub.IS]   -0.143       0.172       0.119      NA
        n            21          22          22          21

1988    #             3           6           3           1
        [H.sub.e]     0.208       0.733       0.37        0
        [H.sub.o]     0.231       0.846       0.462       0
        P             1           0.481       0.713      --
        [F.sub.IS]   -0.091      -0.135      -0.23       NA
        n            26          26          26          26

1983    #             3           6           3           1
        [H.sub.e]     0.092       0.713       0.452       0
        [H.sub.o]     0.095       0.667       0.381       0
        P             1           0.648       0.441      --
        [F.sub.IS]   -0.013       0.089       0.182      NA
        n            21          21          21          21

1982    #             2           5           3           1
        [H.sub.e]     0.188       0.683       0.47        0
        [H.sub.o]     0.211       0.684       0.368       0
        P             1           0.727       0.324      --
        [F.sub.IS]   -0.091       0.025       0.241      NA
        12           19          19          19          18

1978    #             4           9           4           2
        [H.sub.e]     0.194       0.782       0.453       0.022
        [H.sub.o]     0.213       0.702       0.362       0.022
        P             1           0.394       0.27       --
        [F.sub.IS]   -0.086       0.113       0.212       0
        n            47          47          47          45

1943    #             3           6           4           2
        [H.sub.e]     0.155       0.731       0.531       0.033
        [H.sub.o]     0.167       0.567       0.567       0.033
        P             1           0.027       0.893      --
        [F.sub.IS]   -0.058       0.24       -0.051       0
        n            30          30          30          30

Total                             5           9           4
        [H.sub.e]     0.18        0.732       0.463       0.009
        [H.sub.o]     0.198       0.686       0.428       0.008
        P             1           0.175       0.438      --

Year-Class              SOD *        ARGK *       GPI *      AATI *

1994    4             2              4           3           2
        [H.sub.e]     0.375          0.604       0.628       0.133
        [H.sub.o]     0.318          0.591       0.455       0.143
        P             0.568          0.944       0.204       1
        [F.sub.IS]    0.174          0.045       0.298      -0.053
        n            22             22          22          21

1988    #             2              4           3           2
        [H.sub.e]     0.482          0.632       0.628       0.109
        [H.sub.o]     0.577          0.769       0.692       0.115
        P             0.435          0.396       1           1
        [F.sub.IS]   -0.179         -0.198      -0.083      -0.042
        n            26             26          26          26

1983    #             2              3           3           2
        [H.sub.e]     0.472          0.616       0.554       0.047
        [H.sub.o]     0.476          0.684       0.55        0.048
        P             1              0.733       0.865      --
        [F.sub.IS]    0.015         -0.083       0.032       0
        n            21             19          20          21

1982    #             2              5           3           2
        [H.sub.e]     0.45           0.64        0.589       0.145
        [H.sub.o]     0.579          0.79        0.579       0.158
        P             0.345          0.954       0.235       1
        [F.sub.IS]   -0.261         -0.208       0.043      -0.059
        12           19             19          19          19

1978    #             4              5           4           2
        [H.sub.e]     0.529          0.628       0.547       0.156
        [H.sub.o]     0.596          0.575       0.532       0.17
        P             0.382          0.337       0.775       1
        [F.sub.IS]   -0.115          0.095       0.038      -0.082
        n            47             47          47          47

1943    #             3              4           4           3
        [H.sub.e]     0.455          0.585       0.572       0.126
        [H.sub.o]     0.367          0.821       0.5         0.133
        P             0.199          0.021       0.593       1
        [F.sub.IS]    0.21          -0.389       0.144      -0.04
        n            30             28          28          30

Total                 3              4           5           4
        [H.sub.e]     0.46           0.618       0.586       0.119
        [H.sub.o]     0.469          0.704       0.557       0.125
        P             0.642          0.354       0.829       1

Year-Class            GAPDH *      MDH *      IDHP *     Averages

1994    4             1           2           2          2.64
        [H.sub.e]     0           0.482       0.449      0.379
        [H.sub.o]     0           0.429       0.591      0.355
        P            --           0.66        0.338      6.5
        [F.sub.IS]   NA           0.135      -0.294      0.269
        n            22          21          22

1988    #             1           2           3          2.73
        [H.sub.e]     0           0.464       0.517      0.377
        [H.sub.o]     0           0.346       0.5        0.413
        P            --           0.216       1          6.5
        [F.sub.IS]   NA           0.272       0.052      0.213
        n            26          26          26

1983    #             2           2           2          2.64
        [H.sub.e]     0.047       0.49        0.472      0.359
        [H.sub.o]     0.048       0.571       0.571      0.372
        P            --           0.663       0.642      6.5
        [F.sub.IS]    0          -0.143      -0.188      0.231
        n            21          21          21

1982    #             2           2           3          2.73
        [H.sub.e]     0.051       0.478       0.508      0.382
        [H.sub.o]     0.053       0.474       0.632      0.412
        P            --           1           0.777      6.5
        [F.sub.IS]    0           0.036      -0.217      0.177
        12           19          19          19

1978    #             3           2           2          3.73
        [H.sub.e]     0.042       0.489       0.496      0.394
        [H.sub.o]     0.043       0.426       0.575      0.383
        P             1           0.38        0.383      6.5
        [F.sub.IS]   -0.005       0.14       -0.147      0.274
        n            47          47          47

1943    #             3           3           2          3.36
        [H.sub.e]     0.096       0.429       0.473      0.381
        [H.sub.o]     0.1         0.4         0.5        0.378
        P             1           0.76        1          6.5
        [F.sub.IS]   -0.024       0.085      -0.041      0.248
        n            30          30          30

Total                 3           4           3          4
        [H.sub.e]     0.039       0.472       0.486      0.379
        [H.sub.o]     0.039       0.437       0.557      0-383
        P             1           0.737       0.971

#, number of alleles; [F.sub.IS], within-population variability;
[H.sub.e], expected heterozygosity; [H.sub.o], observed
heterozygosity; n, number of geoduck clams genotyped; NA, not
applicable; P, P value for test of conformance to Hardy-Weinberg
equilibrium.

TABLE 3.
Panopea generosa, site 1 summary statistics for 7 microsatellite
loci by sampling station and individual year-class.

Station/Year-Class         Pab3        Pah4        Pah5        Pab6

Station A   #            51          39          18          34
            [H.sub.e]     0.9736      0.9559      0.8907      0.9268
            [H.sub.o]     0.5053      0.3026      0.4421      0.9032
            P            <0.0001     <0.0001     <0.0001      0.7576
            [F.sub.IS]    0.485       0.687       0.508       0.031
            n            95          76          95          93

Station B   #            49          35          18          31
            [H.sub.e]     0.9659      0.9556      0.9064      0.9296
            [H.sub.o]     0.4878      0.2568      0.4217      0.9157
            P            <0.0001     <0.0001     <0.0001      0.3316
            [F.sub.IS]    0.5         0.734       0.539       0.021
            n            82          74          83          83

1994        #            22          25          11          17
            [H.sub.e]     0.9334      0.936       0.8587      0.9088
            [H.sub.o]     0.5385      0.5455      0.3846      0.76
            P            <0.0001     <0.0001     <0.0001      0.1387
            [F.sub.IS]    0.439       0.436       0.566       0.184
            n            26          22          26          25

1992        #            18          13          10          18
            [H.sub.e]     0.9175      0.8876      0.8475      0.8913
            [H.sub.o]     0.35        0.3077      0.55        0.8
            P            <0.0001     <0.0001      0.0005      0.0807
            [F.sub.IS]    0.634       0.676       0.373       0.128
            n            20          13          20          20

1990        #            17          13          12          17
            [H.sub.e]     0.9225      0.9028      0.8688      0.9213
            [H.sub.o]     0.6         0.4167      0.55        1
            P            <0.0001     <0.0001      0.0004      1
            [F.sub.IS]    0.372       0.569       0.389      -0.06
            n            20          12          20          20

1988        #            18          23          15          19
            [H.sub.e]     0.9343      0.9442      0.9069      0.9152
            [H.sub.o]     0.4643      0.3478      0.3571      0.96
            P            <0.0001     <0.0001     <0.0001      0.4488
            [F.sub.IS]    0.517       0.645       0.618      -0.029
            n            28          23          28          25

1983        #            23          16          10          16
            [H.sub.e]     0.9411      0.8737      0.8616      0.9174
            [H.sub.o]     0.5         0.4118      0.3182      0.9091
            P            <0.0001     <0.0001     <0.0001      0.6008
            [F.sub.IS]    0.487       0.55        0.644       0.032
            n            22          17          22          22

1982        #            17          18          11          18
            [H.sub.e]     0.9259      0.9167      0.8673      0.9244
            [H.sub.o]     0.6667      0.3333      0.6111      0.8889
            P            <0.0001      0.0005      0.046       0.3027
            [F.sub.IS]    0.306       0.653       0.321       0.067
            n            18          18          18          18

1981        #            16          15          14          16
            [H.sub.e]     0.9136      0.9136      0.9028      0.9151
            [H.sub.o]     0.3889      0.3333      0.4444      0.9444
            P            <0.0001     <0.0001     <0.0001      0.5902
            [F.sub.IS]    0.593       0.652       0.529      -0.003
            n            18          18          18          18

1978        #            27          39          20          29
            [H.sub.e]     0.9408      0.9548      0.8984      0.9247
            [H.sub.o]     0.4316      0.2024      0.4526      0.8947
            P            <0.0001     <0.0001     <0.0001      0.7099
            [F.sub.IS]    0.545       0.79        0.5         0.038
            n            95          84          95          95

1943        #            18          15          11          17
            [H.sub.e]     0.9244      0.9209      0.8642      0.9118
            [H.sub.o]     0.6111      0.2857      0.6667      0.9412
            P            <0.0001     <0.0001      0.0219      0.5699
            [F.sub.IS]    0.364       0.709       0.255      -0.002
            17           18          14          18          17

Rand.       #            28          39          18          34
            [H.sub.e]     0.9476      0.9559      0.8907      0.9268
            [H.sub.o]     0.4737      0.3026      0.4421      0.9032
            P            <0.0001     <0.0001     <0.0001      0.5391
            [F.sub.IS]    0.504       0.687       0.508       0.031
            n            95          76          95          93

Totals      #            35          55          22          42
            [H.sub.e]     0.9358      0.9274      0.8814      0.9182
            [H.sub.o]     0.4919      0.3313      0.4731      0.9002
            P            <0.0001     <0.0001     <0.0001      0.29

Station/Year-Class         Pab7        Pah8        Pab9      Averages

Station A   #            17          60          17
            [H.sub.e]     0.9131     0.9755       0.918       0.9362
            [H.sub.o]     0.7979     0.4409       0.6957      0.5840
            P             0.0149     0.0043      <0.0001     <0.0001
            [F.sub.IS]    0.131      0.552        0.247       0.381
            n            94          93          92

Station B   #            17          53          18
            [H.sub.e]     0.8985      0.971       0.9255      0.9361
            [H.sub.o]     0.8072      0.4         0.8795      0.59551
            P             0.0032      0.0044      0.7501     <0.0001
            [F.sub.IS]    0.108       0.592       0.056       0.369
            n            83          80          83

1994        #            15          31          14
            [H.sub.e]     0.9         0.9576      0.8992      0.9134
            [H.sub.o]     0.52        0.56        0.72        0.5755
            P            <0.0001     <0.0001      0.0103     <0.0001
            [F.sub.IS]    0.439       0.432       0.219       0.388
            n            25          25          25

1992        #            12          24          12
            [H.sub.e]     0.856       0.945       0.8813      0.8894
            [H.sub.o]     0.6316      0.45        0.8         0.5556
            P             0.0353     <0.0001      0.0572     <0.0001
            [F.sub.IS]    0.287       0.542       0.118       0.399
            n            19          20          20

1990        #            14          18          15
            [H.sub.e]     0.8875      0.9377      0.9087      0.9070
            [H.sub.o]     0.75        0.2105      0.85        0.6253
            P             0.0268     <0.0001      0.6194     <0.0001
            [F.sub.IS]    0.18        0.786       0.09        0.337
            n            20          19          20

1988        #            13          25          15
            [H.sub.e]     0.8832      0.941       0.9135      0.9198
            [H.sub.o]     0.64        0.3704      0.8462      0.5694
            P             0.0032      0.0177      0.0144     <0.0001
            [F.sub.IS]    0.294       0.618       0.093       0.398
            n            25          27          26

1983        #            14          21          14
            [H.sub.e]     0.8698      0.9442      0.9002      0.9011
            [H.sub.o]     0.6818      0.3182      0.9048      0.5777
            P             0.0006     <0.0001      0.9407     <0.0001
            [F.sub.IS]    0.238       0.676       0.019       0.38
            n            22          22          21

1982        #            11          23          15
            [H.sub.e]     0.8765      0.9367      0.9012      0.907
            [H.sub.o]     0.5556      0.6111      0.7778      0.6349
            P            <0.0001      0.0106      0.237      <0.0001
            [F.sub.IS]    0.391       0.372       0.165       0.326
            n            18          18          18

1981        #            14          17          15
            [H.sub.e]     0.8951      0.9244      0.9043      0.9098
            [H.sub.o]     0.6667      0.3333      0.9444      0.5793
            P             0.0048     <0.0001      0.7079     <0.0001
            [F.sub.IS]    0.282       0.656      -0.016       0.388
            n            18          18          18

1978        #            19          63          18
            [H.sub.e]     0.9112      0.977       0.9177      0.9321
            [H.sub.o]     0.6947      0.3723      0.8191      0.5525
            P            <0.0001      0.0039      0.008      <0.0001
            [F.sub.IS]    0.243       0.622       0.113       0.412
            n            95          94          94

1943        #             9          24          13
            [H.sub.e]     0.8596      0.9522      0.8927      0.9037
            [H.sub.o]     0.4444      0.5         0.5294      0.5684
            P            <0.0001     <0.0001     <0.0001     <0.0001
            [F.sub.IS]    0.505       0.497       0.432       0.397
            17           18          18          17

Rand.       #            17          60          17
            [H.sub.e]     0.9131      0.9755      0.9193      0.9327
            [H.sub.o]     0.7979      0.4409      0.6882      0.5784
            P             0.0077      0.0012     <0.0001     <0.0001
            [F.sub.IS]    0.131       0.552       0.256       0.385
            n            94          93          93

Totals      #            21          86          20
            [H.sub.e]     0.8874      0.9542      0.9064
            [H.sub.o]     0.6558      0.4157      0.7846
            P            <0.0001     <0.0001     <0.0001

Stations A and B are randomized subsamples. #,
[F.sub.IS], within-population variability; [H.
heterozygosity; [H.sub.o], observed heterozygo
geoduck clams genotyped; P, P value for test o
Hardy-Weinberg equilibrium.

TABLE 4.
Panopea generosa summary statistics for 7 microsatellite
loci by year-class at site 2.

Year-Class             Pab3        Pab4        Pab5        Pab6

1995    #            11          13          12          13
        [H.sub.e]     0.8521      0.9132      0.8911      0.8867
        [H.sub.o]     0.4615      0.25        0.4667      1
        P            <0.0001     <0.0001     <0.0001      0.9712
        [F.sub.IS]    0.489       0.746       0.503      -0.096
        n            13          12          15          16

1994    #            17          21          17          17
        [H.sub.e]     0.906       0.9376      0.9064      0.9142
        [H.sub.o]     0.3636      0.2174      0.52        0.9615
        P            <0.0001     <0.0001     <0.0001      0.8735
        [F.sub.IS]    0.613       0.777       0.443      -0.032
        n            22          23          25          26

1993    #            23          29          19          27
        [H.sub.e]     0.9335      0.9394      0.9097      0.9313
        [H.sub.o]     0.2817      0.2464      0.5132      0.9221
        P            <0.0001     <0.0001     <0.0001      0.1965
        [F.sub.IS]    0.702       0.741       0.441       0.016
        n            71          69          76          77

1992    #             8           8           6          14
        [H.sub.e]     0.84        0.8438      0.8         0.905
        [H.sub.o]     0           0.25        0.2         0.9091
        P            <0.0001     <0.0001     <0.0001      0.6575
        [F.sub.IS]    1           0.736       0.772       0.043
        n            10           8          10          11

1991    #            20          19          13          18
        [H.sub.e]     0.926       0.8438      0.8769      0.9116
        [H.sub.o]     0.4286      0.3214      0.6071      0.8387
        P            <0.0001     <0.0001     <0.0001      0.031
        [F.sub.IS]    0.55        0.665       0.324       0.096
        n            28          28          28          31

Year-Class             Pab7        Pab8        Pab9      Averages

1995    #            14          22          13
        [H.sub.e]     0.8945      0.9467      0.8828      0.8953
        [H.sub.o]     0.8125      0.7692      0.6875      0.6353
        P             0.4247     <0.0001      0.0231     <0.0001
        [F.sub.IS]    0.124       0.226       0.252       0.324
        n            16          13          16

1994    #            14          27          14
        [H.sub.e]     0.8898      0.952       0.8683      0.9106
        [H.sub.o]     0.7308      0.52        0.6923      0.5722
        P             0.0047      0.0087      0.0343     <0.0001
        [F.sub.IS]    0.198       0.47        0.221       0.39
        n            26          25          26

1993    #            21          58          20
        [H.sub.e]     0.9049      0.9736      0.9245      0.931
        [H.sub.o]     0.7368      0.4085      0.7237      0.5475
        P            <0.0001      0.0401     <0.0001     <0.0001
        [F.sub.IS]    0.192       0.585       0.224       0.418
        n            76          71          76

1992    #            10          15           9
        [H.sub.e]     0.8636      0.9256      0.8595      0.8625
        [H.sub.o]     0.7273      0.3636      0.6364      0.4409
        P             0.071      <0.0001      0.102      <0.0001
        [F.sub.IS]    0.204       0.636       0.303       0.528
        n            11          11          11

1991    #            13          24          14
        [H.sub.e]     0.8829      0.9209      0.8991      0.8944
        [H.sub.o]     0.5161      0.3793      0.7097      0.543
        P            <0.0001     <0.0001      0.0001     <0.0001
        [F.sub.IS]    0.429       0.599       0.226       0.416
        n            31          29          31

#, number of alleles; [F.sub.IS], within-population variability;
[H.sub.e], expected heterozygosity; [H.sub.o], observed
heterozygosity; n, number of geoduck clams genotyped; P, P value
for test of conformance to Hardy-Weinberg equilibrium.

TABLE 5.
Panopea generosa summary statistics for 7 microsatellite
loci by sampling station at site 2.

Station                    Pab3        Pah4        Pah5        Pah6

A           #            30          37          17          30
            [H.sub.e]     0.9364      0.9598      0.8985      0.9304
            [H.sub.o]     0.4271      0.1625      0.4421      0.9368
            P            <0.0001     <0.0001     <0.0001      0.2749
            [F.sub.IS]    0.548       0.833       0.512      -0.002
            n            96          80          95          95

B           #            26          44          21          31
            [H.sub.e]     0.931       0.9571      0.9084      0.9291
            [H.sub.o]     0.4842      0.4674      0.6354      0.9375
            P            <0.000I     <0.0001     <0.0001      0.4751
            [F.sub.IS]    0.484       0.516       0.305      -0.004
            n            95          92          96          96

C           #            30          41          18          30
            [H.sub.e]     0.9473      0.9486      0.8961      0.9247
            [H.sub.o]     0.4409      0.3229      0.4839      0.9149
            P            <0.0001     <0.0001     <0.0001      0.7534
            [F.sub.IS]    0.538       0.663       0.464       0.016
            n            93          96          93          94

D           #            29          37          21          30
            [H.sub.e]     0.9417      0.9212      0.8963      0.9244
            [H.sub.o]     0.4688      0.5158      0.5         0.9479
            P            <0.0001      0.005      <0.0001      0.8817
            [F.sub.IS]    0.506       0.444       0.446      -0.02
            n            96          95          96          96

E           #            28          50          16          31
            He            0.9499      0.9636      0.8959      0.9215
            [H.sub.e]     0.4681      0.2717      0.4681      0.8958
            [H.sub.o]    <0.0001      0.005      <0.0001      0.8242
            P             0.511       0.721       0.482       0.033
            [F.sub.IS]   94          92          94          96

Total       #            40          59          26          42
  no. of
  alleles

Station                    Pab7        Pab8        Pab9      Averages

A           #            16          66          21
            [H.sub.e]     0.9008      0.9765      0.9232      0.9322
            [H.sub.o]     0.5054      0.5368      0.8         0.5444
            P            <0.0001      0.0018      0.0442     <0.0001
            [F.sub.IS]    0.443       0.454       0.139       0.421
            n            93          95          95

B           #            16          50          21
            [H.sub.e]     0.9139      0.9679      0.9136      0.9316
            [H.sub.o]     0.7708      0.3913      0.7188      0.6293
            P             0.0005      0.0036     <0.0001     <0.0001
            [F.sub.IS]    0.162       0.599       0.218       0.329
            n            96          92          96

C           #            20          55          19
            [H.sub.e]     0.9174      0.9628      0.9199      0.931
            [H.sub.o]     0.6667      0.5833      0.734       0.5924
            P            <0.0001      0.0864     <0.0001     <0.0001
            [F.sub.IS]    0.278       0.399       0.207       0.368
            n            93          96          94

D           #            19          52          19
            [H.sub.e]     0.9106      0.9733      0.9105      0.9254
            [H.sub.o]     0.7083      0.3494      0.7917      0.6117
            P            <0.0001     <0.0001      0.0146     <0.0001
            [F.sub.IS]    0.227       0.645       0.136       0.344
            n            96          83          96

E           #            18          48          19
            He            0.9078      0.9706      0.9225      0.9331
            [H.sub.e]     0.6458      0.4891      0.7396      0.5683
            [H.sub.o]    <0.0001      0.0035     <0.0001     <0.0001
            P             0.293       0.5         0.203       0.395
            [F.sub.IS]   96          92          96

Total       #            24          85          26
  no. of
  alleles

#, number of alleles; [F.sub.IS], within-population variability;
[H.sub.e], expected heterozygosity; [H.sub.o], observed
heterozygosity; n, number of geoduck clams genotyped; P, P value
for test of conformance to Hardy-Weinberg equilibrium.

TABLE 6.
Panopea generosa, site 1 collection relatedness by year-class.

Year-Class       R          J/Loci         CI

1994            -0.0001       0.0019       0.0054
1992             0.0094       0.0066       0.0185
1990             0.0062       0.0042       0.0115
1988             0.0045       0.0030       0.0084
1983             0.0026       0.0073       0.0202
1982             0.0021       0.0044       0.0122
1981             0.0013       0.0030       0.0083
1978             0.0007       0.0024       0.0065
1943             0.0015       0.0038       0.0105

Mean relatedness coefficients (R), jackknifed (J) values for
year-classes jackknifed over loci, and 95% confidence intervals
(CI).

TABLE 7.
Panopea generosa, site 2 collection relatedness by station and
by year-class.

Station          R        J/loci      CI       J/Year-Class      CI

A             -0.0008     0.0027     0.0076       0.0040       0.0112
B             -0.0015     0.0018     0.0050       0.0015       0.0040
C             -0.0036     0.0028     0.0079       0.0033       0.0104
D             -0.0054     0.0020     0.0055       0.0030       0.0084
E             0.0004      0.0039     0.0107       0.0049       0.0211

Year-Class       R        J/Loci       CI       J/Station        CI

1995          -0.0004     0.0020     0.0055       0.0044       0.0140
1994          -0.0037     0.0028     0.0078       0.0057       0.0158
1993          -0.0013     0.0028     0.0079       0.0016       0.0045
1992          -0.0012     0.0026     0.0072       0.0032       0.0137
1991          -0.0025     0.0024     0.0068       0.0018       0.0049

Mean relatedness coefficients (R); jackknifed (J) values over loci,
stations, and year-classes; and 95% confidence intervals (CI).

TABLE 8.
Panopea generosa, site 2 collection.

Pair               Chi-Square    df     P Value     Significance

B and A              40.544      14     0.00021          **
C and A              23.185      14     0.05732          NS
C and B              25.795      14     0.02748          NS
D and A              24.071      14     0.04492          NS
D and B              28.526      14      0.0121          NS
D and C              12.640      14     0.55503          NS
E and A              30.020      14     0.00758          NS
E and B              39.576      14      0.0003          **
E and C              22.588      14     0.06732          NS
E and D              46.444      14     0.00002          **
Shallow and deep     40.590      14     0.00021          **

Tests of genotypic differentiation P value for each station pair, plus
deep and shallow pooled sites, across all 7 microsatellite loci
(Fisher's method). Tablewide [alpha] = 0.05, Bonferroni corrected
probability = 0.0045. NS, not significant; ** significant after
Bonferroni correction.
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