microsatellite evaluation of haddock ( melanogrammus aeglefinus ) stocks...

Microsatellite evaluation of haddock(Melanogrammus aeglefinus) stocks in thenorthwest Atlantic Ocean

Christopher Lage, Maureen Purcell, Michael Fogarty, and Irv Kornfield

Abstract: The goal of this study was to gain insight about the impact of intensive fishing on a single haddock(Melanogrammus aeglefinus) stock, and examine the genetic structuring of spatially discrete spawning aggregations inthe northwest Atlantic. We analyzed genetic change at four microsatellite loci for Georges Bank haddock over a 40-year time span in which significant changes in demographics and abundances have occurred in the population. Allelicdiversities have changed little, indicating that, although the commercial fishery has collapsed, stock sizes have remainedlarge enough to insulate against major reductions in genetic variation due to drift. Results indicate significant geneticdivergence among decadally separated samples. Potential causes for these differences include admixture from otherspawning regions, fluctuations in the effective number of spawners contributing to a single spawning event, drift, or acombination of these. Examination of discrete spawning aggregations from Georges Bank, Browns Bank, the ScotianShelf, and Nantucket Shoals indicated significant differences among stocks. Genetic distance based measures supportedthe clustering of Scotian Shelf, Browns Bank, and Georges Bank haddock to the exclusion of Nantucket Shoals had-dock. Haddock spawning on Nantucket Shoals may be genetically discrete from other haddock populations in thenorthwest Atlantic.

Résumé: Le but de notre étude est d’explorer les effets de la pêche intensive sur un stock particulier d’Aiglefins (Me-lanogrammus aeglefinus) et d’examiner la structuration génétique de regroupements isolés de reproducteurs dansl’Atlantique Nord. Nous avons analysé les changements génétiques à quatre locus microsatellites chez les Aiglefins dubanc Georges sur une période de 40 ans, pendant laquelle la population a subi d’importants changements de démo-graphie et de densité. La diversité des allèles a peu varié, ce qui laisse croire qu’en dépit de l’effondrement de lapêche commerciale, les densités des stocks se sont maintenues à un niveau suffisant pour les protéger contre une réduc-tion de la variation génétique due à la dérive. Il y a cependant une divergence génétique significative entre les échantil-lons lorsqu’on les regroupe en classes de 10 ans. Ces différences peuvent avoir été causées par l’immixtion dereproducteurs d’autres régions, par la fluctuation du nombre effectif de reproducteurs qui contribuent à un épisode indi-viduel de reproduction, par la dérive génétique, ou par une combinaison de ces facteurs. L’examen des regroupementsparticuliers de reproducteurs du banc Georges, du banc Browns, de la plate-forme néo-écossaise et des hauts-fonds deNantucket révèle des différences significatives entre les stocks. Des indices basés sur la distance génétique permettentde regrouper les Aiglefins de la plate-forme néo-écossaise, du banc Browns et du banc Georges, mais excluent ceuxdes hauts-fonds de Nantucket. Les Aiglefins qui fraient sur les hauts-fonds de Nantucket sont peut-être isolés généti-quement des autres populations de nord-ouest de l’Atlantique.

[Traduit par la Rédaction] Lage et al. 990

Introduction

The Atlantic haddock,Melanogrammus aeglefinus, is acommercially important species endemic to both sides of theNorth Atlantic. In the northwest Atlantic, haddock range

from Cape Hatteras to Greenland, with the highest concen-tration off the U.S. coast on the Northeast Peak of GeorgesBank. This species spawns in distinct areas, in particular, onoffshore banks, and is characterized by extensive variabilityin annual recruitment (Clark et al. 1982). While there issome indication of seasonal movement in the western Gulfof Maine, a variety of tagging, meristic, and life-historystudies suggest that there is very little adult mixing betweenGeorges Bank and other stocks in the northwest Atlantic,including Browns Bank, Scotian Shelf, Nantucket Shoals,and the western Gulf of Maine (Schroeder 1942; Clark andVladykov 1960; Bowen 1987). The Northeast Channel maybe a significant barrier to adult migration between GeorgesBank and areas to the northeast, as haddock are not usuallyfound in waters deeper than 200 m (Bigelow and Schroeder1953).

Haddock have been selectively fished throughout theirrange, and declines have affected stocks on Georges Bank,

Can. J. Fish. Aquat. Sci.58: 982–990 (2001) © 2001 NRC Canada

982

DOI: 10.1139/cjfas-58-5-982

Received May 2, 2000. Accepted November 21, 2000.Published on the NRC Research Press Web site on April 19,2001.J15742

C. Lage and I. Kornfield.1 University of Maine, School ofMarine Sciences, Orono, ME 04469, U.S.A.M. Purcell. Western Fisheries Research Center, 6505 N.E.65th Street, Seattle, WA 98115-5016, U.S.A.M. Fogarty. Center for Environmental and Estuarine Studies,Chesapeake Biological Laboratory, University of MarylandSystem, P.O. Box 38, Solomons, MD 20688, U.S.A.

1Corresponding author (e-mail: [email protected]).

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in the Gulf of Maine, and on the Scotian Shelf (Gavaris andVanEeckhaute 1994). A subsequent switch in species domi-nance has occurred on Georges Bank, with a replacement ofgadid and flounder species by elasmobranchs, such as dog-fish and skate (Fogarty and Murawski 1998). The cumula-tive long-term consequences for haddock stocks resultingfrom overharvesting and damage to benthic habitat fromfishing gear, as well as predation and competitive pressuresfrom shifts in species dominance, are not yet fully under-stood. Commercial fisheries for haddock have collapsed insome areas. A variety of regulations designed to minimizeimpact on remaining groundfish stocks have been imple-mented in the U.S. and Canada and include closed areas,catch quotas, and trip limits (Fogarty and Murawski 1998).Insight into the population biology of commercial species isparticularly critical when management decisions involverecovery plans for overexploited populations. Large fluctua-tions in population size due to variability in recruitment oroverexploitation may lead to changes in genetic populationstructure and possible reductions in overall genetic variabil-ity. Intensive exploitation of haddock stocks may result inlife-history changes, such as an increased age-specificweight and reduced time to reproductive maturity (Clark etal. 1982); such changes are most likely compensatory physi-ologic responses to overfishing, but may also be due to ashift in underlying genetic control (Policansky 1993). Thedetermination of population structure and genetic variabilityis of paramount importance to the long-term viability ofhaddock as a commercial species.

Techniques for the genetic identification of stocks of ma-rine fish and shellfish have been reviewed by Shaklee andBentzen (1998). Molecular techniques implemented to deter-mine population structure in Atlantic haddock have includedthe use of allozymes (Jamiesen and Birley 1989; Giaever etal. 1995) and mitochondrial DNA (mtDNA) (Zwanenburg etal. 1992; Purcell et al. 1996). These mitochondrial studiessuggest that mtDNA may not be sensitive enough to identifyfine-scale population structure in Atlantic haddock if, in fact,it exists. This study utilizes microsatellite markers to inferpopulation structure in Atlantic haddock, as they have beenfound useful in a number of population studies includingthat of Atlantic cod,Gadus morhua, a closely related gadidspecies (Bentzen et al. 1996; Ruzzante et al. 1996a, 1998).Three microsatellite loci used in this study were developedspecifically for haddock (Lage and Kornfield 1999) and onecod-specific marker was modified for use in haddock(Brooker et al. 1994).

The goal of this project was to gain insight about the im-pact of intensive fishing on a single haddock stock, that ofGeorges Bank, as well as to study genetic structuring of spa-tially discrete spawning aggregates in the northwest Atlantic.This study analyzes changes in a single population over de-cadal periods, a time span in which significant changes in de-mographics and abundances have occurred in the population.

Materials and methods

SamplingHistoric samples were obtained from a collection of archived

scales held at the National Marine Fisheries Service in WoodsHole, Mass. We used these scales to extract DNA dating back to

1958, and to genetically characterize this stock over decadalincrements. Scale samples used in this study were taken from theNortheast Peak of Georges Bank, and were restricted to individualscollected between February and May, a time interval when spawn-ing aggregations are usually present. Scale samples were sorted byyear-class; individuals from the 1963 and 1975 year-classes weretaken from multiple collections of age 5 fish made in 1968 and1980, respectively, while the 1985 year-class came from fish aged2–5 years collected over several years. Prior to the 1960s, aging ofthe scales was not recorded on the individual archived packages,consequently the 1958 sample represents multiple year-classes. Allsamples postdating 1985 also represent multiple year-classes.

Multiple temporally separated samples were obtained from eachof the following northwest Atlantic spawning sites during peakspawning times: Georges Bank, Nantucket Shoals, Browns Bank,and the Scotian Shelf. For comparison, single collections wereobtained from the Grand Banks and Norway (Fig. 1; Table 1). Finclips and muscle tissue were obtained from individual fish and pre-served in 95% ethanol for subsequent DNA extraction. Collectionwas provided by the combined efforts of the U.S. National MarineFisheries Service, the Canadian Department of Fisheries andOceans, and Professor Jarle Mork of Norway.

DNA extraction, amplification, and visualizationPublished protocols were followed for DNA extraction from

ethanol-preserved tissue samples and dried scale samples (Purcellet al. 1996). Haddock-specific dinucleotide microsatellite loci Mae-111, Mae-211, and Mae-249 were exploited in this study (Lage andKornfield 1999). Initial screening suggested that these loci mayprove useful for population discrimination due to high levels ofvariability and heterozygosity. Multiplex polymerase chain reac-tions (PCR) of all three loci were performed, following the pub-lished protocol for a Hybaid OMN-E thermal cycler. FluorescentPCR products were visualized on an ABI377 automated DNA se-quencer (Perkin Elmer). Fluorescent-peak data were analyzed us-ing the GeneScan (version 2.1) and Genotyper (version 2.1)software programs (Perkin Elmer).

A microsatellite locus originally developed for cod (Brooker etal. 1994) was also exploited. PCR fragments for locus Gmo-132were cloned using the PGEM-T kit (Promega Co.), following themanufacturer’s instructions. Multiple bands were sequenced in asingle direction and probed with a (CA)10 repeat. New haddock-specific primers were designed by moving in both primers at least4 base pairs (bp). Original Gmo-132 cod primer sequences are in-dicated with underlining, while new haddock primer sequences(Gmo-132.1) are indicated in bold: GG AAC CCA TTG GATTCA GGC TCC GTA C CA TGT AAC GGT CTG CAC ACTCAC AAT CTC GTT TTT TCT CTC (GT)15 GCG CTG ATTTGT TAT TGG CTC GTC C TT TCG.

PCR amplification and visualization of Gmo-132.1 was per-formed using [g -32P]dATP labeled reverse primer, electrophoreticseparation, and exposure to x-ray film (Kodak). The final concen-trations of the PCR reagents in a volume of 25mL were as follows:10 ng genomic DNA, 1× PCR buffer (pH 9.5; 10 mM KCl, 20 mMTris-HCl (pH 8.3), 10 mM (NH4)2SO4), 2 mM MgCl2, 200 mMeach dNTP, 1mM unlabelled forward primer, 0.5mM unlabelled re-verse primer, 0.5mM [g -32P]dATP labeled reverse primer, and0.75 U of Taq polymerase (Gibco BRL). PCR reactions were car-ried out in a PTC-100 programmable thermal cycler (MJ Research)as follows: an initial denaturation of 4 min at 94°C, followed by 35cycles of 94°C for 45 s, 55°C for 1 min, 72°C for 1 min, with afinal extension of 72°C for 10 min. Electrophoretic separation wasperformed on a 6.5% denaturing polyacrylamide gel electro-phoresed at 70 W. Gmo-132.1 produced crisp low-stutter products.Size was determined using a M13 control DNA sequence ladderfrom the Sequenanase kit (USB/Amersham Co.).

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Genetic analysisPopulations were tested for conformation to Hardy–Weinberg

expectations by the Markov chain method (Guo and Thomson1992), resampling 10 000 iterations per batch for 200 batches inGENEPOP 3.1c (Raymond and Rousset 1995); the null hypothesistested was the random union of gametes within a population. Allloci were tested for genotypic disequilibrium across the entire dataset, as well as for individual populations, using the Markov chainmethod, resampling 10 000 iterations per batch for 200 batches;the null hypothesis tested was that the genotypes at one locus areindependent from the genotypes at the other locus (within each in-dividual population and within the global population).

Population comparisons were tested for divergence of allelic andgenotypic distribution, in which the null hypothesis tested was thatthe distribution is identical across populations. At each geographiclocation in which multiple temporal samples were collected, exacttests for allelic and genotypic divergence were performed amongand between samples. When homogeneity was confirmed withinindividual geographic locations in the northwest Atlantic, the mul-tiple samples were then combined to form a single population sam-

ple. Every location was tested among and between each other forgeographic stock structuring. Comparisons among and between the1963, 1975, and 1985 Georges Bank year-classes were performed,as well as comparisons between the 1958 and 1990s mixed year-classes, to test for long-term genetic stability of this stock (seeDiscussion). We calculated an unbiased estimate of the value of alog-likelihood-based exact test by the Markov chain method(Goudet et al. 1996). To correct for simultaneous comparisons,standard Bonferroni corrections were applied, using a global sig-nificance level of 0.05 (Rice 1989).

Temporally separated Georges Bank samples were tested for dif-ferences in mean heterozygosity across all loci via ANOVA (a =0.05) and pairwiset tests (a = 0.05). Tests between the 1958 and1990s mixed year-class samples, as well as between and among the1963, 1975, and 1985 year-class samples, were performed.

Different genetic-distance measures perform better under differentconditions. Some measures are more appropriate for hypervariableloci and follow different mutational assumptions, thus, data fromthese loci need to be carefully evaluated (Goldstein et al. 1995;Ruzzante 1998; Hedrick 1999). Sample size, number of loci, number

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984 Can. J. Fish. Aquat. Sci. Vol. 58, 2001

Fig. 1. Map of the northwest Atlantic sampling regions. Broken lines indicate the 100-m isobath.



of alleles, and allelic-size range may all affect estimations of geneticdistances. For instance,dm2 (Goldstein et al. 1995), a genetic-distancemeasure developed specifically for microsatellite loci under the step-wise mutational model (SMM) of evolution, may be extremely sensi-tive to individual loci that contribute extreme values, even when thenumber of loci used to estimate the distance is >200 (Cooper et al.1999). Ruzzante (1998) showed thatdm2 and Dsw (Shriver et al.1995), a stepwise-weighted distance measure, may be biased atsmall sample sizes. In terms of bias and variance, it has been shownthatdm2 , Dsw, RST (Slatkin 1995), andFST (Wright 1951) may be thebest performers for microsatellite loci (Ruzzante 1998). Various mea-sures of population subdivision and genetic distance were calculated,includingdm2 , Dsw, Dc (Cavalli-Sforza and Edwards 1967),FST, andRST. Dsw anddm2 are distances based on SMM, whileDc is simplybased on differences in allele frequencies and is idependent of anymutational model. Estimates ofFST were generated following Weirand Cocherham (1984). Strict consensus trees were generated via theneighbor-joining method, with 1000 bootstrap samples for each mea-sure in PHYLIP 3.5c (Felsenstein 1993).

Results

Single-locus statisticsAllelic-size ranges, numbers of alleles, and observed and

expected heterozygosities (Ho and He, respectively) are pre-sented in Table 2. Size ranges, numbers of alleles, andheterozygosities for each temporal Georges Bank samplewere similar, except for the combined 1990s mixed year-class sample (N = 437), for which an increased number oftotal and unique alleles were observed at multiple loci (Ta-ble 3). The 1958 Georges Bank mixed year-class sample wasnot analyzed at locus Mae-111, as template quality andprimer specificity resulted in poor amplification of larger-sized alleles at this locus.

Tests of heterozygosity changeThere were no significant differences in mean observed

heterozygosities among temporally separated Georges Banksamples. Single factor ANOVA analysis between the 1958and 1990s mixed year-class samples (df = 1,a = 0.05,P =0.975), as well as among the 1963, 1975, and 1985 singleyear-class samples (df = 2,a = 0.05,P = 0.878) indicated nosignificant differences in mean heterozygosity values. Allpairwise t tests (1958 vs. 1990s,P = 0.905; 1963 vs. 1975,P = 0.484; 1975 vs. 1985,P = 0.847; 1963 vs. 1985,P =0.669) were not significant fora = 0.05. Heterozygosity testsbetween the 1963, 1975, and 1985 samples included all loci.Heterozygosity tests between the 1958 and 1990s mixedyear-class samples did not include locus Mae-111, owing topoor amplification in the 1958 population sample.

Exact tests of allelic and genotypic divergenceExact tests of genetic divergence were performed between

temporally separated mixed year-class samples at each indi-vidual spawning location. Homogeneity was observed foreach location at all loci, except between the Browns Bank1996 versus 1999 samples at Mae-249 (Pallelic = 0.010;Pgenotypic = 0.001). Temporally separated mixed year-classsamples for each spawning location were pooled in an effortto facilitate statistical analyses. Pairwise comparisons be-tween all pooled northwest Atlantic, Grand Banks, and Nor-way samples were tested for both allelic and genotypicdivergence. When Bonferroni corrections for 15 pairwisecomparisons were applied to measures of divergence (a =0.05, P < 0.003), all significance was lost, except at locusMae-249 for comparisons between Norway versus GeorgesBank, Browns Bank, Nantucket Shoals, and Scotian Shelf,and at locus Gmo-132.1 for the comparison between Nor-way versus Browns Bank.

Exact tests of allelic divergence among all pooled mixedyear-class samples (Table 4), including Georges Bank, BrownsBank, Scotian Shelf, Nantucket Shoals, Grand Banks, and Nor-way, indicate significance (P < 0.0167) for Gmo-132.1, Mae-249, and overall. Tests of allelic divergence among pooledmixed year-class samples excluding Norway indicate signifi-cance for Gmo-132.1 and overall. Tests of allelic divergencefor all pooled mixed year-class samples excluding Norway andGrand Banks indicate significance for Gmo-132.1 and overall.

Exact tests of allelic divergence (Table 4) were performedamong and between single year-class samples, as well as be-tween the mixed year-class samples from Georges Bank.Significance was observed among all single year-class sam-ples (P < 0.025) for Mae-111 and overall. Pairwise compari-sons of single year-class samples showed significance after

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Lage et al. 985

Sampling location Year-class N S N HWE

Georges Bank 1963 113 113 Mae-1111975 105 105 None1985 114 114 None1958 mixed 105 105 None1996 mixed 120 437 Mae-2491997 mixed 1281998 mixed 901999 mixed 99

Browns Bank 1996 mixed 99 229 None1999 mixed 130

Nantucket Shoals 1996 mixed 104 184 Mae-1111997 mixed 80

Scotian Shelf 1995 mixed 90 150 None1997 mixed 60

Grand Banks 1996 mixed 28 28 NoneNorway 1992 mixed 91 91 None

Note: N = the number of individuals;S N = the number of pooledindividuals; in the column headed HWE (Hardy–Weinberg equilibrium),locus names are given for deviations ofS N after Bonferroni correctionfor six populations (mixed year-classes) and three temporal samples(single year-classes). Sampling location and latitude and longitude rangesare as follows: Georges Bank (41°52¢ ± 19¢N, 66°36¢ ± 46¢W), BrownsBank (42°44¢ ± 9 ¢N, 66°3¢ ± 1 ¢W), Nantucket Shoals (40°45¢ ± 24¢N,69°9¢ ± 30¢W), Scotian Shelf (43°11¢ ± 19¢N, 62°29¢ ± 42¢W), andGrand Banks (46°3¢ ± 1°N, 56°22¢ ± 1°39¢W).

Table 1. Sample information and Hardy–Weinberg equilibria.

Locus N n Range (bp) Ho He

Gmo-132.1 1100 16 96–132 0.779 0.778Mae-111 1037 65 193–411 0.902 0.945Mae-211 1365 47 93–202 0.966 0.960Mae-249 1385 70 106–267 0.955 0.950

Note: N = the total number of individuals genotyped;n = the totalnumber of alleles observed; range (bp) = the allelic-size range in basepairs; Ho = heterozygosity observed;He = heterozygosity expected.

Table 2. Single-locus statistics.



Bonferroni correction (P < 0.0167) at Mae-249 (1963 vs.1975) and Mae-111 (1963 vs. 1985 and 1975 vs. 1985). Sig-nificant (P < 0.025) allelic divergence was observed be-tween the 1990s pooled mixed year-class sample and the1958 mixed year-class sample at locus Mae-249.

Hardy–Weinberg equilibrium and linkagedisequilibrium

Pooled mixed year-class samples and individual singleyear-class samples were tested for comformation to Hardy–Weinberg expectations. When Bonferroni corrections formultiple tests were applied, no population sample was out ofHardy–Weinberg equilibrium (HWE) at more than one locus(Table 1). The pooled 1990s Nantucket Shoals sample andthe 1963 Georges Bank single year-class sample were out ofHWE at Mae-111. The pooled 1990s Georges Bank mixedyear-class was out of HWE at Mae-249. Nonconformity wasdue to minor heterozygote deficiencies for the 1990s Nan-tucket Shoals sample at Mae-111 (He = 0.947;Ho = 0.932)and for the 1990s Georges Bank sample at Mae-249 (He =0.947; Ho = 0.939). A more pronounced heterozygote defi-ciency was observed for the 1963 Georges Bank year-classsample at Mae-111 (He = 0.929; Ho = 0.753). Populationsamples that generally conform to expectations of randommating but show a lack of HWE at a single locus may indi-cate some amount of sampling bias, drift, or admixture. Apossible explanation of observed heterozygote deficiency

may be sample admixture; however, this is unlikely, as onewould expect to see similar results at all loci. A more likelyexplanation is that there is a certain amount of scoring errorand (or) null alleles present at these hypervariable loci, espe-cially for the 1963 Georges Bank year-class sample, that hadroutinely difficult DNA amplification at locus Mae-111. Allother population samples were in HWE at all loci.

Tests of genotypic linkage disequilibrium were performedfor all population samples, as well as globally. The global testof linkage disequilibrium between Gmo-132.1 and Mae-249was highly significant (P < 0.001), most likely owing to theanalysis of a single mixture composed of multiple reproduc-tively isolated populations with differing gametic frequencies.After Bonferroni correction, significance was observed onlybetween Gmo-132.1 and Mae-249 for the 1996 mixed year-class Nantucket Shoals sample (P < 0.0001). When pooledwith the 1997 mixed year-class Nantucket Shoals sample, sig-nificance was lost. This suggests that the significant resultsfrom the 1996 Nantucket Shoals sample may be due to driftor sampling bias. No other significance was observed either ata global or a population scale.

FST and RSTFST and RST values were generated for all pairwise com-

parisons between spatially separated samples in the NorthAtlantic. FST- and RST-based strict consensus trees indicatethe clustering of Georges Bank, Browns Bank, and Scotian

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Gmo-132.1 Mae-111 Mae-211 Mae-249

Year N n n* Ho n n* Ho n n* Ho n n* Ho

1958 105 10 0 0.784 — — — 31 0 0.920 46 4 0.9681963 113 12 2 0.859 23 0 0.753 34 0 0.971 41 2 0.9441975 105 10 0 0.806 20 1 0.865 38 4 0.987 40 0 0.9771985 114 11 1 0.737 23 2 1.000 32 1 0.977 39 0 0.9581990s 437 10 0 0.769 49 17 0.864 41 0 0.956 59 8 0.939

Note: N = sample size;n = total number of alleles;n* = number of unique alleles observed;Ho = heterozygosity observed. The 1958 mixed year-classsample did not have scorable amplification at locus Mae-111.

Table 3. Genetic variation of Georges Bank haddock stock.

(A) Exact tests of allelic differentiation among spatially separated samples;P values significant afterBonferroni correction (a = 0.05,P < 0.0167) are indicated in bold.

All spatial samplesAll spatial samplesexcluding Norway

All spatial samples excludingNorway and the Grand Banks

Gmo-132.1 0.0016 0.0106 0.0113Mae-111 0.6086 0.7575 0.6067Mae-211 0.0598 0.0883 0.2239Mae-249 0.0000 0.0579 0.2156All Loci 0.0000 0.0096 0.0422(B) Exact tests of allelic differentiation among temporally separated Georges Bank samples;P values signifi-

cant after Bonferroni correction (a = 0.05,P < 0.025) are indicated in bold.Georges Bank single

year-class comparison

Georges Bank mixed

year-class comparisonGmo-132.1 0.1770 0.9311Mae-111 0.0016 —Mae-211 0.0694 0.3547Mae-249 0.0362 0.0173All Loci 0.0004 0.1117

Table 4. Exact tests of allelic differentiation among North Atlantic haddock stocks.



Shelf populations to the exclusion of the Nantucket Shoalspopulation, with bootstrap support of 77 and 98%, respec-tively (Fig. 2). The Norway and Grand Banks populationsclustered separately from the rest of the northwest Atlanticsamples, with 71 and 65% bootstrap support, respectively.Values ofRST were generally higher than values ofFST, in-dicating that variation in allele size among samples may bemore indicative of population structuring than differencesamong heterozygosities alone for the loci examined. Al-though lowFST values are expected when examining hyper-variable loci, this does not preclude this measure as anestimate of population structuring. Higher values ofRST in-dicate that population structure may be underestimated whenusing onlyFST.

Dsw, Dc, and dm2

Genetic-distance measures were employed between allgeographically separated samples in the North Atlantic.Strict consensus trees based onDsw, Dc, anddm2 distanceswere concordant with each other and with theFST- and RST-based trees, supporting the clustering of Georges Bank,Browns Bank, and Scotian Shelf populations to the exclu-sion of the Nantucket Shoals population, with bootstrap sup-port of 71, 86, and 81% for theDsw-, Dc-, anddm2-basedtrees, respectively (Fig. 2). The Norway and Grand Banks pop-ulations clustered away from the rest of the northwest Atlanticsamples, with 94, 86, and 76% bootstrap support for theDsw-,Dc-, and dm2-based trees, respectively. Regardless ofmutational-model dependency, all distance measures producedconcordant trees with significant bootstrap values.

Discussion

In the last 30 years, the use of molecular markers in fish-eries science has become common (Shaklee and Bentzen1998). High dispersive capabilities of many marine fish areoften correlated with low levels of population divergenceand slight genetic divergence over vast areas (Graves 1998).This may be particularly true when the species is character-ized by high fecundity, large population size, and potentiallylong-distance egg and larval dispersal. However, exampleshave been found where dispersal alone may not be corre-lated with high levels of gene flow (Palumbi 1994). Whenecological and evolutionary processes are responsible forstock structuring, it is necessary to incorporate them intostrategies designed to manage commercially exploited spe-cies (Avise 1998).

Temporal evaluation of the Georges Bank populationGeorges Bank, a large submerged offshore bank located

along the U.S. and Canadian coasts, once supported an in-credibly rich fishery. Georges Bank is shallow and highlyproductive, supporting a large fish biomass. The high pro-ductivity and tightly bound system energetics of GeorgesBank tend to result in relatively stable levels of overallbiomass and total fish production, although major shifts inspecies composition routinely occur (Fogarty and Murawski1998). The largest spawning aggregation of haddock onGeorges Bank is found on the Northeast Peak. The gravel re-gion on the Northeast Peak is an important habitat for theearly demersal phase of haddock and may represent a limit-

ing resource for this stock (Lough and Bolz 1989; Langtonet al. 1996). Georges Bank maintains its own circulationpattern in a slow clockwise gyre that may act as a transpor-tation and retention mechanism for planktonic eggs andlarvae (Smith and Morse 1984; Lough and Bolz 1989;GLOBEC 1992). This subsurface clockwise circulationaround Georges Bank exists throughout the year, howeverthe flow is strongest in late summer through early fall and isweakest and most variable in winter (Butman and Beardsley1987). Haddock larvae are advected away from the spawn-ing grounds and, at age 2, the haddock migrate back to thespawning areas where they tend to remain. Long-term moni-toring of haddock stocks has revealed dramatic fluctuationsin recruitment on Georges Bank (Clark et al. 1982).

The Georges Bank stock is thought to be distinct from thenearby Gulf of Maine and Canadian stocks. Evidence forstock divergence is based on a variety of tagging, meristic,and life-history studies (Schroeder 1942; Clark and Vladykov1960; Bowen 1987). Tagging studies indicate that adult had-dock are not highly mobile and do not tend to migrate largedistances (Schroeder 1942; Halliday and McCracken 1970).

Many approaches have been used to evaluate the temporalstability of populations of marine fish with overlapping gen-erations. Our goal was to examine long-term temporal stabil-ity of the Georges Bank population. In particular, we wereinterested in gross as well as minor changes in allelic-frequency distributions and diversities that might be conse-quential to commercial overharvesting or the combinedeffects of genetic drift and admixture. We examined this intwo ways. First, we examined individual year-classes thatwere separated by decadal increments. Second, we examinedmixed year-class samples that were temporally separated byroughly 40 years. Sampling adults from two successive yearsat a particular location does not necessarily result in two dis-tinct temporal samples. For instance, when generations over-lap and individuals spawn in multiple years, it is difficult tocompare temporal samples separated by only short periodsof time relative to the life-span of the organism. This isbecause samples may consist of the same proportions of in-

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Fig. 2. Strict consensus neighbor-joining trees. Numbers indicatepercent bootstrap support of each branch node fordm2 , Dsw, Dc,RST, andFST (top to bottom, respectively).



dividuals from particular year-classes and, thus, it can beargued that they are not temporally distinct. To compare un-ambiguously temporally separated samples, we examinedmixed year-class samples that were separated by roughly 40years. We examined individual year-classes separated by rel-atively long periods of time (i.e., decadal periods), to evalu-ate the temporal stability of resulting cohorts derived fromindividual spawning events on Georges Bank. Given thatonly a subsection of potential parents contribute gametes tothe gene pool each year, we expected that fluctuations in thegenetic composition of temporal samples would be mostpronounced among individual year-class samples rather thanamong mixed year-class samples. Although single year-classsamples have analytical limitations, they have been ex-ploited in many temporal genetic studies of population struc-ture in marine fish (Bentzen et al. 1996; Ruzzante et al.1996b). Ruzzante (1998) determined that sample sizes of50–100 individuals are necessary for such analyses.

Genetic analysis of four microsatellite loci indicates that,although there have been dramatic fluctuations in recruit-ment and spawning-stock biomass over time, there has beenan overall maintenance of genetic variability in this stock, asindicated by only small changes in both heterozygosities andallelic diversities (Tables 3 and 4). If these loci are represen-tative of the overall genetic background of this stock, itwould seem that little reduction in variability has occurred,even though substantial reductions in population sizes haverepeatedly occurred through history. This may be fostered bythis species’ large population sizes, albeit reduced fromhistorical counts, and extremely high fecundity—a 2-kgfemale may produce more than 800 000 eggs (Bigelow andSchroeder 1953). At its lowest, the Georges Bank haddockpopulation numbered in the millions, not a level associatedwith genetic drift or loss of diversity. Measures of diver-gence suggest that gene frequencies of Georges Bank year-classes have changed from 1963 to 1985. Results suggestthat gene frequencies of the mixed year-class Georges Bankpopulation have changed between 1958 and the 1990s, al-though not as strongly as individual cohorts.

Unique alleles were observed at every temporal sample atone or more loci (Table 3). Most likely this is a samplingartifact of hypervariable loci rather than an indicator of tem-poral heterogeneity in the Georges Bank stock. Allelic fre-quencies at each locus examined in this study follow aroughly normal distribution, in which alleles closer to themean size have increased frequencies. All unique and rarealleles are represented near the edges of their size ranges. Agreatly increased number of total alleles and unique alleleswere observed at the 1990s mixed year-class sample; this ex-pected result is most certainly due to it’s increased samplesize (roughly four times) compared with the other GeorgesBank samples, although temporal changes in allele frequen-cies may also play a minor role.

The results presented here are concordant with a previousgenetic study (Purcell et al. 1996) that revealed significantheterogeneity in the frequencies of mtDNA control regionhaplotypes between decadally separated cohorts. Purcell etal. (1996) suggested that the haddock population spawningon Georges Bank may not be genetically discrete and that,with respect to Atlantic haddock, Georges Bank may not be

viewed as a closed system. Albeit unlikely, this may be dueto some level of gene flow associated with migration of re-productive adults. More likely, this may be due to episodicinfluxes of planktonic eggs or larvae from other spawningaggregations (Cohen et al. 1991; Polacheck et al. 1992), tofluctuations in the effective number of spawners contribut-ing to a single spawning and subsequent recruitment event(Hedgecock 1994), or to other mechanisms of drift. Giventhe great fecundity of haddock, it is possible that a relativelysmall number of highly successful females could give rise toan entire year-class; however, this is unlikely as one wouldexpect to observe significant reductions in genetic variationwithin the stock over time and within individual cohortscompared with the population as a whole. The combined ef-fects of density-independent influences on the survival oflarval haddock (Fogarty 1993), the fine-scale spatial andtemporal patchiness of shelf ecosystems (Leising and Franks1999), and hydrographic effects on egg and larval distribu-tion (Frank et al. 1989; Page and Frank 1989; Page et al.1989) may result in a stochastic pattern of reproductive suc-cess. Disproportionate contributions to the gene poolthrough demographic stochasticity or differential survival oflarvae or egg masses (Hedgecock 1994; Ruzzante et al.1996b) may have similar genetic consequences: it maychange a population’s genetic structuring so that populationsor cohorts may appear to be heterogeneous over time. In the-ory, a single dominant year-class of Atlantic haddock maybe able to support an entire commercial fishery. High fecun-dity and prolonged spawning events (Page and Frank 1989;Hedgecock 1994) may be an evolutionary response to varia-tions in oceanographic conditions and food resources at aparticular spawning area, to increase the probability of larvalsuccess and the maintenance of genetic variation.

Spatial stock structuring of haddock in the northwestAtlantic

Previous genetic work using mitochondrial markers didnot detect a significant difference between the Georges Bankstock and stocks to the north (Zwanenburg et al. 1992).However, that study did detect a cline in frequency fromnorth to south, indicating that stock structure may exist, butthat mitochondrial markers may not be sensitive enough todetect it with statistical significance. Other mitochondrialstudies suggest that the Georges Bank stock may not be agenetically closed system with regard to haddock popula-tions (Purcell et al. 1996). Gadid species such as cod andhaddock share similar reproductive biologies, life histories,and ecological constraints that may result in similar patternsof population genetic structuring. Recent studies usingmicrosatellite markers have demonstrated a significant dif-ference between cod on Georges Bank and cod on the Sco-tian Shelf (Ruzzante et al. 1998). Interestingly, the highestlevel of significance was reported for locus Gmo-132, thecod-specific locus from which the haddock-specific primersused in this study were redesigned.

Exact tests of allelic divergence among geographicallyseparated samples showed overall significance (P < 0.0167)when all samples were analyzed and when the Norwegiansample was excluded. When both the Norwegian and GrandBanks samples were excluded, significance (P < 0.05) was

© 2001 NRC Canada




observed—however it was lost after Bonferroni correction.Most of this significance comes from Gmo-132.1 and Mae-249. Pairwise comparisons of all geographically separatedsamples showed Bonferroni-corrected significant differences(P < 0.003) only for Norway versus Georges Bank, BrownsBank, Nantucket Shoals, and Scotian Shelf comparisons atGmo-132.1, and for Norway versus Browns Bank compari-sons at Mae-249.

Measures ofFST, RST, Dsw, Dc, anddm2 support the Fisher’sexact test results of stock divergence. Measures ofFST weregenerally very low, indicating that this metric may not be ap-propriate for loci with such high heterozygosities and varia-tion (Hedrick 1999). Measures ofRST were generally higherthan those ofFST, although similar in result, indicating thatRST may be a more reliable measure for such loci or simplythat levels of population structure may be underestimatedwhen usingFST alone. All strict consensus trees were gener-ally concordant with each other: all trees supported the clus-tering of Georges Bank, Browns Bank, and Scotian Shelfpopulations to the exclusion of the Nantucket Shoals popula-tion with high bootstrap support. The Norway and GrandBanks populations clustered away from the rest of the north-west Atlantic samples with high bootstrap support.

These results indicate that the Georges Bank, BrownsBank, Scotian Shelf, and Nantucket Shoals haddock popula-tions are genetically distinct from those populations to thenorth (i.e., the Grand Banks) and in the eastern Atlantic (i.e.,Norway). Results also indicate that Nantucket Shoals had-dock are genetically distinct from Georges Bank, BrownsBank, and Scotian Shelf haddock. Episodic fluxes of eggsand larvae from the Scotian Shelf and Browns Bank ontoGeorges Bank may act to homogenize the genetic structureof these three spawning regions (Cohen et al. 1991;Polacheck et al. 1992). Once on Georges Bank, planktoniceggs and larvae may be entrained and would then be trans-ported to gravel settlement sites (Smith and Morse 1984;GLOBEC 1992). There is a possibility that adult haddockmay move between these regions; however, it is extremelyunlikely, as these areas are separated by deep channels thatare regarded as significant barriers to migration (Bigelowand Schroeder 1953).

The Nantucket Shoals population may be genetically dis-tinct, owing to isolation from entrainment in the GeorgesBank gyre, as well as limited movement of adults betweenNantucket Shoals and other regions. Eggs and larvaespawned on Nantucket Shoals most likely do not enter thisgyre system; thus, they do not settle on Georges Bank butrather on the shoals itself or are transported by prevailingcirculation to the southwest (Fogarty and Murawski 1998).Tagging studies suggest that there is very little mixing be-tween Georges Bank and nearby areas such as NantucketShoals and the Scotian Shelf (Schroeder 1942; Halliday andMcCracken 1970). Haddock from the Gulf of Maine maymigrate seasonally along the coast to Nantucket Shoalswhere there is no barrier to movement. If this is true, theNantucket Shoals sample that we analyzed may actually berepresentative of a Gulf of Maine – Nantucket Shoals mixedpopulation. Additional analyses are needed to evaluate thehypothesis that Nantucket Shoals haddock are geneticallydistinct from those spawning along the coast of the Gulf of

Maine. Our research suggests that the haddock spawning onNantucket Shoals are genetically differentiated from had-dock spawing in other regions of the northwest Atlantic andshould be managed as such.

Acknowledgements

Several primers were generously donated by the DalhousieUniversity Marine Gene Probe Laboratory for use in initialscreening. We thank the captains and crew of the R/VNeedlerand R/VAlbatross IV, as well as the scientists from the Cana-dian Department of Fisheries and Oceans and the U.S. Na-tional Marine Fisheries Service (NMFS). In particular, wethank Nina Shepard, John Galbraith, and Dan DenDanto forassistance in obtaining samples. We also thank Frank Almeidaand staff at the Northeast Fisheries Science Center, NMFS,who generously assisted our examination of archived mate-rial. This work was funded in part by the University of Maineand the University of New Hampshire Sea Grant Program(NA56RG0159 and NA76RG0084).

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