Growth variation of silver hake (Meduccius bilineu~s) larvae in relation to oceanographic

conditions on Western Bank, Scotian Shelf

Jennifer Alice Jefiey

Submitted in partial fùlfllment of the requirements for the degree of Master of Science

Dalhousie University Halifax, Nova Scotia

February 2000

O Copyright by Jennifer A Jefiey, 2000

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Table of Contents

List of Tables ....................................................................................................... vi

.. List of Figures ...................................................................................................... VII

Abstract ............................................................................................................... x

List of Abbreviations .......................................................................................... xi

.. Acknowledgements .............................................................................................. XII

..................................................................................... 1 General Introduction 1

......................................................................... 2 Otoliths of silver hake larvae 8 ......................................................................................... 2-1 Introduction 8

2.2 Methods ............................................................................................... 11 ...................................................................... 2.2.1 Data colIection 11

........................... 2.2.2 Otoiith preparation and measuremenf error 11 ......................................................... 2.2.3 Validation experiments 13

.................................................... 2.2.4 Precision of age estimation 15 ................................................ 2.2.5 Otoiith-fish size relafionships 15

............. 2 - 2 6 Changes in l m a l Zength due to ethanoi preservation 16 2.3 Results ................................................................................................. 17

.................................... 2.3.1 GeneraC resrtlts and ewor assesment 17 ............................... 2.3.2 VaZidirtion experimen b - Fertilized eggs 18

................... 2.3.3 Validation experiments - M C marking of Zarvae 18 .................................................... 2.3.4 Pt-ecision of age estimation 19

................................................ 2.3.5 Otoiith-fish size relationships 23 2.3.6 Changes in h v a l l e n e due to ethanol preservation ............. 29

............................................................................................ 2.4 Discussion 36 .......................................................... 2.4. 1 Validation experiments 36

.................................................... 2.4.2 Precision of age estimation 37 ......................................... 2.4 3 Otoii th-fih size relatiorrships .. 3 9

2-44 Changes in ZarvaZ Zen@ due to ethanol pre~ervation~ ...II.....I -40

3 Growth variation among temporal cohorts and within rnonthly cohorts ................... ......................................................................... 41

3.1 Introduction ........................................................................................ 41 3.2 Methods ............................................................................................ ... 42

........................ 3.2. I Oceanogrqhic smpling and data collection 42 3.2.2 Hy&ogr@y ...................................................................... 45

...........................*........................... ... . 3.2.3 Data Annlyses .... ....... .. 45 ................................................................................................. 3.3 Results 52

................................................ 3- 3.1 OtoIi th-fish size relationships 52 3- 3.2 Growfh vananafr*on among temporal cohorts ............................ 53 3-33 Growth vmktion wifhin monthly c o h o ~ s ............................... 59

3 -4 Discussion ......................................................................... 68 3-41 O foli th-fish sze relafiomhips ................................................ 6 8 3 . A2 Growth vananation among temporal cuhorts ............................ 69 3-43 Gravth varrarratïon within monthIy cohorfs. .............................. 74

4 Test of hypotheses related to growth variation among temporal . and within monthly cohorts ..............~...o.....~.~....................................... 81 4.1 Introduction ......................................................................................... 81 4.2 Methods ............................................................................................... 83

42.1 Oceunogrciphic sampling and data collection ........................ 83 42.2 Hydrogrqhy ......................................................................... 86

........................................................................ 42.3 Da fa anaZyses 88 4.3 Results ................................................................................................. 92

4.3.1 O folifh-fish size relationships krpotheses I to 3) ..... .. ........... 92 4.3.2 Growth variation among temporal cohorts

................................................................. (hypotheses 4 fo 8) 94 43 .3 Growth vuriation within monMy cohorîs

fiyporheses 9 to I I ) ............................................................ 102 4.4 Discussion. ........................................................................................ 112

4 4- I Otoli th-@ size relationships f ipo theses I fo 3) .................. I l 2 4.4 2 Growth variation arnong temporal cohorts

@putheses 4 to 8) ................................................................. 117 4- 4.3 Growth variation wifhin monthly cohorts

fiputheses 9 to II) ............................................................... 122

5 Thesis summary ............................*................................................................. 127 ..... 5.1 Utility of otoliths for age and grow th anabses in dver hake Zarvae 127

5.2 Grow th vananazîafron among temporal cohorts ........................................... 127 2 3 Grow th vuriarion within rnonthly cohurfs ............................................. 129 5- 4 hplications for grow fh and mortality .................................................. 131 5.5 Recornmendarions for JUtzire research .................................................. 133

........................................................................................................... References. 134

List of Tables Table 2.1. List of published studies that address daily otolith increment deposition in larvae of the suborder Gadoidei ........................................................ 9

Table 2.2. 3ummary of methods and results for Alizarin Cornplexone mxking expenments ............................................................................................. 14

Table 2-3. Summary of percent change in SL for saver hake larvae preserved in 95% ethanol.,.-,,..-,.-. .......................................................................... 35

Table 3.1. Summary of silver hake coIIected, analyzed and assigned ................................................................... to each of cohort-1, -2, and -3 in 1997 47

Table 3 -2. Least squares regression statistics for the relationships between ASGR and AOGR and environrnental variables for sitver hake larvae collected on Western Bank in September 1997 ................................................. 61

Table 3 -3. Least squares regression statistics for the relationships between ASGR and AOGR and environmental variables for silver hake larvae

.......................................................... collected on Western Bank in October 1997 65

Table 4.1 List of published studies and the number of independent data sets upon which conclusions were based ........................................................ 82

Table 4.2. Summary of silver hake collected, analyzed and .......................................................... assigned to each of cohort-A and -B in 1998 89

Table 4.3. Summary of slope of length-at-age relations, average GDD ............................................ and zooplankton biomass for cohort-1, -2, -A and -B 100

Table 4.4- Least squares regression statistics for the relationships between ASGR and AOGR and environmental variables for silver hake larvae

.......................................................... collected on Western Bank in October 1998 107

Table 4.5. Least squares regression statistics for the relationships between ASGR and AOGR and environrnental variables for silver hake larvae

...................................................... collected on Western Bank in November 1998 109

Table 4.6. Sumrnary of the results of the hypotheses tested in Chapter 3 and Chapter 4 ....................................................................................... 1 15

Table 4.7. Conceptual model to predict relative growth rates for temporal ........................ cohorts from the interaction between GDD and prey concentration 120

List of Figures Figure 2.1. Spotted hake sagitta stained using Alizarh Complexone ...................... 20

......................................... Figure 2.2. Sagitta and lapillus fiom a silver hake larva 2 1

Figure 2.3. Relationship between the number of increments estimated * * *

for sagittal pairs wthm silver hake larvae .............................................................. 22

Figure 2.4. Relationship between the number of increments estimated ..................................................... for Iapilli and sagittae within silver hake lamie 24

Figure 2 5 Relationship between the number of increments estimated for lapillar pairs within silver hake Iarvae .............................................................. 25

Figure 2.6. Relationship between the difference in the number of increments and surface area of sagittal pairs and sagittae and lapilli tvithin silver hake larvae ........................................................................................ 26

Figure 2.7. Relationship between repeated counts of incrernents on silver hake sagittae .......................................................................................................... 27

Figure 2.8. Relationship between increment counts on silver hake ............................ sagittae by the principal reader and another experienced reader -28

Figure 2.9. Relationship between surface area of sagittal pairs within ................................................................................................... silver hake larvae 30

Figure 2.10. Relationship between surface area of lapillar pairs within silver hake Iarvae ................................................................................................... 3 1

Figure 2.11. Relationship between larval total length and sagittal surface area for silver hake collected between Septemb er and Novernber 1997 ..................................................................................................... 32

Figure 2.12. Relationship between Iarval total length and Iapitlar surface area for silver hake collecteci in September 1997 ....................................... 33

Figure 2.13. Residuals of the relationship between larval TL and sagittal surface area .................... .. ....................................................................... 34

Figure 3.1. Bathymetric charts of the Western Bank region on the Scotian Shelf showing locations fiom where silver hake larvae were collected in September, October and November 1997 and the locations of moorings where surface temperature was measured ........................................... 43

vii

List of Figures (cont'd)

Figure 3 -2. Relationships between larval total length and sagittal surface area for silver hake collected in September, October

.............................................................................................. and November 1997 52

Figure 3.3. Residuals of the relationship between Iarval TL and sagittal ........................................... surface area for silver hake collected in October 1997 54

Figure 3 -4. Linear relationship between larval total length and sagittal surface area for silver hake collected in October 1997 ........................................... 55

Figure 3 S. Relationship between Iarval total length and age for silver hake in cohorts-1, -2 and -3 .................................................................................. 56

Figure 3.6. Surface temperature tirne series for 28 August to 27 October 1997 fiom 2 moorings on Western Bank ....................................................................... 58

Figure 3 -7. Residuals of length-at-age relations for silver hake Iarvae in cohort-l and cohort-2 ........................................................................................ 60

Figure 3.8. Average somatic and otolith growth rates for 10 to 20 day old silver hake Iarvae collected over Sm water depth intervals in September 1997 ..................................................................................................... 63

Figure 3.9. Back-calculated individual TL and daily growth rate series for silver hake larvae used in the repeated measures MANOVA to compare individual growth series among larvae collected on and off Western

..................................................................................... Bank in September 1997 ... 66

Figure 3.10. Back-calculated average TL and daily growth rate series for silver hake Iarvae collected on and off Western Bank in September 1997 .............. 67

Figure 4.1. Ba thpe tnc chart of the Western Bank region, indicating locations fiom where silver hake larvae were collected in October and November and the location of temperature recorders and temperature collections by PanCanadian in Auturnn 1998 ......................................................... 84

Figure 4.2. Relationship between wet weight and displaced volume of plankton fiom formalin-preserved collections.. ...................................................... 87

Figure 4.3. Relationships between larval total length and sagittal surface area for silver hake collected in October and November 1998 ................ .... 93

viii

List of Figures (cont'd)

Figure 4.4. Relationships between Iarval total length and sagittal d a c e area for silver hake collected dunng the Autumn of 1997 and 1998 ....................................................................................................... 95

Figure 4.5. Relationships between larval total length and age for ............................................................................... silver hake in cohort-A and -B 97

Figure 4.6. Relationships between larval total length and age for silver hake collected in Autumn 1997 and 1998 ....................................................................... 98

Figure 4.7. Surface temperature tirne series on Western Bank between September and November 1998 .............................................................................................. 99

Figure 4.8. Average somatic and otolith growth rates for 10 to 20 day old larvae collected over 5m water depth intervals on Western Bank in

......................................................................................................... October 1998 103

Figure 4.9. Average somatic and otolith growth rates for 10 to 20 day old larvae collected over 5m water depth intervals on Western Bank in November 1998 ..................................................................................................... 104

Figure 4.10. Residuals of the length-at-age relationships for silver hake larvae in cohort-A and -B in 1998 ........................................................................ 106

Figure 4.1 1. Scattergram of ASGR and AOGR in relation to density for silver hake iarvae collected on Western Bank in November 1998 ........................ .. 1 10

Figure 4.12. Back-calculated individual TL and daily growth rate series for silver hake larvae collected in two water masses near Western Bank in November 1998 ................................................................................................. 113

Figure 4.13. Average back-calculated TL and daily growth rate series for silver hake larvae collected in two water masses near Western Bank in November 1998 ............................~.~.~~~~..~.......................................................... 114

Figure 4.14. Scattergram of observed growth rates and growth rates predicted using multiple regression analysis with GDD and prey concentration as independent variables for temporal cohorts of silver hake larvae ............................................................................................................ 121

Abstract The sagittal otolith is shown to be an ideal tool for assessing growth variation in silver hake larvae and is used to examine patterns of growth variation among temporal cohorts, and among individuals wîthin rnonthly cohorts, in relation to temporal and spatial variation in oceanographic conditions on and around Western Bank, Scotian Shelf. Larvae collected in September and October 1997 and October and November 1998 defined 4 temporal cohorts (1,2, A and B respectively) identified using inferred hatchdates. Hypotheses developed using data collected in 1997 were tested using data collected in 1998.

Length-at-age relationships were developed for each temporal cohort to examine variation in growth rate throughout the Autumn. In 1997, length-at-age relations were not significantly different between temporal cohorts (slopes 0.1 8 and 0.17 mm-6'; p=0.62) despite large differences in growing degree days (GDD; 435 vs. 3 18OC-d) and average potential prey concentration (0.14 vs. 0.27 gm-3). However, in 1998, the larval cohort hatched early in the season (cohort-A) had a significantly (p<0.001) greater growth rate (0.24 vs. 0.15 mmd") relative to the later cohort (cohort-B). This was consistent with higher GDD (427 vs. 27S°C-d) and higher average potential prey concentration (0.30 vs. 0.17 g-nf3) earlier in the Auturnn of 1998. The variation in length-at-age among temporal cohorts in 1997 and 1998 is most easily reconciled by the combination of temperature and prey concentration. From this, a conceptual mode1 is developed to predict relative cohort growth rates from temperature and zooplankton biornass estimates.

Individual average somatic and otolith growth rates were calculated for a subset of Iarvae collected in each month to examine spatial variation in growth rates in relation to water mass characteristics. In September 1997, larvae colleaed off-bank had a growth rate advantage of >O. 1 mm-d" relative to similar aged larvae collected on-bank. Analyses of daily growth trajectories suggested that larvae collected on- and off-bank likely shared a cornmon origin and larvae swept off-bank incurred a growth advantage relative to those that were retained on-bank. This suggests that variations in the flow field on and around Western Bank may be important for the prediction of spatial variation in growth rates. In 1998, no significant differences (p0.05) in growth rate were observed for larvae collect ed on- and off- bank. Density and temperature, representing water mass structure, were each able to explain >35% of the variance in somatic growth rates within the November 1998 cohort. Within al1 monthly cohorts potential prey concentration explained <IO% of the spatial variation in growth rates. These results suggest that variation in physical oceanographic variables (particularly variation in flow) are likely to be the best predictors of spatial variation in Iarval growth rates within cohorts in this region-

List of Abbreviations

Abbreviation Definition Units

TL Total length mm ALC Aiizarin cornplexone - SL Standard length mm Rs Age estimated fiom right sagitta d Ls Age estimated fiom left sagitta d S Age estimated fiorn sagittae d L Age estimated from lapilli d RL Age estimated fiom right lapillus d LL Age estimated fiom left lapillus d Agem Difference in estimated age between otoliths d SA-diff Difference in surface area between otoliths clm2 ci First age estirnate d c2 Second age estimate d % Age estimated by principal otolith reader d & Age estimated by an outside otolith reader d RSSA Right sagittal surface area w2 LSSA Left sagittal surface area w2 RLs.4 Right lapillar surface area clm2 LLSA Lefi Iapillar surface area wm2 SSA Sagittal surface area vm2 LS A Lapillar surface area pm2 CTD Conductivity, temperature, depth - GDD Growing degree days OC-d ASGR Average somatic growth rate mmed-' AOGR Average otolith growth rate pm2-d-L Lc Total length at capture mm Lh Total length at hatch mm oc Otolith area at capture pm2 o h Otolith area at hatch W2 GR Back-calculated daily growth rate mm-d-' PW Wet weight of plankton g LI Displaced volume of plankton ml TPC Temperature provided by PanCanadian OC TTR Temperature measured by temperature recorders OC S ~ ~ G R Daily sagittal growth rate pm2-d-'

Acknowledgments 1 would first like to thank my supervisor, Chns Taggart, for his support and faith in me throughout this undertaking. Also, thank you for afi of the discussions, and at times arguments, about my research and for pushing me to excel beyond the expectations of myself and others.

Thank you also to my advisory cornmittee, Steve Campana and Dan Kelley, for many helpful cornments, suggestions and for some interesting cornmittee meetings. A special thanks also to Christian Reiss who has been a great heIp from the idea and planning to the wrïting of this thesis-

There are a nurnber of people without whose work in the Iab and field this research would never have seen the light of day. Thanks to Enn Arnold, Patrkia Avendano, Amanda Barney, Jonathan Fisher, Peter Groenkjaer, Alison Pickle, and Angelia Vanderlaan. Also thanks to the Captains, crews and scientific staEwho worked so hard to collect silver hake for my work. Thanks to DREA (Q242), Doug Sameoto 07063) and Mike Power (N98068) for larval collections and Stephen Full and Susan Woodbury at PanCanadian Resources for providing me with temperature data, Also thanks to Julia Blanchard and Mark Showell for collecting and fertilizing eggs on the 1998 groundfish survey f ~ r my validation experirnents.

Thanks to Iain Suthers for his many helpfil comments throughout the development and completion of this research.

Special thanks to al1 those on the CCGS Parizeau cruise 98-058 for their valiant efforts to maintain my sanity during many, many consecutive days of stormy weather.

Thank you to Chris Taggart and Barry Ruddick for fùnding provided as part of the GLOBEC Canada Programme and to NSERC Post-graduate Scholarships.

Thanks to Arran McPherson for the many professional and personal discussions about everything under the sun and for being such a good friend over the past few years.

Thanks to al1 my fiends in the department and outside the department who have made my stay in Halifax full of good times and good fnends. Special thanks to Erin Hildebrand and Kirsten Querbach.

Thanks to my parents and brother for their support when 1 decided to pick up and move out East and for always listening when 1 wanted to babble on about my research.

Lastly, a very speciaf tharks to Matt, for his encouragement, support, and for never doubting that 1 could do it.

Chapter 1:

General Introduction

A principal goal in fisheries oceanography is the determination of those factors

responsible for variations in year-class strength in marine fish. It is hypothesized that

these variations are controlled by events that occur during the early iife history, usually

within the first year of life (Hjort 19 14, 1926). A key factor thought to regulate year-class

strength is Iarval mortality, which in tum may be influenced by larval growth rate (Houde

1987). Variations in growth during the pre-recmitment period (first year of life) are

thought to contribute to recruitment variability through regulation of the length of the

larval stage (Houde 1987, Pepin 1991). Larger, or faster growing, larvae may experîence

a contracted larval duration, reducing the time during which they are subject to predation

and reducing the probability of starvation associated with small size and limited motility

(e.g. Rice et al. 1993, Meekan and Fortier 1996, Hare and Cowen 1997). Thus a rapid

transition through the l a r d stage should enhance s u ~ v a l (Rice et ai. 1993, Meekan and

Fortier 1996, Hare and Cowen 1997). Larval growth rates may depend on oceanographic

conditions such as temperature and wind-induced turbulence (Pepin 199 1, Gallego et al.

1996) and biological conditions such as feeding success (Govoni et al. 1985, Kiarboe et

a t 1988). Therefore, if we can predict growth rates based on these variables and

parameters, we may be able to predict survival and ultimately post-lard recruitment.

Thus, detennination of the factors that influence larval growth rates may contribute

towards achieving the primary goals of fisheries research.

A l a s e volume of literature has aîtributed growth rate variability in l a r d or juvenile fish

to variation in prey concentration done (e-g. HaIdorson et al. 1989, Garcia et al. 1998),

temperature alone ( e g Bolz and Lough 1983, Hovenkamp 1989, Hovenkamp and Witte

199 1, Jordan 1994, Oxenford et al. 1 994, Rutherford and Houde 1995) or temperature

and prey cûncentration together (e-g. Jones 1985, Leffler and Shaw 1992, Arnara et ai-

1994, Betsill and Van Den Avyle 1997, Rutherford et al. 1997, Gallego et ai. 1999).

Other oceanographic variables (cg. saiinity, mixed-layer depth, water depth,

stratification) and processes (e-g. transport), while often measured or caiculated, have not

been adequately assessed as factors that may explain growth variation. Variation in

temperature and prey levels are the most likely mechanisms by which growth variation is

achieved; however, they can not aiways explain a significant proportion of the variability

in growth observed among lmal fish (e-g. Castro and Cowen 1991, Campana 1996).

Thus other oceanographic variables may prove useful in the prediction of growth

variability in time and space and relationships between growth and these other variables

should be explored as they have been for recruitment bear-class strength) in many

marine fish populations (e-g. Hempel 1978, Lasker 1978, Bakun et al. 1982, Frank et al.

1988, Helbig et al. 1992). Limiting analyses to traditionally studied variables (e-g. prey

concentration and temperature), while they must be considered, may limit Our ability to

predict growth, and ultimately survival, using oceanographic conditions.

Many studies that have examined larval growth rates (inferred fiom size-at-age relations)

have averaged the growth rate estimates over populations or cohorts of fish (see

discussion in Rice et al. 1987). However, the practice of averaging growth rates may

mask relations between growth and the environment (Ruherford and Houde 1995).

Furthemore, as size-selective mortality (acting t hrough predation andior starvation) acts

at the level of the individual, focussing on population- or cohort-averaged growth rnay

preclude testable predictions of survivorship when growth is used as a predictor, The

analysis of individual growth rates within well-defined cohorts may thus be key to

resolving the processes responsible for growth variation and ultimately survival

variability in larval fish (Pepin 1989, Rice et al. 1993, Chambers and Miller 1995,

Campana 1996, Meekan and Fortier 1996, Fortier and Quinonez-Velazquez 1998).

Variability in the growth of individual larval fish can be exarnined through the study of

otolith rnicrostmcture (Campana and Neilson 1985, Thorrold and McB. Williams 1989,

Chambers and Miller 1995). Daily growth rings or increments on the otoliths (ear stones)

of larvae (Merluccius bilinearis, Gadus morha and Urophycis cchss) were first

described by Pannella (1971). Since then, the nurnber of published studies using the daily

aging technique for Iarvae has increased dramatically (Jones 1992). The number of daily

otolith increments can be used to determine the age of individual larvae and, therefore,

can be used to define temporal cohorts and to estimate the average growth rate over the

life of individuals (assuming growth rate is linear or has a known fùnctional form) using

somatic or otolith size at capture. However, perhaps of greater utility is the width of daily

otolith incrernents that Vary in relation to environmental conditions such as temperature

(Gutiérrez and Morales-Nin 1986, Eckmann and Rey 1987, Fitzhugh et al. 1997) and

wind-mixing (Maillet and Checkley 1991, Gallego et al. 1996) and are presumably

related to the day-to-day variation in the somatic growth rate of larvae. Otolith

increments, therefore, provide a record of growth variability over the life of the fish (see

review by Campana and Neilson 1985). There is some uncertainty as to whether somatic

and otolith growth are correlated on a day-to-day basis as some researchers have

indicated a de-coupling of otolith and somatic growth when growth rates are highly

variable (ide, faster growing Iarvae have smaller otoliths relative to body size than slower

growing larvae; e g Mosegaard et al. 1988, Secor et al. 1989, Secor and Dean 1992).

Others, however, have found that larval size and otolith size remain highly correlated

regardless of the growth rate (e-g. Dickey et al. 1997) and it is generally accepted that

otoIith growth is a "running average" of somatic growth (Campana and Neilson 1985).

The analysis of individual growth rates and otolith increment widths in relation to

environmental variation should, therefore, prove their utility by defining those penods in

the early life history of fishes when environmental variability can explain a significant

proportion of the variation observed in growth. Variability in otolith increment widths

can also be used to identiQ larvae that have Iikely experienced similar environmental

conditions and thus can be used to make inferences about spawning locations and tirnes,

and larval transport (Fitzhugh et al. 1997, Suthers et al. 1989).

Most studies that use otolith increment widths to examine growth variability arnong

larvae and to assess relations between growth and the environment have averaged growth

rates over multiple increments or individuals. This may mask relations with the

environment or growth similarities or differences arnong individuals. There are, however,

some exceptions. Eckrnann and Rey (1987) and Gallego et ai. (1996) examined otolith

growth on a daily time scale and at the level of individual larvae. Gallego et al. (1996)

identified a dome-shaped relationship between wind-inferred turbulence and otolith

growth in hemng larvae but the identification of relationships related to temperature were

limited by Iow variation in temperature throughout their study penod. Eckrnann and Rey

(1987) observed a decrease in increment widths associated with decreased temperatures

in Coregonus spp. but performed no quantitative analysis of their results. Most other

studies have averaged growth rates over 3 to 10 day penods and/or over groups of

individuals. It is clear that studies to date have not adequately resolved the influence of

oceanographic conditions on growth processes at the level of individual Iarvae on short

time scales (Le. daily).

Silver hake (Merhccilcs bihzearis) is a mode1 species for testing growth and environment

hypotheses in larvae at a variety of temporal and spatial scales, and Western Bank on the

Scotian Shelf is the ideal location to conduct such tests. Silver hake is a bentho-pelagic

species that spawns on the Scotian Shelf in summer and autumn (Scott and Scott 1988).

Larvae of silver hake are pelagic for the first 3 to 5 months post-hatch and they are

generally found in the upper mixed layer (Fortier and Villeneuve 1996). There are few

documented studies on somatic or otolith growth of silver hake larvae (Nichy 1969, >20

mm oniy; Koeller et al. 1989, juveniles; Buckley et aI. 1993, larvae). However, Pannella

(1 97 1) in his pioneering work on otolith microstructure concluded that identifiable

increments are deposited daily on the sagittal otoliths of silver hake larvae after he

estimated an average of 360 increments between the annuli of age-3 and -4 year old hake.

Furthemore, daily otolith increment deposition has been confirmed for species closely

related to silver hake: Merluccizrs prodz~ctzis, Merhccius angustirnanus, Mehccizis

ccpensis and Merhccitcs paradomis (Brothers et al. 1976, Bailey 1982, Morales-Nin

1987). Finally, Buckley et al. (1993) observed a weak inverse relationship between

mortality and growth in silver hake larvae reared in the laboratory which suggests that

growth variability in the field may in part explain survival variability in silver hake. To

my knowledge otolith microstructure has not been used to examine growth rate

variability in larval silver hake. This is surprising as (apart fiom the obvious benefits of

studying a species for which very little is known) the prolonged spawning period of the

adults combined with the persistence of the larvae (and eggs) in regions like Western

Bank on the Scotian Shelf over much of the Autumn (O'Boyle et al. 1984, Reiss et al.

2000) provide an ideal opportunity to examine age and growth of larvae f?om different

cohorts that have experienced different environmental conditions in time and space.

In Chapter 2 of this thesis 1 provide evidence that otoliths are an ideal tool for studying

age and growth in silver hake larvae. In Chapter 3 , 1 use otolith microstmcture to devetop

hypotheses related to growth variability and oceanographic variability among temporal

cohorts and among individuals and water masses within monthly cohorts. In Chapter 4,1

test the hypotheses developed in Chapter 3. In Chapter 5,1 sumrnarize my findings and

provide recornmendations and testable hypotheses for fùture studies.

A rnodified synthesis of Chapters 2 and 3 has been accepted pending minor revisionis

(January 2000) by the Canadian Journal of Fishenes and Aquatic Science as a manuscript

entitled "Growth variation and water mass associations in Iarvai silver hake (Merlzïc=cizïs

b i h e m s ) on the Scotian Shelf'. Various aspects of Chapters 2 and 3 were presented at

the 1999 Canadian Conference for Fisheries Research (Edmonton, AS, January 1999),

Amencan Fisheries Society 23d Annual Larval Fish Conference peaufort, NC, Apml

1999) and the GLOBEC Canada National Science Meeting @artmouth, NS, May 1999).

Results from Chapters 3 and 4 were presented at the 2000 Canadian Conference for

Fis heries Research (Fredericton, NB, January 2000).

Chapter 2

Otoliths of silver hake Iarvae

2.1 Introduction

A number of assumptions underlie the use of otoliths as tools for studying age and growth

in lamal fish. The main assumptions are that age c m be accurately and precisely

deterrnined £kom otolith microstructure and that otolith growth reflects somatic growth

(see Geffen 1992). Age validation studies aim to establish the relationship between age

and the number of otolith increments (Geffen 1992) and involve deteminhg the

periodicity of increment formation and the timing of initiai increment formation. Validation

can be accomplished by: 1) rearing larvae in which the number of increments on the

otoliths can be rerated to the known age of the Iarvae (e.g. Baiiey 1982, Radtke 1989,

Geffen 1992); 2) chernically marking the otoliths of live larvae so that the number of

increments post-marking can be related to the number of days elapsed since marking (e-g.

Lang and Buxton 1993, Szedlmayer and Howe 1995, Thomas et al. 1995, Beckman and

Shulz 2996, Iglesias and Rodriguez-Ojea 1997); and 3) counting the number of increments

between annuli in age 1 + fish (3 65 increments between annuii would be consistent with

daily increment deposition). Pannella (197 1) concluded that silver hake larvae deposit one

increment per day on the sagittal otolith using the latter method after observing an average

of 360 increments between annuli of 3 and 4 year old silver hake. Daily increment

deposition rate has also been validated for many species in the family Merlucciidae (Table

2.1).

Table 2.1. List of published studies that address daily otolith ùicrement deposition in the larvae of species in the suborder Gadoidei.

Species Daily otolith Reference increments

validated (Y/N)? Meduccius bilinenris Y PannelIa (197 1)

Merizzrccizzrs prodzrctzrs Y Bailey (1 982)

Merlzlccius cqensis Y Morales-Nin ( 1 987)

Merlztccizrs pmadox2zrs Y Morales-Nin (1987)

Merluccizrs angusfimmus Y Brothers et al. (1976)

Y Pannella (1 97 1) Campana and Hurley (1 989) Campana (1989) Radtke (2989) Geffen (1995) Clemmesen and Doan (1996)

Theragra chaicogramrna Y Nishimura and Yamada (1 984) Bailey and Stehr (1 988)

Pollachizrs virens Y Campana (1989)

Melmzogrammzrs aegIefirn~s Y Campana (1989)

In addition to validating the penodicity and timing of initial increment deposition,

variability of age estimates within otolith types and between otoiith types as well as within

and among investigators is necessary to assess biases, accuracy and precision in larval age

and growth studies.

The assumption that otolith growth reflects somatic growth can be venfied on a broad

scale by demonstrating a strong population-specinc relationship between a measure of

larval size and otolith size. Although it is generaily accepted that on average otolith size

reflects somatic size, it is more difficult to confïnn that otolith growth reflects somatic

growth on a daily basis (see review by Campana and Neilson 1985). A number of

researchers have concluded that daily otolith growth reflects somatic growth (although

sometimes with a lag period; e g Dickey et al. 1997) while other researchers have

observed a de-couplùig ofotolith and somatic growth particularly when growth rates are

low (e-g. Mosegaard et al. 1988, Secor and Dean 1992). However, if otolith and somatic

size are proportional (Le. a linear relationship) then otolith size at different ages can be

used to back-calculate larval size-

In this chapter 1: 1) present general methods for otolith preparation and results related to

esthating measurement error of larval total length and otolith surface area; 2) assess the

assumption that age can be accurately and precisely determined from otolith increments in

silver hake larvae; 3) assess the assumption that otolith growth reflects sornatic growth in

silver hake larvae; and 4) estimate percent change in larval length due to preservation in

ethanol.

2.2 Methods

2- 2- 1 Data collection

Larvae used for the analyses in this chapter were collected f?om naturally occurrhg larval

populations in September, October and November 1997 (precision of age estimates,

otolith-fish size relations) and October 1998 (preservation and validation experiments

only). Details of the field collections are provided in Chapter 3 (1 997 collections) and in

Chapter 4 (1 998 collections).

2.2.2 Otolith prepmcrtian and meauirement error

Pnor to otolith removal, the total lengths (TL, M. 1 mm) of larvae were measured using

either: 1) an ocular micrometer and dissecting microscope (Wdd M5); or 2) a digital image

(taken with a Sony XC-711 CCD video carnera mounted on a Wild M5 dissecting

microscope) and Optirnas image analysis software (Ver. 5.1, OOPTIMAS Corporation

1995). Lapilli and sagittae from the left and ri@ sides were removed fiom larvae using

fine insect needles and attached to microscope slides using either cyanoacrylate glue

(Krazy Glue@ +Précision, Elmer's Products Canada Inc., Brampton, Ontario) or clear nail

polish (Sally Hansen@ Hard As NailsB, Del Laboratories (Canada) Inc., Barrie, Ontano).

Otoliths were polished using alumimum oxide microfishing film (1, 3, 9, 12 and 30 p m

3M Imperia1 Microfinishing Film purchased £tom D. k Sears & Sons Ltd. Abrasive

Specialists and Related Equipment, Hansport, Nova Scotia) whenever necessary. The

number of otolith increments were counted at 200 to lOOOx magnification using a

compound microscope (Wild M20). Total otolith surface area was rneasured on a digital

image taken at 40 to 400 x magniflcation using the compound microscope and either: 1) a

(23 Sony XC-7 1 1 CCD video camera (Chapters 2 and 3); or 2) a @Kodak Megaplus

Camera, mode1 1.4i (Chapter 4). Surface area was measured on the digital images using

either 80ptimas or BSigmaScan Pro (Ver. 50.0, SPSS, Inc. 1999) image analysis

software. Fine scale otolith measurements (surface area of individual increments) were

made using a digital image taken with the high resolution @Kodak Megaplus camera and

measurements were made using 8SigmaSca.n Pro.

Prior to the avaiiabiiity of an image analysis system the TL of 8 1 larvae collected in

S eptember 1 997 were measured using an ocular micrometer and dissecting microscope.

Thereafter, aiI larvae were measured using the digital image. The TL for 17 individuds

were estirnated using both procedures and were compared to control for difEerences in TL

measurements using the two methods.

The TL of 57 larvae and the surface area of 40 sagittae were measured twice to estimate

the measurement error on a single image-

22.3 VaIidQndQnon experiments

Althou& PanneIla (1971) concluded that silver hake Iarvae likely deposit daily otolith

increments, 1 attempted to validate this by: 1) using larvae hatched on a known date and;

2) marking otoliths of iive larvae usïng Alîzarin Cornplexone (ALC; e-g. Beckman and

Shulz 1996).

Two attempts were made to hatch larvae f?om eggs using: 1) eggs strîpped f?om fernale

silver hake captured during the August 1998 Department of Fisheries and Oceans

groundfish survey and fertilized with sperm fkom males captured at the same time; and 2)

eggs coilected in plankton tows on the October 1998 GLOBEC Canada &se to Western

Bank (Hazen and Reiss 1999). The eggs in both experiments were maïntained in the lab at

temperatures rangïng fiom 10 to 16 OC. The water was changed daily and dead eggs

(opaque) were removed daily.

During the October 1998 cniise, experiments were conducted to stain the otoliths of live

silver hake larvae or juveniles with ALC and then maintain them in clean sea water for a

number of days post-stahïng. A total of 5 silver hake and 1 spotted hake (Urophycs

regiu) were placed in varying concentrations of non-buffered ALC solutions (1 00 to 150

rng-~-l) for 12 to 24 hours (Table 2.2). Following immersion in the ALC solution, silver

hake larvae were maintained until naturd death in clan seawater at a regulated

temperature and fed natural zooplankton at least once per day. Attempts were made to

Table 2.2. Summary of methods and results for AIizarin Cornplexone (ALC) marking expenments designed to validate the rate of otolith increment deposition in silver hake and spotted hake.

S pecies Post- Concentration Immersion Survival time post- preservation of ALC (mg/L) time in ALC marking (hours)

TL (mm) (hours)

S ilver hake 27 150 12 -

Silver hake 22 100 7 -

Silver hake 15 1 O0 12 -

S ilver hake 20 1 O0 12 14

S ilver hake 22 100 12 24

S potted 38 100 24 hake

produce a natural 1ight:dark cycle for these individuds, however, problerns with the light

sources prevented this fiom occuning. Al1 iarvae were preserved in 95% ethanol upon

their death.

2.2.4 Precision of age esrimation

The number of otolith increments were compared within sagittal pairs, lapillar pairs and

between randomly selected Iapilli and sagittae within individuals to determine the

consistency of otoIith increment deposition and interpretation within and among otolith

Spes. The relationships involvuig sagittae were assessed using larvae collected in

September, October and November 1997 while the reIationships involving lapilli were

determined using a subset of larvae collected in September 1997 only (see Chapter 3 for

collection methods). The number of sagittal increments was also compared within and

between readers for a subset of larvae. The increments on 50 randomly selected larvae

were counted twice by the principal investizator, separated by at Ieast 2 weeks, and

compared. Additiondy, the number of increments counted on 12 sagittae were compared

between those estimated by the principal reader (myself) and an experienced outside

reader (Peter Groenkjaer, Depart ment of Marine Ecology, Aarhus University, Denmark).

Al1 data were tested for normaiity and when this assumption was not met non-parametric

pair-wise statistical tests (Wiicoxon S i g Test) were used for comparisons.

2-25 Otolith-fTsh size rela fionships

The surface area of left and nght sagittae and left and right lapilii were compared to ensure

consistency of otolit h size w i t h otolith types. The relationships between otolith surface

area (the average of the left and right otoliths or the single measurement when only a

single otolith was available) and lamil TL were determuied for both sagittae and lapiili.

2.2.6. Changes in IawaI Ce@ due to ethanolpreservation

Experiments were conducted during the Septernber-October 1 9 98 survey on Western

Bank (Hazen and Reiss 1999) to estimate the change in standard length (SL) of silver hake

larvae after preservation in 95% ethano1:fieshwater (vo1:vol). Larvae were removed fiom

plankton coUections immediately after net retrievd and videotaped prior to preservation in

individual vials. Larvae were videotaped again after >3 months preservation- The SL of

larvae both pre- and post-preservation were measured on the videotaped images by

Jonathan Fisher (Department of Biology, Queen's University, Kingston, ON). The percent

change in SL was cahlated for each individual as:

% Change in SL = (Preserved SLILive SL - 1) x 100

Larvae that were darnaged pre- or post-preservation (14%) were eliminated fiorn the

analyses. Larvae were separated into 2 mm size classes based on the live SL and the

average, standard deviation and range of the percent change in SL was calculated for each

size class. The percent change in SL was compared among size classes using Analysis of

variance (ANOVA) .

AL1 statistical analyses throughout the thesis were performed using Systat 8.0 (SPSS Inc.

1988) or NCSS 6.0 (Hintze J. 1998).

2.3 Results

2.3- 1 General reszdîs and e m r assesment

The sagittae and lapilli were consistently located and removed fiom both sides of the silver

hake iarvae. The sagittae were generalIy easier to locate and remove than the lapilli as they

were noticeably larger in larvae with TL greater than -3 mm. For larvae <20 mm otolith

increments were clear and otoliths were not polished. Otoiïths were origindy atnxed to

microscope slides using cyanoacrylate glue but surface cracking, which began in the s p ~ g

of 1999, obscured the otoliths. Attempts were made to deterrnine the cause of this

cracking by allowing glue to dry in either a dessicator, a humidifier, or a vacuum. None of

these treatments elirninated suiface cracking and, therefore, subsequent otoliths were

f i e d to slides using clear nail poiish.

There was no significant difference between Iarval TL measurements made using the

ocular micrometer with the dissecting microscope or on a digital image using Optimas

@=0.56, N=17, paired t-test). Therefore, no adjustment to either set of measurements was

performed.

The TL of 57 larvae were measured twice on the same image using Optirnas and the

absolute diEerence in the two measurements ranged fiom 1 -2~10-' to 0.42 mm with an

average of 7.3~10~' mm. The coefficient of variation for the repeated TL measurements

ranged fiom 1 . 3 ~ 1 0 ~ to 5.1x10-~ and was not related to l a r d size which indicates that

relative measurement error was constant across the range of sizes examined (1.7 to 8.3

mm). Ail TL measurements were, therefore, esthated H. 1 mm. The surface areas of 40

otoiïths were measured twice and the absolute difference between the measurements

ranged f?om 0.72 to 410 pn2 with an average of -67 The coefficient of variation for

the surface area measurements ranged fiom 3 -6xl o4 to 2.3~10" and increased with otolith

size. This suggests that the relative measurement error on Iarger otoliths is greater than

that on smaiier otoliths perhaps due to the lower magnïfïcation requirwl to measure the

surface area of larger otoliths. AU otolith surface area measurements were, therefore,

estimated +IO0

2.3.2 Validation experiments - Fertilized eggs

The two attempts (July 1998 and October 1998) to hatch silver hake larvae fiom eggs and

validate the timing of initial hcrement formation and increment deposition rate were

unsuccessfùl. No larvae hatched from the eggs coliected and fertilized during the 1998

groundfish survey. The researchers on this survey indicated that the female silver hake

were not yet ripe and running and suggested that the eggs were perhaps not viable (J.

Blanchard 1998, Pers. Comrn., Department of Biology, Dalhousie University, Hallfax,

NS). Five of the eggs collected in plankton collections during October 2998 hatched but

none s u ~ v e d beyond 24 to 36 hours post-hatch and no otoliths could be recovered fiom

these individuals.

2.3.3 Validation eqverirnents - ALC markrkrng of h a e

Five silver hake and one spotted hake were irnrnersed in ALC solution to mark the otoliths

in an attempt to validate increment deposition rate. Three of the five silver hake larvae

died in the ALC solution in 112 hours and the otoliths were poorly marked (Table 2.2).

The lapilli, however, tended to be more clearly marked than the sagittae. Two silver hake

and the one spotted hake survived immersion in the ALC solution (Table 2.2) and the

otoliths of al1 three were clearly marked. The whole otolith present at ALC immersion was

staïned but the otolith material at the edge of the stain was more prorninently marked and

this Wtely represents the material laid down whiIe the larvae were immersed in the ALC

solution. One of the silver hake s u ~ v e d for 14 hours and the other for 24 hours post-

marking and both displayed otolith growth after the absorption of ALC into the otolith.

This indicates that the siiver hake larvae deposited matterial on their otoliths in the 14 to 24

hours post-marking but whether this growth represented one complete increment per 24

hour period could not be discerned. It was observed that neither the ALC marking nor the

subsequent otolith growth was syrnrnetrical around the sagittae. The spotted hake

s u ~ v e d for 5 days post-marking and had 5 distinct increments after the ALC stain on the

otolith (Fig. 2. l).

2- 3- 4 Precision of age estimation

Otolith increments were visible on both sagittae and lapilli although the increments on

sagittae were easier to i d e n t e and enumerate (Fig. 2.2). No significant differences were

observed between the number of increments counted on sagittal pairs @=O. 54, N=3 82,

Wilcoxon Sign Test; Fig. 2.3) or on a randomly chosen sagitta and IapiUus (p=0.44, N=47;

edge 4 3

Figure 2.1. Edge of a spotted hake sagitta stained with Alizann Cornplexone (dark) 5 days pnor to death. Arrows point to the discontinuous zones of the first 4 daily incrernents formed after immersion in ALC and the edge of the otolith which represents growth on the fifih day pnor to preservation in ethanol .

Figure 2.2. (a) Sagitta and (b) lapillus from a silver hake larva (6.3 mm TL). The age of the larva was estimated as 15 days using the sagitta and lapillus. Note the different magnifications for each image.

Number of increments on lefi sagitta

Figure 2.3. Least squares regression for the relationship between the number of increments estimated for right (Rs) and left CLs) sagittae within 3 82 silver hake lanrae collected on Western Bank, Scotian Shelf between September and November 1997 (R~=0.56+0.97L~; 2=0.96). Solid lines are the 95% confidence bands for the regression and dashed lines a r e the 95% confidence bands for the prediction for an individual with a given number of increments on the lefi sagitta The dotted line is a 1 : 1 relations hip.

Fig. 2.4) withh individuals. However, the number of incrernents counted on lapillar pairs

within individuals were signifïcantly dBerent @=0.020, N=34, Wilcoxon Sign Test; Fig.

2.5)- No relationship was observed between the difference in the number of increments

counted on sagittal pairs and the dinerence in surface area behveen the left and right

sagittae (slope not si@cantIy different fiom zero, p=O.Z, N=304; Fig. 2.6a). A

mar30inaUy si@cant positive relationship was observed between the difference in the

number of increments counted on a sagitta and Iapillus and the dEerence in the area of the

sagitta and lapiIlus within individuals @=0.0 19, N=3 5; Fig- 2.6b). However, fiirther

analyses (Hat diagonal) indicated that one data point (denoted by a plus in Fig. 2.6b) with

a large difference in the size of the sagitta and lapilius (high leverage in x-space) should be

considered influential (Hintze 1995). When this datum was removed the slope of the

relationship was not significantly dinerent fiom zero @=0.068).

The absolute difference in repeated age estirnates by the principal reader on a subset of

otoliths ranged from O to 4 days with an average of 1.2 days and the repeated counts were

not sigdicantly different (p=0.096, N=50, Wilcoxon Sign Test; Fig. 2.7). The number of

increments counted on a subset of Iarvae by the principal reader and an outside reader

were, however, significantly dEerent @<0.0 1, N= 12, Wilcoxon S ign Test; Fig. 2.8).

2- 3.5 Otolith-fsh size relationships

Otolith surface area was not significantly different between left and right sagittae @=O. 89,

Number of increments on sagitta

Figure 2-4. Least squares regression for the relationship between the number of increments estirnated for lapilli (L) and sagittae (S) within 47 silver hake larvae collected on Western Bank, Scotian Shelf in September 1997 (L=2.3+0.88S; r2=0.93). Solid lines are the 95% confidence bands for the regression and dashed lines are the 95% confidence bands for the prediction for an individual with a given number of increments on the sagitta The dotted line is a 1 : 1 relationship.

Number of increments on lefi lapillus

3.5. Least squares regression for the relationship between the number of increments estirnated for right (ICL) and left (k) lapilli w Ï t b 34 silver hake larvae collected on Western Bank, Scotian Shelf in September 1997 m4.0H.86L; rZ=0.80). Solid lines are the 95% confidence bands for the regression and dashed tines are the 95% confidence bands for the prediction for an individual wÏth a given number of increments on the leil lapillus. The dotted line is a 1 : 1 relationship.

O 20000 40000 60000 80000 100000 120000 140000 Difference in surface a r a of sagitta and lapilius

Figure 2.6. Least squares regression for the relationship between (a) the dserence in estimated number of incrernents counted on sagittal pairs (Agediff) and the difference in surface area (SAdin) of sagittal pairs within 3 04 individuals (Agedp0.094+1.1~1 o4 S b , r2=0.0047; slope not significantly different fiom zero, p=0.23) and (b) the df i rence in estirnated number of increments counted on a sagitta and Iapillus (Ag%=) and the difference in surface area of the sagitta and lapillus (SAdin) within 35 individuals ( ~ ~ e d i ~ 0 . 4 1 + 4 . 9 ~ 1 O%&; ?=O- 16; dope significantly different fiom zero, p=0.0 19). The outlier in (b) is denoted by a plus and when this data point is removed fiom the analyses the slope of the regression is not significantly different from zero ( ~ 4 . 0 6 8 ) - SoIid lines are the 95% confidence bands for the regressions and dashed Iines are the 95% confidence bands for the prediction for an individual with a given difference in otolith surface area.

Number of increments (second count)

Figure 2.7. Least squares regression for the relationship between repeated increment counts (Ci and C2) on 50 sagittae by the principal reader (Ci=0.72+l .OCz; r2=0.95). Solid Iines are the 95% confidence bands for the regression and dashed lines are the 95% confidence bands for the prediction for an individual with a given number of increments (C& The dotted line is a 1: l relationship.

Number of increments counted by principal investigator

Figure 2.8. Least squares regression for the relationship between the number of increments counted on 12 sagittae by the principal investigator (%) and another experienced reader (%) (%=-3.5+1.1&, r2=0.99). Solid lines are the 95% confidence bands for the regression and dashed lines are the 95% confidence bands for the prediction for an individual with a given number of incrernents counted by the principal investigator. The dotted line is a 1:1 relationship.

N=3 11, Wilcoxon Sign Test; Fig. 2.9) or left and right lapiIli withuz individuals (p=0.34,

N=25, Wilcoxon Sign Test; Fig 2.10). M e r otolith surface area was square root

transformed, significant linear relationships (p<0.00 1) were observed between both

sagittal surface area and 1apiUar surface area and larval TL (Fig. 2-2 1 and 2-12)- Although

the hear regession fit to the sagittal area - TL data was sigdïcant, the relationship

appears to be non-iinear. The residuals of the relationship between sagittal surface area

and larval TL showed pattern associated with the month of coIlection (Fig 2.13) and this

may in part explain the non-linearity observed when al1 larvae were considered collectively

(see Chapter 1). Larvae coilected in October (10) and November (1 1) had almost

exclusively positive residuals and Iarvae collected in September (9) had aImost exclusively

negative residuals.

2.3.6. Changes in Zarvnl le@ dzre to ethanol preservatioii

A totaI of 97 larvae ranging in live standard length (SL) from 3.5 to 10.6 mm were

measured pre- and post-preservation in 95% ethanol. Of these larvae, 14 were not used in

the analyses due to poor condition and, therefore, unreliable SL measurements either

before or after preservation. The percent change in SL for the rernaining larvae (N=83)

ranged from -15 to +19 % with an average of -2.2 %. The average percent change in SL

was positive (Iarval expansion) for the srnallest size class examined (3.0 to 4.9 mm live

SL) and was increasingly negative (larval shrinkage) for the larger size classes (Table 2.3).

SignXcant dzerences in the percent change in SL were observed arnong the four size

classes (ANOVA, p<0.01).

Left sagittal surface area @mZ)

Figure 2.9. Least squares regression for the log-log reiationship between surface area of sagittal pairs (RSSA and LSsA) within 3 11 silver hake larvae collected on Western Bank, Scotian Shelf between September and November 1997 (Logio(RSsA)=0.078+0.98 Logio(LSs~); r2=0.98). Solid lines are the 95% confidence bands for the regression and dashed fines are the 95% confidence bands for the prediction for an individual with a given left sagittal surface a r a The dotted line is a 1 : 1 relationship.

Lefi lapillar s u ~ a c e area (pm2)

Figure 2.10. Least squares regression for the log-log relationship behveen surface area of lapillar pairs (RLsA and LLsA) within 25 silver hake larvae collected on Western Bank, Scotian Shelf in September 1997 (L0!&()~~)=0 .070+1 .OLogia 0; ?=0.97). Solid Iines are the 95% confidence bands for the regression and dashed lines are the 95% confidence bands for the prediction for an individual with a given Ieft lapillar surface area. The dotted line is a 1: 1 relationship.

Sagittal surface area (pn2)

Figure 2.1 1. Least squares regression for the relationship between Iarval total length (TL) and sagittal surfàce area (SSA) for 339 silver hake larvae collected on Western Bank, S cotian S helf between S eptember and November 1997 (TL=I. 7+0. o ~ ~ ( s ~ J ~ - ~ ; ?=O. 84). Solid lines are the 95% confidence bands for the regression and dashed lines are the 95% confidence bands for the prediction for an individual with a given sagittal surface are.,

Lapillar surface area (pn2)

Figure 2.12. Least squares regression for the relationship between Iarval total length (TL) and lapillar surface area (LSA) for 40 silver hake larvae collected on Western Bank, Scotian Sheif in September 1997 ( ~ ~ = 1 . 1 + 0 . 0 9 1 ( ~ ~ ~ ~ ~ ~ ; r2=0.94). Solid lines are the 95% confidence bands for the regression and dashed lines are the 95% confidence bands for the prediction for an individual with a given lapillar surface area.

Sagittal surface area @m2)

Figure 2.13. Residuals of the relationship between larval TL and sagittal su f i ce area for silver hake larvae collected on Western Bank, Scotian Sheif between September and November 1997. Nurnbers on the scattergram represent the month of the year in which larvae were collected (September-9, October-10 and November-1 1).

TabLe 2.3 - Sumrnary of average, standard deviation and range of percent change in SL due to preservation in 95% ethanol for silver hake larvae in 4 Iive SL classes.

Live SL Average % Standard Range of % Sarnple size (mm) change in SL deviation of % change in SL

change in SL

2.4 Discussion

2.4. l Valid;atr-on e.xpeMents

The results of the ALC experiments indicate that the silver hake larvae deposi~ed material

on their otoliths in the 14 to 24 hours post-marking but were inconclusive in validating

that one increment is deposited per day. The experiments did, however, suggest that

spotted hake may deposit one otolith increment per day (aithough N=l) and ïndicates that

the technique of ALC marking itselfwas successfùl. Although spotted hake are in a

different f d y than silver hake, the observation that their increment depositicsn is d d y is

consistent with the assumption that most species deposit daily otolith incrernemts during

the larval stage. To my knowledge aii of the studies that have tested this assumption for

species in the suborder Gadoidei, which includes the family Merluccüdae, have validated

the assumption of daiiy increment deposition (Table 2.1). For the remainder o f this thesis

it is assumed that otolith increment deposition is daily in silver hake larvae (as concluded

by PanneiIa 1971). The timing of initial increment formation in silver hake is , however,

unknown due to the lack of hatching success during the egg incubation trials. T h e estirnate

of lamal age used throughout this study, therefore, also assumes that daily sagittal

increment formation beguis at hatch. 1 am confident that this represents the rebt ive ages

of larvae, however, 1 recognize that this estimated age may not accurately reflect larval

age from hatch. This is not, however, critical to the analysis of growth variabilnty in this

study given the assumption (as in Jenkins and Davis 1990) that the timing of initial

increment formation is constant for al1 individuals.

The results of the ALC validation experhents indicated that otolith growth, at least in

large larvae and juveniles, is not symrnetic about the origin. This is a cause for concern

when measuring growth time series on Iarvae as daily growth rates obtained fiom merent

axes around the otolith could Vary. The measurement of otolith area used throughout this

study may provide a superior estimate of larval s u e and gowth rate than measurement

a1ong a single axis as area accounts for otolith matend deposited on multiple axes of the

otolith and avoids the seemingiy arbitrary selection of a single measurement axis (Secor

and Dean 1992, Sepulveda 1994).

2.42 Precisian of uge estimation

The consistency of larval age estimates between otolith types, within sagittae and withÏn

the principal otolith reader indicate that precise estimates of larval age (as constrained by

the above explicit assurnptions) in silver hake larvae can be obtained by enumerating

otolith increments. The utility of using otoliths to age other species in the family

Merluccidae (Merhccizts capensis, Merhcci~csparadox1ts, MerZzrcciztsp7.oditctus) has

been recognized by a number of researchers (Brothers et al. 2976, Bailey 1982, Morales-

Nin 1987, Butler and Nishimoto 1997). Both the sagittae and IapUi were successfuliy

removed fiom most siiver hake larvae although the sagittae, larger in larvae greater than

-3 mm TL, were generdy easier to Iocate and remove. Futthermore, although there was

no significant dinerence in the ages estirnated fiom lapilli and sagittae, the increments on

sagittae were easier to read and provided more consistent age estimates within larvae than

did the lapilii. The sagittae, therefore, were used for age and growth analyses of silver

hake larvae throughout the rernainder of this study. The results indicate that either a

randorniy chosen (lefi or right) sagitta or the average number of incrernents counted on a

pair of sagittae can be used to estimate age. For the rernainder of this study, the average

number of incrernents were used to estimate larval age when both the lefi and right

sagittae were available. When only one sagitta was available for an individual, the number

of increments were counted once.

The larval ages estirnated by the p ~ c i p a l reader (myself) and another experienced reader

were signincantly difEerent, however, the maximum digerence in age estimates was only 2

days. These results suggest that there was a systematic dserence in the number of

increments counted by each reader with my age estimates greater than those of the outside

reader for young fish (<20 days) and approaching sirnilar age estimates in fish older than

-20 days. Thus, the aging of older larvae may be more precise. The actual age of the

larvae in this study are unknown and, therefore, the accuracy of the age estimates by both

readers can not be assessed. Al1 age estimates in this study were determined by the

principaI reader (myself) and it is assumed that any bias introduced will be constant and

thus wilI not idluence the analyses of relative growth rates.

It has been suggested that ifresolution of increments near the primordium is a problem in

agùig larvae using otoliths then the number of increments counted on the smaller of a pair

of otoliths &om a single individual will be less than the number of increments counted on

the larger otolith of the pair (Campana et al. 1987). No relationship was observed between

the dzerence in the number of incrernents counted on the left and right sagittae and the

ciifference in surface area between the two sides. A weak positive relationship was

observed between the dEerence in the number of increments counted on a sagitta and

lapillus and the difference in surface area between the two otolith types within individuals.

Thus, 1 conclude that the resolution of sagittal incrernents is unlikely ïmpaired near the

primordium in silver hake larvae and, therefore, will not influence the results of this study.

However, the resolution of increments may be irnpaired in the smaller l a p a and caution

should be taken if the lapilli is used in age and growth studies of silver hake larvae-

2 - 4 3 Otolifh-fish size relntianships

Siadcant Iinear relationships were observed between sagittal surface area and lapillar

surface area (square root-transformed) and l a r d total length. However, there is some

evidence of non-linearity (even f i e r transformation of the data) particularly in the otolith-

fish size relationship developed using the sagittal otolith. These results suggest that the

sue of either otolith type can be used to estimate larval size at different ages. Surface area

estimates were consistent within otolith pairs for both sagittae and lapilli but again because

of ease of removal, preparation and analysis the sagittae were used throughout the

remainder of this study. The pattern in the residuals of the sagittal area - larval TL

relationship ïndicate that the otolith-fish size relationships are different for larvae collected

throughout the Autumn (see Chapter 3). This suggests that otolith growth trajectones

should not be compared directly for larvae that have experienced different environmental

conditions (e.g. Mosegaard et al- 1988, Secor et al. 1989, Hare and Cowen 1995) and

cohort-spefic otolith-fish size rnodels should be developed.

2-44 Changes in lailval lengrh due to erhanolpresewation

The TL of larvae was not corrected for change in length due to preservation in 95%

ethanol. The percent change in SL for a11 size classes ranged f?om -1 5 to +19% and whïle

significant differences were observed among size classes, the range in percent change was

high within al1 live SL classes. Therefore, any correction in SL, to account for the effects

of preservation, would be made with a high degree of uncertainw. Fowler and Smith

(1983) observed O to 20% (average 7%) shrinkage of ethanol-preserved silver hake larvae

and a decrease in percent shrinkage in larger larvae. When analyses are limited to larvae

that shnink due to preservation (negative percent change in SL), the range of O to 15%

shrinkage observed in this study is similar to that observed by Fowler and Smith (1983).

However, the opposite trend was observed in this study as the percent change in SL

(shnnkage) was greatest for the largest larvae examined (9 to 10.9 mm). The results

observed in this study and FowIer and Smith (1983) indicate that the trends and magnitude

in shrinkage of silver hake Imae due to preservation is still unresolved and can be highly

variable. A possible explanation for the variable shrinkage of larvae is that it is related to

larval condition. This is a testable hypothesis that if explored in future studies has the

potential to provide a method for estirnating condition of field-caught larvae based on

shrinkage,

Chapter 3:

Growth variation among temporal cohorts and within monthly cohorts

3.1 Introduction

Growth variation of larval fish may play a critical role in the regdation of s u ~ v a l during

the pre-recruitment penod and thus rnay be a principal determinant of year-class strength

in marine fish populations (Houde 1987, Pepin 1991, Campana 1996). Iflarvai growth

variation can be predicted using oceanographic conditions then survival and ultùnately

year-class strength could perhaps be predicted as early as the larval stage.

Many studies of larvai growth have: 1) averaged variation over cohorts or populations of

larvae (Rice et al. 1987); and 2) focussed attention on temperature and prey concentration

as factors responsible for, or able to predict, larval growth variability (see Chapter 1).

Limiting analyses in these ways may hinder the prediction of larval growth based on

oceanographic conditions. Processes occurring within cohorts may be key to resolving the

relationships between growth and the environment (Pepin 2989, Rice et al, 1993,

Chambers and MiUer 1995, Meekan and Fortier 1996, Fortier and QuEonez-Velazquez

1998). Furtherrnore, the analysis of growth varïability in relation to physical conditions

(e-g. salinity, water depth, mixed layer depth and transport processes) may provide fkrther

insights into the processes responsible for variability in growth and may provide

oceanographic measures that can be use to predict Iarval growth variation in tirne and

41

space. In this chapter growth varîation among temporal cohorts (length-at-age) and within

monthly cohorts arnong individuals and water masses (individual growth rates and growth

trajectories) are examined in relation to temporal and spatial variability in biologicd and

physical oceanographic conditions. In this study, cohorts are broadly defined as larvae

coliected in a given month with hatchdates not overlapping with larvae collected in the

subsequent or previous month. Two specifïc operational definitions are used throughout

this study: 1) tempord cohorts (larvae 9 5 d of age collected in a given month) are used

to examine temporal variation in growth rates throughout the Autumn; and 2) monMy

cohorts (10 to 20 day old larvae collected within a given month) are used to examine

spatial variation in growth rates around Western Bank within months.

3.2 Methods

3.2- 1 Oceanopaphic sampling and abta collection

Larvae and hydrographie data were coliected fiom the Western Bank region (Fig. 3.1)

dunng surveys conducted between 15 and 26 September (Defense Research Establishment

Atlantic cruise 4-242, CFAV Endeavoicr; Reiss 1997), 25 October and 10 November

(H97063, CCGS Xz~dson; Reiss 1998b) and 21 and 27 November 1997 (N9770, CCGS

Needler; Reiss 1998a). In September and November l w a e w-ere coliected using 63 cm

diameter BONGO samplers (Posgay and Marak 1980) fit with 333 pm-mesh nets. The

gear was towed in an oblique manner to within 5 rn of the bottom at depths 4 0 0 m. In

deeper water (>IO0 m) gear was towed to within 10 m of the bottom (November) or to

Figure 3.1. Bathymetric charts of the Western Bank region on the Scotian Shelf showing 40, 60, 80, 100 and 200 m isobaths and indicating locations from which silver hake larvae were collected in (a) September, (b) October and (c) November 1997 and (d) location of moorings where temperature time senes were measured, On charts (a) to (c) numbers represent stations inchded in cohort-1, -2 and -3 respectively. Diarnonds on chart (a) represent additional stations from which >25 silver hake larvae were collected and pluses and circles on charts (b) and (c) respectively represent additional stations from which silver hake larvae were coliected.

-65% of the total bottom depth (September). Plankton collected fkom one net were

preserved in 5% (vo1:vol) buffered formalin:seawater and the other in 95% (vo1:vol)

ethanolfieshwater. In October larvae were collected within dierent depth strata using a

0.5 rn diarneter BIONESS (Sarneoto et ai. 1980) fit with ten 243 pm-mesh nets- Two sets

of collections were made at each station, each set consisting of 4 collections Eom different

strata and one depth-integrated collection fiom -10 m above the bottom to the surface (a

total of 10 collections per station; 5 per set). One set of the samples was preserved in

ethanol and the other in formaiin as detailed above. Al1 larvae used for otolith analysis

were selected fiom the samples preserved in ethanol.

Larvae collected with the BONGO samplers (September and November) and formalin-

preserved were enumerated and identified to species. The total number of silver hake

Iarvae in the formalin-preserved samples were used to determine the stations and the

number of ethanol-preserved larvae that were selected for otolith analysis. Larvae

coUected with the BIONESS (October) and ethanol-preserved were identified to species,

enumerated, and ail silver hake &om the 4 depth-discrete samples per station were used

for otolith analysis.

The concentration of silver hake larvae (n~-rn-~), aU species of larvae ( n ~ - m - ~ ) and

zooplankton wet biomass (g-m-') were recorded for each collection. These measures were

calculated using the BONGO collections preserved in formalin in September and

November. For the BIONESS collections in October the larval concentrations (hake and

ail species) were calculated for each of the 4 depth-discrete sarnples preserved in ethanol

and averaged (volume weighted) to obtain one value per station. The zooplankton

biomass was calculated f?om the 4 depth-discrete sarnples preserved in formalin and again

averaged to obtaui one measure for each station. Wet weight of plankton was measured

for each collection after the removal of larvae, eggs, ctenophores and large zooplankton.

The remaining plankton was collected on netting with a mesh size smaller than the

collection nets, partialiy dned until no longer drippïng, and weighed. Volume fikered, as

measured by flow meters inside each net, were used to caiculate plankton biomass per

cubic metre for each collection.

3.2.2 Hydrography

Conductivity (C) and temperature (T) at depth @) were measured at each of the stations

fiom which biologïcal samples were collected using a OSeabird Electronics SBE 25e CTD

promer. Density was calculated fiom temperature and sdinity using the equation of state

(Gill 1982). Temperature data were recorded at half hour intervals between 1 August and

6 December 1997 at 2 moorings separated by approximately 15 km over the crest of

Western Bank (Fig. 3. Id). At each mooring temperature was recorded using two S4

current meters (Interocean) rnoored at 1 1 m depth and 2 temperature recorders (Vemco,

Inc., Dartmouth, Nova Scotia) moored at 2 m depth.

3.2.3 Daia Analyses

The relationship between sagittal surface area and l a r d TL was determined separately for

larvae coilected from each series of sarnple collections and the slopes were compared

using analysis of covariance (ANCOVA).

Age estimates were obtained usuig the nurnber of sagittal increments for a representative

number of larvae collected during each sampling period. Ages were obtained for 175 of

the 9526 silver hake larvae collected in September representing 23 of the 33 stations fiom

which hake larvae were coliected. Collections with c25 individuals in September were not

included in the analyses of growth variation among temporal cohorts. In October al1 larvae

fiom the ethanol-preserved depth discrete sarnples (5 stations; Fig. 3. ib) were selected for

otolith analysis (N=l35) and ages were obtained for 128 of these larvae. In November ail

ethanol-preserved larvae were removed fiom collections that had larvae in the formdin-

preserved sarnple (N=205 fiom 19 stations). However, poor preservation of the

November collections lirnited aging to 52 larvae from 10 locations on or near Western

Bank (Fig. 3. lc). Three temporal cohorts were defhed as larvae coliected in each month

with ages 125 days at capture (referred to as cohort-1, -2 and -3 collected in September,

October and November respectively; Table 3.1). The length-at-age relationships for each

temporal cohort were determùied and the slopes were compared using ANCOVA

The integrated temperature (growing degree day; GDD; OC-d) and average daily

temperature were calculated for a 25 day penod beginning on the earliest inferred

hatchdate for each temporal cohort using the in situ temperature time senes measured

Table 3.1. Sumrnary of silver Iiske larvae collected, analyzed and assiyned to each of cohort-1, -2, and -3 in September, October and November 1997. Values in brackets represent the nomber of stations from which larvae were collected.

Cwise Sampling period Estimated no. Nuinber of aged Nuinber of larvae Cohorl Inferred cohort larvae available larvae (no. 525 d (no. hatchdates (no. stations) stations) stations)

Q242 15 to 26 Sept. 9526 (33) 175 (23) 165 (21) 1 28 Aug. to 20 Sept.

H97063 25 Oct. to 1 O Nov. 135 (5) 128 (5) 101 (4) 2 3 Oct, to 25 Oct,

N9770 2 1 to 27 Nov. 205 (19) 52 (IO) 17 (8) 3 29 Oct. to 17 Nov,

over the crest of Western Bank. Each temperature series was smoothed with a 25-point

rnoving median and the daily temperature estimate was calculated as the average £?om the

four series at noon of each day. ALI evidence available to date (Fortier and Villeneuve

1996; C. Reiss, Department of Oceanography, Dalhousie University, Halifax NS,

unpublished data) suggests that silver hake larvae reside in the upper rnixed layer when the

water column is stratified. Furthermore, in this study >80% of the larvae coiIected in

discrete depth strata in October were coliected at depths c i 0 m. Thus, 1 am confident that

temperature measures at 2 and 11 m depth represent the water temperatures in which the

silver hake were developing. The average zooplankton biomass, total larval concentration

and larval silver hake concentration were calculated for each of the temporal cohorts from

the station-specific data,

The residuals of the length-at-age relationships for cohort-1 and -2 (collected in

September and October respectively) were examùied in relation to geographic location of

capture and water mass characteristics at those locations at the time of capture- Additional

larvae were exarnined £rom collections in September to provide growth rate estimates of

larvae coUected frorn water masses with variable oceanographic conditions. Average

somatic growth rates (ASGR; mm-6') and average otolith growth rates (AOGR; pm2-d")

were calcdated using equations 3.1 and 3 -2 for 10 to 20 day old larvae coliected in

September and October (monthly CO horts) . These two monthly CO horts are hereaf3er

referred to as the Septernber cohort and the October cohort.

ASGR = (L, - Lh)/age

AOGR = (0, - Oh)/age (3 -2)

Le is the l a n d TL at capture, Lh is the estimated TL at hatch as deterrnined from the

intercept of the length-at-age relationship for each temporal cohort, 0, is the otolith area

at capture and Oh is the estimated otoiith area at hatch caiculated by substituthg the

estimated TL at hatch (Lh) into the otolith size-fish size relationship for each temporal

cohort. Lh and Oh, therefore, dEered among cohorts. However, as ASGR and AOGR are

only compared within cohorts and Lh and Oh are constant for ail individuals in a given

cohort the definitions and values used for Lh and Oh are not critical to the results of this

study. Larval age was uiferred fkom the number of daily sagittal increments. The

calculation of ASGR and AOGR using these equations assumes that growth rate is

constant (hear) throughout the period examined and that a constant somatic and otolith

size at hatch can be used to represent the hatch size of ali individuals within a monthly

cohort (as in Geffen 1995). Thus variation in l a r d hatch size due to materna1 infiuences

within cohorts is not accounted for in this calculation of average growth rates. However,

as there is evidence fiom the intercepts of the length-at-age relations that hatch size may

Vary among cohorts, cohort-specific l a r d and otoiith sizes at hatch are used in the

calculation of average individual growth rates.

The ASGR and AOGR for larvae in each monthly cohort were examined in relation to a

suite of physical (water depth, salinïty, density, temperature, mixed layer depth, GDD) and

biological (age, hatchdate, larval silver hake concentration, total larval concentration,

zooplankton biomass) variables using both simple linear and multiple regression models.

Otolith microstructure of 22 individuals fiom 2 defined water masses (on- and off-bank)

within the September cohort were used to fùrther examine growth variability among

individuais_ The otolith surface area was measured at each well-defhed increment

including the distinct increment near the prirnordium bresumed to be the hatchchec k)

whenever possible. The otolith area-at-age data were used to back-calculate Iarval length

at different ages using the biologicd intercept method (Campana 1990). As no

observations of larval and otolith size-at-hatch were available for silver hake, the

biological intercept was defined using the Iarval TL (1.5 mm) and otolith area (225

for the srnallest available larva (denoted by a plus in Fig. 3.2a). Both the back-calculated

length-at-age (mm) and the back-calculated daily growth rate (mm-d") series were

calculated for each individual. For 5 larvae from each water mass, complete back-

calculated length-at-age and daily growth rate series from increments 3 to 10 and 4 to 10

respectively were obtained and these were compared arnong individuals collected on- and

off-bank using repeated measures multivariate analysis of variance (rm MANOVA;

Chambers and Miller 1995). The 5 larvae fi-om each water mass were grouped and a single

length-at-age and daiIy growth rate series were calculated for each water mass. The slopes

of these growth trajectories (using loge transforrned data) were compared between the on-

and off-bank larvae using ANCOVA. Using the data for al1 22 individuals, water mass-

specific growth series were again calculated and the slopes (after transformation) were

compared between the on- and off-bank larvae ushg ANCOVA. To identie where the

average growth trajectories diverged for larvae on- and off-bank, the back-calculated

12 ' (a) September

10 -

8 -

Sagittal surface ares (pn2)

Figure 3 -2. Least squares regression of larval total length (TL) on sagittal surface area 0.5 2 for silver hake larvae collected in (a) September (TL=1.3+0.043(Ss~) ; r 4-87;

N=l68), (b) October (TL=2.7+0.036(~~~)~-~; iL0.88; N=127) and (c) November ( T L = ~ . ~ + O . O ~ O ( S ~ A ) ~ - ~ ; r2=0.93, N=44) 1997 on Western Bank, Scotian Shelf. The slopes are signifïcantly dBerent among larvae collected in the three months (ANCOVA, p=0.002). The bio log i d intercept (Campana 1990) used in al1 back-calculations of somatic size from otolith size is indicated by a plus in (a). Solid lines are the 95% confidence bands for the regressions and dashed lines are the 95% confidence bands for the predictions for an individual with a given sagittal surface area.

length-at-hatch, length-at-each age and growth rate for each age were compared for larvae

collected fiom the 2 water masses using ANOVA (a set at 0-005 to account for the

reduced degrees of fieedom in the multiple cornparisons ushg the same set of individuals).

3.3 Results

3.3.1 Otoiith-fish size reZutionships

Significant (p<0.00 1) linear relationships between larval TL and sagittal surface area

(square root-transfonned) were observed for larvae collected during al1 sarnpling periods

Vig. 3.2). The slopes of the relationships between larval TL and sagittal surface area were

significantly different (ANCOVA, p=0.002) arnong larvae conected in September (0.043),

October (0 -03 6) and November (0.040) indicating that the relationship is not robust

throughout the season and should be calculated separately for larvae collected throughout

the Auturnn (Fig. 3 -2). No pattern was observed in the residuals of the otolith-fish size

relationships for September and November and thus it was concluded that these

relationships were linear. However, in October the otolith-fish size relationship was non-

Iinear with a slight decrease in dope for larvae 26 mm TL (Fig. 3.2b). Fitting Gompertz,

logistic or exponential functions did not, however, result in a significant irnprovement in

the correlation coefficient over the least squares linear regression. The slopes of the

length-at-age relations for larvae with TL 1 6 mm and larvae witli TL <6 mm collected in

October were 0.14 mm-d-' and 0.15 mm-6' respectively. Analyses of the residuals of the

October otolith-fish sue relationship did not reveal any pattern associated with geographic

location of collection (Fig. 3 -3). As the back-cdculation models assumes that otolith size

and fish size are proportional (a linear relationship; Campana 1990, Campana and Jones

1992) the October sagittal surface area data were fhther transformed (Fig. 3 -4) to meet

this requirement.

3.3.2 Growfh vananation among temporal cohorts

Inferred ages for the representative samples oflarvae ranged fi-om 3 to 39 days in

September, fi-om 3 to 39 days in October and fi-om 10 to 47 days in November. As age

data were obtained for only 52 individu& colIected in November the larvae included in

the analyses do not represent ali stations in constant proportion. The three temporal

coho~ts defined from the September, October and November coilections had inferred

hatchdates (date of capture - inferred age) of 28 August to 20 September (cohort-1,

N=165), 3 October to 25 October (cohort-2, N=101) and 29 October to 17 November

(CO hort-3, N=17) respectively (Table 3.1). The length-at-age data for cohort-3 are

presented for cornparison with cohorts- l and -2 (Fig. 3 - 5 ) but the data are not used in

further analyses due to the smali sarnple size-

The length-at-age relationships for cohorts-1 and -2 were best fit with linear least squares

regession (Fig. 3.5) and the dopes were not significantly different (ANCOVA, p=0.63)

between these temporal cohorts.

Sagittal surface area @m2)

Figure 3 -3- Residuals of the reiationship between larval TL and sagittal surface area for 127 siiver hake larvae collected on Western Bank, Scotian Shelf in October 1997- The numbers on the scattergram represent the stations fiom which individual larvae were CO llected.

Sagittal suiface area (pn2)

Figure 3.4. Least squares regression for the relationship between larval total length (TL) and sagittal surface area (SSA) for 127 Iarvae collected from Western Bank, Scotian Shelf in Octo ber 1 997 (TL=-5. 5+6. O L O ~ , ~ ( S ~ ~ ) ~ - ~ ; ?=O. 90). Solid lines are the 95% confidence bands for the regression and dashed lines are the 95% confidence bands for the prediction for an individuaf with a given sagittal surface area.

a Cohort- L (September) O Cohort-2 (October)

Age estimated fiom number of sagittaI increments (d)

Figure 3.5. Least squares regression of Iarval total Iength (TL) on age, as estimated fiom the number of daily sagittal increments, for silver hake Iarvae in cohorts-1 and -2 coI1ected on Western Bank, Scutian SheIf in September and October 1997. The relationships are linear for cohort-1 (TL=1.6+O.l8Age; r2=0. 65; N=165) and cohort-2 (TL=l. 7+û. 1 7Age; ?=O. 82; N=10 1) and the dopes are not significantly different (ANCOVA, p=0.63). The data for cohort-3 is inchdeci for cornparison but no Ieast squares regression was fit to the data due to the small sampIe size and limited range of both TL and estirnated age. The dotted (cohort-1) and dashed (cohort-2) Iines are the 95% confidence bands for the prediction for an individual of a given age in each of the cohorts.

AU of the larvae in cohort-2 and -52% of the Iarvae in cohort-1 were coIiected during

daylight. Daylight was defined as 07100 to 19:OO and 07:30 to 18100 local time (Atlantic

Standard Tirne) for cohort-1 and -2 respectiveiy. The slopes of the length-at-age

relationships for larvae caught during the day (TL= 1.7 +O. 17age; ?=0.73; N=86) and

night (TL=l.4+O.l9age; ?=0.58; N=79) in cohort-1 were not significantly different

(ANCOVA, p=0.35). Therefore, it was not necessary to separate the day and night

collections for the among temporal cohort length-at-age analyses.

The October larvae were collected at discrete depth strata while the September larvae

were collected within oblique tows. Larger and older larvae were couected at greater

depths in October, but there was no relationship between ASGR and depth of collection

within cohort-2 (ASGR=O. 1 6+4.7x104depth; ?=0.025, p=0.11). Therefore, variation in

the depth strata sampled in October relative to September is unlikely to confound the

comparison of growth rates between cohort-l and -2.

The temperature tirne series were similar among locations and depths over the crest of

Western Bank (Fig. 3.6). The estïmated GDD was 435°C-d for cohort-1 and 3 18°C-d for

cohort-2 (Fig. 3 -6). These GDD estimates represent average daily temperatures of -17OC

and -13 OC for larvae in cohort- 1 and -2 respectiveiy. The average (k 1 standard

deviation) zooplankton biomass was 0.14 t 0.08 1 g-rri3 for cohort-1 and 0.27 t 0.18 gmm3

for cohort-2. The average (i 1 standard deviation) concentrations of larvae were 4.9 + 4.5

Cohort-1 GDD j

230 240 250 260 270 280 290 300 310 320 330

Day of year

Figure 3.6. Temperature tirne series treated with a 25 point moving median for 28 August to 27 October 1997 (days 240 to 300) fiom 2 moorings over Western Bank with temperature recorders at both 2 m and 11 m depth. Growing degree days for cohort-1 and -2 were calculateci ushg the average temperature fiom the 4 recorders at noon of each day -

and 0.23 + 0.18 -m" and the average concentrations of siiver hake larvae were 4.5 f 4.4

and 0.22 t 0.18-m-' for cohort-1 and -2 respectively.

3.3.3 Growth variation within month& cohorts

The residuals of the length-at-age relationship for cohort-1 revealed a pattern that

reflected geographic location of capture, most notably with larvae collected at stations 3 3 ,

16 and 50 (Fig. 3.7a). Approximately, 79% of the larvae coUected at station 33 had

negative residuals while -92% and -93% of the larvae colIected at stations 16 and 50

respectively had positive residuds. ASGR (N=164) and AOGR (N=149) were calculated

for larvae within the September monthly cohort (larvae between 10 and 20 days of age at

capture). One additional Iarva was excluded because it had a preserved TL at capture of

less than 1.6 mm (the estirnated post-preservation hatching TL frorn the cohort-1 length-

at-ase relationship) that resulted in a negative ASGR As otoliths do not shrink with

preservation it is assumed the AOGR should provide a better measure of growth rate

throughout the Life of each fish. However, variabil* in the otoIith size-fish size

relationship may artificially create variability in the AOGR that does not reflect variability

in ASGR (AOGR = - ~ ~ + ~ . ~ x ~ o ' A s G R ; ?=0.59). AU analyses were, therefore, performed

with both ASGR and AOGR estirnates.

The single factor that explained the highest proportion of the variance in ASGR in the

September cohort was water depth (Table 3 -2). Salùuty averaged over the mixed layer

explained the highest proportion of the variance in AOGR (Table 3 -2). Multivariate

Age estimated fiorn number of sagittal incrernents (d)

Figure 3.7. Residuals of length-at-age relations for silver hake larvae in (a) cohort-l and (b) cohort-2 coilected f?om Western Bank, Scotian Shelf in September and October 1997 respectively. Numbers on scattergram represent stations from which larvae were collected.

Table 3.2. Least squares regression statistics (dope, intercept, r2) for the relationships between average somatic growth rate (ASGR; N=164) and average otolith growth rate (AOGR; N=149) and al1 physical and biological variables examined for 10 to 20 d old silver hake larvae collected on Western Bank, Scotian Shelf in September 1997. (*p<0.05, **p<O.OO 1).

AOGR

Variable Slope Intercept ? Slope Intercept ?

Water depth (m)

Salinity (psu)

Density (kg*m4)

Hake concentration (no..mJ)

Larval concentration (no.ems)

Zooplankton biomass (gmJ)

Hatchdate

Age (dl

Temperature (OC)

Growing degree days ("Cd)

Mixed layer depth (m)

Collection date

analyses using water depth, sahi ty and larval silver hake concentration explained 60% of

the variance in ASGR. Silver hake concentration had a negative coefficient and a marginai

(CS%), but significant, influence on the proportion of variance in ASGR explained by the

model. A multivariate model with water depth, saIinity and hatchdate explained 62% of

the variance in AOGR.

Water depth a d o r salinity appear to be important factors in explainhg the variance in

growth rates of larvai fish near Western Bank in S eptember 1997. In general, salinity and

water depth are correlated simply because higher salinity water typicaiiy occurs over

greater water depths on the Scotian Sheif Partial correlations between ASGR and water

depth with the effect of saiinity removed (Pearson r=0.52, Spearman r=0.46) and between

ASGR and salinity with the effect of water depth removed (Pearson ~0.25, Spearman

14.2 1) suggest that ASGR is more highly correlated with water depth than salinity.

Average (k 2 standard error) ASGR and AOGR caiculated for each 5m water depth

interval increased by -0.17 mm-d-' and 220 pm2-d-' respectively between depths of -40

and 95 m reflecting geographic location on and off the bank (Fig. 3 -8).

Contrary to the pattern observed in the residuals of the length-at-age relationship for

cohort-1, there was no pattern in the residuals of the length-at-age relationship for cohort-

2 (Fig. 3 -7b). The relationship between ASGR and AOGR was weak within the October

monthly CO hort (AOGR = -7.7 + 7.7~1 o2 ASGR; ?=0.20) perhaps reflecting the non-

linearity in the otolith-fish size relationship observed for CO hort-2. Consequently the

30 50 70 90 110 130 150 Water depth (m)

Figure 3.8. Average, + 2 standard errors, (a) somatic and (b) otolith growth rates for 10 to 20 day old silver hake larvae collected over Sm water depth intervals on Western Bank, Scotian Shelf in Septernber 1997. Numbers above each box plot represent the sample s izes .

results d iered for ASGR and AOGR within the October cohort, Significant linear

relationships were observed between AOGR and larval age, hatchdate and GDD (all inter-

related variables) while these relationships were weak for ASGR (Table 3 -3). Only weak

relationships were observed between ASGR or AOGR and any of the other biologïcal or

physical variables measured (Table 3.3). Date of collection was the same for ail larvae in

October and was, therefore, not included in the analyses. A multivariate model with GDD

and depth was able to explain ody 4.3% of the variance in ASGR within the October

cohort but a multivariate model with depth and age was able to explain 3 8% of the

variance in AOGR with only age contributhg sigmfïcantly to this model.

There was no signi£icant difference in the back-calculated TL-at-hatch for larvae collected

on (<70m depth) and off (XSm depth) the bank in September 1997 (ANOVA, p=0.27,

N=15). The rm MANOVA also indicated no signifmnt differences in the trajectories of

the back-cdculated length-at-age and daily growth rate series for 5 larvae fkom on- and

off-bank (p=0.41 and 0.27 respectively; Fig. 3.9). However, when these same 5 larvae

from each water mass were grouped to represent water mass-specific populations, the

length-at-age and daily growth rate slopes were each significantly greater for larvae

collected off-bank than on-bank (ANCOVA, p<0.00 1). Furthemore, when data for al122

larvae were compiled to define a single Iength-at-age and daily growth rate series for

larvae collected on- and off-bank, the s1opes for both series were again significantly

greater for l w a e collected off-bank relative to larvae collected on-bank (ANCOVA,

p<0.00 1 ; Fig. 3.2 0). Individual ANOVA at each increment (using data ti-om 22 larvae)

Table 3.3. Least squares regression statistics (slope, intercept, r2) for the relationships between average somatic growth rate (ASGR) and average otolith growth rate (AOGR) and al1 physical and biological variables examined for 10 to 20 d old silver hake larvae (N=53) collected on Western Bank, Scotian Shelf in October 1997. (*p<0.05, **p<0.001).

AOGR

Variable SIope Intercept r? Slope Intercept ?

Water depth (m)

Salinity (psu)

Density (kg.mW3)

Hake concentration ( n ~ . m ' ~ )

Larval concentration (n0.m-')

Zooplankton biomass (gemJ)

Hatchdate

A@ (dl

Temperature (OC)

Growing degree days (('Cd)

Mixed layer depth (m)

(b) - On bank larvae ----O- - - - Off bank larvae t O. - P

? - # SC'

3 4 5 6 7 8 9 10 Age estimated f!iom number of sagittal increments (d)

Figure 3.9. Individual (a) total length and (b) daily growth rate series (back-calculated using surfâce area of each increment and the biological inrercept model; Campana 1990) for 5 iarvae collected on-bank and 5 larvae collected off-bank near Western Ba& Scotian Shelf in September 1997.

-3 ,. -01 t 1 I I I 1 1 I I 1 1 1 I 1 I I f

-1 O Z 2 3 4 5 6 7 8 9 2 0 1 1 1 2 1 3 1 4 1 5 Age estimated fiom number of sagittal increments (d)

Figure 3.10. Average (a) TL and (b) daily growth rate (GR) series (back-calcuiated using surface area of each increment and the biological intercept model; Campana 1990) for silver hake larvae collecteci on and off Western Bank, Scotian S heif in September 1997. Nonlinear regressions fit using al1 estirnates are shown by the dashed (off-bank) and solid (on-bank) lines and regression equations and correlation coefficients are provided in the legends. Average (Il standard deviation) TL and daily growth rate esthnates and sample size are shown for each age (open syrnbols, off-bank and closed symbols, on-bank). S Iopes of the TL and daily growth rate series are significantly daerent for on- and off- bank larvae (ANCOVA, p<0.001). Ages for which signifiant difTerences are observed between on- and off-bank larvae are indicated (* pc0.005).

indicated that the average back-calculated length and growth rate at each increment were

not significantly dïerent (p0.005) for larvae collected on- and off-bank until increment 8

(Fig. 3.10). After this age, larvae collected h m off-bank were significantly larger at a

given age and had greater daily growth rates relative to larvae collected on-bank (except

when sarnple sizes were limited; Fig. 3.10).

3.4 Discussion

3-41 O tolith-fish size relationships

Although signifïcant linear relationships were observed between sagittal surface area and

l a r d TL for larvae collected in September, October and November, the slopes of these

relationships were diEerent. This is consistent with other studies that have shown that the

otolith-fish size relationship c m be dependent on temperature (h4osegaard et al. 1988) and

prey concentration (Secor et al. 1989) through their influence on somatic growth rate

(Secor et ai. 1989, Hovenkarnp 1990, Secor and Dean 1992). A widely supported

hypothesis suggests that faster growing larvae have smaller otoliths relative to body size

than do slow growing larvae (Secor et al. 1989, Hovenkarnp 1990, Secor and Dean 1992).

The resuks of this study, however, are inconsistent with this hypothesis arnong temporal

cohorts of silver hake larvae as the length-at-age relations were the same for cohort-1 and

-2 although the otolith-fish size relationships varied. This result is also consistent with the

non-linearity in the October otolith-fish size relationship that could not be explained by

ditferent length-at-age relations for lawae <6 m and 26 mm TL collected during this

sampling penod. However, within each of September, October and November a

sigdicant @<0.002) positive relationship between the residuals of the length-at-age

relationships and the residuals of the otolith-fish size relationships was observed. This is

consistent with the hypothesis that faster growing larvae have smaller ototiths relative to

body size than sIower gowing larvae. Thus, the explanation for variability in the otolith-

fish size relationships among temporal cohorts is not easily deterrnined with these data,

however variation in the otolith-fish size relationships w i t b cohorts can in part be

explained by growth rate. I conclude that the relationship between otolith and fish size in

silver hake larvae is not robust for larvae that have experienced a variety of environmental

conditions during development andor dflerent growth rates and thus ototith-fish size

models should be calculated independently for different cohorts of silver hake larvae-

Furthemore, it should be recognized that larvae growing faster or slower than the cohort

average may have individual otoiïth-fish size relations that daer fiom the cohort-specific

models. Thus caution should be taken when lanral size is back-calculated from otolith size

using the regression coefficients for a given cohort and the use of the biological intercept

model (Campana 1990), which does not rely on either the dope or intercept of the otolith-

fish size model, may be preferred. The hypotheses that otolith-fish size relationships Vary

throughout the Autumn and the variation among and within these relations is independent

of variation in length-at-age are tested using larvae collected in 1998 (see Chapter 4).

3 - 4 2 Growth variation amoizg temporal cohorts

The length-at-age relations developed for the temporal cohorts in this study were best

described by linear least squares regression and had slopes of 0.17 and 0.18 mmd-' for

cohort-1 and -2 respectively. To my knowledge, these are the first estimates of length-at-

age relations for silver hake larvae in the Northwest Atlantic. The slopes for cohort-1 and

-2 are s i d a to the length-at-age slope of -0.16 m d - ' reported for Pacific hake

(Mer~uccizis prodzcctz~s) lanrae <20 days o t d (Bdey 1 982, Butler and Nishirnoto 1997)

and are also within the range (0.135-0.279 rnm-d-=) reported by Cass-Cday (1997) for

Pacsc hake larvae coliected in envkonments with varying prey concentrations.

In this study, the length-at-age relations were not si&cantly different between cohort-1

and -2. This is surprising given the GDD for larvae differed by approxirnately 117"C.d (an

average difference in daily temperature of -4°C) and the zooplankton biomass was -2 fold

greater for cohort-2 than cohort-1.1 am confident of the reliability of the temperature data

given the nearly identical temperature recorded at 2 rn and 11 m depth at hvo rnoonngs

over Western Bank (Fig. 3 -6) and ali evidence suggesting that silver hake larvae reside in

the upper mixed Iayer (Fortier and Villeneuve 1996, C . Reiss, Department of

Oceanography, Dalhousie University, Halifax NS, B3H 451, unpublished data). 1 am more

wary of the interpretation related to zooplankton biomass as the collections were made

with dinerent mesh sizes and gear types for each temporal cohort (333 pm BONGO for

cohort- 1 and 243 prn BIONESS for cohort-2). However, Colton et al. (1980) found no

significant difference in the displaced volume of plankton (positively correlated with

plankton biomass; see Fig. 4.2) coUected with 253 pm and 333 prn mesh at tow speeds

similar to those used in this study (-1 to 2 knots). What is most important is the sidarity

in growth rates obsenred between temporal cohorts that have expenenced different

thermal and feeding enviroments. Neither temperature nor potential prey concentration

alone can explain the similar growth rates observed for cohort- l and -2 and, therefore, the

combination of these factors, and perhaps others, must be considered (e-g. Jones 1985,

Lemer and Shaw 1992, Amara et al. 1994, Betsill and Van Den Avyie 1997, Rutherford et

al. 1997, Gallego et al. 1999). Furthemore, these resuks indicate that larvae experiencing

diffierent environmental conditions c m not be assumed to have daerent growth rates.

Length-at-age relations did not differ significantly for larvae coiiected d u ~ g day and ni&

in September 1997 and thus 1 cm conclude that dserential gear avoidance due to day-

night sampling can not explain the similarïty in length-at-age between temporal CO horts.

The hypothesis that growth rate does not Vary with t h e of collection is tested usirig data

Eom 2 temporal cohorts collected in 1998 (Chapter 4). Larvae coiiected at different

depths in October also had sirnilar growth rates. This suggests that oblique tows may be

suEcient for studies of growth variation in silver hake larvae 125 days of age and larvae

collected fiorn different depth strata in October relative to September can not explain the

sùnilarity in length-at-age relations observed between cohort- 1 and -2. Furthermore, the

potentidy confounding influences of tirne and depth of collection are also unlikely to

affect the results of growth variation within monthly cohorts and thus need not be

considered fùrtber.

The obsenration that length-at-age was similar for temporal cohorts experiencing different

environmentai conditions, however surprising, is not unique. Yoklavich and Bailey (1990)

found no differences in growth rates of wdeye pollock larvae collected in diEerent years

despite variability in the average May temperature of -2°C (dzerence of -24 to 38 GDD

for 14 d old larvae based on ciifferences of 1.7 to 2.7"C in average May temperature

arnong years). Furthemore, no relationship was observed between growth rate and

temperature in Pacific hake larvae coilected at temperatures between 10-5 and 12-4OC

(dserence of -48 GDD for a 25 d old larvae experkncing daiIy temperature dzerences of

- l .g°C; Cass-Calay 2997). 1 hypothesize that the suniIarity in growth rates between

temporal cohorts in this study rnay be explained by: 1) insufficient variability in

temperature and zooplankton biomass to produce a measurable merence in growth rates

in the e s t 25 days post-hatch; 2) the combined effects of temperature and zooplankton

biomass (potential prey concentration) on growth; 3) enhanced prey requirement s for

larvae with increased metabolic rates related to higher water temperatures (Anderson

1988) that would suggest that prey concentration may play a role in deterrnining growth

rate; and 4) size-selective mortality acting on one or both of the temporal cohorts. The

first hypothesis is inconsistent with other studies and is unWcely given the large range in

temperature and potsntial prey levels experienced by cohort-1 and -2. However, the other

3 hypotheses are not easily disrnissed. The GDD experienced by cohort-2 was lower than

cohort-1 while the zooplankton biomass available at coliection for larvae in cohort-2 was

almost twice that available for larvae in cohort-1. Temperature and potential prey

concentration could, therefore, have acted in concert to resuk in sirnilar growth rates for

larvae in the two temporal cohorts (hypothesis 1) or the lower potential prey levels

available for larvae in cohort-1 may have been insufficient to meet the increased metabolic

demands incurred by the higher temperature (hypo thesis 2). Consistent with hypot hesis 4,

Barkrnan and Bengtson (1987) found that sunriving fish in two separate years (2 cohorts)

had almost identical growth rates despite variable environmental conditions in the two

years (including variable temperature). Therefore, perhaps in 1997 1 have sampled only the

survivors, with similar growth rates, of both cohorts-1 and -2. This would imply that size-

selective rnortality was acting within both temporal cohorts (but see below).

It will be difficult to distinguish between hypotheses 2 and 3 in field studies. However, the

hypot hesis t hat temperature and potential prey levels interact to deterrnine length-at-age

relations in temporal cohorts of silver hake larvae can be tested using independent data

sets where temporal cohorts of larvae have experienced diflFerent combinations of

temperature and zooplankton biomass variability. 1 predict that temporal cohorts that

experience either: 1) higher temperature and higher zooplankton biomass; 2) similar

temperature but higher zooplankton biomass; or 3) similar zooplankton biornass but higher

temperature; would have a growth advantage over larvae in less optimal environmental

conditions. This hypothesis is tested using larvae cotlected in Auturnn 1998 (see Chapter -

4)-

The similarity in the slopes of the length-at-age relations for cohorts-1 and -2, despite

varying environmental conditions, suggest that studying growth of silver hake larvae at the

monthly scale may be of limited use in predicting growth rates based on the environment

and ultimately will not prove useful in the prediction of s u ~ v a l based on growth ifsize-

selective predation is the driving force. Thus the prediction of growth, and ultimately

survivai, based on environmental variability may require the analysis of growth rate

variability at finer scales incIudimg within cohorts and among individual larvae (Rice et al.

1987, Pepin 1989, Rice et al. 1993, Chambers and Miller 2995, Rutherford and Houde

1995). This shidy benefits fiom a species and system in which these h e r scales of growth

variabifity can and have been exarnined.

3.4 3 Growfh vananafion within monthly coho~ts

The residuals of the length-at-age relationships indicated that growth varied systernatically

with geographic location withïn cohort-1 but not within cohort-2. The dzerent results

observed for cohort- 1 and -2 demonstrate the value of examining growth within multipIe

cohorts or months as conclusions based on the results of one cohort can not be assumed

to apply to others.

The mostly positive residuals for larvae collected in deeper water off the crest of Western

Bank during September suggests that larvae that are swept off the bank incur a growth

advantage over larvae that are retaùied on the bank. The higher individual growth rates

(ASGR and AOGR) for 10 to 20 day old larvae collected off the bank relative to those

collected on the bank in September is consistent with this pattern in the residuals. The

ASGR and AOGR show sirnilar patterns within September and thus 1 am confident of the

results related to growth variation withh the September cohort. However, in October

dEerent results were observed using the ASGR and AOGR and 1 am, therefore, wary of

the results related to growth variation within the October cohort. Both measures of

growth should be examined whenever possible and conclusions should be limited when

ASGR and AOGR results are inconsistent.

The variation in growth rate on- and off-bank indicates that growth is not homogeneous

around Western Bank durhg late September at scales of -15 km. This has serious

implications for sarnpling and the calculation of population or temporal cohort growth rate

estirnates as these could be easily skewed towards either low or high growth estimates

depending on the water masses in which the majority of sampiing is conducted. Ifgrowth

estimates are biased due to sarnpling the prediction of suMval based on growth rate will

also be compromised.

The mechanism that results in the growth advantage of larvae off the bank in the

September rnonthly cohort is unknown, however, in this system the shelf-break current is

bathymetncdy steered (Hannah et al. 2000) around Western Bank and, therefore, tarvae

off the bank are in a different water mass than those on the bank. PossibIe explanations for

the higher growth rates off the bank are: 1) size-selective predation on or off the bank; 2)

food-limitation on the bank where larval concentrations are high; 3) different origins for

on- and off-bank larvae and thus different larval growth trajectories fiom hatch; and 4) a

cornmon origin (the crest of Westem Bank; O'Boyle et al. 1984) for on- and off-bank

larvae and enhanced growth for individuals transported off-bank perhaps through the

reduction of density dependent processes related to low off-bank larval concentrations.

The sirnilar variance in growth rates on and off the bank and the negative relationship

between ASGR and larval concentration (hake or al1 species) are inconsistent with size-

selective predation (hypothesis 1). The negative relationship between ASGR and hake

concentration suggests that larvae on the bank may be food-limited at high l a r d

concentrations, however, no relationship was observed between somatic growth rate and

zooplankton biomass among locations on and around the bank and the results are,

therefore, inconsistent with food-limitation (hypothesis 2). Furthemore, McLaren et al.

(1997) concluded that although differences were observed in the taxa of prey items and

the ,out f i lhess of cod larvae collected fiom different water masses in the Western Bank

region during November 1992, the average gut fûhess was indexed as "partly füll" to

"quite fùll" in all water masses. This suggeçts that although dioerences in feeding among

water masses may occur, larvae do not appear to be food-limited in this system. The

analysis of individud growth trajectories for Iarvae collected on and off Western Bank

indicate that the back-calculated length-at-hatch was similar for ail larvae and the average

back-calculated length-at-age and daily growth rate of larvae fiom the two water masses

was similar until -8 days post-hatch. After this, the larvae coliected off-bank had both a

greater TL,-at-age and a greater daily growth rate than larvae collected on-bank. These

results suggest that larvae collected &om the on- and off-bank water masses likely had a

cornmon origin and that growth rates diverged -8 days post-hatch. This is inconsistent

with the hypothesis that larvae had dBerent origins and thus difEerent larval growth

trajectories f?om hatch (hypothesis 3) and is consistent with the hypothesis that larvae

shared a common origin and those individu& transported Eom the bank experience

enhanced growth (hypothesis 4). Using the scaluig arguments of Loder et al. (1 98 8), the

time scale for the along bank d a was estimated as -10 days ushg the average current

speed (-0.07 M-s-', fiom the current meter recorders) and the dong-bank length scale

(-60 km). This is of the same order as the observed divergence in growth rates of larvae

on and off the bank at 8 days post-hatch. I, therefore, hypothesize that growth variability

within montldy cohorts is in part deterrnined by larval transport and the resulting water

mass associations of larvae that are removed fiom or remain over the crest of the bank.

Thus the analyses of growth variation in relation to physical oceanographic conditions

(e-g transport, water mass characteristics) will be required for the prediction of l a n d

growth variation in space and analyses limited to consideration of historicdy important

environmental variables (e-g. temperature and prey concentration) may preclude the

identification of relationships between growth rate and the environment that may allow for

the prediction of s u ~ v a l . The hypothesis that Iarvae removed fiom the bank incur a

growth advantage over Iarvae that remain over the shailows of the bank will be tested with

larvae coUected in 1998 (see Chapter 4).

The differences in average growth seties on and off the bank are not supported statistically

by the repeated measures multivariate analyses of variance (rm MANOVA) performed

with 5 lawae from each water mass perhaps due to the small sample size andor the short

t h e series used for the rm MANOVA. However, even with the snali sample size, the

differences in growth trajectories are apparent among individuals and when the 5 larvae

from each water mass were treated as a population the slopes of the length-at-age and

daily growth rate senes for larvae coilected off-bank were significantly greater than the

slopes for lanrae collected on-bank. Thus, the rm MANOVA results should be interpreted

with caution especialiy as the individual series only extend over the fïrst 10 days post-

hatch and the separation in growth trajectones detennined at the population level only

become apparent at 8 days post-hatch. Thus, the average growth series for larvae

collected on- and off-bank is a better indicator of the divergence in growth rates of larvae

fkom the two water masses. The s m d sample size and short time series used in the rm

MANOVA were a hc t i on of electing to measure the more consemative and possibly less

biased surface area of each otoiith increment as opposed to increment widths dong a

single axis. The rneasurement of increment surface area requires exceptionally clear and

distinct otoliths and, therefore, restricts the sample size that c m be used in these analyses.

Although 1 recognize the technical constraints (time and otolith quality) involved in

m e a s u ~ g the surface area of individual increments it avoids choosing an axis of

measurement and incorporates growth on multiple axes of the otolith (Secor and Dean

1992, Sepulveda 1994).

The observation that larvae in September collected off Western Bank incur a growth

advantage over larvae of the same age that are retained on Western Bank is consistent

with the hdings of Buckiey and Lough (1987) and Frank and McRuer (1989) who

observed that haddock Iarvae in the shallow, mixed conditions on Georges Bank and

Browns Bank respectively were in worse condition than larvae collected in deeper,

stratified waters. Furthemore, the observations in this study that growth of silver hake

larvae is enhanced off the shallows of a bank is not inconsistent with results reported by

Taggart et al. (1 989) who found larvae of a variety of species (cod, lumpfish, agonidae)

were larger in the higher salinity, deeper stratined waters than in the lower saIinity water

over the Akpatok Shallows. They hypothesized that the occurrence of larger larvae in the

deeper water could be a result of: 1) oIder and, therefore, larger larvae; or 2) faster

growing larvae and dflerentid mortality. Evidence Eom this study is consistent with the

observation that faster growing larvae are found in deeper, higher salinity water masses-

In contrat to that observed in September, no relationship was observed between grawth

rate and water mass charactenstics or geographic location (or any of the biological

variables measured) in October 1997 as was suggested by the lack of pattern in the

residuals of the length-at-age relationship for cohort-2. The observation that growth rate

varied systematically within cohort-1 but not within cohort-2 could be the result of the

spatiaily constrained samples collected in October and consequently the iimited water

masses fiom which larvae were coiiected. The September collections were re-sampled to

approximate the spatial distribution of the October collections to test this hypothesis. The

proportion of the variance in growth rates explained by environmental variables (water

depth, salinity, density, Iarval concentration, hake concentration and zooplankton biomass)

decreased when the September collections were spatialiy constrained. Therefore, 1 can not

reject the hypothesis that the lack of pattern in the October data is in part due to the

spatially constrained samples collected during this period. This hypothesis is again tested

with data coilected in 1998 (Chapter 4).

Based on hypotheses that suggest that larger or faster growing larvae have a s u ~ v a i

advantage over smaller, slower growing Iarvae (MilIer et ai. 1988, Rive et al. 1993,

Campana 1996, Meekan and Fortier 1996, Hare and Cowen 1997) the results of this

study suggest that survival should be greater for silver hake larme that are rernoved fiom

the crest cf Western Bank early in developrnent. Thus, examining lanral distributions in

relation to transport mechanisms and water mass characteristics within monthly cohorts

may prove useful in predicting variability in larval s u ~ v a l based on growth variability.

Chapter 4:

Test of Hypotheses Related to Growth Variation Among Temporal and Within Monthly Cohorts

4.1 Introduction

Many studies on l a n d growth andior survival in fishes base conclusions on a single year

of data without t esting hyputheses and/or assumptions using independent data. Taggart

and Frank (1990) suggest that this may in part be responsible for the low predictive ability

of recmitment variation. In a survey of 60 studies published since 1980, nearly 50% of the

studies based thek conclusions about growth andor survival variation of l a r d fish on a

single year of data (Table 4.1). Some of these studies did expand their data sets in further

publications (e.g. Townsend and Graham 1981, Bolz and Lough 1983, Kisrboe et al.

1988), however, explicit tests of hypotheses were scarce. Post-publication fdure and poor

predictive power due to smail sample sizes c m be related to the number of independent

data sets upon which conclusions are developed. Taggart and Frank (1990) suggest that

these are two of the reasons why researchers are wary of conclusions related to

recruitment and environrnental variables. Thus, to predict larval growth, and ultimately

recruitment, from environmental variation, hypotheses must be explicitly tested with

independent data. The faiIure to do so may have consequences for the relations between

growth, recruitment and the envirorient and for the predictive power of growth and

recruitment based on environrnental measures.

S I

Table 4.1. Results of a literature survey of 60 papers published since 1980 on growth andor s u ~ v a l variation of larvai fish showing the number of independent data sets bears of data) upon which conclusions were based. Nearly 50% of these studies based their conclusions on a single year of data.

Reference Years Reference Years of data of data

Amara et al. 1994 1 Barkrnan & Bengtson 1987 I Bolz & Lough 1983 1 Buckiey & Lough 1987 1 Cass-Calay 1997 1 Fitzhugh et al. 1997 1

Fortier & Gagné 1990 1 Fowler & Short 1996 1 Gallego et al. 1996 1 Gallego et al. 1999 1 &cia et al. 1998 1 Hovenkarnp 1989 1 Hovenkamp 1990 1 Jenkins 1987 1 Jenkins & Davis 1990 1 Kiorboe et al- 1988 1 Lang et al. 1994 1 Le& & Houde 1987 1 Lough et al- 1982 I Maillet & Checkley 199 1 1 Morales-Nin 1987 1 Munk 1993 1 Munk et al. 1991 1 Oxenford et al. 1994 1 Palomera et al. 1988 1 Sepulveda 1994 1 Suthers & Sundby 1993 1 Thorrold & McBWilliams 1989 1 Townsend & Graham 198 1 1 Grimes & Tsely 1996 1 to 4

Suthers & Sundby 1996 Bailey et al. 1995 Betsill & Van Den AvyIe 1997 Campana 1989 Castro & Cowen 199 1 Fortier & Quinonez-Velazquez 1998 Jones 1985 Leffler & Shaw 1992 McGurk 1987 Meekan & Fortier 1996 Nishimura & Yamada 1984 Penney & Evans 1985 Suthers et al. 1989 Thomas 1986 Rutherford & Houde 1995 Rutherford et al. 1997 Govoni et al, 1985 Graham & Townsend 1985 Haldorson 19 89 Hovenkarnp & Witte 199 1 Jordan 1994 Neilson et al. 1985 Peters & Schmidt 1997 WarIen 1988 BoIz & Lough 1988 Yoklavich & Bailey 1990 Campana 1996 Bolz & Burns 1996 Koutsikopolous et al. 1989 Mooij & van Nes 1998

Independent collections of silver hake Iarvae and oceanographic conditions in 1997 and

1998 provided me with the opportunity to test the hypotheses examined in Chapter 3. The

hypotheses tested in this chapter are: 1) otolith-fish size relations are not significantly

dïerent among cohorts of larvae; 2) variation in otoiith-fish size relations among

temporal cohorts is independent of variation in length-at-age relations; 3) variation in

otolith-fish size relations within cohorts is independent of variation in individual growth

rate; 4) length-at-age relations are not significantly dBerent among temporal cohorts

throughout the Autumn; 5) length-at-age variation among temporal cohorts is independent

of temperature alone; 6 ) length-at-age variation among temporal cohorts is independent of

potential prey concentration alone; 7) length-at-age variation among temporal cohorts is

independent of the combined influences of temperature and potentid prey concentration;

8) length-at-age relations within temporal CO horts are not significantly different for larvae

collected during day and night; 9) growth variability within monthly cohorts is independent

of water depth, representing geographic location around Western Bank; 10) growth

variation within monthly cohorts is independent of the spatial distribution of larval

collections; and Il) growth variation within monthly cohorts is independent of physical

oceanograp hic conditions.

4.2 Methods

4.2. I Oceanographic smpling and data collecîiorz

Larvae and hydrographic data were collected fiom the Western Bank region (Fig. 4.1)

Figure 4.1. Bathymetnc chart ofthe Western Bank region, Scotian Shelf showing 40,60,80, 100 and 200 m isobaths and showing locations fiom which silver hake larvae were collected in (a) October and (b) November 1998 and (c) location of temperature recorders rnoored at 9m depth (closed circles) and the location of surface temperature measurements provided by PanCanadian (P). On charts (a) and (b) numbers represent stations fkom which larvae assigned to cohorts-A and -B (aged O to 25d) were collected. On chart (a) diarnonds represent additional stations fiom which larvae included in the within monthiy cohort analyses were collected and squares represent additional stations fiom which >10 silver hake larvae were collected. On chart (b) pluses represent additional stations fiom which >IO silver hake lamie were collected.

between 28 September and 21 October (P98058, CCGS Pmieazr; Hazen and Reiss 1999)

and between 12 Novernber and O I December 1998 (N98068, CCGS Needler; Power

1999) hereafler referred to as October and November sampling periods. Tn October larvae

were collected using a 63 cm diarneter BONGO sampler (Posgay and Marak 1980) fit

with 333 pm-mesh nets and a Lm2 BIONESS (Sarneoto et al. 1980) fit with ten 333 Pm-

mesh nets. In October two collections (-LOm above bottom to the surface and pycnocline

to the surface) were made zt each station when the BONGO sarnpler was used. Only the

collections made fiom -1Om above the bottom to the surface were used in this study. The

starboard and port collections were preserved in ethanol and formalin respectively as

detailed in Chapter 3. One BIONESS sample was collected from -10 rn above the bottom

to the surface and between 3 and 6 samples were coilected over discrete depth strata. The

oblique BIONESS collections were preserved in ethanol and all depth discrete sarnples

were preserved in formalin-

In November 1998 larval fish were coUected using a 6 1 cm BONGO sarnpler fit with 3 33-

pm mesh nets and the sarnples were coiiected through the water column fiorn -5 m above

the bonom to the surface. Samples were preserved as above.

Formalin-preserved larvae collected with the BONGO and formalin- and ethanol-

preserved larvae collected with the BIONESS were idensed to species and enumerated.

The number of silver hake larvae in the formalin-preserved BONGO and ethanol-

preserved BIONESS collections were used to determine the sarnple collections that would

be used in the analyses and the number of ethanol-preserved larvae that would be selected

for otolith analyses.

Depth-averaged zooplankton wet biomass was determined for each collection

using the formalin-preserved sarnpIes as detailed in Chapter 3 . Zooplankton wet weight

was not measured for the formalin-preserved collections in November and was, therefore,

esthated fiom the measured displaced volume of the plankton coiiections. A Iinear

regression was used to estimate the relationship between displaced volume (Pm$ and wet

weight (P,) for formaiin-preserved plankton sarnples (Fig. 4.2) using coilections fiom

November 1997 (N9770), July-August 1998 (P98035), August 1998 (P98038) and

October 1998 (P98058). This relationship explained 80% of the variance in wet weight

(Loglo(Pm) = 00.034 + 0.89LogLo(PWi); r2=0.80; Fig. 4.2) and was used to estirnate the

zooplankton biomass f?om the displaced volume for the formalin-preserved collections in

November. The average zooplankton biomass £tom the formalin-preserved collections was

calculated for each of the temporal cohorts fiom the station-specitic data.

4 2.2 Hydrography

Conductivity (C) and temperature (T) at depth @) were measured at each station in

October and November using a BSeabird SBE-25 CTD profiler. Temperature data were

recorded at ?4 hour intervals between 1 August and 16 to 18 October 1998 at 2 moorings

located over the crest of Western Bank (Fig. 4.1~). At each mooring temperature was

measured ushs temperature recorders (Vemco, Inc., Dartmouth, Nova Scotia) moored at

Plankton displaced volume (mL)

Figure 4.2- Least squares regression for the relationship between wet weight of plankton (PM) and displaced volume of plankton (PWi) fiom formalin-preserved collections (Loglo(P4 = 0.034 t 0.89Log~~(P,,); ?=O. 80; N=223). Solid lines are the 95% confidence bands for the regression and dashed Iines are the 95% confidence bands for the prediction for an observation given a known displaced volume.

-9 m depth. Sea surface temperature recorded using an i&ared themorneter (Everest

mode1 230, Everest Interscience Inc., Tucson, AZ) at 3 hour intervals between 0 1 August

and 30 November (43.8O N, 60.7O W) were also provided by PanCanadian Resources

(Halifax, Nova Scotia; Fig. 4. lc).

4 2-3 Data anaiyses

Larvae were measured, otoliths prepared and rneasured and ages estimated as described in

Chapter 2. In October, 10% of the larvae collected at each station were selected for

otolith analysis. Therefore, stations with less than 10 silver hake Iarvae were not included

in the length-at-age analyses. In November ali ethanol-preserved larvae from stations with

>10 silver hake were selected for otolith analysis (see Table 4.2 for the number of larval

collections and sample sizes for each sampling period).

The relationship between sagittal surface area and larvai TL was determined separately for

a representative sample of larvae coliected during each samphg penod in 1998. The

slopes of the otolith area-fish TL relationships were compared between sampiing penods

in 1998, among aii sampling penods in 1997 and 1998 and between larvae pooled by year

(1997 and 1998) using ANCOVA-

Temporal cohorts were defined as larvae coilected from a single sampling period with

Sen-ed ages between O and 25 d at capture, analogous to the temporal cohorts defined h

Chapter 3. lnferred hatchdates (date of capture-inferred age) did not overlap for the two

Table 4.2. Summary of silver hake larvae collected, analyzed and assigned to each of cohort-A and -B in October and November 1998. Values in brackets represent the number of stations from which larvae were collected.

Cw ise Sampling period Estimated no. of No. of larvae No, of larvae Cohordl Inferred Iiatchdates larvae available aged (no. 525 d (no.

(no. stations) stations) stations)

P98058 28 Sept. to 21 Oct. 1430 (52) 122 (1 7) 109 (1 6) A 07 Sept. to 04 Oct.

NP8068 12 Nov, to 01 Dec, 226 (34) 113 (9) 61 (7) R 23 Oct. to 17 Nov,

temporal cohorts (hereafter referred to as cohort-A and -B to avoid confiilsion with

cohorts 1 to 3 in 1997; Table 4.2). The slopes of the length-at-age relations were

compared between cohort-A and -B in 1998, among al1 temporal cohorts in 1997 and

2998 and among larvae aged O to 25 days pooled by year using A N C O V L

The integrated temperature (GDD; OC-d) and daily average temperature foc larvae in

cohort-A was calculated as described in Chapter 3 using the temperature tiZme series

measured at 2 rnoorings located over the crest of Western Bank. The temperature

recorders were retrieved pnor to the hatchdates for cohort-B. Therefore, sea surface

temperature measured every 3 hours provided by PanCanadian was used t o esthate the

GDD and daiiy average temperature experienced by larvae in cohort-B. The PanCanadian

data were treated with a 5 point moving median and the temperature each day at noon was

used as the daily temperature estirnate. A linear regression was used to estiimate the

relationship between the daily PanCanadian temperature (TPC) and the average daily

temperature measured at the temperature recorders (TTR) for 07 Septembe~ to 0 1 October

1998 and both an off-set and a dope greater than one were observed (T---Z.6+f. ~TTR;

?=0.21). Thus, the temperature recorded by PanCanadian was consistently- lower than that

measured by the temperature recorders for this t h e period and a correctiom to the

PanCanadian data using the linear relationship between the two temperature series was

deemed necessary. This relationship was tested using the temperature measured by the

temperature recorders and the PanCanadian data for 0 1 to 3 1 August. The relationship

failed for August 1998 as the relationship between the temperature recorder data and the

PanCanadian data was insignïfïcant before and after the correction ( h . 0 1). However, as

no better correction is available, the equation was then used to correct the PanCanadian

temperature data for 23 October to 16 Novernber and the corrected data was used to

estirnate the GDD and daily average temperature for cohort-B. The results should,

however, be interpreted with caution due to the uncertainty in the correction.

The residuals of the length-at-age relations for cohort-A and -B were examined for

patterns associated with location of collection. Individual average somatic (ASGR) and

average otolith growth rates (AOGR) were calculated for 10 to 20 day old tarvae as

detailed in Chapter 3 (equations 3.1 and 3 -2). These larvae represent the monthly cohorts

in 1998 and wiii be referred to as the October 1998 and November cohorts. The estimated

otolith area-at-hatch was ornitted fiom equation 3 -2 as substituting the estimated TL-at-

hatch (Lh) into the otoiith-fish size relationship for each of cohort-A and -B resulted in a

negative or zero otolith area-at-hatch. The AOGRs are, therefore, usefùl for relative

comparisons of growth rates within monthly cohorts but cannot be used to compare

AOGR among cohorts. This does not hinder the analyses in this study as comparisons of

AOGR among monthly cohorts is not deemed necessary. ASGR and AOGR were

examined in relation to water depth and the sarne physical and biological variables used in

Chapter 3.

OtoIith microstructure of 7 individuds between 10 and 20 days of age fiom two defined

water masses in November 1998 were used to fürther examine growth variability among

ïndividuals as in Chapter 3- The total otolith surface area was measured at each well

defined increment whenever possible. Sornatic size was back-calculated using the

biological intercept mode1 (Campana 1 990) and the biological intercept defined in Chapter

3 (TL=1.5 mm; ~ ~ = 2 2 5 p n ~ ) . TL- and growth rate-at-age series were back-calculated for

each individual. The larvae fiom each water mass were grouped and the slopes of the TL-

and growth rate-at-age trajectorïes (using log, transformed data) were compared between

the water masses using N O V A The average TL and daiiy growth rate for each age

were also compared between larvae ~ o m each water mass using ANOVA-

4.3 Results

4-3.1 O t o l i t h - - size reIationships (hypotheses 1 to 3)

Significant (p<0.00 1) hear relationships were observed between TL and sagittal surface

area for lanrae colIected in October and November 19%. The slopes of these relationships

were not ~i~onificantly different (although marginal) throughout the auturnn of 1998

(ANCOVA p=0.063; Fig. 4.3). This is contrary to the observations in 1997 where the

otoIith-fish size relationships were signifïcantly dBerent for larvae collected in September,

October and November and, therefore, in 1998 1 cannot reject the hypothesis that otolith-

fish s i x relations are not significantly difEerent among cohorts of larvae (hypothesis 1).

The slopes of the sagittal area - larval TL relationships were signincantly dEerent

(ANCOVA p=0.00 1) arnong sarnpling penods in 1997 and 1998 when each survey was

considered separately (September 1997, October 1997, November 1997, October 1998

O 2500 10000 22500 40000 62500 Sagittal surfàce area @m2)

Figure 4.3. Least squares regressions for the relations hips between sagittal surfàce a r a and larval total length for silver hake larvae coliected on Western Bank, Scotian Shelf during (a) Octo ber TL=^ .5+0.042(~~~)"'; r2=0. 96; N=113) and (b) November TL=^. SM. 03 9(ssA)*-'; r2=0. 82; N=I 1 O) 1 998. Sagittal surface area was square root transfomed to linearize the relat ionships. The dopes are not significantly diEerent between October and November (ANCOV4 p=0.063). Solid lines are the 95% confidence bands for the regressions and dashed lines are the 95% confidence bands for the prediction for an individual with a given sagittal surface area

and November 1998). However, there was no significant dflerence in the slopes of the

otolith-fish size relationships between 1997 (sIope=0.044) and 1998 (slope=0.043)

(ANCOVA, p=0.39; Fig. 4.4) when data were pooled by year. Thus 1 must reject the

hypothesis that otolith-fish ske relationships are not signïficantly diierent throughout the

Autumn when each month is considered separately. However, at the annual scale, the

otokh-fish size relations were similar and thus consistent with the hypothesis that annual

cohorts have similar otolith-fish size relations.

The otolith-fish size relationships for cohort-A and -B in 1998 were similar despite

variation in the length-at-age relations for larvae in the two temporal cohorts. This is

contrary to the observations in 1997 when otoiith-fish size relations were dserent but

length-at-age relations were sirnilar for cohort-1 and -2. In both years, however, 1 cannot

reject the hypothesis that variation in otolith-fish size relations among cohorts is

independent of variation in length-at-age (hypothesis 2). As in 1997, significant @<0.001)

positive relationships were observed between the residuals of the length-at-age reIations

and the residuals of the otoIith-fish size relations within October and Novernber 1998.

Thus, 1 again reject the hypothesis that variabiiity in otolith-fish size relations within

cohorts is independent of variability in individual growth rate (hypothesis 3).

43.2 Grow th variafion among temporal cohorts (i5pothese.s 4 to 8)

Contrary to that observed in 1997, the slopes of the length-at-age relations for cohorts-A

and -B in 1998 (0.24 and 0.15 mm-ddL respectively) were significantly different

O 2500 1 O000 22500 40000 62500 Sagittal surface area (pn2)

Figure 4.4. Least squares regressions for the relationships between sagittal surface area and Iarval total length for silver hake larvae collected on Western Bank, Scotian Shelf during the auturnn of 1 997 TL=^ .7-k0.044(~~~)*-~; r2=0.84; N=33 9; solid line) and 1998 (TL=l .8+0 .043(~~~)~-~ ; r2=0. 9 1; N=223 ; dashed line). The slopes are not significantly different between 1997 and 1998 (ANCOVA, ~ 4 . 3 9 ) . Dash-dot (1997) and dotted (1 998) Iines are the 95% confidence bands for the prediction for an individual with a given sagittal surface area in 1997 and 1998.

(ANCOVA p<0.00 1; Fig. 4.5)- Larvae collected in October (cohort-A) had a size-at-age

advantage over larvae collected in November (cohort-B). Thus 1 must reject the

hypothesis that length-at-age relations are not significantly different among temporal

cohorts of larvae hatched throughout the Auturnn (hypothesis 4)-

The slopes of the length-at-age relationships for larvae collected in 2997 and 1998 were

signincantly dflerent when temporal cohorts were considered separately (cohorts-1, -2, -

3, -A and -B; ANCOVA p<O.OOl). The result of the ANCOVA did not change with the

omission of the data-limited cohort-3. When ali larvae were pooIed by year the slopes

were again significantly different between 1997 and 1998 (ANCOVA p=0.042). The

slopes of the length-at-age relations were 0.17 mmd-' in 1997 and 0.19 mm-d-L in 1998

when ail temporal cohorts were pooled (Fig 4.6). 1, therefore, again must reject the

hypothesis that length-at-age relationships are not si34cantly different among temporal

cohorts of larvae.

The GDD for cohort-A was 427 OC-d and for cohort-B was 275°C-d (Fig. 4.7)

representing average daily temperatures of -17°C and 11°C for cohort-A and -B

respectively. These are similar to the GDD's of 435 OC-d and 3 18 OC-d (average daiIy

temperatures of - 17°C and 13 OC) calculated for cohort-1 and -2 respectively in 1997 (see

Table 4.3). However, contrary to the observations in 1997, temperature variation alone in

1998 can in part explain length-at-age variation between temporal cohorts (hypothesis 5) .

Age estimated fiom number of sagittal increments (d)

Figure 4.5. Least squares regressions for the length-at-age relationships of larvae in cohort-A (TL=l. 5M.24Age; r2=0. 88; N=lOg; so lid h e ) and CO hort-B (TL=2.2+0.1 SAge; r2=0.68; N=61; dashed line) collected on Western Bank, Scotian S helf during October and November 1998 respectively. The slopes are significantly different between CO hort-A and -B (ANCOVA, p<0.001). Dot-dash (cohort-A) and dotted lines (cohort-B) are the 95% confidence bands for the prediction for an individual with a given age in cohort-A and -B.

Age estimated fiorn number of sagittal incrernents (d)

Figure 4.6. Least squares regressions for length-at-age relationships of larvae collected on Western Bank, Scotian S helf in autumn of 1997 (TL=1.7+O.l7Age; r2=0. 76; N=283 ; solid line) and 1998 (TL=1 %O. 19Age; r2=0.8 1 ; N=170; dashed line). The slopes are significantly different between 1997 and 1998 (ANCOVA p=0.042). Dot-dash (1997) and dotted (1998) lines are the 95% confidence bands for the prediction for an individual with a given age in 1997 and 1998.

Day of year

Figure 4.7. Daily temperature t h e series on Western Bank rneasured at 2 temperature recorders at 9m depth between 07 September and 01 October 1998, raw data provided by PanCanadian, and corrected PanCanadian data for 23 October to 16 November 1998. The PanCanadian data were corrected using the relations hip between the temperature series fiom the temperature recorders (Tm) and the raw PanCanadian data (TpC) for 07 September to 01 October (Tpc=-2.6+l.lTTR; 24-21) . The GDD for cohort-A was calculated using the average of the two temperature recorders and the GDD for cohort-B was calculated us ing the CO rrected PanCanadian data.

Table 4.3. Surnmary table of the slope of the length-at-age relationship for cohorts-1, -2, -A and -B and the average GDD and zooplankton biomass experienced by larvae within each temporal CO hort-

Cohort Inferred Slope of length- GDD (OC-d) Average (k 1 hatchdates at-age standard deviat io n)

relationship zooplankeon biomass (mm-d-') (g. m-3)

1 28 Aug. to 20 O. 18 43 5 0.14 f 0.081 Sept. 1997

A 07 Sept. to 04 0.24 427 0.30 t O, I 1 Oct. 1998

B 23 Oct. to 17 O. 15 275 0.17 f 0,050 Nov. 1998

The higher growth rate observed for cohort-A is consistent with the higher temperatures

experïenced by larvae in thns temporal cohort.

The average (+ 1 standard deviation) zooplankton biomass for the stations represented in

each temporal cohort in 1998 was greater for cohort-A (0 -30 + 0.1 1 g-m-') than for

cohort-B (0.17 + 0.050 g-rnrn3; see Table 4.3). The opposite trend was observed in 1997

with higher potential prey concentrations associated with the later cohort (0.14 + 0.08 1

and 0.27 f 0.18 g+m-3 for cahort- 1 and -2 respectively). Hïgher zooplankton biomass

earlier in the season in 1998 is consistent with the observed greater length-at-age for the

earlier temporal cohort. Thaxefore, unlike in 1997, tbis is inconsistent with the hypothesis

that length-at-age variation among temporal cohorts is independent of potential prey

concentration alone (hypothesis 6). However, temperature and prey concentration

together are also able to extplain the growth variation between cohort-A and -B and thus 1

reject the hypothesis that lemgth-at-age variation among temporal cohorts is independent

of the combined influences lof prey and temperature (hypothesis 7).

Sirnilar to the observations in 1997, the slopes of the length-at-age relationships were not

signifÏcantly difEerent for larvae collected during the day and night within cohort-A or -B

in 1998 (ANCOVA p=0.70 and p=0.97 respectively). Daylight was defined as 06: 15 to

1730 for cohort-A (as per a u ~ s e and sunset on 09 October 1998) and 07:OO to 16:30 for

cohort-B (as per sumise and sunset on 19 November 1998) local time. I, therefore, cannot

reject the hypothesis that length-at-age relationships are not significantly different for

larvae coilected during day and night (hypothesis 8) and the observed variability in growth

rates among or within cohorts in 1998 cannot, therefore, be attriiuted to time of

collection. The slopes of the length-at-age relationships were also not significantly

different for larvae collected with the BONGO (slope =O -22 mm-d-') and BIONESS

(slope=0.24 mm-d-l) sarnplers in October 1998 (cohort-B; ANCOVA p=0.46). This

suggests that the use of different sarnpling gear wilI also not confound the resdts of

growth variation either among temporal cohorts or within monthly cohorts.

4-3.3 Growrh variation withn rnonthly cohorts Fyporheses 9 tu I l )

The ASGR and AOGR for 10 to 20 day old larvae coliected over 5 m water depth

intervals in October and November 1998 were compared to test the hypothesis that lanral

growth variation within cohorts is independent of the depth of the water column

(geographic location relative to Western Bank). Larvae between ZO and 20 days of age

collected in each month define the two monthly cohorts in 1998, hereafter referred to as

the October 1998 cohort and November cohort. Unlike in 1997, there were no significant

differences (p0.05) in ASGR or AOGR for larvae collected over different water depths

within either of the monthly cohorts in 1998 (Fig. 4.8 and 4.9) and 1, therefore, cannot

reject the hypothesis that growth variation within rnonthly cohorts is independent of water

depth (hypothesis 9).

30 50 70 90 110 130 150

Water depth (m)

Figure 4.8. Average, + 2 standard errors, (a) somatic and (b) otolith growth rates for 10 to 20 day old silver hake larvae collected over Sm water depth intervals near Western Bank, Scotian Shelf in October 1998. Numbers above each box plot represent the sample sizes.

30 50 70 90 110 130 150 Water depth (m)

Figure 4.9. Average, t 2 standard mors, (a) somatic and (b) otolith growth rates for 10 to 20 day old silver hake lawae collected over Sm water depth intervals near Western Bank, Scotian Shelf in November 1998. Numbers above each box plot represent the sarnple sizes.

The residuais of the length-at-age relation for cohort-A did not indicate any pattern that

reflected geograp hic location of capture (Fig. 4.1 Oa). In cohort-B, however, weak pattern

in the residuds was observed with 75% of the larvae collected fkom station 23 (off-bank)

and 83% of the larvae fiom station 102 (on-bank) displaying positive residuals (Fig.

4. lob). In both 1997 and 1998 one tempord cohort only (cohort-1 in 1997 and cohort-B

in 1998) displayed variation that codd be explained by location of collection ancilor water

mass structure. 1 hypothesized that the lack ofgrowth variabiliq in cohort-2 in 1997 was

due to the spatially constrained sarnples and 1 provided supporting evidence for this

hypothesis. In 1998, however, the collections in cohort-A had a greater spatial coverage

and were taken fkom water masses with greater spatial variation in temperature and

sa l i n i t y than cohort-B, and 1, therefore, cannot reject the hypothesis that the limited

growth variation observed within cohort-A in 1998 is independent of the spatial

distribution of the Iarvai collections (hypothesis 10).

For direct comparisons with the results presented in Chapter 3, the relationship between

ASGR and AOGR and a suite of physical and biological environmental variables were

assessed. Within the October 1998 cohort no significant @<O. 05) relationships were

observed between ASGR and any of the variables exarnined, but AOGR was signincantly

related to GDD, hatchdate, age, l a r d concentration and larval hake concentration (Table

4.4). A multivariate mode1 with water depth and concentration of silver hake larvae was

only able to explain 8.6% of the variance in ASGR within the October 1998 cohort and

neither variable explained a significant proportion of the variance in the multivariate

O 2 4 6 8 10 12 14 16 18 20 22 24 26 Age estimated &om number of sagittal increments (d)

Figure 4.10. ResiduaIs o f the length-at-age relationships for silver hake larvae in (a) cohort-A and (b) cohort-B coiiected in October and November 1998 respectively on and around Western Bank, Scotian Shelf Numbers on the scattergram represent the stations fkom which larvae were collected-

Table 4.4. Least squares regression statistics (slope, intercept, r2) for the relationships between average somatic growth rate (ASGR; N47) and average otolith growth rate (AOGR; N=5 1) and all pliysical and biological variables examined for 10 to 20 d old silver hake larvae collected on Western Bank, Scotian Shelf in October 1998. (*p<0.05, **p<0.001).

AOGR

Variable Slope Intercept 3 Slope Intercept r2

Water depth (m)

Salinity (psu)

~ e n s i t ~ ( k ~ 8 m")

Hake concentration (r10.m'~)

Larval concentration (no. 9mJ)

Zooplankton biomass (gm-3)

Hatclidate

Age (4 Temperature ("C)

Growing degree days ("Cd)

Mixed layer depth (m)

Collection date

0.040

0.047

0,064

0.11*

O, IO*

0.05 1

0,13*

0,43**

q0.01

0,44**

<0.0 1

<o.o 1

model. A model with GDD and concentration of siiver hake Iarvae was able to explain

5 1 % of the variance in AOGR with both variables contributing significantly to the

proportion of the variance explained. The proportion of the variance in ASGR and AOGR

explained by these multivariate models in October 1998 is similar to the observations for

the October cohort in 1997 where a multivariate mode1 with GDD and water depth was

able to explain only 4.3% of the variation in ASGR but water depth and age were able to

explain 38% of the variation in AOGR. The similar results within these two monthly

cohorts, despite inferred hatchdates that difFered by -21 calendar days, suggest that

cohorts with similar patterns of growth variation can not be identifïed based on hatchdates

alone.

Densis was the single variabIe that explained the greatest proportion of the variance in

ASGR within the Novernber cohort (Table 4.5). Larvae coliected f?om lower density

water had greater average somatic growth rates than larvae fiom higher density water

(Fig. 4.11). Other significant (p<0.05) relationships between ASGR and temperature,

salinity, Mxed layer depth and date of collection were observed (Table 4.5). Variance in

AOGR within the November cohort was explained in equal proportion by temperature,

hatchdate and collection date (all with ?=0.25) with density the only other variable that

explauied a signincant proportion of the variability in AOGR (Table 4.5). Multivariate

regession models including age and GDD explained 50% of the variance in ASGR and

33% of the variance in AOGR within the November cohort. Both age and GDD

contributed signincantly to the mode1 for ASGR but only GDD contributed significantly to

Table 4.5. Least squares regression statistics (dope, intercept, r2) for the relationships between average somatic growth rate (ASGR; N=18) and average otolith growth rate (AOGR; N= 18) and al1 physical and biological variables examined for 1 O to 20 d old silver hake larvae collected on Western Bank, Scotian Shelf in November 1998. (*p<0.05).

Variable

Water depth (m)

Salinity (psu)

Density (kg-mm3)

Hake concentration (no;mJ)

Larval concentration (no..m4)

Zooplankton biomass (g-m*3)

Hatchdate

Age (dl Temperature (OC)

Growing degree day (OCwd)

Mixed layer deptli (m)

Collection date

Slope Intercept r2 Slope Intercept r2

o 1 1 , ! 1 1

I 1 1 1 1 1 I 1 I

1023 -8 1023.9 1024.0 1024.1 1024.2 1024.3 1024.4 1024-5 1024.6

Surface layer density ( k g ~ n - ~ )

Figure 4- 1 1. Scattergram of (a) ASGR and (b) AOGR and surface Iayer density for silver hake larme aged 10 to 20 days coiiected on Western Bank, Scotian SheIf in November 1998,

the mode1 explainïng AOGR This is less than, but of the same order, as the variance in

ASGR explained by water depth, salinity and silver hake concentration (60%) and the

variance in AOGR explained by water depth, saiïnity and hatchdate (62%) within the

September cohort in 1997. However, surprisingly, none of the environmental variables

were common arnong the models for the September cohort in 1997 and the November

cohort in 1998.

As in 1997, the growth variation within monthly cohorts in 1998 was best explained by

physical oceanographic variables (GDD, density). Potential prey concentration was not

usefiil for predicting growth variation within montMy cohorts in either 1997 or 1998. As

in 1997,I reject the hypothesis that growth variation within monthly cohorts is

independent of variation in p hy sical environmental variables (hypothesis 1 1).

DSerent water masses fiom which larvae were coliected in November 1998 were defined

using temperature andor density. The partial correlation between ASGR and density with

the effect of temperature removed (Pearsons ~ 0 . 3 1, Spearmans r-0.34) was greater

than between ASGR and temperature with the effect of density removed (Pearsons F-

0.26, Spearmans r--0.22). Furthemore, with the effect of density removed the

relationship between ASGR and temperature was negative. This suggests that ASGR is

more highly correlated with density than temperature. This is analogous to the greater

dependence of ASGR on water depth relative to saiinity observed for September 1997. In

November 1998 larvae coliected in the lower density (1024 kg-m") water mass had

significantly higher ASGR (-0.18 vs. 0.15 mm-6'; p=0.0070) and AOGR (-240 vs. 190

pn2-6'; p=0.039) than larvae collected in the higher density (1024.4 to 1024.5 kg-m-3)

water Fig, 4.1 1)-

No dineremes in individual back-calculated growth trajectories were apparent for larvae

collected from the Iower and higher density water masses in November 1998 although the

sampte size was low (Fig. 4.12)- Furthemore, the slopes were not significantly different

for the water mas-specific length-at-age (ANCOV4 p=0.85) or growth rate-at-age series

(ANCOVA, p=0.21) and no significant dserences in average TL or gowth rate at each

age were observed bebveen larvae collected f?om the Iower and higher density water

masses (ANOVA , p>0,070; Fig. 4- 13).

Of the 1 1 hypotheses tested in Chapter 3 and Chapter 4, results between 1997 and 1998

were consistent for 5 of the hypotheses, inconsistent for 5 of the hypotheses and partially

consistent for one hypothesis depending on the scale considered (hypothesis 1). A

surnrnary of the consistencies and inconsistencies between the 1997 and 1 998 resuhs are

presented in Table 4.6.

4.4 Discussion

4. A i Otolith-fish size rehtionships Fypotheses i to 3)

Si@cant h e a r relationships were observed between otolitli area and larval total length

for the October and November collections in 1998. The slopes of these relations were not

- Lower density water m a s 9 ---O--- Higher density water mass

(b) - Lower density water mass - ---mm-- EXïgher density water m a s

2 3 4 5 6 7 8 9 10 11 12 13 14 4 e estimated fiom number of sagittal increments (d)

Figure 4.12. Individual (a) total length and (b) daily growth rate series (back-calculated using surface area of each hcrement and the biological intercept model; Campana 1990) for silver hake brvae collecteci in lower density, higher temperature (solid lines) and higher density, bwer temperature (dashed luies) water masses around Western Bank, Scotian Shelf in November 1998.

(a)

Lower density water TL=^ .4e(0070Age), ?=0.98) ------- Higher density water (TL=~ .4e(0-073Age), ?=O. 86)

Lower density watet (GR=O.O~ 1 do- ' '*gel, ?=O. 87) - - - - - - - Higher density water ( ~ ~ , 0 . 0 6 3 e ( ~ - ' ~ ~ ~ ) , ?=0.77)

-1 O 1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 Age estimated fkom number of sagittal increments (d)

Figure 4.13. Average (a) TL and (b) daily gowth rate (GR) series (back-calculated using the surface area of each increment and the bio logical intercept model; Campana 1990) for silver hake larvae collected in lower density and higher density water masses around Western Bank, Scotian S helf in November 1998. Nonlinear regressions fit using al1 estirnates are shown by the solid (lower density water mass) and dashed (higher density water mass) lines and the regression equations and correIation coefficients are provided in the legends. Average (itl standard deviation) TL and daily growth rate estimates (open syrnbols, lower density water and closed symbols, higher density water) and sample size for each age (above, Iower density water and below, higher density water) are s h o w Slopes of the TL and daily growth rate series are not significantly different (ANCOVA, p>0-50) between water masses.

sirncantly dEerent within 1998. This is contrary to the diEerent otolith-fish size

relationships observed for larvae collected during three periods in 1997 and, therefore, in

1998 I cannot reject the hypothesis that otolith-fish size relations are not significantly

different among cohorts. However, the slopes of the otolith-fish size relationships

were significantly dBerent for larvae coliected in 1997 and 1998 when each of the 5

collection periods (September 1997, October 1997, November 1997, October 1998 and

November 1998) were considered separately but the slopes were not significantly diierent

when Iarvae were pooled by year (1997 and 1998). Therefore, the resuIts suggest that

otolith-fish size relationships Vary at the scale of months but may not Vary at the inter-

annual scale. The variation in the otolith-fish size relationships observed among months in

1997, while not observed in 1998, highlights the necessity for cohort- or population-

specifk otolith-fish size models if regession coefficients are used in the back-calculation

of somatic size fiom otolith size.

The cause of the variability in the otolith-fish size relationships among cohorts is not easily

detennined with these data as in both 1997 and 1998 variation in the otolith-fish size

relationships could not be explained by variation in length-at-age relations among cohorts.

In 1997 considerable variation in the slopes of the otolith-fish size relationships were

observed throughout the season but no variation in length-at-age relationships were

observed. The inverse was observed in 1998, with similar otolith-fish size relations but

variable length-at-age relations. Therefore, the results at the scale of arnong cohorts

challenges the hypothesis that faster growing larvae have smaller otoliths relative to body

size than slow growing larvae (Secor et al- 1989, Mosegaard et al. 19S8, Secor and Dean

1992) in silver hake. However, within all cohorts in 1997 and 1998, a s i m c a n t positive

relationship was observed between the residuals of the length-at-age relationships and the

residuals of t he otoiith-fish size relationships. This indicates that within CO horts faster

growing larvae do have srnaller otoiiths relative to body size than slower growing larvae

as suggested by a number of researchers (Secor et al. 1989, Mosegaard et al. 1988, Secor

and Dean 1992). Thus the results suggest that length-at-age variation can not explain

variation in otolith-fish size relations among cohorts; but w i t h cohorts some variation in

the otolith-fish size relations can be explained by individual variation in growth rate. Thus

the relationship between otolith and fish size may Vary among and within individuals

depending on growth rate. As concluded in Chapter 3, back-calculation of somatic size

from otolith size using the regression coefficients £?om the otolith-fish size reIationship

should be approached with caution and use of the biological intercept mode1 (Campana

1990) for back-calculation rnay be preferred. The use of a biologically detennined

intercept for back-calculation of somatic size f?om otolith size does not depend on the

relationship between otolith size and fish size and thus will not be influenced by the effect

of growth rate variation on the cohort-specific models (Campana 1990).

44.2 Growth variation among temporal cohorts @ypotheses 4 to 8)

In 1998 the length-at-age relationships were significantly different between cohort-A and -

B with larvae hatched early in the spawning season (when temperature and zooplankton

biomass were highest) incurring a iength-at-age advantage over larvae that hatched later.

Thus 1 must reject the hypothesis that length-at-age relations are not significantly difEerent

arnong temporal cohorts of Iarvae and unlike in 2 997, either temperature or potential prey

concentration alone were able to explain some of the length-at-age variation between

temporal cohorts in 1998- However, the combination of temperature and potential prey

concentration in 1998 were also able to explain the length-at-age variability between

cohort-A and -B. Therefore, as in 1997, I again reject the hypothesis that variation in

growth rates among cohorts is independent of the combination of temperature and

potentid prey concentration.

The analysis of alI temporal cohorts in 1997 and 1998 provides further evidence consistent

with the hypothesis that the interaction between temperature and zooplankton provides

the simplest explanation for the variation in lengt h-at-age arnong temporal CO horts. For

example, cohort- 1 in 1997 and cohort-A in 1998 had inferred hatchdates separated by only

10 calendar days and had experienced similar GDD (435 and 427 OC-d respectively) but

dif3erent zooplankton biornass (-2 fold greater for cohort-A). Given the hypothesis that

temperature and zooplankton interact to produce variability in length-at-age among

cohorts it is reasonable to expect that cohort-A would have a greater growth rate than

cohort-1. The results are consistent with this hypothesis. The slopes of the length-at-age

relations for these two temporal cohorts were signtncantly different with the slope for

cohort-A in 1998 -0.06 mm-6' greater than that for cohort-1 in 1997. Most evidence to

date, therefore, suggests that temperature and zooplankton biomass can be used

interactively to predict relative length-at-age slopes for temporal cohorts of silver hake

larvae (Table 4.7). A conceptual model was developed that predicts enhanced growth -wdl

be observed for temporal cohorts that experience: 1) higher temperature and higher prey

concentration; 2) higher temperature and similar prey concentration; or 3) higher prey

concentration and sirnilar temperature; aii relative to other tempord cohorts. Similar

growth rates are predicted for temporal cohorts that have experienced opposite trends in

temperature and prey concentration such that one experiences high prey concentration but

low temperature and the other experiences low prey concentration but high temperature-

Evidence for the validity of this conceptual model is provided in Table 4.7. Furthemore, a

multiple regression model using the dope of the length-at-age relationship (growth rate) as

the dependent variable and GDD and prey concentration as the independent variables i s

consistent with the conceptual model. Although the sample size is exceedingly srnail

(N=4), the multiple regression can explain 90% @=0.3 1) of the variation in growth rates

among these four temporal cohorts and the coefficients for both temperature and prey

concentration are positive as predicted fkom the conceptual model (Fig- 4.14). It should be

noted that neither the multivariate model nor the contributions of temperature or prey

concentration were signifiant (p0.05) and the sample size is low. To detennine the

probabiiity of obtaining these results by chance alone, 40 random sets of GDD and

zooplankton biomass data (uniformly distributed within the observed data ranges) w e r e

used in a series of multiple regressions with the observed cohort growth rates as the

dependent variable. The randomization test showed that the probability of having both

coefficients positive, an r2>0.90 and p10.30 was 0.18. In the shplest tenns, although t8ie

sample size is small, there is less than a 20% chance of the multivariate rnodel results

Table 4.7. Conceptual model for predicting the relative cohort growth rates (slopes of length-at-age relations) for two hypothetical cohorts (C and D) using the interaction between GDD (temp erature) and prey concentration. Predict ed relationships between cohort growth rates are indicated above the diagonal and consistent or inconsistent evidence fiom this study is indicated below the diagonal.

Cohort-C + E g h High Low Low temperature and temperature and temperature temperature high prey Iow prey and high prey and iow prey

Cohort-~ 4 concentration concentration concentration concentration

High temperature and high prey concentration

High temperature and low prey concentration

Low temp erature and high prey concentration

Low temperature and Iow prey concentration

Consistent: Cohort-A >

Cohort- l

No evidence available

Consistent: Cohort-A > Cohort-B

and Co hort-A> Co hort-2

and *Inconsistent:

Co hort-2~ Co ho rt-B

Consistent: Cohort-lz Cohort-2

and Cohort- l= Co hort-B

No evidence No evidence available available

* The conceptuai model predicts a higher growth rate for cohort-2 than cohort-B and although the growth rate is -0.02 mmd-' higher for cohort-2, the difference in the growth rates is not signincant @>O-05).

Independent Regression Standard Probability variable coefficient error value Intercept -3.8~10" 6.3~10-" 0.96 GDD 3 .4x104 1.5~10" 0.27 Prey concentration 0.30 0.16 0.3 1

Predicted growth rate from multiple regression model (mm-d-l)

Figure 4.14. Scattergram of observed growth rates (slopes of length-at-age relations) and growth rates predicted using multiple regression analysis with growing degree day (GDD) and prey concentration as independent variables for four temporal cohorts of larvae collected in Auturnn 1997 and 1998. The regression coefficients, standard errors and probability values for each of the coefficients are provided in the table (Note: there is one degree of freedom remaining). The model explains -90% of the variance in growth rates but is not significant (p=0.3 1). The dashed Iine is a 1 : 1 relationship.

being due to chance alone.

One observation is partially inconsistent with the proposed conceptual model. Based on

the model, 1 would predict that cohort-2 would have a greater growth rate than cohort-B

as the GDD and prey concentration experienced by cohort-2 were greater than that for

cohort-B. The slope of the length-at-age relationship for cohort-2 is -0.02 mm-d" greater

than that for cohort-B and this is consistent with the prediction. However, the difference

in slopes is not sigd5cant and thus the slopes must be considered as similar. Further

testing of this mode1 is necessary but the evidence provided in Table 4.7 strongly suggests

that temperature and prey concentration combined may prove usefùl for predicting relative

growth rates among temporal cohorts.

4.43 Growth variation within monthly cohorfs Fypotheses 9 to I l )

No significant relationships between ASGR or AOGR and water depth were observed

within either the October 1998 or November cohort. 1, therefore, cannot reject the

hypothesis that variation in growth rates within cohorts is independent of location relative

to the crest of Western Bank. However, variabiIity in ASGR and AOGR within the

November cohort was weakly associated with water mass structure. Larvae coilected fiom

a single station, characterized by lower density and higher temperature water, had ASGR

and AOGR that were on average -0.03 mm-d-' and -50 pn2-d-' greater than larvae

coilected from stations in higher density, lower temperature water masses. Possible

explanations for the dEerence in growth rates between these water masses are: 1) food

limitation in the higher density water mass; 2) size-selective predation in either water

mas; 3) dEerent origins for larvae collected fiom the two water masses and thus different

growth trajectories from hatch; and 4) a common orïgin for larvae and faster growth rates

for larvae transported into the lower density water mass (perhaps due to the higher water

ternperatures). No relationship was observed between zooplankton biomass and either

ASGR or AOGR This is inconsistent with food-limitation as an explanation for larval

growth varïability w i t h the November cohort and is consistent with the conclusions in

1997 when only weak relationships were observed between zooplankton biomass and

ASGR or AOGR. The lower variance in growth rate in the higher density water mass

(where growth rate is lowest) is consistent with size-selective predation in this water mass.

The results in 1997 are inconsistent with size-selective predation in either water mass as

the variance was sirnilar on- and off-bank. Kowever, if size-selective predation was

occurring in November 1 998, the data indicate that the fast-growing larvae were

eliminated fiom the lower density water mass (Fig. 4.10) and not the slow-growing larvae

as predicted by most growth-predation hypotheses. Although the sample size is Iow, the

sirnilarity in otolith growth trajectories for larvae fiom the two water masses is

inconsistent with the hypothesis that larvae had different origins and thus different growth

trajectories from hatch. As in September 1997, the results are consistent with the

hypothesis that larvae fiom the two water masses had a cornmon origin but in Noveniber

1998 no divergence in growth rates was observed arnong individuals. Average growth

trajectories for iarvae collected on- and off-bank in September 1997 were re-calculated

with similar sarnple sizes to those available in November 1998 to determine whether the

similady in average growth trajectories in 1998 could be exphined by the low sample size

done- Average cumulative growth trajectories for on- and off-bank larvae were calculated

using 3 randomly chosen larvae &om on-bank and 4 randody chosen Iarvae fkom off-

bank. These analyses were repeated 10 times with merent sets of larvae. Of the 10 sets of

analyses, 5 hdicated significantly greater TL-at-age for larvae collected off bank (as

concluded in Chapter 3), 4 indicated no signincant differences in lena@-at-age, although in

al1 sets some divergence was observed with off-bank larvae displaying faster growth than

on-bank larvae, and one series was not long enough to ailow for any conclusions. These

results suggest that growth ciifferences in September 1997 could be observed with the

smali sample sizes available in November 1998, however, signincant dserences were not

always observed. Thus the sirnilarity in growth trajectories for larvae fiom the two water

masses in 1998 could be the result of the s m d sample size and may not be representative

of the average growth trajectories for larvae Erom the two water masses.

The sirnplest explanation for the variation in growth rates among water masses in 1998 is

temperature (Le. faster growth rate in the higher temperature, lower density water mass).

In September 1997, the results suggested that growth variation within cohorts was

explained by transport and the resulting water mass associations of larvae that were

removed fiom or remained over the crest of the bank. The simplest explanation for the

results in November 1998 is similar to this but in place of the on- and off-bank dzerences

in growth, the growth variation was related to temperature and density. Thus, ùi 1998, it

appears that larvae entrained into the higher temperature, lower density water mass

experienced enhanced growth relative to larvae entrained into the lower temperature,

higher density water mass.

Although a few variables (GDD, age, larval concentration, larval hake concentration and

hatchdate) explained signincant proportions of the variance in AOGR within the October

1998 cohoa, the predictive power of these relationships (with the exception of age and

GDD) were low (&O. 15) and none of these variables explained a signifïcant proportion of

the variability in ASGR within the October 1998 cohort. Due to the low predictive power

and conflicting resdts for ASGR and AOGR within this monthly cohort no fkm

conclusions c m be drawn fiom these data. In Chapter 3, I hypothesized that the lack of

growth variability in the October 1997 cohort was related to the lirnited spatial coverage

of the collections in October 1997 and provided supporting evidence. However,

collections in the October 1998 cohort had a greater spatial coverage than collections in

November 1998.1, therefore, cannot reject the hypothesis that the lack of pattern in the

October 1998 cohort is independent of the spatial coverage of larval collections. However,

as water mass characteristics appear to be important in d e t e m g growth rate, it is not

spatial coverage per se that should be exarnined but variation in water mass properties.

The variation in temperature and saiinity at collection was greater in October than

November 1998 and, therefore, I also cannot reject the hypothesis that the lack of pattern

in growth rate w i t h the October 1998 cohort is independent of the variation in water

mass characteristics fiom which larvae were collected.

The inconsistency of the results between 1997 and 1998 for 50% of the testable

hypotheses indicate the dangers of basing conclusions on one year of data. Furthemore,

the fadure to test hypotheses related to growth variation at a variety of scales may hinder

the prediction of growth and recruitrnent f?om environmental variables. Attempts to relate

suMval to growth variation with only a single year of data may lead to erroneous

conclusions about the relations hips between s u ~ v a l and environmental variables. It is

cntical that testable hypotheses related to larvai growth variabiiity are fonned and

subsequently tested with independent data ifwe are to advance our insights and Our ability

to predict growth, and subsequently s u ~ v a l , of larval fish.

Chapter 5

Thesis Summary

5. I UtiIity of otoliths for age andgrowth analyses in &ver hake Imue

Otoliths are shown to be an ideal tooI for assessing growth variation in silver hake lawae

(Chapter 2). Due to uncertainty in the timing of initial increment formation, accurate age

estimates for larvae couid not be obtained in this study, However, the precision of age

estimates between otolith types and within sagittae and the significant linear relationships

between larval size and otolith area indicate that relative age, size and/or growth

estimates can be obtained from the sagittal otolith. Sagittae were used to examine growth

variation among temporal cohorts and within monthly cohorts in an oceanographic

fkamework (Chapter 3 and 4).

5.3 Gruwth variation among temporal cohorts

Three temporal cohorts were defined in 1997 and two in 1998. In 1997, the length-at-age

relations were similar for cohort-1 and -2 and this could not be explained by either

temperature or potential prey concentration alone. 1 hypothesized that temperature and

potential prey concentration could be acting in concert in 1997 to result in similar growth

rates for the two temporal cohorts- In 1998, different growth rates were observed for

cohort-A and -B with larvae spawned early in the season incurring a size-at-age

advantage over larvae spawned later. This could be explained by temperature or

zooplankton alone (both higher early in the season) or by the combined influences of

127

temperature and zooplankton. When al1 temporal cohorts in 1997 and 1998 were

considered, the relative variation in length-at-age could most easily be explained b y the

combination of temperature and zooplankton concentration. A conceptual model (Table

4.7) for predicting relative cohort growth rates fiom temperature and zooplankton

biomass estirnates was presented in Chapter 4 and should be tested with further data.

Length-at-age relations did not differ significantly for larvae collected during day and

night in September 1997, October 1998 o r November 1998. Furthemore, the length-at-

age relations were not significantly different for larvae collected using the BONGO or

BIONESS in October 1998 and there was no relationship between ASGR and depth of

collection in October 1997. These results suggest that time and depth of collection and

gear type deployed will not confound the results of age and growth studies using silver

hake larvae (at least up to a size of -8mm and age of 25 days). Thus silver hake may be a

model species with which further studies of the relationship between growth and the

environment can be pursued.

The relationship between otolith size and fish size varied among larvae collected

throughout the Autumn. Variation in length-at-age could not explain the variation in

otolith-fish size relations among temporal cohorts of silver hake. Within cohorts,

however, faster growing larvae had smaller otoliths relative to body size than slower

growing larvae, as has been observed for other species (Secor et al. 1989, Hovenkarnp

1990, Secor and Dean 1992). Thus, the mechanism responsible for variation in otolith-

fish size relations among cohorts could not be determined with these data, however,

variation in otolith-fish size relations within cohorts could in part be explained by

variation in growth rate. The causes of the variation in the otolith-fish size relations in

silver hake larvae should be investigated fùrther and caution should be taken if regession

coefficients fiom the otolith-fish size relations are used for back-calculation of somatic

size fiom otolith size.

5.3 Growth variation wifhin monthly cohorts

In September 1997, water depth explained a significant proportion of the variance in

growth rates arnong individuals. In 1998, water depth couid not be used to predict relative

growth rates within either temporal cohort. However, other physical oceanographic

characteristics (density and temperature) were the best predictors of growth variation in

November 1998. Surprisingly, potential prey concentration, which played a major role in

explaining the growth variation among temporal cohorts, consistently showed no, or

little, relationship to spatial growth variation within monthly cohoas and among water

masses. Thus, potential prey concentration appears to be an important variable at the

seasonal scale (among temporal cohorts) but does not seem to contribute to growth

vax-iabiiity at spatial scales over small temporal periods. This suggests that the same

environmental factors may not be useful for predicting growth variation at dserent

temporal and spatial scales. Furthemore, limiting analyses to traditionally studied

variables (temperature and prey concentration) may limit Our ability to explain and

predict larval growth variation based on oceanographic conditions. The mechanism(s)

responsible for the spatial variation in growth rates around Western Bank is unresolved.

However, the results of this study suggest that research should focus on variation in

physical oceanographic properties, particularly variations in flow (see below), as the most

likely fiiture predictors of spatial variation in larval growth in this region.

The analyses of individual growth patterns among water masses in 1997 and 1998

suggest that larvae collected on and around Western Bank Iikely orïginated ftom a single

spawning site (probably the crest of Western Bank; O'Boyle et al. 1984) w-d variations in

size-at-age were achieved post-hatch. The simplest explanation for these growth patterns

is varïability in oceanographic conditions experienced by the larvae (Le- larvae that

experience "bette? conditions display enhanced growth rates). There is some evidence

that higher growth rates are related to greater water depths (Chapter 3) and lower density

(higher temperature) water mass characteristics at collection (Chapter 4). However,

environmental conditions measured at collection may be a poor indicator of the

conditions experienced by larvae given that they exist in a highly dynamic physical

environment on and around Western Bank. Thus oceanographic conditions at collection

may not always be correlated with spatial patterns in growth variation (as was observed

in October 1997 and 1998). The flow field in the Western Bank region may in part be

responsible for the distribution of larvae into different water masses (Reiss et al. 2000)

and, thereby the spatial variation in larval growth rates. For example, in September 1 997

it was observed that larvae that were retained over the crest of the bank had slower

growth rates relative to those larvae that were swept off-bank. Thus, studies that focus on

the variations in flow in the Western Bank region, and the resulting distribution of larvae,

may prove usefùl in developing predictive models of larval growth based on

oceanographic conditions. Future work rnay benefit f?om the analyses of individual

growth patterns and the inferred spatio-temporal distribution (inferred fiom the growth

pattern itself andor fiom estimates of current velocity) of Iarvae in areas such as Western

Bank.

5.4 Implications for grow th and mortakty

It has been hypothesized that larger, or faster growing, larvae have a higher probability of

sunrival than smaller, or slower growing, larvae (e.g Rice et al. 1993, Meekan and

Fortier 1996). This has not been shown conclusively for silver hake larvae although

Buckley et al. (1993) in a laboratory study did observe a weak inverse relationship

between growth and mortality in silver hake. The results of the present study indicate that

growth variation in silver hake larvae in natural populations is related to environmental

variables at a variety of scales. However, the driving variables have not yet been

adequately resolved, particularly at the finer scales of spatiaI variation in growth within

narrow temporal penods. Given the assumption that faster growing larvae have a higher

probability of survival, the results of this study have implications for the prediction of

survival fiom growth-environment relationships and the scale and variables that should

be explored. The results suggest that the interaction between temperature and potential

prey concentration may allow for the prediction of growth rates for temporal cohorts of

larvae and, therefore, may also be usefil for predicting relative s u ~ v a l of temporal

cohorts. The importance of the interaction between potential prey concentration and

temperature in determining survival or recruitment of marine fish has been recognized by

other researchers (e-g. Anderson 1988, Ellertsen et al. 1989). Studies on hatchdate

distributions or growth histories of surviving silver hake larvae or juveniles (e-g.

Campana 1996, Meekan and Fortier 1996, Fortier and Quiîionez-Velazquez 1998) are

required to determine whether temporai cohorts with faster growing larvae are

contributing significantly more individuals to populations than cohorts with slower

growing larvae and thus to determine the utility of studying growth at the broad scale of

among temporal cohorts.

The results of this study suggest that within monthly cohorts, the relationships between

growth sumival and the environment should focus on physical oceanographic variables.

In the Western Bank region attention should be directed at predicting transport processes

and the resuIting distribution of larvae and their water mass associations. The results of

both 1997 and 1998 suggest that these processes will be important in predicting growth

variation within monthly cohorts. It is rny opinion that fùrther studies of growth and

suMval variation in silver hake larvae will most benefit fiom the study of growth within

cohorts and among water masses. This scale benefits from its focus on individuals, which

researchers have argued is the scale that should be focussed upon, and f?om the

repeatability of studies and large sample sizes that can be obtained for research at this

scale.

5.5 RecommendiAtiom f o r w r e research

Little was known about the growth of silver hake larvae prior to this study. However, the

evidence provided herein suggests that it cm be used as a model species for studying the

relationships between growth, suMval and environmental conditions. A number of

hypotheses developed during this research warrant fiirther investigation: 1) age can be

acçu~afeZy deterrnined using the number of otoiith increments; 2) the initia1 otolith

increment is formed at hatch; 3) the condition of field caught larvae can be estimated

using measures of the change in length due to preservation; 4) growth variation among

temporal cohorts c m be predicted using GDD and zooplankton biomass (conceptual

model); 5) spatial variation in growth rates within cohorts cm be predicted using physical

oceanographic conditions; 6 ) individual growth trajectories can be used to infer water

mass associations throughout the life of an individual larva; and 7) Iarval survival, and

ultimately recruitment, can be predicted £tom growth variation.

References

Amara, R, Desaunay, Y., and Lagardere, F. 1994, Seasonal variation in growth of lamal sole Solea solea (L-) and consequences on the success of larval immigration, Neth. J. Sea Res. 32: 287-298.

Anderson, 5. T. 1988. A review of size dependent survival during pre-recniit stages of fishes in relation to recruitment. J. Northw, Atl, Fish. Sci. 8: 55-66,

Bailey, K. M- 1982- The early life history of the Pacific hake, Merluccius prodztcfz~s. Fish. Bull. 80: 589-598.

Bailey, K. M., and Stehr, C . L.. 1988. The effects of feeding periodicity and ration on the rate of increment formation in otoliths of larval walleye poliock Zkeragra chakogrmma (Pallas). J. Exp. Mar. Biol- Ecol. 122: 147-161.

Bailey, K. M., Canino, M- F., Napp, J. M., Spring, S. M., and Brown, AL. 1995. Contrasting years of prey levels, feeding conditions and mortality of larval walleye pollock ïheragra chalcogmma in the western Gulf of Alaska. Mar. Ecol. Prog. Ser. 1 19: 1 1-23.

Bakun, A, Beyer, J., Pauly, D., Pope, J. G., and Sharp, G. D. 1982. Ocean sciences in relation to living resources. Can. J. Fish. Aquat- Sci. 39: 1059-1070.

Barkman, R C., and Bengtson, D. A 1987. The record of daily growth in otoliths of Atlantic silversides, Menzdia menzdia, fiom field and laboratory. J. Fish Biol- 3 1: 683-695.

Beckman, D. W., and Shulz, R. G. 1996. A simple method for marking fish otoliths with Alizarin compounds. Trans. Am. Fish, Soc. 125: 146-149.

Betsill, R. K., and Van Den Avyle, M. J. 1997. Effect of temperature and zooplankton abundance on growth and survival of larval threadfin shad. Trans. Am. Fish. Soc. 226: 999-1011.

Bolz, G. R., and Burns, B. R 1996. Age and growth of Iarval Atlantic herring, CZqea harerips: a comparative study. Fish. Bull. 94: 387-397.

Bolz, G. EL, and Lough, R. G. 1983. Growth of larval Atlantic cod, Gadus rnorhua, and haddock, Metanogrammus aegCeJims, on Georges Bank, spring 198 2 . Fish. Bull. 8 2 : 827-83 6.

Bolz, G. R., and Lough, R. G. 1988. Growth through the first six months of Atlantic cod, Gadus morha, and haddock, Melanogrammus aeglefimrs, based on daily otolith increments- Fish Bull. 86: 323 -23 5,

Brothers, E. B., Mathews, C . P., and Lasker, R 1976. Daily growth increments in otoliths f?om larval and adult fishes. Fish- Bull- 74: 1-8.

Buckley, L. J-, and Lough, R G. 1987. Recent growth, biochemical composition, and prey field of larval haddock (Melanogrammus aeglefims) and Atlantic cod (Gadus morha) on Georges Bank. Can. J- Fish. Aquat. Sci. 44: 2 4-25.

Buckley, L, J., Smigielskii A S., Halavik, T, A,, Burns, B. R, and Laurence, G. C. 1993. Growth and survival of the larvae of three temperate marine fish species at discrete prey densities. II, Cod (Gadus morhua), winter flounder (Pseudopleuronectes ame~~carnïs), and silver hake (Merhccius biZineans). In Physiological and Biochemical Aspects of Fish Development. Edired by B. T. Walter and H. J. Flyhn. Univ. of Bergen, Norway. pp. 183-1 95.

Butler, J. L., and Nishimoto, R N. 1997. Growth and cohort dynarnics of larvai Pacific hake (Meduccius productus). CalCOFI Rep. 3 8 : 63 -68.

Campana, S. E. 1989. Otolith microstructure of three larval gadids in the Gulf of Maine, with inferences on early life history. Can. J. 2001. 67: 140 1-1410.

Campana, S. E. 1990. How reliable are growth back-calculations based on otoliths? Can. J. Fish. Aquat. Sci- 47: 2219-2227-

Campana, S. E. 1996. Year-class strength and growth rate in young Atlantic cod Gadus morhua. Mar. Ecol. Prog. Ser. 13 5: 2 1-26.

Campana, S. E., and Hurley, P. C. F. 1989. An age- and temperature-mediated growth mode1 for cod (Gadus morhua) and haddock (Melanogrammus aegZefims) larvae in the Gulf of Maine. Cm. J. Fish. Aquat. Sci. 46: 603-613.

Campana, S. E., and Jones, C . M, 1992. Analysis of otolith microstructure data- In Otolith Microstructure Examination and Analysis. Edited by D. K- Stevenson and S. E. Campana. Can. Spec. Publ. Fish. Aquat. Sci. 117: 73-100.

Campana, S. E., and Neilson, J. D. 1985. Microstructure of fish otoliths. Can. J. Fish. Aquat. Sci, 42: 1014-1032,

Campana, S. E., Gagné, J. A., and Munro, J. 1987. Otolith microstructure of larval herring (CZupea harengus): Image or reality? Can. J- Fish. Aquat. Sci. 44: 1922- 1929,

Cass-Calay, S. L. 1997. Relation of mean growth rate to concentration of prey-sized particles for larvae of Pacific hake (Merluccziurproduchrs). CalCOFI Rep. 38: 69- 76-

Castro, L. R, and Cowen, R K. 199 1. Environmental factors aEecting the early life history of bay anchovy Anchoa rnifchillli in Great South Bay, New York Mar. Ecol- Prog. Ser. 76: 235-247.

Chambers, R C-, and Miller, T. J. 1995. Evaluating fish growth by means of otolith increment malysis: special properties of individual-level longitudinal data In Recent Developments in Fish Otolith Research. Edited by D. H. Secor, J. M. Dean and S. E. Campana. University of South Carolina Press, Columbia, South Carolina. pp. 155-1 75-

Clemmesen, C., and Doan, T. 1996. Does otolith structure reflect the nutritional condition of a fish larva? Cornparison of otolith structure and biochemical index (RNADNA ratio) determined on cod larvae. Mar. Ecol. Prog- Ser. 13 8: 3 3-39.

Colton, J. B. Jr., Green, 9. R, Byron, R. R, and Frisella, J. L. 1980. Bongo net retention rates as effected by towing speed and mesh size. Can. J. Fish. Aquat. Sci. 37: 606- 623,

Dickey, C. L., Isely, J. J., and Tomasso, J. R. 1997. Slow growth did not decouple the otolith size-fish size relationship in striped bass. Tram Am. Fish. Soc. 126: 1027- 1029,

Eckmann, R, and Rey, P. 1987. Daily increments on the otoliths of larval and juvenile Curegomrs spp., and theu modiftcation by environmental factors. Hydrobiologia. 148: 137-143.

Ellertsen, B., Fos- P., Solemdal, P., and Sundby, S. 1989. Relation between temperature and s u ~ v a l of eggs and first-feeding larvae of northeast Arctic cod (Gadus morhua L.). Rapp. P.-v. Réun. Cons. int. Explor. Mer. 19 1 : 209-2 19.

Fitzhugh, G. R, Nixon, S. W., Ahrenhoiz, D. W., and Rice, J- A. 1997. Temperature effects on otolith microstructure and birth month estimation fiom otolith incrernent patterns in AtIantic menhaden. Tram Am. Fish. Soc. 126: 579-593.

Fortier, L., and Gagné, J. A. 1990. Larval hening (Chpea harengus) dispersion, growth, and s u ~ v a l in the St. Lawrence estuary: match/mismatch or membership/vagrancy? Can. J. Fish. Aquat. Sci 47: 1898- 19 12.

Fortier, L., and \lilleneuve, A 1996. Cannibalism and predation on fish larvae by larvae of Atlantic mackerel, Scomber scomdrus: Trophodynamics and potential impact on recmitment. Fish, Bull. 94: 268-2381.

Fortier, L., and Quiîionez-Velazquez, C. 1998. Dependence of survival on growth in larval pollock Pollachius virens and haddock Melanogrammus aegleflms: a field study based on individual hatchdates. Mar. Ecol. Prog. Ser. 174: 1-12.

Fowler, A J., and Short, D. A. 1996. Temporal variation in the early life-history characteristics of the King George Whiting (SiZlagïnodespzrnctara) fkom analysis of otolith microstmcture. Mar. Freshwater Res. 47: 809-8 1 8.

Fowler, G. M., and Smith, S. J. 1983, Length changes in silver hake (Merluccius 6iCinemi.s) larvae: effects of formalin, ethanol, and fieezing. Can. J. Fish Aquat- Sei. 40: 866-870.

Frank, K- T., and McRuer, J. K, 1989. Nutriltional status of field-collected haddock (MeZ'ogrammzis aeglefirn(s) larvae fiom southwestern Nova Scotia: An assessrnent based on morphometric and vertical distribution data. Cam J. Fish. Aquat. Sci. 46 (SuppI. 1): 125-133.

Frank, K, T-, Perry, R I., Drinkwater, K. F., and Lear, W. H. 1988- Changes in the fishenes of Atlantic Canada associated with global increases in atmospheric carbon dioxide: A preliminary report. Can. Tech. Rep. Fish. Aquat. Sci. 1652: 1- 52.

Gallego, A., Heath, M. R, McKenzie, E., and Cargill, L. H. 1996. Environmentally induced short-term variability in the growth rates of larval herring. Mar. Eco:. Prog. Ser, 137: 11-23,

Gallego, A., Heath, M. R, Basford, D. J., m d Mackenzie, B. R, 1999. Variability in growth rates of larval haddock in the northem North Sea. Fish- Oceanogr. 8: 77- 92.

Garcia, A, Cortés, D., and Ramirez, T. 1998. Daily larval growth and RNA and DNA content of the NW Mediterranean ancchovy Engraulis encrasicolus and their relations to the environment. Mar. Ecol- Prog. Ser. 166: 237-245,

Geffen, A. J. 1992. Validation of otolith increment deposition rate. In Otolith Microstructure Examination and Analysis. Edited by D. K. Stevenson and S. E. Campana. Can. Spec. Publ. Fish. Aquat. Sci. 11 7: 10 1-1 13.

Geffen, A. J. 1995. Growth and otolith microstructure of cod (Gadus rnorhua L.) larvae. J. Plankton Res. 17: 783-800.

Gill, A. E. 1982- Atmosp here-Ocean Dynamics- Academic Press, New York.

Govoni, J. J., Chester, k J., Hoss, D. E., and Ortner, P. B. 1985. An observation of episodic feeding and growth of larval Leiostomus xmthurus in the northem Gulf of Mexico. J, Ptankton Res. 7: 137-146-

Graham, J. J., and Townsend, D. W. 1985. Mortality, growth, and transport of larval Atlantic herring CZqea harengus in Maine coastal waters. Trans. Am. Fish. Soc. 114: 490-498.

Grimes, C. B., and Isely, J. J. 1996. Influence of size-selective mortality on growth of gulf menhaden and king rnackerel larvae. Trans. Am. Fish. Soc. 125: 741-752.

Gutiérrez, E., and Morales-Nin, B. 1986. Time series analysis of daily growth in Dicenfrarchs Zahrax L. otoliths. J. Exp. Mar. Biol. Ecol. 103: 163-179-

Haldorson, L., Paul, A J*, S t e m D., and Watts, J. 1989. Annual and seasonal variation in growth of larval walleye pollock and flathead sole in a southeastern Alaskan bay. Rapp. P.-v. Réun. Cons. int. Explor. Mer. 191 : 220-225.

Hannah, C. G-, Shore, J. A., Loder, J. W., and Naimie, C. E. 2000. Seasonal circulation on the Western and Central Scotian Shelf. Submitted to J. of Phys. Ocean.

Hazen, D., and Reiss, C. S. 2999. GLOBEC-Canada Western Bank Report 1998/2 CCGS Parizeau Cruise 98-058 Western Bank Leg. Department of Oceanography, Dalhousie University, Halifax, NS .

Hare, J. A , and Cowen, R. K. 1995. Effect of age, growth rate, and ontogeny on the otolith size-fish size relationship in bluefish, Pomafomus saZta&ix, and the implications for back-calculation of size in fish early life history stages- Cam J. Fish. Aquat. Sci. 52: 1909-1922.

Hare, J. A., and Cowen, R. K. 2997. Size, growth, development, and survival of the planktonic larvae of Pomatomus saZta?x (Pisces: Pomatornidae). Ecology. 78: 24 2 5-243 1.

Helbig, J., Mertz, G., and Pepin, P. 1992. Environmentai influences on the recruitment of Newfoundland/Labrador cod. Fish. Oceanogr. 1 : 3 9-56.

Hempel, G. 1978. North Sea fisheries and fish stocks - A review of recent changes. Rapp. P.-v. Réun. Cons. int. Explor. Mer. 173: 145-167.

Hintze, J. 1998. Number Cruncher Statistical Software. Version 6.0. NCSS Statistical Software, Kay sville, Utah.

Hjort, J. 1914. Fluctuations in the great fisheries of northem Europe viewed in the light of biological research. Rapp. P.-v. Réun. Cons. int. Explor. Mer. 20: 1-288.

Hjort, J. 1926. Fluctuations in the year classes of important food fishes. Journal du Conseil 1: 1-38.

Houde, E. D. 1987. Fish early life dynanics and recruitment variability. American Fisheries Society Symposium. 2: 17-29.

Hovenkamp F. 1989. Wit hin-season variation in growth of larval plaice (Plezwonectes plutessa L.). Rapp. P.-v. Réun. Cons. int. Explor. Mer. 191: 248-257.

Hovenkamp, F. 1990. Growth differences in larval place Pleuronectesplatessa in the Southem Bight of the North Sea as indicated by otolith increments and RNADNA ratios. Mar. Ecol. Prog. Ser. 58 : 205-2 15.

Hovenkamp, F., and Witte, J. 1. J. 1991. Growth, otolith growth and RNA/DNA ratios of larval plaice Pleuronectes platessa in the North Sea 1987 to 1989. Mar. Eml. Prog. Ser. 70: 105-1 16.

Iglesias, J., and Rodriguez-Ojea, G. 1997. The use of alizarîn cornplexone for immersion marking of the otoliths of embryos and larvae of the turbot, Scophthalmzis rnuximtis (L.): dosage and treatment time. Fisheries Management and Ecology. 4: 405-4 17.

Jenkins, G. P. 1987. Age and growth of CO-occurrhg larvae of two flounder species, Rhornbosolea fqirina and Ammotretis rostratzts. Mar. Biol. 95: 157-166.

Jenkins, G. P-, and Davis, T. L. 0. 1990. Age, growth rate, and growth trajectory determined corn otolith microstructure of southem bluefin tuna Thzinmts rnaccuyiz larvae. Mar. Ecol. Prog. Ser. 63: 93-104.

Jones, C. 1985. Within-season differences in growth of larval Atlantic herring, Chpea harengics harengzrs. Fish. Buil. 83: 289-298.

Jones, C . M. 1992. Development and application of the otolith increment technique. In Otolit h Micro structure Examination and Analysis. Edited by D. K. Stevenson and S. E. Campana. Can. Spec. Publ. Fish. Aquat. Sci- 117: 1-1 1.

Jordan, A. R. 1994. Age, growth and back-calculated birthdate distributions of larval jack mackerel, Trachms declivis (Pisces: Carmgidae), fiom eastern Tasrnanian coastal waters. Aust. J. Mar. Freshwater Res. 45: 19-33.

Kimboe, T., Munk, P.,Richardson, K., Chnstensen, V., and Paulsen, H, 1988. Plankton dynamics and iarval hemng growth, drift and suMval in a fiontal area. Mar. Ecol. Prog. Ser- 44: 205-219.

Koeller, P. A., Coates-Markie, L., and Neilson, J. D. 1989. Feeding ecology ofjuvenile (Age-O) Silver hake (Merluccius bilinems) on the Scotian Shelf. Can. J. Fish. Aquat- Sci. 46: 1762-1768.

Koutsikopolous, C., Karakiri, M., Desaunay, Y., and Dore1 D. 1989. Response of juvenile sole (Solea solea (L.)) to environmental changes investigated by otolith microstructure analysis. Rapp. P.-v. Réun. Cons. int. Explor. Mer. 19 1 : 28 1-286.

Lang, J. B., and Buxton, C. D. 1993. Validation of age estimates in sparid fish using fluorochrome marking. S. Afr. J. Mar. Sci. 13: 195-203.

Lang, K. L., Grimes, C . B., and Shaw, R F. 1994. Variations in the age and growth of yellowfin tuna larvae, ï?tunms alaucares, collected about the Mississippi River plume. Env. Biol. of Fishes. 39: 259-270,

Lasker, R 1978. Ocean vanability and its biological effects - regional review - Northeast Pacific. Rapp. P.-v. Réun. Cons. int. Explor. Mer. 173 : 168-18 1.

Leak, J. C., and Houde, E. D. 1987. Cohort growth and suMval of bay anchovy Anchoa mitchilli larvae in Biscayne Bay, Flonda. Mar. Ecol. Prog. Ser. 37: 109-122.

Lenler, D. L., and Shaw, R. F. 1992. Age validation, growth, and mortality of larval Atlantic bumper (Carmgidae: ChZoroscornbnrs c h ~ s ~ m s ) in the northem Gulf of Mexico. Fish. Bull. 90: 711-719.

Loder, J. W., Ross, C . K., and Smith, P. C. 1988. A space- and time-scale characterization of circulation and mixing over submarine banks, with application to the Northwestem Atlantic continental shelf. Can. J. Fish. Aquat. Sci. 45: 1860- 1885.

Lough, R. G., Pennington, M., Bolz, G. R, and Rosenberg, A A. 1982. Age and growth of larval Atlantic hemng, CZupea hmengus L., in the Gulf of Maine-Georges Bank region based on otolith growth increments. Fish. Bull. 80: 187-199.

Maillet, G. L., and Checkley, D. M., Jr. 1991. Storm-related variation in the growth rate of otoliths of larval Atlantic menhaden Brevoortia tyrmms: a time series analysis of biological and physical variables and implications for larva growth and mortality. Mar. Ecol. Prog. Ser. 79: 1-16.

McGurk, M. D. 1987. Age and growth of Pacific herring Iarvae based on length- fiequency analysis and .otolith ring number. Env. Biol. of Fishes. 20: 3 347.

McLaren, 1. A, Avendaîio, P., Taggart, C- T., and Lochrnann, S. E. 1997. Feeding by larval cod in different water-masses on Western Bank, Scotian Shelf. Fish. Oceanogr. 6: 250-265,

Meekan, M. G-, and Fortier, L. 1996. Selection for fast growth during the larval life of Atlantic cod Gadzrs rnorhta on the Smtian Shelf. Mar-. Ecol. Prog. Ser. 137: 25-

Miller, T. J., Crowder, L. B., Rice, J. A., and Marschall, E_ A 1988. Larval size and recruitment mechanisms in fishes: toward a conceptual fiamework- Can. J, Fish- Aquat. Sci. 45: 1657-1670.

Mooij, W. M., and van Nes, E. H- 1998- Statistical analysis of the somatic growth rate of O+ fish in relation to temperature under natural conditions. Can. J. Fish. Aquat. Sci- 55: 451458.

Morales-Nin, B. Y. 0. 1987. The influence of environmental factors on microstnicture of otoliths of three demersal fish species caught offNamibia. S. Af?. J. Mar. Sci. 5: 255-262.

Mosegaard, Y Svedang, H., and Taberman, K. 1988. Uncoupling of somatic and otolith growth rates in Arctic char (Salcelinus alpimts) as an effect of differences in temperature response. Can. J. Fish. Aquat. Sci. 45: 15 14- 1524.

Munk, P. 1993. Differential growth of larval sprat Sprattus sprattus across a tidal front in the eastern North Sea. Mar. Ecol. Prog. Ser. 99: 17-27.

Munk, P., Heath, M., and S kaarup, B. 199 1. Regional and seasonal differences in growth of larval North Sea hemng (Clupea harengus L.) estimated by otolith microstructure analysis. Cont. S helf Res. 1 1 : 64 1-654,

Neilson, J. D., Geen, G. H., and Bottom, D. 1985. Estuarine growth of juvenile Chinook salmon (Oncorhynchts tshawytscha) as inferred fkom otolith microstructure. Can. J. Fish. Aquat. Sci. 42: 899-908.

Nichy, F. E. 1969. Growth patterns on otoliths fkom young silver hake Merluccius bilinearis (Mitch.). ICNAF Res. Bull. 6: 107-1 17-

Nishimura, A., and Yamada, J. 1984. Age and growth of larval and juvenile walleye pollock, Theragra chalcogramma (Pallas), as determined by otolith daily growth increments. J. Exp. Mar. Biol. Ecol. 82: 191-205.

O7Boyle, RN., Sinclair, M., Conover, R, J., Mann, K, H,, and Kohler, A, C. 1984- Temporal and spatial distribution of ichthyoplankton communities of the Scotian S hel f in relation to bio logical, hydrological, and phy siograp hic features. Rapp. P .- v- Réun. Cons, int Explor. Mer. 183: 27-40.

Optimas Corporation. 1995. Optimas. Version 5.0. Optimas Corporation, Bothell, Washington.

Oxenford, H. A-, Hunte, W., Deane, R., and Campana, S. E. 1994. Otolith age validation and growth-rate variation in flyingfish (Hirrrndichfhys afinis) from the eastem Caribbean- Mar- Biol. 118: 585-592.

Palomera, I., Morales-Nin, B. Y. O-, and Lleonart, J, 1988. Larval growth of anchovy, Engraulis encrasicolus, in the Western Mediterranean Sea. Mar. Biol. 99: 283- 291.

Pannella, G. 197 1. Fish otoliths: Daily growth layers and periodical patterns. Science. 173: 1124-1 127-

Pemey, R. W., and Evans, G. T. 1985. Growth histones of larval redfish (Sebastes spp.) on an offshore Atlantic fishing bank determined by otolith increment analysis. Can. J. Fish. Aquat. Sci. 42: 1452-1464.

Pepin, P. 1989. Using growth histories to estimate larval fish mortality rates. Rapp. P.-v. Réun. Cons. int. Explor. Mer. 191: 324-329.

Pepin, P. 1991. Effect of temperature and size on development, mortality, and survival rates of the pelagic early life history stages of marine fish. Can. J- Fish. Aquat. Sci- 48: 503-518.

Peters, J. S., and Schmidt, D- J. 1997. Daily age and growth of larval and early juvenile S panish mackerel, Scomberomorus macuZatzis, f?om the South Atlantic B ight. Fish. Bull. 95: 530-539.

Posgay, J. A., and Marak, R. R. 1980. The MARMAP bongo zooplankton samplers. J. Northwest Ati. Fish. Sci. 1: 91-99.

Power, M. 1999- Mission Report 98-068. Department of Fisheries and Oceans Science Branch Maritimes Region- Biological Station, St. Andrew's, N.B.

Radtke, R L. 1989. Larval fish age, growth, and body shrinkage: Infurmation available fiom otoIiths. Cm. J. Fish. Aquat. Sci. 46: 1884-1894.

Reiss, C. S. 1997. GLOBEC Canada Westem Bank Report l997/2 DREA cruise Q-242 Westem Bank. Department of Oceanography, Dalhousie University, Halifax, NS.

Reiss, C. S. 1998a. GLOBEC Canada Western Bank Report 199714 CCGS Needler cruise (97-070) to Central and Eastern Scotian Shelf and Westem Bank. Department of Oceanography, Dalhousie University, Halifax, NS.

Reiss, C. S. 1998b. GLOBEC Canada WesternBankReport 199713 CCGS Hudson cruise (97-063) to the Scotian Shelf and Western Bank. Department of Oceanography, Da1 housie University, Halifax, NS .

Reiss, C . S ., Panteleev, G., Taggart, C . T., Sheng, J., deYoung B ., and Power, M. 2000. Observations on larvd fish transport and retention on the Scotian Shelf in relation to geostrophic flow. Resubrnitfed to Fish. Oceanogr.

Rice, J. A, Crowder, L. B., and Holey, M. E. 1987. Exploration of rnechanisms regulating larval survival in Lake Michigan bloater: A recniitment analysis based on characteristics of individual larvae. Trans. Am. Fish, Soc. 116: 703-718-

Rice, J. A., Miller, T. J., Rose, K. A., Crowder, L. B., Marschall, E. A-, Trebitz, A S., and De Angelis, D. L. 1993. Growth rate variation and larval survival: Inferences from an individual-based size-dependent predation model. Can J. Fish. Aquat. Sci- 50: 133-142.

Rutherford, E. S ., and Houde, E- D. 1995. The influence of temperature on CO hort- specific growth, survival, and recruitment of striped bass, Morone saxarils, larvae in Chesapeake Bay, Fish- Bull. 93 : 3 15-332.

Rutherford, E. S., Houde, E. D., and Nyman, R. M. 1997. Relationship of larval-stage growth and mortality to recruitment of striped bass, Morone smratilis, in Chesapeake Bay. Estuaries. 20: 174- 198.

Sameoto, D. D., Jaroszynski, L. O., and Fraser, W. B. 1980. BIONESS, a new design in multiple net zooplankton samplers. J. Fish. Res. Board Can. 37: 722-724.

Scott, W. B., and Scott, M. G. 1988. Atlantic fishes of Canada. University of Toronto Press, Toronto.

Secor, D. H., and Dean, J. M. 1992. Cornparison of otolith-based back-calculation methods to determine individual growth histories of larval striped bass, Morone scrxarilis. Can. J . Fish. Aquat. Sci. 49: 1439-1454.

Secor, D. H., Dean, J. IM, and Baldevarona, R. B. 1989. Cornparison of otolith growth and somatic growth in larval and juvenile fishes based on otolith 1engWfish length relationships. Rapp. P.-v. Réun. Cons. int. Explor. Mer. 19 1 : 43 1-43 8-

Sepulveda, A. 1994. Daily growth increments in the otoliths of European smelt Omenrs eperlmus larvae. Mar. Ecol. Prog. Ser. 108: 3 3 -42.

SPSS Inc. 1998. Systat. Version 8.0. SPSS, Inc., Chicago, IiIinois.

SPSS Inc. 1999. SigrnaScan Pro. Version 5.0.0. SPSS, Inc., Chicago, Illinois.

Suthers, 1. M.. Frank, K. T., and Campana, S. E. 1989. Spatial comparïson of recent growth in postlarval Atlantic cod (Gadzis rnorhua) off southwestern Nova S cotia: inferior growth in a presumed nursery area. Can. J. Fish. Aquat. Sci. 46 (Suppl 1): 113-124.

Suthers, 1. M., and Sundby, S. 1993. Dispersai and growth of pelagic juvenile Arcto- Norwegian cod (Gudus rnorhia). inferred fiom otolith microstructure and water temperature. ICES J- mar- Sci. 50: 26 1-270.

Suthers, 1. M., and Sundby, S. 1996. Role of the Mdnight Sun: comparative growth of pelagic juvenile cod (Gadtrs morha) from the Arcto-Norwegian and a Nova Scotian stock. ICES J- mar. Sci. 53: 827-836-

Szedlmayer, S. T., and Howe, J. C. 1995. An evaluation of six marking methods for age- O red dmm, Sciaenops ocelZafzis. Fish. Bull. 93: 191-195.

Taggart, C. T., and Frank, K. T. 1990. Perspectives on larval fish ecology and recruitment processes probing the scales of relationships. In Large marine ecosystems: Patterns, prgcesses, and yields. Edited by K. Sherman, L. M. Alexander and B. D. Gold. American Association for the Advancement of Science, Washington, D. C. pp- 151-264.

Taggart, C. T., Drinkwater, K. F., Frank, K. T., McRuer, J., and LaRouche, P. 1989- Larval fish, zooplankton community structure, and physical dynamics at a tidal front. Rapp. P.-v. Réun. Cons. int. Explor. Mer. 191 : 184-194.

Thomas, L. M., Holt, S. A., and Arnold, C . R. 1995. Chernical marking techniques for larval and juvenile red drum (Sciaenops ocellatus) otoliths using different fluorescent markers. In Recent Developments in Fish Otolith Research. Edired by D. H- Secor, J. M. Dean and S. E. Campana. University of South Carolina Press, Columbia, South Carolina. pp. 703-7 1%

Thomas, R M. 1986. Growth of larval pelagic fish in the south-east Atlantic fkom daily otolith rings in 1982/83 and 1983/84 S. Afr- J. mar. Sci. 4: 61-77.

Thorrold, S. R, and McB. Williams, D. 1989. Analysis of otolith microstructure to determine growth histories in Iarval cohorts of a tropical herring (Herklotsichthys casfelnaui). Cam J. Fish. Aquat- Sci 46: 1615-1624.

Townsend, D. W., and Graham, J. 1. 1981. Growth and age structure of larval Atlantic hemng, Clupea hwenps harengus, in the Sheepscot River estuary, Maine, as deterrnined by daiiy growth increments in otoliths. Fish. Bull. 79: 123-130.

Warlen, S. M 1988. Age and growth of larval gulf menhaden, Brevoortia patromrs, in the northern Gulf of Mexico. Fish. Bull. 86: 77-90.

Yo klavich, M. M., and Bailey, K. M. 1990. Hatching period, growth and sumival of young walleye pollock Dzerugra chaCcogramma as detennined fiom otolith analysis. Mar. Ecol. Prog. Ser. 64: 13-23.