Journal of Fish Biology (2000) 57, 1290–1311doi:10.1006/jfbi.2000.1397, available online at http://www.idealibrary.com on

Vertical distribution and feeding of larval blue whiting inturbulent waters above Porcupine Bank

N. H*‡ M. K†*Biologische Anstalt Helgoland in der Stiftung Alfred-Wegener-Institut fur Polar- und

Meeresforschung, Notkestraße 31, 22607 Hamburg, Germany and †Universitat Hamburg,Institut fur Hydrobiologie und Fischereiwissenschaft, Olbersweg 24, 22767 Hamburg,

Germany

(Received 10 January 2000, Accepted 3 July 2000)

In April 1995 a patch of blue whiting larvae Micromesistius poutassou was found at lowillumination levels below 20 m depth near Porcupine Bank, west of Ireland, together with highdensities of copepod nauplii and reduced turbulence rates, suggesting that larval blue whitingvertical distribution was determined by prey concentration, illumination and turbulence. Most(83·8%) larvae (2·0–7·5 mm Ls) had food in their guts. Feeding incidence and feeding intensitiesincreased with increasing larval length. Only larvae >5·5 mm reduced numerical in favour ofweight-based feeding intensity, indicating a shift in dietary composition. Maxima of the dielrhythms of feeding incidence and intensities occurred at 1800 and 2100 hours and minima atdawn (0600 hours). Proportionately, more nauplii were eaten by day but more copepod eggsand tintinnids at night. The distinct diel pattern in larval blue whiting feeding suggests that anyanalysis of factors mediating feeding must take into account diel feeding cycles. Larval feedingwas significantly affected by wind speed. The larvae ate more and larger items at low than athigher turbulence levels. The data suggest that the maximum level of turbulence was notbeneficial for larval blue whiting, but more moderate wind speeds could have had an enhancingeffect on larval feeding success. � 2000 The Fisheries Society of the British Isles

Key words: blue whiting larvae; diet; diurnal feeding; wind mixing; light.

‡Author to whom correspondence should be addressed. Tel.: +49 40 42838 6625; fax: +49 40 428386618; email: NHillgruber@compuserve.com

INTRODUCTION

While there is evidence to doubt the generality of Hjort’s (1926) critical periodhypothesis (Petermann et al., 1988), high and variable mortality rates cancontribute significantly to year-class strength (Bradford & Cabana, 1997).Starvation may not be the main reason for larval mortality, but poor feedingconditions affect larval survival through reduced growth rates and diminishedpredator avoidance (Houde, 1987). Often field estimates of prey densities relatepoorly to larval feeding success, suggesting that other factors than absolute preydensity, such as light (Blaxter, 1986; Miner & Stein, 1993), temperature (Paul,1983; Michaud et al., 1996) and wind-induced turbulence (Dower et al., 1997aand literature therein), may mediate feeding success.

Fish larvae are primarily visual predators that rely on sufficient illumination ofthe water column to detect and capture prey organisms (Paul, 1983; Blaxter,1986). Larval feeding success, i.e. the proportion of feeding larvae and thequantity of ingested prey items, often follows a distinct diel pattern (Conway

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0022–1112/00/111290+22 $35.00/0 � 2000 The Fisheries Society of the British Isles

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et al., 1998; MacKenzie et al., 1999), with species-specific timing of peak feedingand duration of feeding periods. Knowledge of such diel feeding patterns isimperative for interpreting correctly the impact of other mediating factors onfeeding success.

Small-scale turbulence affects larval feeding success (Dower et al., 1997a).Strong mixing events may disrupt the layers of high prey density and dissipateprey concentrations, leading to reduced feeding success and increased mortalityrates (Petermann & Bradford, 1987). In contrast, small-scale turbulence inducedinto the mixed layer of the water column might increase encounter rates betweenplanktonic predators and prey (Rothschild & Osborn, 1988), leading to effectiveprey concentrations higher than their measured densities. Failure to consider theinfluence of small-scale turbulence in prey densities <35 l�1 might result in an upto 11-fold underestimation of encounter rates (MacKenzie et al., 1994). Therelationship between turbulence and feeding success appears to be dome-shapedrather than linear, indicating an optimal magnitude of turbulence outside whichfeeding success is reduced (MacKenzie et al., 1994; Bakun, 1996 and literaturetherein; Gallego et al., 1996). This optimum value may vary depending onspecies and developmental stage (Fiksen et al., 1998).

Blue whiting Micromesistius poutassou (Risso), a gadoid species ranging alongthe western European shelf edge from Spain to Norway, spawn in the area of thecontinental shelf break, prior to spring bloom (Hillgruber & Kloppmann, 1999).At the time of larval hatching the water column is generally unstratified anddensities of primary prey items for blue whiting larvae, namely copepod eggs andnauplii (Conway, 1980; Hillgruber et al., 1997; Hillgruber & Kloppmann, 1999)are low. However, in spite of low prey concentrations, blue whiting larvaemaintain generally high feeding incidences and intensities (Conway, 1980;Hillgruber et al., 1997; Hillgruber & Kloppmann, 1999). In the area west of theBritish Isles, blue whiting larvae hatch at a time when mixing reaches its greatestdepth (Ellett et al., 1986), exceeding 600 m (Meincke, 1986). It may behypothesised that blue whiting larvae utilise turbulence to enhance their foragingsuccess.

This study focuses on a detailed analysis of feeding of larval blue whitingbased on data acquired using a larval tracking sampling design, which permitteddescription of diel patterns of biological characteristics within a larval patchunder low and high turbulence.

MATERIALS AND METHODS

FIELD SITE AND SHIPBOARD METHODSData were collected from the RV ‘ Heincke ’ in the area of Porcupine Bank, west of

Ireland—a major spawning area of blue whiting (Bailey, 1982). In April 1995, a densepatch of blue whiting larvae was located using repeated Bongo hauls (Fig. 1) above thewestern slope of Porcupine Bank, where larval blue whiting are abundant (Kloppmannet al., in press). The patch was marked with a drifter, using a drogue positioned at 30 mdepth. The drogue consisted of four 2 m2 (0·5�4·0 m) crosswise arranged rectangularDacron� sails which were connected at their long sides (Kloppmann, 1994). Positioningof the drogue at depth followed the description of typical vertical distribution of bluewhiting larvae (Coombs et al., 1981; Kloppmann et al., in press). The drogue wasmarked with a drift buoy especially designed for low wind susceptibility. The buoy was

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F. 1. Map showing the Porcupine Bank. (a) Location of the bongo hauls (+) and density of bluewhiting larvae [m�2]; arrow marks the beginning of drift study; (b) station position along the pathof the drifter.

equipped with a radar reflector and a flash light. During 5–7 April, samples were takenevery 3 h alongside the drifter to evaluate periodicity of distribution and feeding of bluewhiting larvae relative to prey field and meteorological forcing (Fig. 1). Sampling startedat 0000 hours local time (=0 h of the drift study) and lasted 48 h, i.e. two full days.

True wind speed and direction were calculated from measurements of apparent windspeed and direction recorded every hour by a masthead anemometer and the ship’s speedand direction.

At each station, physical data were recorded to a depth of 100 m using a conductivity-temperature-depth (CTD) system. Light intensities in the water column were measuredat mid-depth of each depth stratum (i.e. at 90, 70, 50, 30 and 10 m) using a LI-COR lightsensor attached to the CTD system during daytime only. At low light intensities,particularly around the threshold value for larval feeding, measurements were not reliabledue to noise inherent in the system (J. S. Briggs, LI-COR Inc., pers. comm.).

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The CTD was connected to a rosette sampler and physical data were recorded at every0·5 dbar pressure increment on the down-cast. Microzooplankton were collected on theup-cast, at the midpoint of each multiple opening-closing net (MCN) interval (i.e. 90, 70,50, 30 and 10 m depth) in 10-l bottles connected to the rosette sampler. Water from thebottles was passed through a 45-�m sieve and the concentrated samples were preservedwith 4% buffered formalin-sea water solution.

Ichthyoplankton were collected using a MCN with a mouth-opening of 0·25 m2 andequipped with 200-�m mesh nets. One oblique MCN cast was conducted to a depth of100 m and samples collected at 20 m sampling intervals (i.e. 100–80, 80–60, 60–40, 40–20,and 20 m-surface).

After retrieval of the MCN each net was washed carefully, codends were detached andsamples rinsed into sieves. The concentrated samples were preserved in 4% bufferedformalin-sea water solution. Sampling time from opening the first net to preservation ofthe larvae was �20 min.

For convenience, microzooplankton refer to the zooplankton taxa captured with themethod described. Because of increased swimming abilities, late stage copepodites andadult copepods might have escaped capture with the water bottles and their densities arelikely to be underestimated. Also, due to their small size, tintinnids were retained onlypartially by the sampling strategy and are excluded from further analysis.

LABORATORY ANALYSESBlue whiting were enumerated and a sub-sample measured to the nearest 0·1 mm

standard length (Ls), without correction for larval shrinkage due to net-capture damageor preservation.

Microzooplankton from the water bottle samples were identified to the lowestpossible taxon and developmental stage, enumerated and measured to the nearest0·01 mm using a stereo microscope. Carapace length, total length and width weremeasured for copepod nauplii; diameter for eggs; metasome length, total length andwidth for copepodites and adult copepods; and length and width for all other organisms.Using those measurements, wet weights of prey items were calculated (Nishiyama &Hirano, 1983).

For the analysis of feeding habits, larvae were sub-sampled from eight size classes(<3·0, 3·0–3·49, 3·5–3·99, 4·0–4·49, 4·5–4·99, 5·0–5·49, 5·5–5·99, �6·0 mm Ls). The termfeeding was used to describe larval gut contents. Each larva was placed on a microscopeslide and the entire alimentary canal was excised. The gut was positioned in a drop ofglycerin, opened and the contents examined. Each item was identified to the lowestpossible taxonomic group and developmental stage, counted and measured, using thesame strategy as employed for the water bottle samples.

In comparison with clupeoid larvae (Arthur, 1976), gadoid larvae appear to be lesssusceptibile to evacuation of their gut contents due to sampling and fixation. Walleyepollock Theragra chalcogramma (Pallas) larvae did not regurgitate after handling andanaesthesia (Canino & Bailey, 1995), but 50% of the larvae voided the contents of thehind-gut prior to preservation. While the relatively high feeding incidence in the presentstudy makes it unlikely that blue whiting larvae had evacuated their guts completely, apartial defecation due to net-capture or fixation cannot be ruled out.

STATISTICAL ANALYSESTo obtain a measure of the wind-induced impact on feeding success, wind generated

energy dissipation rate (�) was estimated following MacKenzie & Leggett (1993):

log10 �=2·688�log10 W�1·322�log10 z�4·812

where W is the wind speed in m s�1 and z the water depth in m. To compare the resultingvalues of � in W m�3 with literature data given in cm2 s�3, � was multipled by a factorof 104 ��1 (Kiørboe & Saiz, 1995; Fox et al., 1999), � being the density of local sea water(1027 kg m�3).

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Abundance of blue whiting larvae was computed as number m�2. For furtheranalyses blue whiting larvae were divided into size classes <4·5 mm (representing firstfeeding larvae) and �4·5 mm. Vertical distribution of blue whiting larvae was calculatedas the density weighted mean depth (D) distribution down the sampled water column.

where i is the number of the sampled depth stratum, xi the density of blue whiting larvae(in numbers . 100 m�3) and di the mean depth of that depth stratum.

For the presentation of the vertical aggregation of blue whiting larvae Lloyd’s index ofmean crowding (L; Lloyd, 1967) was chosen:

L=1+(s2x�1�1)x�1

where x is the mean density of blue whiting larvae down the sampled water column ands2 the variance of x.

Density of microzooplankton was expressed as number 1�1. As for blue whitinglarvae, Lloyd’s index of mean crowding was calculated to analyse vertical aggregation ofmicrozooplankton.

Feeding incidence, the proportion of feeding larvae, per station, sampling depth andsize class was calculated. �2-tests of independence were used to test the null hypothesesthat feeding was uniform with respect to time of the day, sampling depth and size of thelarvae. The mean number of food items per gut (numerical feeding intensity) and themean weight of food per gut (weight-based feeding intensity) were calculated usingfeeding larvae only. The null hypotheses that feeding intensities were evenly distributedwere tested with ANOVA. Normality was tested using normal probability plots andLillefors Test (Daniel, 1990). When necessary, data were transformed using either asquare-root or a Box-Cox power transformation (Sokal & Rohlf, 1981). If significantdifferences were found, Scheffe’s or Tukey’s multiple comparison procedures were used totest for pairwise relationships.

RESULTS

HYDROGRAPHY AND METEOROLOGYThe day before the start of the drift study relatively strong winds force 6–7 Bft

(12–14 m s�1) resulted in deep mixing of the water column and high values ofestimated turbulent dissipation rates of �>10�3 cm2 s�3 down to a depth of60 m. Towards the start of the drift study wind speeds declined to <10 m s�1

but increased again at the start of the experiment.During the drift study from 5–7 April 1995, a distinct change in wind stress

was experienced [Fig. 2(a)]. During the first day southerly winds of 9–12 m s�1

prevailed but abated during the night. On the second morning wind speedsdecreased to <2 m s�1, but increased again around noon to 4–6 m s�1.

Wind generated turbulent energy dissipation rates declined exponentially withincreasing depth [Fig. 2(b)]. However, during 5 April relatively high values of�>10�3 cm2 s�3 were estimated to reach down to a depth of 35–40 m, the layersof maximum blue whiting density. On 6 April, � decreased to <10�5 cm2 s�3

during the morning due to the slackening of the wind. Following the rise in windstress around noon, � increased again to >10�4 cm2 s�3 in the layers of highblue whiting larval abundance.

The trajectory of the drifter revealed a mainly wind-driven movement pattern.On the first day of the drift experiment, the drifter was forced steadily in a

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north-easterly direction, but slowed down considerably on the next day, andre-circulated above the shallower parts of Porcupine Bank (Fig. 1).

At the time of the drift experiment, sea surface temperature was 10·1–10·3� Cand salinity values of about 35·5. The water column was well-mixed with nostratification within the upper 100 m [Fig. 3(a), (b)] and daylight intensities of0·06–116·4 �E m�2 s�1 (Fig. 4). At depth of maximum blue whiting abun-dance (20–40 m, see below) daytime light intensities varied between 2·61 and22·86 �E m�2 s�1 with maximum values occurring around noon.

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BLUE WHITING DISTRIBUTIONA total of 21 663 blue whiting larvae was caught within the upper 100 m

resulting in an average abundance of 572·0 m�2 (s=280·7; median=471·4; range309·5–1342·5). Larvae ranged from 2·0–7·5 mm and showed a bimodal lengthdistribution with modes in the 3·0 and 4·0 mm length classes. The abundance oflarvae <4·5 mm was similar on days 1 and 2 but larvae�4·5 mm were fewer onday 2 (Table I).

Most larvae were in the top 60 m of the water column with highest densitiesbetween 20 and 40 m depth, deeper on the first day than on the second with no

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conspicuous differences between the two size classes [Fig. 5(a)]. They tended tobe at shallower depths at low light intensities, namely during dusk and dawn.Vertical aggregation indices were less variable and lower on the first day than onthe second. On the first day, probably due to their greater swimming ability, thelarger larval size class was much more aggregated than the smaller class, butsimilarly aggregated on the second [Fig. 5(b)].

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MICROZOOPLANKTONA total of 16 361 potential prey items was counted, and 6958 of these

(42·5%) were measured and identified. Averaged over all depths and stations,copepod nauplii accounted for 81·1% of these, with a mean naupliar densityof 18·2 l�1 (range 5·9–38·5) within the upper 100 m of the water columnIn contrast, few copepod eggs were encountered (x=0·22 l�1; range 0·0–2·2 l�1).

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While the vertical distribution of copepod eggs was uniform (ANOVA,F=0·917, P=0·460), copepod nauplii varied significantly with depth (ANOVA,F=20·35, P<0·001). Peak densities of nauplii occurred at 30 m depth, with the10 and 30 m depth strata containing significantly more copepod nauplii than thewater layers below [Fig. 6(a), (b)].

Except for copepod eggs, there was no significant difference in density ordepth distribution of microzooplankton groups between days. Althoughmicrozooplanktonic groups seemed more shallowly distributed on day 2, butonly copepod eggs were significantly so (ANOVA, F=6·84, P<0·05).

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F. 4. Vertical distribution of light intensity (�E m�2 s�1) during 2-day drift experiment, 5–7 April1995. *, 10 m; �, 30 m; �, 50 m; �, 70 m; , 90 m.

T I. The abundance of each blue whiting length class for both days of the drift study

Day 1 Day 2

<4·5 mm LS �4·5 mm LS <4·5 mm LS �4·5 mm LS

Mean 475·0 261·5 396·5 47·5.. 204·8 299·5 182·4 20·3Median 414·1 196·8 346·8 43·6Minimum 258·5 73·4 248·8 17·2Maximum 819·3 928·4 860·0 83·2

FEEDING BY SIZEOf the total 1640 blue whiting larvae examined, 1375 (83·8%) contained food

items. Feeding incidence was significantly different among larval size classes[Fig. 7(a)] at all times and was driven mainly by first-feeding larvae �4·5 mm.

Larval size had a significant effect on numerical feeding intensity (ANOVA,F=90·89, P<0·001), with larger larvae up to 5·5 mm ingesting more prey

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[Fig. 7(b)]. The change at 5·5 mm may indicate a shift in diet at that size(Table II). Weight-based feeding intensity increased more steadily withincreasing larval size throughout [Fig. 7(c)].

First-feeding blue whiting larvae relied heavily on tintinnids and copepodnauplii. As larvae grew tintinnids became less important, while copepoditestages and adult copepods became more so, explaining the decrease in numericaland the increase in weight-based feeding intensity.

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F. 5. Mean depth distribution (a) and mean aggregation index (b) of two size classes of blue whitinglarvae during the two-day drift study, 5–7 April 1995, in the area of Porcupine Bank (,night-time; �, daytime). The dashed lines bridge one missing station due to gear failure. ,<4·5 mm; �, �4·5 mm.

DIEL FEEDING PATTERNSDuring the day, 89·2% of larvae <4·5 mm and 99% of those �4·5 mm had

food in their guts [Fig. 8(a)], with only two blue whiting larvae �4·5 mm havingempty guts. Feeding incidence was reduced at 0600 hours (sunrise). Larvalfeeding incidence was significantly less at night than by day for both size classes(<4·5 mm: �2=114·16, P<0·001; �4·5 mm: �2=52·01, P<0·001). Feedingintensity (numerical and weight) was also reduced between 0300 and 0900 hourson both days for both size groups [Fig. 8(b), (c)].

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A diel pattern was evident also in the prey composition (Fig. 9). Copepod eggsand tintinnids were proportionately more prevalent between 0300 and 0900hours, while the proportion of developmental stages of copepods increasedduring daytime, peaking at nightfall.

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F. 6. Vertical structure of prey field for larval blue whiting during two-day drift study 5–7 April 1995.(a) Vertical distribution of copepod eggs (l�1); (b) vertical distribution of copepod nauplii (l�1).

VERTICAL FEEDING PATTERNSDepth influenced feeding incidence of larvae <4·5 mm significantly

(�2=39·896, P<0·001), but not of those �4·5 mm (�2=5·577, P=0·233), withtwo of the larger larvae with empty guts during the day [Fig. 10(a)].

The highest mean numerical feeding intensities occurred in the 40–20 and20–0 m depth strata, but depth differences were not significant, due to a high

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F. 7. Feeding success of blue whiting larvae in relation to larval size (interval indicates confidencelimits). (a) Mean proportion of feeding larvae; (b) mean numerical feeding intensity (preylarva�1); (c) mean weight-based feeding intensity (�g larva�1). �, Day; �, night.

variation in intensities at the 80–60 and 100–80 m depth strata [Fig. 10(b)]. Atthe 80–100 m depth stratum, the high numerical feeding intensity for larvae�4·5could be biased by a low sample size of n=16, but since intensity was high forlarvae <4·5 mm also (n=116), this explanation does not seem sufficient.Kloppmann (1994) estimated that the closed nets of the MCN might becontaminated by up to 2·3% of the total catch, so that about half of the larvaesupposedly captured at 100–80 m might have been the result of contaminationwhile towing the closed net through layers of high blue whiting larvae densities.So the high feeding intensities in the deepest stratum might be an effect ofcontamination.

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Weight-based feeding intensities were highest in the two near-surface strataand peaked at the 40–20 m layer [Fig. 10(c)]. Larvae <4·5 mm had significantlyhigher prey weights (ANOVA, F=3·775, P<0·01) in the two near-surface depthstrata than larvae at 80–60 m depth [Fig. 10(c)], but no significant differenceswere detected for larvae �4·5 mm (ANOVA, F=1·458, P=0·217).

T II. Diet of blue whiting larvae as the percentage number (%) of the principal food items in eachof the eight larval length categories for the two days of the drift study

DayLength

class(mm)

Number oflarvae

analysed

Number oflarvaefeeding

%

Tintinnids Eggs Nauplii Copepodites Adults

1 <3·0 129 82 55·3 20·1 24·6 0·0 0·03·0–3·5 164 121 23·8 40·8 35·3 0·1 0·04·5–4·0 131 107 3·7 35·2 60·1 1·0 0·04·0–4·5 142 118 12·7 34·6 50·4 1·5 0·84·5–5·0 118 101 9·4 34·3 49·8 3·3 3·35·0–5·5 63 56 6·7 41·2 42·1 7·0 2·95·5–6·0 25 21 2·5 49·8 31·7 10·9 5·1�6·0 12 10 0·0 44·4 30·8 12·1 12·8

Total 784 616 17·0 35·3 44·0 2·3 1·4

2 <3·0 128 100 43·5 23·2 33·3 0·0 0·03·0–3·5 209 175 18·7 30·8 50·3 0·2 0·14·5–4·0 157 136 4·6 33·1 60·6 1·6 0·14·0–4·5 170 162 3·2 33·5 59·0 3·0 1·34·5–5·0 120 117 1·9 30·3 59·7 5·2 3·05·0–5·5 53 50 0·5 28·2 56·5 9·7 5·05·5–6·0 14 14 0·9 21·7 53·7 11·5 12·2�6·0 5 5 0·0 17·3 47·0 17·4 18·3

Total 856 759 11·6 30·3 53·8 2·8 1·5

INFLUENCE OF TURBULENCE ON FEEDINGA significantly higher proportion of blue whiting larvae fed on day 2, the day

of lower wind mixing (all larvae: �2=30·79, P<0·001; larvae <4·5 mm: �2=22·99,P<0·001; larvae �4·5 mm: �2=14·42, P<0·001) [Fig. 11(a)]. Likewise numericalfeeding intensity was significantly higher on the second day [Fig. 11(b)] (larvae<4·5 mm: ANOVA, F=55·76, P<0·001; larvae �4·5 mm: ANOVA, F=30·56,P<0·001), as was weight-based intensity (larvae <4·5 mm: ANOVA, F=37·85,P<0·001; larvae �4·5 mm: ANOVA, F=14·54, P<0·001) [Fig. 11(c)].

Blue whiting larvae of both size classes ingested significantly larger preyitems on the second day (ANOVA, F=17·85, P<0·001; ANOVA, F=5·46,P<0·05) (Fig. 12). Both size groups ate proportionately more cyclopoid andcalanoid nauplii but less tintinnids and copepod eggs on the second day andlarvae �4·5 mm ate a higher proportion of copepodites and adult copepodsas well.

1302 . .

0.048

25.0

Hours

(c)Lar

vae

< 4.

5 m

m L

s

00.0

100.0

Lar

vae

4.

5 L

s

20.0

15.0

10.0

5.0

80.0

60.0

40.0

20.0

3 6 9 12 15 18 21 24 27 30 33 36 39 42 45

0.048

30.0

(b)Lar

vae

< 4.

5 m

m L

s

00.0

70.0

Lar

vae

4.

5 L

s

20.0

15.0

10.0

5.0

50.0

30.0

40.0

10.0

3 6 9 12 15 18 21 24 27 30 33 36 39 42 45

0.0048

1.00

(a)Pro

port

ion

indi

vidu

als

0

0.80

0.60

0.40

0.20

3 6 9 12 15 18 21 24 27 30 33 36 39 42 45

25.0 60.0

20.0

>>

F. 8. Periodicity of larval blue whiting feeding during 2-day drift experiment, 5–7 April 1995, in thearea of Porcupine Bank (, night-time; �, daytime; interval indicates confidence limits).(a) Proportion of feeding larvae; (b) mean numerical feeding intensity (prey larva�1); (c) meanweight-based feeding intensity (�g larva�1). , <4·5 mm; �, �4·5 mm.

DISCUSSION

Often drift studies are faced with the problem of following a marked patch oflarvae correctly. The length composition of the blue whiting larvae differedconspicuously between days and there were proportionately much fewer largerlarvae caught on the second day than on the first. Therefore, a loss of theoriginal patch cannot be ruled out. Strong winds, vertical shear in the currentfield and strong gradients in the horizontal velocity field are the usual reasons forsuch loss (Incze et al., 1990). The latter two reasons can be ruled out since thecurrents in the area are homogeneously weak (Meincke, 1986) and with very littlevertical structure (Mohn, 2000). On the other hand, the relatively strong winds

1303

0.0048

70.00

Hours

(b)

% I

ndi

vidu

als

0

60.00

50.00

40.00

30.00

20.00

10.00

454239363330272421181512963

0.0048

60.00(a)

0

50.00

40.00

30.00

20.00

10.00

454239363330272421181512963

F. 9. Periodicity of dietary composition in blue whiting larvae during 2-day drift study (, night-time;�, daytime). (a) <4·5 mm; (b) �4·5 mm: �, tintinnids; �, eggs; �, cyclopoid nauplii;�, calanoid nauplii; *, adults and copepodites.

during the first day might have caused the drifter to move away from the originalpatch. However, there was no significant difference in the prey field betweendays, so the possible loss of the original patch should have no influence on theresults of the present study.

In the Porcupine Bank area, blue whiting spawn in March and April. Athatching, larvae experience a thermally unstratified water column. Hillgruber &Kloppmann (1999) characterized blue whiting as early strategists that initiatefeeding weeks before the peak abundance of copepod nauplii, their main prey.This was the case in 1994 when prey concentrations were low, namely 7·4 and 5·4nauplii l�1 in the upper 100 m of the secondary shelf edge current and above thePorcupine Bank (Hillgruber & Kloppmann, 1999). In the present study, preyconcentrations were distinctly higher with an overall mean of 18·2 nauplii l�1 inthe upper 100 m of the water column. The difference in naupliar density mightbe explained by differences in the wind forcing in the 2 years. In 1994 the strongwesterly winds may have postponed the onset of primary productivity. In 1995wind speeds were relatively low and highly variable in direction (Bartsch &Coombs, 1997) and surface levels of NO3, PO4 and Si above Porcupine Bankwere reduced, indicating the onset of spring bloom above the bank (White et al.,1998), which might in turn account for the higher abundance of copepod nauplii.However, most nauplii belonged to the Oithonidae, which are proportionately

1304 . .

100

60.00

Gut wet weight (µg)

(c)0

80

60

40

20

10.00 20.00 30.00 40.00 50.00

100

30.00

Prey/gut

(b)

Dep

th (

m)

0

80

60

40

20

5.00 10.00 15.00 20.00 25.00

100

1.00

Proportion individuals

(a)0

80

60

40

20

0.20 0.40 0.60 0.80

(68.4)

(39.5)

0.00

0.00

0.00

F. 10. Feeding success of blue whiting larvae in relation to sampling depth (interval indicates confidencelimits). (a) Proportion of feeding larvae; (b) mean numerical feeding intensity (prey larva�1);(c) mean weight-based feeding intensity (�g larva�1). , <4·5 mm; �, �4·5 mm.

more abundant in autumn and winter (Sabatini & Kiørboe, 1994), indicatingthat blue whiting larvae initiated feeding prior to the seasonal secondaryproductivity maximum.

In this study, blue whiting larvae avoided the near-surface layers of the watercolumn and concentrated between 20 and 40 m depth, except at dusk and dawn,as found by Coombs et al. (1981) and Kloppmann et al. (in press). The larvalpreference for certain depth strata has been related to various physical andbiological environmental parameters that may secure the fishes optimal survival(Heath, 1992). Food concentration may be one of the most important of theseparameters. While not highly aggregated on either day of the drift study,copepod nauplii were densest at 30 m, but mean depth of both larval size classeswas c. 10 m shallower than that of their potential prey. Therefore, food

1305

0.004.5

60.00

Larval length group (mm)

(c)

Gu

t w

et w

eigh

t (µ

g)

< 4.5

75.0850.00

40.00

30.00

20.00

10.00

0.00

30.00(b)

Pre

y/gu

t

< 4.5

25.00

20.00

15.00

10.00

5.00

0.00> = 4.5

1.00(a)

% F

eedi

ng

< 4.5

0.80

0.60

0.40

0.20

>

4.5>

F. 11. Comparison of larval blue whiting feeding on the 2-day drift experiment, 5–7 April 1995, in thearea of Porcupine Bank (interval indicates confidence limits). (a) Mean proportion of feedinglarvae; (b) mean numerical feeding intensity (prey larva�1); (c) mean weight-based feedingintensity (�g larva�1). , Day 1; �, day 2.

concentration cannot be the only factor determining larval blue whiting verticaldistribution. However, food availability for fish larvae is determined not simplyby the concentration of food items, but also by light (Munk et al., 1989) andturbulence (Rothschild & Osborn, 1988).

Fiksen et al. (1998) found that, while turbulence may increase the encounterrates between fish larvae and their food, sufficient illumination is needed for thefish larvae to use that turbulence. In the present study larvae seemed to preferdepths with low light levels c. 20 �E m�2 s�1, since highest concentrationsoccurred below c. 30 m during daytime, and they rose to the surface layers onlyduring dusk and dawn. However, to benefit from the high turbulence thatmay be encountered in this particular area, higher light levels are needed (Fiksenet al., 1998). As the larvae are small and the light levels are low at their preferreddepth, their visual range is short (Aksnes & Utne, 1997). Therefore, under highlyturbulent conditions prey items are likely to leave the larva’s visual range beforethe fish can react and capture the prey. Even in the surface layer, high levels of

1306 . .

0.0

45.0>

Day 1

40.035.030.025.020.015.010.05.0

Day 2

0.0

45.0Larvae < 4.5 mm

Day 1

40.035.030.025.020.015.010.05.0

Day 2

Larvae 4.5 mm

F. 12. Mean proportion of dietary composition in blue whiting larvae in relation to day of sampling.�, Tintinnids; �, eggs; �, cyclopoid nauplii; , calanoid nauplii; *, copepodites and adults.

100 �E m�2 s�1 were exceeded only once, while turbulent energy dissipationrates were highest at these depths.

In particular, the smaller larval size classes were unable to compensate for highturbulent velocities, which was evident by constantly low aggregation valuesduring the first day of the drift study. So it would be expected that they wouldprefer deeper layers especially during that time of the year (see below), to avoiddetrimental turbulence rates. For herring larvae Clupea harengus L., high windvelocities caused a dispersion of the population and an increase in the meandepth distribution (Heath et al., 1988). For a visual predator, maximum depthis limited by the amount of available light. Thus, the depth distribution of bluewhiting larvae may be explained as an optimal combination between foodabundance, light intensity and turbulence.

During daytime most blue whiting larvae had prey in their guts, reachingnearly 100% for larvae �4·5 mm. Few first-feeding larvae had empty stomachs.Daytime feeding incidences were distinctly higher than those in 1994 (Hillgruber& Kloppmann, 1999), and in 1967/1968 in the Rockall area (Conway, 1980).With increasing length up to 5·0 mm blue whiting larvae ingested more andlarger prey items. Above 5·0 mm they took less prey by number and weight. At�5·5 mm they took more copepodite stages and adult copepods and fewertintinnids. Due to this shift in diet, prey counts continued to decrease in larvae>6·0 mm, while prey weights increased again.

In this study, blue whiting larvae exhibited a distinct diel foraging pattern,with peak numbers and weights of gut contents occurring towards dusk(1800–2100 hours). Gut contents decreased during the night, with minimumvalues towards dawn (0600 hours). Similarly, the highest proportion of empty

1307

guts was observed at that time, clearly due to reduced foraging associated withthe larval reliance on vision for feeding (Blaxter, 1986). At the same timeingested food particles are digested and assimilated more efficiently duringperiods of discontinuous feeding (Canino & Bailey, 1995). The decline of feedingintensity and proportion of feeding larvae at night has been described for manyother fish species (Conway, 1980; Kellermann, 1990; Conway et al., 1994a;MacKenzie et al., 1999). Blue whiting feeding did not cease completely at night,since there were freshly ingested organisms in the larval guts throughout thenight. Fish larvae start feeding at light intensities c. 0·1 lx (Blaxter, 1986), anintensity at which measurements with the system used in this study becomeunreliable. Thus, while the light may not have been enough for feeding on highlymobile prey items, it may still have been sufficient for feeding on immobiletintinnids and copepod eggs. Copepod eggs could provide an especially valuableenergy source, but frequently they withstand larval digestion (Redden &Daborn, 1991; Conway et al., 1994b). In the present study a high proportion ofcopepod eggs in the larval gut showed no sign of digestion, making it doubtfulwhether blue whiting larvae would actually benefit from ingesting copepod eggs.

The highest winds off western Ireland occur between October and February,but intense wind-mixing is still likely when blue whiting larvae initiate feeding, inMarch and April (DHI, 1967). Therefore, blue whiting larvae should be welladapted to a highly turbulent environment. Short-term wind-induced mixingmay increase larval mortality by disrupting food concentrations and so reducingfeeding success (Lasker, 1975; Petermann & Bradford, 1987; Dower et al.,1997a). Lagadeuc et al. (1997) observed a homogenisation of the verticaldistribution of copepod nauplii, attributed partly to a low swimming capacity ofthe nauplii relative to the vertical mixing intensity. However, even though allmicrozooplankton in the present study were distributed slightly deeper on theday of higher wind mixing, there was no homogenisation of the prey field.

Turbulence may change the encounter probability between prey and predator.Theoretically, wind-generated small-scale turbulences increase the encounter rateof prey and predator which might increase larval ingestion rates (Rothschild &Osborn, 1988). However, the effect of turbulence on larval ingestion rates hasbeen predicted to be dome-shaped rather than linear (Matsushita, 1991;MacKenzie et al., 1994; Gallego et al., 1996), suggesting that at high turbulencelevels larvae may be unable to take advantage of increased encounter rates, dueto a decrease in the probability of successful pursuits.

In the present study on the first day, when wind mixing was higher, a lowerproportion of both size classes of blue whiting larvae had eaten prey. Similarly,Landry et al. (1995) found at comparable prey densities that larval fatheadminnow Pimephales promelas (Rafinesque) reduced prey intake linearly asturbulent velocities increased.

Dower et al. (1997b) found that radiated shanny Ulvaria subbifurcata (Storer)larvae reduced feeding intensity significantly on high turbulence days, but preysize was larger, translating into a 5–55% increase of larval gut contents. In thepresent study, blue whiting larvae took larger prey items (calanoid and cyclopoidnauplii) when wind mixing was lower and smaller prey (tintinnids and copepodeggs) at high turbulence conditions. These findings are in agreement with aprediction by MacKenzie et al. (1994), that in high turbulence conditions, larval

1308 . .

diet selectivity might shift towards more vulnerable prey, which require shorterpursuit times for the larval predator.

Also, in order to test the impact of turbulence on larval feeding Dower et al.(1997b) took daily samples somewhere between 0700 and 1900 hours. Thepresent study has shown that feeding intensity and composition of diet can varydramatically within a few hours, making it difficult to assess the impact of otherfactors on larval feeding.

While the present results provide little support for increased feeding successwith increased small-scale turbulence, feeding intensities of blue whiting larvaedid increase after 1500 hours on the second day when wind speeds increased. Itcould be suggested that the increased wind-induced turbulences increased feedingsuccess through increased contact rates, but 48 h data were insufficient for testingthis hypothesis.

In summary, the proportion of feeding blue whiting larvae as well as thenumber and weight of prey ingested, followed a strong diel pattern. Todetermine the effect of factors like turbulence on feeding success, it is imperativeto understand the larval feeding cycle. While turbulence might have had anenhancing effect on larval feeding success on the second day of the drift study,this could not be established statistically. However, there was a significantnegative effect of wind-induced turbulence at �>10�3 cm2 s�3, when bluewhiting larvae ingested fewer and smaller items, relying more heavily ontintinnids and copepod eggs than on cyclopoid and calanoid nauplii.

This study was funded as part of the EU/AIR grant no. AIR2-CT93-1105. We thankthe captain, first and second mate and crew of RV ‘ Heincke ’ for their valuable andunwavering support at sea; H. v. Westernhagen, J. Thorpe and two anonymous reviewersfor suggestions; and K. Barz, M. Bomplitz, A. Castello, S. Grabbert, H. Keuthen, O} .Kocoglu, N. Raethke, J. Wohlfart and B. Wurche for their assistance in the laboratory.This article is based in part on a doctoral study by NH in the Faculty of Biology,University of Hamburg. NH was supported by a graduate scholarship provided by the‘ Biologische Anstalt Helgoland ’, Germany.

References

Aksnes, D. L. & Utne, A. C. W. (1997). A revised model of visual range in fish. Sarsia82, 137–147.

Arthur, D. K. (1976). Food and feeding of larvae of three fishes occurring inthe California Current, Sardinops sagax, Engrualis mordax and Trachurussymmetricus. Fisheries Bulletin US 74, 517–530.

Bailey, R. S. (1982). The population biology of blue whiting in the North Atlantic.Advances in Marine Biology 19, 257–355.

Bakun, A. (1996). Patterns in the Ocean. Ocean Processes and Marine PopulationDynamics. La Paz, Mexico: California Sea Grant College System and Centro deInvestigaciones Biologicas del Noroeste.

Bartsch, J. & Coombs, S. (1997). A numerical model of the dispersion of blue whitinglarvae Micromesistius poutassou (Risso), in the eastern North Atlantic. FisheriesOceanography 6, 141–154.

Blaxter, J. H. S. (1986). Development of sense organs and behaviour of teleost larvaewith special reference to feeding and predator avoidance. Transactions of theAmerican Fisheries Society 115, 98–114.

1309

Bradford, M. J. & Cabana, G. (1997). Interannual variability in stage-specific survivalrates and the causes of recruitment variation. In Early Life History and Recruit-ment in Fish Populations (Chambers, R. C., Trippel, E. A., eds), pp. 469–493.London: Chapman & Hall.

Canino, M. F. & Bailey, K. M. (1995). Gut evacuation of walleye pollock larvae inresponse to feeding conditions. Journal of Fish Biology 46, 389–403.

Conway, D. V. P. (1980). The food of larval blue whiting, Micromesistius poutassou(Risso), in the Rockall area. Journal of Fish Biology 16, 709–723.

Conway, D. V. P., Coombs, S. H., Fernandez de Puelles, L. & Tranter, P. R. G. (1994a).Feeding of larval sardine, Sardina pilchardus (Walbaum), off the north coast ofSpain. Boletın del Instituto Espanol de Oceanografia 10, 165–175.

Conway, D. V. P., McFadzen, I. R. B. & Tranter, P. R. G. (1994b). Digestion ofcopepod eggs by larval turbot Scophthalmus maximus and egg viability followinggut passage. Marine Ecology Progress Series 106, 303–309.

Conway, D. V. P., Coombs, S. H. & Smith, C. (1998). Feeding of anchovy Engraulisencrasicolus larvae in the northwestern Adriatic Sea in response to changinghydrobiological conditions. Marine Ecology Progress Series 175, 35–49.

Coombs, S. H., Pipe, R. K. & Mitchell, C. E. (1981). The vertical distribution of eggs andlarvae of blue whiting (Micromesistius poutassou) and mackerel (Scomberscombrus) in the eastern North Atlantic and North Sea. Rapport et Proces-Verbaux des Reunions du Conseil International pour l’Exploration de la Mer 178,188–195.

Daniel, W. W. (1990). Applied Nonparametric Statistics. Boston: PWS-Kent.DHI (1967). Monatskarte fur den Nordostatlanitschen Ozean. 4. Auflage, Hamburg:

Deutsches Hydrographisches Institut, Nr. 2420, Atlas.Dower, J. F., Miller, T. J. & Leggett, W. C. (1997a). The role of microscale turbulence

in the feeding ecology of larval fish. Advances in Marine Biology 31, 170–220.Dower, J. F., Pepin, P. & Leggett, W. C. (1997b). Enhanced gut fullness and an apparent

shift in size selectivity by radiated shanny (Ulvaria subbifurcata) larvae in responseto increased turbulence. Canadian Journal of Fisheries and Aquatic Sciences 55,128–142.

Ellett, D. J., Edwards, A. & Bowers, R. (1986). The hydrography of the RockallChannel—an overview. Proceedings of the Royal Society of Edinburgh 88B, 61–81.

Fiksen, Ø., Utne, A. C. W., Aksnes, D. L., Eiane, K., Helvik, J. V. & Sundby, S. (1998).Modelling the influence of light, turbulence and ontogeny on ingestion rates inlarval cod and herring. Fisheries Oceanography 7, 355–363.

Fox, C. J., Harrop, R. & Wimpenny, A. (1999). Feeding ecology of herring (Clupeaharengus) in the turbid Blackwater Estuary. Marine Biology 134, 353–365.

Gallego, A., Heath, M. R., McKenzie, E. & Cargill, L. H. (1996). Environmentallyinduced short-term variability in the growth rates of larval herring. MarineEcology Progress Series 137, 11–23.

Heath, M. (1992). Field investigations on the early life stages of marine fish. Advances inMarine Biology 28, 1–174.

Heath, M., Henderson, E. W. & Baird, D. L. (1988). Vertical distribution of herringlarvae in relation to physical mixing and illumination. Marine Ecology ProgressSeries 47, 211–228.

Hillgruber, N. & Kloppmann, M. (1999). Distribution and feeding of blue whitingMicromesistius poutassou larvae in relation to different water masses in thePorcupine Bank area, west of Ireland. Marine Ecology Progress Series 187,213–225.

Hillgruber, N., Kloppmann, M., Wahl, E. & von Westernhagen, H. (1997). Feeding oflarval blue whiting and Atlantic mackerel: a comparison of foraging strategies.Journal of Fish Biology 51(Suppl. A), 230–249.

Hjort, J. (1926). Fluctuations in the year classes of important food fishes. ConseilPermanent International pour l’Exploration de la Mer 1, 5–38.

Houde, E. D. (1987). Fish early life dynamics and recruitment variability. AmericanFisheries Society Symposium 2, 17–29.

1310 . .

Incze, L. P., Ortner, P. B. & Ortner, J. D. (1990). Microzooplankton, vertical mixing andadvection in a larval fish patch. Journal of Plankton Research 12, 365–379.

Kellermann, A. (1990). Food and feeding dynamics of the larval Antarctic fishNototheniops larseni. Marine Biology 106, 159–167.

Kiørboe, T. & Saiz. (1995). Planktivorous feeding in calm and turbulent environmentswith emphasis on copepods. Marine Ecology Progress Series 122, 135–145.

Kloppmann, M. (1994). Kleinskalige Vertikalverteilungen von Fischlarven beiHelgoland. PhD thesis, Universitat Hamburg, Germany.

Kloppmann, M., Mohn, C. & Bartsch, J. (in press). The distribution of blue whiting eggsand larvae on Porcupine Bank in relation to hydrography and currents. FisheriesResearch.

Lagadeuc, Y., Boule, M. & Dodson, J. J. (1997). Effect of vertical mixing on the verticaldistribution of copepods in coastal waters. Journal of Plankton Research 19,1183–1204.

Landry, F., Miller, T. J. & Leggett, W. C. (1995). The effects of small-scale turbulence onthe ingestion rate of fathead minnow (Pimephales promelas) larvae. CanadianJournal for Fisheries and Aquatic Sciences 52, 1714–1719.

Lasker, R. (1975). Field criteria for survival of anchovy larvae: the relation betweeninshore chlorophyll maximum layers and successful first feeding. Fisheries BulletinUS 73, 453–462.

Lloyd, L. (1967). Mean crowding. Journal of Animal Ecology 36, 1–30.MacKenzie, B. R. & Leggett, W. C. (1993). Wind-based models for estimating

the dissipation rates of turbulent energy in aquatic environments: empiricalcomparisons. Marine Ecology Progress Series 94, 207–216.

MacKenzie, B. R., Miller, T. J., Cyr, S. & Leggett, W. C. (1994). Evidence of adome-shaped relationship between turbulence and larval fish ingestion rate.Limnology and Oceanography 39, 1790–1799.

MacKenzie, B. R., Ueberschar, B., Basford, D., Heath, M. & Gallego, A. (1999). Dielvariability of feeding activity in haddock (Melanogrammus aeglifinus) larvae in theEast Shetland area, North Sea. Marine Biology 135, 361–368.

Matsushita, K. (1991). How do larvae of limited motility encounter nauplii in the sea?Bulletin of the Plankton Society of Japan (Special Vol.) 1991, 251–270.

Meincke, J. (1986). Convection in the oceanic waters west of Britain. Proceeding of theRoyal Society of Edinburgh 88B, 127–139.

Michaud, J., Fortier, L., Rowe, P. & Ramseier, R. (1996). Feeding success andsurvivorship of Arctic cod larvae, Boreogadus saida, in the Northeast Waterpolynya (Greenland Sea). Fisheries Oceanography 5, 120–135.

Miner, J. G. & Stein, R. A. (1993). Interactive influence of turbidity and light on larvalbluegill (Lepomis machochirus) foraging. Canadian Journal of Fisheries andAquatic Sciences 50, 781–788.

Mohn, C. (2000). U} ber Wassermassen und Stromungen im Bereich des europaischenKontinentalrandes westlich von Irland. Dissertation, Universitat Hamburg.

Munk, P., Kiørboe, T. & Christensen, V. (1989). Vertical mgiration of herring, Clupeaharengus, larvae in relation to light and prey distribution. Environmental Biologyof Fishes 26, 87–96.

Nishiyama, T. & Hirano, K. (1983). Estimation of zooplankton weight in the gut oflarval walleye pollock (Theragra chalcogramma). Bulletin of the Plankton SocietyJapan 30, 159–170.

Paul, A. J. (1983). Light, temperature, nauplii concentrations, and prey capture by firstfeeding pollock larvae Theragra chalcogramma. Marine Ecology Progress Series13, 175–179.

Petermann, R. M. & Bradford, M. J. (1987). Wind speed and mortality rate of a marinefish, the Northern anchovy (Engraulis mordax). Science 235, 354–356.

Petermann, R. M., Bradford, M. J., Lo, N. C. H. & Methot, R. D. (1988). Contributionof early life stages to interannual variability in recruitment of northern anchovy(Engraulis mordax). Canadian Journal of Fisheries and Aquatic Sciences 45, 8–16.

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Redden, A. M. & Daborn, G. R. (1991). Viability of subitaneous copepod eggs followingfish predation on egg-carrying calanoids. Marine Ecology Progress Series 77,307–310.

Rothschild, B. J. & Osborn, T. R. (1988). Small-scale turbulence and plankton contactrates. Journal of Plankton Research 10, 465–474.

Sabatini, M. & Kiørboe, T. (1994). Egg production, growth and development of thecyclopoid copepod Oithona similis. Journal of Plankton Research 16, 1329–1351.

Sokal, R. S. & Rohlf, F. J. (1981). Biometry, 2nd edn. San Francisco: W. H. Freeman.White, M., Mohn, C. & Orren, M. J. (1998). Nutrient distribution across the Porcupine

Bank. ICES Journal of Marine Science 55, 1082–1094.