a numerical model of the dispersion of blue whiting larvae, micromesistiuspoutassou (risso), in the...

A numerical model of the dispersion of blue whiting larvae,Micromesistius poutassou (Risso), in the eastern NorthAtlantic

J. BARTSCH1 AND S. COOMBS2

1 Biologische Anstalt Helgoland, Notkestrasse 31,22607 Hamburg, Germany2 Plymouth Marine Laboratory, Prospect Place, The Hoe,Plymouth PL1 3DH, United Kingdom

ABSTRACT

A numerical circulation and transport model systemwas used to simulate the dispersion of larvae of bluewhiting, Micromesistius poutassou (Risso) in the easternNorth Atlantic. The area of the model extends fromthe northern Bay of Biscay to the Norwegian Sea andcovers the shelf-edge and adjacent waters at a hori-zontal resolution of around 20 km in 16 vertical layers.Larval input data were based on the long-term meandistribution, abundance and seasonal occurrence oflarvae, derived from historical information. The cir-culation model was run using tidal forcing and cli-matological density ®elds as well as bothclimatological meteorological forcing and actual six-hourly wind stress ®elds for 1994 and 1995. Transportfrom the main spawning areas to the west of theBritish Isles and north of Porcupine Bank was associ-ated with currents along the shelf-edge and in theRockall Trough. Tracers were either dispersed to thenorth and north-east along the shelf-edge, extendinginto the northern North Sea and Norwegian Sea, orwere retained in the Rockall Gyre and over PorcupineBank. A less intense southerly ¯ow from PorcupineBank was observed both under climatological condi-tions and in the 1995 simulation, when winds weremore variable than in 1994. The results based on the1995 meteorological conditions showed the most ex-treme retention of tracers in the Rockall Trough/shelf-edge area west of Scotland and a low penetration oftracers onto the shelf. These results are discussed inrelation to the observed distribution of 0-group juve-niles and to indices of year-class strength ± in par-

ticular, in relation to the 1995 year class, which is thehighest year-class estimate of blue whiting on record.

Key words: blue whiting larvae, Micromesistiuspoutassou, recruitment, shelf-edge current, transportmodel

INTRODUCTION

The SEFOS project (Shelf-Edge Fisheries andOceanography Studies 1994±96) is a multinationalinvestigation of the Shelf-Edge Current (SEC) ex-tending from Portugal, via Biscay and the west of theBritish Isles, to the Norwegian Sea. An importantfeature of the work was the formulation of a numericalcirculation and transport model system of the samearea. Biological studies of the ®sh stocks associatedwith the shelf-edge were also included in the study,with particular emphasis on their interaction with theSEC and on how changes in the current might affectdifferent aspects of their life history.

The egg and larval stages of ®sh species that spawnat the shelf-edge were of particular interest becausethese planktonic stages are especially vulnerable toadvection to areas of unsuitable larval food supply/increased predation risk or to subsequent inappropriatenursery grounds; numerous studies having indicatedthat much of the mortality regulating future year-classstrength takes place during these early developmentalstages (Houde, 1987).

Blue whiting, Micromesistius poutassou (Risso), isone of the major ®sh stocks that spawn along the edgeof the European continental shelf. The spawning stocksize is around 4.5 million tonnes (Monstad et al.,1996a) and there is a long spawning season and anextensive spatial distribution, from at least February/March in Biscay to June at the Faeroes (Bailey, 1982).The scale of these factors creates excessive logisticaldemands in order to follow the evolution of the initialspawning distribution. It is in this context that atransport model is a useful approach to investigatingthe effects of actual or long-term climatological windpatterns on the dispersion of the planktonic stages.

The SEC in the SEFOS study area is part of thepoleward eastern boundary current of the north-east

Received 29 January 1997

Revised version accepted 20 June 1997

Correspondence: J. Bartsch, Biologische Anstalt Helgoland,

Notkestrasse 31, 22607 Hamburg, Germany

FISHERIES OCEANOGRAPHY Fish. Oceanogr. 6:3, 141±154, 1997

Ó 1997 Blackwell Science Ltd. 141

Atlantic which has been observed along the shelf-edgefrom north-west Africa to Norway. Continuity of theslope current along the entire length is, as yet, notestablished, but observations indicate a year-roundpoleward ¯ow from 47.5°N northwards, closely fol-lowing the depth contours (Huthnance and Gould,1989). Large increases in volume transport north ofthe Wyville-Thomson Ridge suggest additional en-trainment of Atlantic water from the west into theboundary ¯ow. Current speeds range from 3 to30 cm s)1, with speeds greater than 10 cm s)1 usuallyoccurring north of 57°N. The core of the slope currentis characterized by warm, saline water which, off thewestern edge of Porcupine Bank, is found at depths of200±350 m with a lateral extent of generally 20±50 km (Mohn and Bartsch, 1996). Core depth varieswith latitude, becoming shallower towards the north,while both current speed and core width are subject toshort-term and seasonal variability. In the more su-per®cial layers above the SEC, water mass transport isstrongly in¯uenced by the local wind ®eld and Ekmantransport dynamics, which, at least for the area ofPorcupine Bank and Porcupine Seabight, has includedobservations of both generally northwards, but also ofsoutherly ¯ow (Mohn and Bartsch, unpublished data).

A preliminary version of the present modellingstudy is given in Bartsch and Coombs (1996). At thesame ICES meeting, Svendsen et al. (1996) described asimilar exercise to study the drift of blue whiting lar-vae, but from a slightly different modelling perspectiveand using alternative input data. Essentially, the twostudies produced comparable results, the main differ-ence being one of emphasis, where Svendsen et al.(1996) concentrated more on aspects of longer timeseries, whereas the work of Bartsch and Coombs(1996) related to results for two speci®c years.

Similar modelling work has also been carried out instudies of a number of other ®sh species, for example,among others, on walleye pollock, Theragra chalco-gramma, in the Gulf of Alaska (Hermann et al., 1996)and on herring, Clupea harengus, in the North Sea(Bartsch, 1993). The drift study on walleye pollockinvestigated interannual differences in modelled larvalconcentrations and the effects of large-scale atmo-spheric pressure patterns on these distributions. Re-sults showed that the broad-scale features of themodelled and observed larval distributions were re-lated to meteorological conditions (Hermann et al.,1996). Using a similar model system to that ofthe present paper, Bartsch (1993) compared simu-lated tracer distributions with observed sequentialdistributions of herring larvae and showed the pre-dictive hindcast ability of the transport model.

MATERIALS AND METHODS

The circulation and transport models

A three-dimensional, non-linear, baroclinic numericalmodel is used to simulate the circulation of the NorthSea, the shelf-edge area and adjacent oceanic regionsof the eastern North Atlantic. The circulation modelis based on HAMSOM (HAMburg Shelf OceanModel) which was developed at the Institut fuÈrMeereskunde, Hamburg and transferred to the north-ern SEFOS area. Details of the model have beenpublished by Backhaus (1985).

The model area extends from 45°N to 64°N andfrom 25°W to 14°E (Fig. 1). The horizontal grid size is12¢ of latitude (22.2 km) and 20¢ of longitude (21.2 kmat 55°N). Vertical resolution is to a maximum of 16layers, the layer thicknesses ranging from 10 m to 40 min the upper 100 m and increasing progressively in thedeeper layers to a maximum depth of 5000 m. Themodel is forced by the M2 tide and either six-hourlywind stress and air pressure ®elds from ECMWF (Eu-ropean Centre for Medium-Range Weather Forecast-ing) or mean monthly climate ®elds (Backhaus et al.,1985), as well as monthly climatological density ®eldswhich are treated prognostically but are relaxed to-wards the climatological monthly mean.

The time step of the circulation model is 20 min-utes. Owing to the high data-storage requirements, thecurrent data, as well as the variance of the current,were output only on a daily basis, i.e. the currents wereintegrated over two M2 tidal cycles. The daily three-dimensional current and variance ®elds serve as inputto the transport model. A schematic diagram of themodel system is given in Fig. 2.

In the transport model, the simulations of the driftroutes are performed by means of tracers, in essence`marked' water particles representing the ®sh larvae,which are introduced into the model area and pursuedin time and space domains. A simple methodwhich was used for simulation of the transport of thetracers was the Monte-Carlo method (Bork and Maier-Reimer, 1978). It is assumed that the current ®eld canbe split into a large-scale mean current (u) and asmall-scale random ¯uctuation (u¢), i.e. U � u� u0.The small-scale ¯uctuations are parameterized usingthe current variance (Backhaus, 1989; Bartsch andKnust, 1994). Thus, during each time-step, the tracersexperience a directional transport by the mean current(advection) as well as a random transport, in bothmagnitude and direction, by the small-scale ¯uctua-tions (diffusion).

The boundary conditions in the transport modelprescribe a no-¯ux condition at closed boundaries,

142 J. Bartsch and S. Coombs

Ó 1997 Blackwell Science Ltd., Fish. Oceanogr., 6, 141±154.

whereas the tracers may leave the model area at openboundaries. The model area, grid size and the verticalresolution are in accordance with that of the circula-tion model, while the time step of the transport modelis 3 hours.

Spawning area, larval abundance and time of spawning

There have been no wide-scale synoptic surveys ofblue whiting egg or larval distributions, thus it wasnecessary to collate all published information to gen-erate the required input data on time of spawning andlarval distribution and abundance. Bailey (1982) pro-duced a qualitative summary of spawning distributionand seasonal occurrence; many of the same sources asused in his synopsis have been used here, together withmore recent additions.

One of the main sources of information on larvaldistribution is the Continuous Plankton Recorder(CPR) survey, results from which have been presentedby Bainbridge and Cooper (1973), Coombs (1979,1981) and Coombs and Pipe (1978, 1981). CPRsampling is at a single depth (a nominal 10 m); use ofthese data thus required conversion to the more usualnumbers m)2 by reference to the vertical distributionof the larvae (Coombs et al., 1981 and more recent un-published data).

Other signi®cant information on distribution andseasonal occurrence is given by Bailey (1974) for eggsand larvae in the Rockall area and west of Scotland,and Arbault and Boutin (1968, 1969) for the Bay ofBiscay. A number of Russian contributions with rather

Figure 1. Model area and bathymetry showing the 100 m, 200 m, 500 m, 1000 m and 2000 m depth contours(WTR, Wyville-Thomson Ridge).

Figure 2. Schematic diagram of the model system.


Blue whiting transport model 143

sparse station coverage, but having good annual con-tinuity from 1983 to 1993, were used to add infor-mation on larval occurrence west of the British Isles,particularly over the deeper and more distant areasfrom the shelf-edge (Belikov et al., 1993 and earlierpapers cited therein). More recent contributions, aspart of the SEFOS programme, have included detailedsampling around Porcupine Bank and surrounding ar-eas (Monstad et al., 1994, 1995; Kloppmann et al.,1996; McFadzen and Cook, 1996).

The overall chart of spawning distribution, i.e. themodel input on day zero, was based primarily on datafrom the above sources, using contour package inter-polation and averaging routines where appropriate.The more limited information contained in a numberof subsidiary publications was used to make small localadjustments. Essentially, this composite distribution ismore coherent and covers a wider spawning area thanlikely to be encountered in any particular year. The®nal data were represented as numbers m)2 allocatedto logarithmic categories of 1±10, 10±100 and 100±1000 m)2 by grid rectangle of the model resolution.

Because there is negligible information available onthe geographical distribution and abundance of eggs ofblue whiting, the initial spawning distribution wasbased solely on the distribution of the larvae. Theduration of development for blue whiting eggs is in theregion of 4±5 days (Coombs and Hiby, 1979), whereasthe transport model was run for up to 120 days; thusthe embryonic period represents only a relatively smallproportion of the modelled time period.

Based primarily on the sources quoted above, theaverage seasonal time of spawning in each modelrectangle was calculated in a similar way as for thespatial distribution of spawning, a 10-day discrimina-tion in timing being employed. The average time ofpeak spawning was progressively later from south tonorth, this being from the beginning of March in northBiscay, late March/early April at Porcupine, mid-Aprilwest of Scotland and mid-May at the Faeroes.

The model simulations were run for up to 120 daysfrom spawning. At that age, postlarvae would be in theregion of 15 cm in length (Bailey, 1982) and wouldhave developed signi®cant locomotory ability. Whilethe simulations do not take account of this transferfrom planktonic to nektonic habit, they are intendedto give an indication of the most extended period ofdrift likely to be encountered.

Vertical distribution

A simpli®ed scheme based on historical and recent ®elddata on the vertical distribution of blue whiting larvaealong the shelf-edge was used in the transport model.

Blue whiting spawn at depths of around 200±400 mand, after hatching, there is an ontogenetic movementof the larvae towards the surface such that by lengths>5 mm (from approximately one week after hatching)they are concentrated in the upper 60 m of the watercolumn (Coombs et al., 1981 and more recent unpub-lished data). Because there is no clear evidence of dielvertical migration (Hillgruber et al., 1995; Coombs,unpublished data), the tracers representative of bluewhiting larvae were given a random migration withinthe upper 60 m of the water column, i.e. spending anequal amount of time in the top four model layers be-tween 0 and 60 m and being subjected to the combinedeffects of the currents in these model layers. Tracersthat went deeper than 60 m were reintroduced at arandom depth in the 0±60 m layer at the next time step.

Tracer simulations

The initial larval distribution and abundance, as out-lined above, provides the starting conditions for thethree tracer dispersion scenarios examined. Larvalabundance ranges over three orders of magnitude, withthe number of tracers per model grid box being takenas proportional to these values. In the absence of anyinformation on differential larval mortality betweenareas, which would consequently affect the tracerdistributions, no mortality was considered in thetransport model; the abundance of tracers thus re-mained constant except for some loss through themodel boundaries. As spawning progresses in timefrom south to north, the tracers are released into themodel domain at the appropriate spawning time.

Three simulation scenarios were carried out forperiods of up to 120 days:· Scenario 1: Climatological, using mean monthly

meteorological ®elds (1955±82);· Scenario 2: 1994, using actual meteorological ®elds

from ECMWF for that year;· Scenario 3: 1995, using actual meteorological ®elds

from ECMWF for that year.The transport model in the climatological scenariorelies on currents simulated using monthly averagewind stress for input to the circulation model. It thuslacks the effect of six-hourly meteorological variabili-ty, but does provide a useful reference point for com-parison with the other model runs.

It should be noted, that the resultant tracer distri-butions do not represent the situation for a speci®ccalendar date, but relate to an elapsed time after theirintroduction into the model domain, this varyingthroughout the model area, i.e. each tracer was fol-lowed for the relevant simulation period (60 or 120days) from its starting time (time of spawning in the



appropriate model grid box). The ®nal tracer distri-butions are thus the sum of all the individual tracertrajectories, irrespective of their particular ®nishingtimes. That is, the distribution maps show where onewould catch 60- or 120-day-old ®sh, irrespective of thedate when caught.

To elucidate the results of the different simulationscenarios, the model area was divided into 10 areas(Fig. 3) in which tracers were counted at speci®ctimes; these values then represent the ¯ux of tracersbetween areas.

Wind stress

A comparison of the wind data for 1994 and 1995 wasbased on averaged monthly winds at three selectedstation positions, central Porcupine Bank (52°30¢N,13°30¢W), north Rockall Trough (56°30¢N, 11°50¢W)and west of the Hebrides (57°54¢N, 08°30¢W). Be-cause no statistical differences were found betweenthese sets of data (Wilcoxon signed-rank tests,P > 0.01 for a comparison of the direction and mag-nitude of the wind, as well as overlapping standarddeviations of the magnitude and x- and y-componentsof wind stress), the data for Porcupine Bank are pre-sented as being representative of the wind ®eld for thePorcupine/Rockall areas.

The most notable difference between the two yearsis that during March and the ®rst half of April 1994:westerly winds were much stronger than during thesame period in 1995. Also, during the remainder of thetime period considered (March±August), winds weregenerally stronger during 1994 than during1995 (Table 1; Fig. 4).

An additional parameter, the index of stability (S),was also calculated as S � 100 � �W=w�, where W isthe average vectorial magnitude and w is the arith-metic magnitude of wind stress, i.e. the averagedmagnitude irrespective of direction; thus a unidirec-tional wind will yield a stability of 100% and a highlyvariable wind equally from all compass quadrants willgive an S-value of 0%.

The difference between the wind data (this beingessentially the only forcing function for the circulationmodel which varies between the different scenarios) for1994 and 1995, shows that in 1995, winds were morevariable in all months, except in May, than in 1994(Fig. 5). This variability is also seen in the persistence inwind direction; for example, in 1994 there were morepersistent westerlies and south-westerlies comparedwith the winds in 1995 (Table 1). Although 1995 stillhad a relatively high proportion of westerly and south-erly winds, as expected at these latitudes, it also hadrather more northerly winds than did 1994 (Table 1).

Figure 3. Areas used for monitoring the ¯ux of tracers.



RESULTS

Initial distribution

In the initial distribution, the majority of blue whitinglarvae (90.4%) are in area 6, which includes PorcupineBank, Rockall Bank and the Rockall Trough (Figs. 3and 6; Table 2). Only 2.1% of all larvae are foundover deep water west of Porcupine and Rockall(area 3), whereas 6.6% are in the southern tail of thedistribution adjacent to the shelf-edge (area 4) southof Porcupine Bank. Shelf areas < 200 m in depth (area5) are practically devoid of larvae in the initial dis-tribution (< 1%), the overall pattern clearly showingthe constraint of the 200 m depth contour to theeasterly extension of spawning at intermediate levelsof abundance (10±100 larvae m)2; Fig. 6).

Scenario 1 ± mean climatological regime

After 60 days of model simulation (Fig. 7), the co-herent initial distribution has become dispersed, al-though the original areas of high concentration canstill be discerned. A proportion of tracers has movedalong the shelf-edge and into the Norwegian Sea, andinto the northern North Sea via the Fair Isle currentand around the Shetland Islands; there has been acomplementary marked decrease in abundance oftracers in the Faeroe Shelf and Faeroe Bank areas.Relatively less change is observed in the distributionfrom Porcupine Bank to the south. In all areas, butparticularly west of Rockall Bank, the western fringesof the distribution have diminished in abundance.

The distribution after 120 days (Fig. 7) shows acontinuation of the trends outlined above. Highconcentrations of tracers remain in the eastern

Rockall Trough (around half the original numbers)owing to retention in the currents of the Rockall Gyre.More tracers have ventured along the shelf-edge andinto the northern North Sea (area 2) which nowcontains 13.9% of all tracers released. The easterlydrift and increased penetration of tracers along theentire western shelf (area 5) is also considerable (a netincrease of 27.6% of tracers ± Table 2). From Porcu-pine Bank, tracers have moved south-eastwards to-wards the Goban Spur into areas 4 and 5c (13.3% asopposed to 7.0% at the start). Only in the mostsoutherly area, the northern Bay of Biscay, havetracers shown any signi®cant dispersion away from theshelf-edge. Finally, 2% of the tracers have been lostfrom the model area, most of these through thenorthern model boundary, but also a smaller numberthrough the southern border.

Scenario 2 ± 1994 meteorological regime

After 60 days of forcing by the 1994 meteorologicalconditions, transport into the Norwegian Sea and theNorth Sea (areas 1 and 2) is super®cially similar tothat of the climatological scenario (Fig. 8; cf. Fig. 7),as is the retention in the main Rockall/Porcupinearea (area 6) and drift onto the western shelf (area 5;Table 2). Particular features of the 1994 simulation are

Figure 4. Wind stress at Porcupine Bank plotted as dailymagnitude and direction (top plot) together with north±south (sy ± middle plot) and east±west components (sx ±bottom plot) for (a) 1994 and (b) 1995; for clarity of pre-sentation the vector plots have been rotated 90° anticlock-wise so that east is vertical.

c

Table 1. Wind direction by month for 1994 and 1995 at Porcupine Bank as the percentage of observations by compassquadrant.

N NE E SE S SW W NW

March 1994 2.4 0.0 2.4 0.8 10.4 12.8 69.6 1.6March 1995 4.0 0.0 0.8 1.6 12.0 10.4 56.8 14.4

April 1994 10.7 14.1 6.6 2.5 10.7 9.9 33.9 11.6April 1995 25.6 1.7 14.9 3.3 17.4 12.4 18.2 6.6

May 1994 9.6 20.0 31.2 4.0 9.6 5.6 18.4 1.6May 1995 10.4 8.0 10.4 7.2 28.0 7.2 22.4 6.4

June 1994 6.6 0.0 0.8 2.5 22.3 19.0 42.1 6.6June 1995 19.8 11.6 19.8 1.7 9.9 5.0 25.6 6.6

July 1994 6.4 0.0 0.8 3.2 36.0 20.0 26.4 7.2July 1995 14.4 2.4 3.2 6.4 24.8 11.2 27.2 10.4

August 1994 16.1 9.7 8.1 3.2 12.1 8.9 37.1 4.8August 1995 12.1 8.1 11.3 2.4 29.0 7.3 25.0 4.8



the area of low tracer abundance in the centre of theRockall Trough, indicative of a large-scale gyre, andthe more complete separation of tracers north andsouth of Porcupine Bank. The southern tail of thedistribution in Biscay is also noticeably to the west anddetached from the 200 m depth contour.

After 120 days under the 1994 wind regime(Fig. 8), more tracers have drifted onto the shelf (7.5%more in area 5), particularly west of Scotland (area5a), compared with the climatological scenario, whilefewer have been retained in the main Rockall/Porcu-pine area (10.3% less in area 6; Table 2). The con-centrations of tracers in the Porcupine Seabight andGoban Spur areas, which extend southwards intoBiscay, remain distinct from the concentrations to thenorth of Porcupine Bank. Tracer numbers in theNorwegian Sea and the North Sea are similar to thosein the climatological scenario, although slightly moretracers have been lost to the system (2% more), mostlythrough the northern boundary, than under meanclimatological conditions (Table 2).

Scenario 3 ± 1995 meteorological regime

After 60 days of the 1995 meteorological regime, thetracer distribution (Fig. 9) is similar to the other 60day distributions, but with noticeably less drift intoareas of the western shelf (area 5) and the North Sea(area 2). Conversely, around 10% more have remainedin the main initial area of concentration of Porcupine

Table 2. Percentage of tracers by area (see Fig. 3) for different model runs.

Scenario Area 1: Area 2: Area 3: Area 4: Area 5: Area 6: Total 1±6:NorwegianSea

North Sea Deep waterwest of Rockall/Porcupine

Shelf-edgeof Biscay

Westernshelf

Porcupine/RockallFaeroes

All areas

Climate 0 days 0.0 0.0 2.1 6.6 0.9 90.4 100.0

Climate 60 days 4.0 4.7 1.1 8.0 13.1 68.9 99.81994 60 days 3.6 5.3 2.9 9.1 11.0 67.1 99.01995 60 days 5.3 1.6 1.4 7.4 5.0 78.9 99.6


Scenario Area 5a: Area 5b: Area 5c: Area 6a: Area 6b: Area 6c: Total 5+6:Shelf westof Scotland

Shelf westof Ireland

ShelfCeltic Sea

North RockallTrough andFaeroes

Rockall Bankand Trough

PorcupineBank

Porcupine/RockallFaeroes + wesr shelf

Climate 0 days 0.3 0.2 0.4 9.6 61.0 19.8 91.3



Figure 5. Indices of wind stability at Porcupine Bankcalculated as S � 100 � �W=w�, where W is the averagevectorial magnitude and w is the arithmetic magnitude ofwind stress.



and Rockall (area 6; Table 2). The tracer concentra-tions show more continuity around Porcupine and intoBiscay, with little evidence of drift away from theshelf-edge (Fig. 9; cf. Fig. 8).

After 120 days of model simulation (Fig. 9), theabove differences become more marked. The retentionof tracers in the initial area of Rockall/Porcupine(area 6) is higher, with 56.5% remaining, as opposedto 33.9% for 1994 and 44.2% in the same area for theclimatological scenario (Table 2). In area 6a there is anoticeable retention of a small area of tracers south ofthe Faeroe Shelf and Faeroe Bank which, by 120 days,has been lost in the other scenarios. The drift onto theshelf (area 5) is much reduced, with only 17.4% oftracers in that area compared with 36.0% for 1994 and28.5% under mean climatic conditions. Drift into theNorth Sea is also reduced (about two-thirds of thenumbers compared with the other scenarios; Table 2)while more tracers both reach the Norwegian Sea andpass further north out of the model area comparedwith the other scenarios. The concentration of tracersto the north of Porcupine Bank maintains a continuitywith those further south, extending into Biscay wherethere are fewer tracers dispersed over deeper waterthan in the other two scenarios.

DISCUSSION

The three model simulations showed generally similarpatterns. Most signi®cantly, these were the markedelongation of the tracer distribution along the shelf-edge and into the Norwegian Sea and northern North

Sea, and, west of the British Isles, their less pro-nounced easterly on-shelf drift. Dispersion in the up-per layers of the SEC was strongly guided by bottomtopography. This is clearly evidenced by the confor-mity of the distributions to the 200 m contour alongthe shelf-edge and to the 100 m depth contour in thenorthern North Sea.

A closer inspection of the modelled distributionsreveals differences between years which may be relatedto subsequent indices of recruitment success. The mostpersistent winds were in 1994 (Table 1, Fig. 5),these resulting in increased transfer of tracers ontothe western shelf and a corresponding reduction in thearea of Rockall and Porcupine Bank. (Fig. 10). The

Figure 7. Vertically integrated tracer distribution from 0to 60 m depth after 60 and 120 days of dispersion underclimatological wind conditions.

Figure 6. Initial larval (tracer) distribution; abundance isrepresented at three category levels of 1±10 (yellow), 10±100(orange) and 100±1000 (mauve) m)2. The 200 m depthcontour is also shown.



year-class strength for blue whiting for 1994, as re-cruits at age 0, is currently estimated as being 79%of the 1981±1993 mean; 1995 was the strongestyear class on record, with a preliminary estimate ofnearly 4 ´ the 1981±1994 mean level of recruitment(Table 3; although the value for 1995 is possibly anoverestimate, because there has not yet been suf®cientelapsed time to allow the most reliable calculation ofthis parameter). The wind data for 1995 showed lowdirectional stability (Table 1, Fig. 5) and, as a conse-quence, more retention of tracers in the Rockall/shelf-edge area west of Scotland and low penetration oftracers onto the shelf (Fig. 10). At a less marked level,

there was also a lower transfer of tracers to the NorthSea and a small increase in those entering the Nor-wegian Sea (Fig. 10).

Super®cially this would indicate the survival ben-e®ts of retention in the spawning area, although thereduction in transport onto the shelf, irrespective oflatitude, might be of more signi®cance. A number ofexplanations can be postulated for enhanced survivalalong the shelf-edge, e.g. the elevated productivity inthat region (Pingree et al., 1982; Coombs et al.,1990), and avoidance of drift into relatively un-pro-ductive deep water; Bailey and Heath (1996) havingrecently shown evidence for higher growth rates and

Figure 9. Vertically integrated tracer distribution from 0to 60 m depth after 60 and 120 days of dispersion under 1995wind conditions.

Figure 8. Vertically integrated tracer distribution from 0to 60 m depth after 60 and 120 days of dispersion under 1994wind conditions.



potential survival of blue whiting larvae in the shelf-edge zone.

The general pattern of dispersion of the tracers isessentially similar to that ®rst outlined for the drift ofthe larval stages by Fraser (1958) and as suggestedby Bailey (1982), although more tracers are retainedin the main spawning area west of the British Isles(between one-third and two-thirds of tracers remain-ing in area 6 after 120 days ± Table 2) than implied inthe latter report. Similarly, the predicted distribution

of tracers after both 60 and 120 days shows someagreement with the distribution of 0-group bluewhiting as summarized by Bailey (1982); for example,the drift of tracers into the northern North Sea issupported by observations of 0-group in that area andlikewise for areas to the west of Scotland.

South of the Faeroe Shelf and in the area of FaeroeBank, the widely dispersed initial distribution wasconcentrated along the shelf-edge and advected intothe Norwegian Sea and North Sea (Fig. 6; cf. Figs. 7±9). This is consistent with observations of markedlyincreased north-easterly along-slope transport, north ofthe Wyville-Thomson Ridge (Huthnance and Gould,1989); this ¯ushing of the area west of the ridge andthe re-circulation pattern south of Faeroe Bank beinga quasi-permanent feature of the modelled circulation®eld (for example see Fig. 11).

More recently, Monstad et al. (1996b) summarizedthe distribution of 0-group blue whiting in researchtrawl catches for the period 1979±1995. Althoughsampling was much less intensive than further south,there was still a remarkably low occurrence of 0-groupin areas west of Scotland where the model predictssigni®cant accumulation of tracers. Resolution of thisapparent disparity requires more extensive directedsurveys for postlarvae and 0-group, using the predicteddispersal pattern as a guide to sampling location.

In the south of the model area, there is some in-dication of a southerly drift of tracers from Porcupinetowards Biscay to augment the relatively low levels ofspawning in that area. The separation of tracers in thearea of Porcupine Bank also has some bearing on stockidentity and hence management strategy. In a discus-

Table 3. Blue whiting recruit numbers (from Anon.,1996).

Year Abundance ( ´ 108)

1981 561982 2461983 2441984 1351985 1101986 1061987 831988 971989 2331990 971991 721992 531993 90a

1994 99a

1995 462b

a Possibly a slight underestimate.b Possibly an overestimate.

Figure 10. The percentage of tracer particles in model areas (see Fig. 3 and Table 2) after 120 days of dispersion underdifferent wind regimes, compared with their initial abundance in the same areas.



sion of the population age structure of blue whiting,Isaev and Seliverstov (1991) suggested the existenceof separate Hebridean (i.e. west of Scotland) andPorcupine populations, with a division at 56°N. Fur-thermore, these authors suggested that a knowledge ofthe dispersion pattern of the eggs and larvae mightassist in giving a clearer differentiation of these pop-ulations. The initial distribution shows a continuityfrom west of Scotland to south of Porcupine (Fig. 6);in contrast, the tracer distributions, in particular forthe 1994 scenario (Fig. 8), show a degree of separationover Porcupine Bank at around 53°/54°N. This givessome justi®cation for the proposals of some stockseparation, but possibly with a more southerly divisionthan indicated by Isaev and Seliverstov (1991).

In areas further a®eld, 0-group blue whiting areregularly reported off Iceland and Greenland, but it islikely that these are derived substantially from inter-mittent local spawning (MagnuÂsson et al., 1965;SveinbjoÈrnsson, 1975; Bailey, 1982). Equally, the oc-currences of larvae, postlarvae and 0-group off north-ern Norway (Zilanov, 1968) and in the Barents Sea(Boldovsky, 1939; Lahn-Johannesen, 1968) wouldappear to be attributable to local spawning, the modelresults not indicating any signi®cant drift that farnorth-westwards. In support of this suggestion are theobservations of limited local spawning along theNorwegian coast (Lopes, 1979; Bjùrke, 1983, 1984).

Surveys of the 0-group have tended to reveal a morepatchy distribution than shown in the model simula-tions. This disparity may be attributed, in part, to thecoherent long-term larval distribution used for the initial

tracer distribution, when in reality in any particular year,more local variation is seen. In particular, there is onlyvery limited literature information on the abundance oflarvae in the central regions of the Rockall Trough,thereby leading to over-simpli®cation and possibleoverestimation of their initial abundance in that area.

Behavioural characteristics of the postlarvae, suchas shoaling and vertical migration, will also in¯uencesubsequent dispersal as the increased motility of thelater larval stages makes them less in¯uenced by passiveplanktonic drift. Growth rates of blue whiting post-larvae are not well established, but estimates of lengthafter periods of 60 and 120 days are in the region of10 cm and 15 cm, respectively (Bailey, 1982). Post-larvae/juveniles at these lengths would typically haveat least some degree of diel vertical migratory behav-iour (Fraser, 1961), a shoaling instinct and signi®cantswimming capability. At the same time, developmentof thermal strati®cation would be expected to interactwith larval behaviour and vertical distribution pat-terns. Thus, simulations of dispersion beyond about 60days, and certainly beyond 120 days, will be increas-ingly unrealistic without some input of these behav-ioural characteristics. Equally, larval mortality, whichis not included in the present study, will affect larvalabundance during their period of drift and hence willmodify the resultant distributions. It is evidently im-portant that such biological characteristics be incor-porated in any re®nement of the model system.

At the same time, it is recognized that the presentresults are derived from computer simulations and thattheir interpretation is dependent on how realisticallythe model re¯ects the actual situation. In this context,the horizontal resolution of the circulation model andof the forcing functions (wind stress and density ®elds)should be considered. The wind stress ®elds used in thesimulations have a resolution of 1° of latitude andlongitude which is interpolated onto the model grid.Small-scale fronts which are linked to strongly ¯uc-tuating momentum ¯uxes at the sea surface (vonStorch, 1984) or mesoscale vortices which give rise toexceptional strong winds (Paulus, 1983) can causestrong local currents, but these phenomena are notresolved by the wind stress ®eld used for the forcing ofthe circulation model. Additionally, because no quasi-synoptic density ®elds for the model area and the timeunder consideration are available, monthly climato-logical density ®elds were used (Levitus, 1982). Thesedata also have a resolution of 1° of latitude and lon-gitude which is interpolated onto the model grid.Although these data give a good approximation of themonthly density ®eld for the area under consideration,they will, nevertheless, be different from the real

Figure 11. Modelled circulation pattern on 25 June 1995in model layer 4 (30±60 m depth). The smallest arrows de-note current speeds <2 cm s)1; larger arrows represent suc-cessive increments of 2 cm s)1 in current speed.



density ®elds. These differences will in¯uence thecurrents in speci®c regions and will not be re¯ected bythe simulated currents. Thus, the relatively coarseresolution of the input data and of the circulationmodel may not be ideal for studies of mesoscale phe-nomena. However, the large-scale circulation, whichis of particular relevance to the regional drift of bluewhiting larvae, is reproduced effectively.

In conclusion, two signi®cant points emerged inrespect of the use of such model systems. Firstly, to testtheir general predictive hindcast ability, large-scalesurveys of the late postlarvae/early juveniles are re-quired. For blue whiting this would be a particularlyextensive task, covering a wide distributional rangeand extended season. Secondly, more information onthe biology of the later planktonic stages is needed,especially the regional variation in growth and mor-tality rates for incorporation into a biophysical trans-port model. These points are currently being addressedin a follow-on proposal to the work described here.

ACKNOWLEDGEMENTS

This research was funded, in part, by the EuropeanUnion under Contract No. AIR2-CT93±1105.Thanks go to ECMWF (European Centre for Medium-Range Weather Forecasting) in Reading and to theDKRZ (Deutsches Klima Rechenzentrum) for makingavailable the meteorological data. Finally, we wouldlike to thank all SEFOS colleagues who participatedeither directly or indirectly in this investigation, fortheir contribution.

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a numerical model of the dispersion of blue whiting larvae, micromesistiuspoutassou (risso), in the...

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