Parental effects on early life history traits of Atlantic herring (Clupea harengus L.) larvae

Journal of Experimental Marine Biology and Ecology 334 (2006) 51 – 63 www.elsevier.com/locate/jembe

Parental effects on early life history traits of Atlantic herring (Clupea harengus L.) larvae Anders Bang a,⁎, Peter Grønkjær a , Catriona Clemmesen b , Hans Høie c a

Department of Marine Biology, Institute of Biological Sciences, University of Aarhus, Finlandsgade 14, DK-8200 Aarhus N, Denmark b Leibniz-Institute of Marine Sciences at Kiel University (IFM-GEOMAR), Düsternbrooker Weg, 20,D-24105 Kiel, Germany c University of Bergen, Department of Biology, P.O. Box 7800, N-5020 Bergen, Norway Received 9 August 2005; received in revised form 6 January 2006; accepted 9 January 2006

Abstract A significant part of the variation in the early life history traits of fish can be ascribed to the parental origin of the individual larvae. The primary source of this parental contribution has been attributed to maternal effects and evidence for paternal effects is equivocal. Maternal effects are a non-genetic contribution of a female to its offspring but most reported maternal effects are products of both genetic and non-genetic contributions, i.e. female effects. In this study, parental effects on traits of larvae of Atlantic herring (Clupea harengus L.) at hatch were investigated at one temperature using a 5 × 3 factorial mating design (North Carolina Design II). This allowed estimation of the true maternal effect and the additive genetic variation (heritability). Furthermore, relationships between individual traits were examined and for the first time nucleic acid content and otolith size at hatch were examined together. A significant correlation between the two was found and it is argued to support the notion that otolith growth is more related to metabolic rate than to somatic growth. Maternal effects were detected in larval weight and yolk-sac volume, while paternal and, hence, genetic effects appeared in larval length, yolk-sac volume, RNA : DNA ratio, and lapillar area. The findings suggest that an increased emphasis should be placed upon the importance of male influence on success of early larval fishes. © 2006 Elsevier B.V. All rights reserved. Keywords: Full factorial mating design; Heritability; Metabolic rate; Otolith size at hatch; Paternal effects; RNA : DNA ratio

1. Introduction Parental effects on early life history traits of fish larvae are widely recognized and so is their importance for the fitness of the individual larva (Heath and Blouw, 1998). Already at hatch parental origin is the cause of large variation among individual larvae in important traits such as length and weight. These initial size differences within a population can cause very large differences in survival chances among individual larvae ⁎ Corresponding author. Tel.: +45 8942 4379; fax: +45 8942 4390. E-mail address: [email protected] (A. Bang). 0022-0981/$ - see front matter © 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.jembe.2006.01.003

and cohorts and, consequently, parental effects may have a substantial influence on recruitment (Miller et al., 1988; Rice et al., 1993). It is usually assumed that most of this parentally induced variation in larval traits is attributable to maternal effects propagated through the egg characteristics and, generally, paternal effects are not considered. As a consequence, much of the previous research has focused on detecting maternal effects in the phenotypic traits of eggs and evidence for significant maternal effects on egg size is now well-established for many species (Chambers and Leggett, 1996). However, even though a maternal effect is defined as the non-genetic contribution of a female to its offspring

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A. Bang et al. / Journal of Experimental Marine Biology and Ecology 334 (2006) 51–63

(Reznick, 1991) the reported maternal effects in most studies on early life history traits are in reality female effects, i.e. products of both genetic and non-genetic contributions. The genetic and maternal effects can be discerned in fish using the proper experimental design (Lynch and Walsh, 1998) but, nevertheless, very few have made an effort to partition the observed variation due to female influence into its underlying genetic and non-genetic (maternal) components (but see Pakkasmaa and Jones, 2002). Paternal or male effects, on the other hand, are almost always considered as synonymous with genetic effects, since the only significant contribution of the sperm is DNA. The ability to observe potential paternal and, hence, genetic effects on early life history has, however, been impaired by the fact that researchers often pool milt from multiple males when fertilizing eggs (Rideout et al., 2004) and in field studies eggs from a single spawning event are often fertilized by multiple males (Bekkevold et al., 2002). In the few studies that have looked specifically for paternal effects the evidence is equivocal, but male effects on certain early life history traits have been demonstrated for Atlantic herring (Høie et al., 1999a,b), brown trout (Vollestad and Lillehammer, 2000) and haddock (Rideout et al., 2004). The variable results on the degree to which males and females affect larval traits are probably dependent on the difference in egg size between females. If egg sizes are similar, it may allow male-induced effects to be observed, but these effects may be masked if egg sizes are very different (Rideout et al., 2004). Few studies have examined parental effects on important physiological traits such as metabolic rate, which together with feeding rate strongly influence the growth rate of a fish larva (Jobling, 1985; Kiørboe et al., 1987). The growth rate of an individual larva has important consequences for its chances of survival but, obviously, it can only be determined in the period following hatch at which time environmental effects potentially mask or confound any parental effects. Since metabolic rate influences growth rate it would perhaps be better to measure effects directly on this trait, but this has proven difficult for early life stages and, once hatched, metabolic rate is also very prone to environmental influence (Huuskonen et al., 2003). Recently, however, Bang et al. (2004) measured oxygen consumption rate in the embryonic stage of individual zebrafish eggs and argued that this reflected the predetermined basal metabolic level at that temperature. Measuring oxygen consumption rate on individual fish eggs in numbers required for parental effects analyses is not yet feasible, but Bang and Grønkjær (2005) showed that

there was a positive correlation between the cumulated oxygen consumption for the embryonic period of the zebrafish and the size of the otolith at hatch. Hence, it was possible to assess the metabolic level of the zebrafish larvae indirectly through measuring otolith size at hatch. Another potentially important trait which, like the otolith size at hatch, may assess the metabolic state of an organism is the nucleic acid content, in particular the amount of RNA and the RNA : DNA ratio (Clemmesen, 1994, 1996). Small larvae have very high RNA concentrations compared to larger fish, which suggests an initial provision of RNA that is independent of food consumption rate (Houlihan et al., 1995). Furthermore, RNA concentrations in eggs and larval fish show high variability as indicated by RNA to DNA ratios (Clemmesen, 1987, 1994) and parental effects have been found in both RNA and DNA content (Høie et al., 1999a; Heyer et al., 2001). Only a few studies have examined parental effects on otolith size at hatch (an indicator of metabolic rate) (Høie et al., 1999b) or RNA content (an indicator of protein synthesis capacity) (Høie et al., 1999a; Heyer et al., 2001), and no studies have concurrently examined both. Based on their association with metabolism a connection between the two traits is expected. This would explain why otolith size at hatch seems to be a fitness related trait (Meekan and Fortier, 1996; Grønkjær and Schytte, 1999) and lend support for the use of otolith size at hatch as a tool for studies of the effects of metabolic rates on larval viability (Bang and Grønkjær, 2005; Bochdansky et al., 2005). Finally, if paternal effects on early life history traits exist they might be more likely to be expressed in physiological traits such as these rather than in traits which are likely to be a direct consequence of egg size. In this study we used a factorial mating design to analyze the maternal and paternal effects on the early life history traits of Atlantic herring larvae (Clupea harengus L.) and partition the observed phenotypic variance into its underlying genetic and non-genetic components. Furthermore, we looked at correlations among traits with special emphasis on the correlations between otolith size at hatch and RNA : DNA ratio of the larvae. 2. Materials and methods 2.1. Experimental design Ripe Norwegian autumn-spawning herring (C. harengus L.) were caught on September 30, 2003, off south-western Norway (60°34′ N and 05°01′ E). The surface water temperature at catch was 10.4 °C. Three

A. Bang et al. / Journal of Experimental Marine Biology and Ecology 334 (2006) 51–63

males and five females were chosen so as to create the largest possible size range for the parental fish. Eggs from the females were fertilized separately with sperm from the males resulting in a 3 × 5 factorial mating design (North Carolina Design II; Lynch and Walsh, 1998). Eggs were fertilized by stripping gametes onto two glass plates for every parental combination and incubated in the laboratory at 9.8 ± 0.1 °C (range) in two incubation tanks (215 × 40 cm, 10 cm depth). Tanks were continuously supplied with 1.0 μm filtered seawater (33.7 ± 0.1 psu) at a rate of 4.0 l min− 1 and kept at a light regime of 12L : 12D (light intensity approx. 100 lux). Each plate, which contained approximately 500–1000 eggs, was examined under a dissecting microscope to determine the fertilization success of each parental combination on the first day after fertilization. Grey eggs with no sign of cell division were classified as unfertilized. Six and seven days after fertilization 48 successfully developing eggs from each parental combination (24 eggs from each replicate tank) were scraped off the glass plates. Furthermore, an extra 48 eggs from a randomly chosen parental combination were taken for use as a reference in the RNA :DNA analyses (see later). All eggs were placed individually in 24-well plastic plates (Nunc) so that the eggs of every family were still kept separate with each family having their eggs in two 24-well plates. They were subsequently returned to the incubation tanks along with the remaining eggs on the glass plates. Each well in the plastic plates was 20 mm deep, 16 mm in diameter and had a volume of 4 ml. A lid with a 15 mm hole for each well was placed over each plate. A 250 μm plankton mesh was placed between the wells and the lid to prevent larvae from escaping. Water exchange was enhanced by manually flushing water over each plate every morning and evening during the incubation period. At the same time the plates were examined for dead eggs and hatching larvae. Nine and ten days after fertilization digital pictures were taken of all eggs inside their respective wells at 25× magnification using a dissecting microscope and an Olympus Camedia C-4040 camera. These pictures were used for subsequent measurements of egg diameter. Hatched larvae from the wells were removed on the day of hatching and also digitally photographed at 12.5× magnification. They were then frozen in a drop of sea water in individually labelled 1.5 ml Eppendorf tubes in liquid nitrogen prior to being stored in a − 80 °C freezer until further analyses. From the digital pictures, egg diameter was estimated as the longest distance across the egg shell while larval standard length, SL, was measured as the distance from the tip of the upper jaw to the notochord end. For yolk-

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sac volume, Vy, the formula for a prolate spheroid was used based on the shape of the yolk sac Vy ¼

k  L  H2 6

where H is the height and L the length of the yolk sac (Blaxter and Hempel, 1963). All lengths were estimated to the nearest 0.01 mm using the image analysis software ImageTool 3.0 (UTHSCSA). The remaining eggs from the incubation tanks (two glass plates per family) were transferred to 5 l buckets, one for each parental combination, the day before hatching was expected to occur. For each combination hatching success was then determined by counting unhatched eggs on the plates a few days after the modal hatching date. To check for potential average differences in survival, 100 hatched larvae from each parental combination were kept in the buckets without food and dead larvae were counted and removed each day. 2.2. Otolith and nucleic acid analyses Larvae were transferred from the freezer directly to a freeze-drier (-Christ alpha 1–4) and dried for 16 h at −57°C. Freeze-dried larval mass was then recorded to the nearest microgram on a Sartorius Micro SC2 balance. Larvae were put on ice before otolith removal. Right and left sagitta and lapillus were quickly (2–3 min) removed from individual larvae under a dissecting microscope at 60× magnification using a cold polarised light source and fine insect needles mounted on handles. The unpolished otoliths were embedded in thermoplastic resin (Buehler) until further analyses. The thermoplastic resin was subsequently reheated and otoliths turned so as to reveal the maximum area of each otolith before image analysis. Remounting of otoliths indicated that the positioning process gave accurate and precise estimates of maximum area. Furthermore, in order to avoid optical distortion, excess resin was removed so only a thin layer covered the otoliths. All otoliths were essentially spherical but some had to be omitted from further analyses due to having two or more cores or an irregular shape (2%). Digital pictures of the otoliths were taken at 400× magnification using a light microscope equipped with an Olympus DP50 highresolution video camera. The otolith area was measured manually on-screen with the image analysis software ImageTool 3.0 (UTHSCSA). Otolith area was measured instead of the more commonly used otolith radius since area is a better estimate of otolith size than any unidimensional measure (Meekan et al., 1998). The analyses of whole-larva RNA and DNA content were performed using a modification of Clemmesen (1993)

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A. Bang et al. / Journal of Experimental Marine Biology and Ecology 334 (2006) 51–63

as described in Malzahn et al. (2003) and Belchier et al. (2004). Briefly, following otolith removal the larvae were rehydrated in Tris–SDS buffer (Tris 0.05 M, NaCl 0.1 M, EDTA 0.01 M, SDS 0.01%) for 30 min. Cells were disrupted by shaking in a cell-mill with a mixture of two different size glass beads (diameters 2 mm and 0.17–0.46 mm). The homogenate was centrifuged at 3829 g at 1°C for 8 min and only the supernatant was analysed. Nucleic acids were quantified fluorimetrically using ethidium bromide as the fluorophor in a microtitre fluorescence reader (Labsystems, Fluorescan Ascent) with excitation and emission wavelengths set at 355 and 590 nm, respectively. Total fluorescence in a sample was measured first. RNAwas then enzymatically digested by the addition of RNase (Ribonuclease A, from bovine pancreas; SERVA 34388) and the RNA values determined by subtraction after a second reading. Standard calibration curves for RNA were constructed using serially diluted preparations of 16Sand 23S RNA (Boehringer Mannheim, 206936). DNA values were obtained from the RNA standard curve using a conversion factor of 0.4545, the Lepecq ratio (Lepecq and Paoletti, 1966). Due to the possibility that the removal of otoliths from the larvae before nucleic acid analyses could influence the DNA and RNA content, a reference sample was run. This was a replicate from a randomly chosen combination (F7) where otoliths were not removed before the analyses of nucleic acids. It confirmed that the handling procedure resulted in a significant loss of DNA and RNA content (12.5% and 12.9%, respectively), probably due to the small amounts of tissue that came free with the otoliths. Since it varied how much tissue was removed when dissecting each larva, absolute amounts of nucleic acid could not be used in the analyses. However, the RNA :DNA ratio itself was not affected (t45 = 0.206, P= 0.838) and was consequently used in further analyses. 2.3. Statistical analyses To avoid any possible confounding effects of hatching date on other early life history traits, only larvae which hatched on the day of modal hatch were used in the analyses. This reduced the initial sample size of 48 eggs per family to maximally 25 (Table 3). For the analyses of variance the sample size was further reduced to 20 per parental combination to achieve a balanced design (Table 6). Partial correlations (Pearson product-moment correlations) between relevant early life history traits were calculated both at the individual level and as family mean values. This was done because with the large sample size in the individual analyses the value of the correlation coefficient required to achieve statistical sig-

nificance is rather low. Before comparison, non-normal variables were Box-Cox transformed. Due to multiple comparisons an adjustment of the significance level was performed using the Dunn–Sidák method (Sokal and Rohlf, 1995). However, according to the hypotheses described in the Introduction the correlation between otolith size and relative RNA content is considered to be a priori and, hence, not adjusted with Dunn–Sidák. The data were analysed by analysis of variance (ANOVA) and t-tests, and examined for homogeneity of variances by Levene's test. If variances were heterogeneous data were Box-Cox transformed. Fertilization and hatching percentages were arcsine transformed before analysis. Because of the mating design (North Carolina II) the total phenotypic variance in the offspring traits could be partitioned into maternal, genetic and environmental components following a two-way ANOVA with sire and dam as random effects and offspring trait as dependent variable (Lynch and Walsh, 1998). Specifically, the additive genetic variance, VA, can be estimated. This variance is relevant for the prediction of a response to a selection as the effects of selection depend on VA and not on genetic variation in general. The sire component, Vsire, estimates 0.25 of VA and VA was estimated as 4Vsire. The dam component, Vdam, also estimates 0.25 of VA, but in addition, it includes maternal effects variance, VM, of both genetic and non-genetic origin, and consequently VM was estimated as Vdam − Vsire. The variance due to the interaction between sire and dam estimates 0.25 of dominance genetic variance, VD, and VD was estimated as 4Vdam × sire. Finally, the residual variance represents additive dominance and environmental effects, and environmental variance VE was estimated as VE = VP − 0.5VA − 0.75VD, where Vp is the total phenotypic variance. Heritability, h2, was estimated as VA / VP. Furthermore, the following hypothesis was evaluated 2 by use of F tests; σsire = 0 (Fsire,dam × sire = MSsire / 2 2 MSdam × sire) and σsire = σdam (Fsire,dam = MSsire / MSdam), which tests if there are significant heritability and maternal effects, respectively (Lynch and Walsh, 1998). All statistical analyses were performed using the statistical package SPSS for Windows (Release 10.0). 3. Results 3.1. Parental fish, incubation and hatching The parental fish used constituted a wide range in ages (4–7 years) and sizes (30–36 cm TL) (Table 1). Fertilization and hatching rates were generally high for all parental combinations with only female 3 showing somewhat reduced egg fertilization (Table 2). Data was

A. Bang et al. / Journal of Experimental Marine Biology and Ecology 334 (2006) 51–63 Table 1 Data on parental fish used in the experiments Fish

Total length (cm)

Weight (g)

GSI (%)

Age (years)

Female 1 Female 2 Female 3 Female 4 Female 5 Male 1 Male 2 Male 3

35.0 34.0 32.5 32.0 29.5 36.0 32.5 31.5

453 412 346 341 213 445 401 340

22.7 25.2 16.7 12.6 19.8 11.7 26.1 28.0

6 7 5 4 4 7 5 4

Total length was measured to the nearest 0.5 cm. Weight is wet weight before stripping. GSI is the gonadosomatic index. The fish were aged by counting annual zones in the otoliths.

analyzed as an unreplicated two-way ANOVA and overall, there was no influence from male (fertilization, F2,8 = 0.275, P = 0.766; hatching, F2,8 = 1.334, P = 0.316) or female effects (fertilization, F4,8 = 2.411, P = 0.135; hatching, F4,8 = 3.673, P = 0.055), although the female effect on hatching was nearly significant. Furthermore, the larvae from the different parental combinations kept until starvation did not show any apparent difference in their general mortality pattern (data not shown). Individual eggs from the 24-well plates hatched at night over 4 days with peak hatching at day 13. The remaining eggs on the glass plates had mean hatching date a day earlier on day 12. 3.2. Early life history traits and their correlation A summary of the recorded early life history traits of all larvae at hatch is shown in Table 3 and visualized as box-plots in Fig. 1. Not all of the characteristics could be measured on every larva due to incomplete measurements, e.g. irregular shaped otoliths with multiple cores. A paired t-test revealed no difference in otolith areas between right and left lapillus (t345 = 1.868, P = 0.063) or sagitta (t340 = 0.527, P = 0.598). Furthermore, the mean difference in otolith areas between sides (1.0 and 3.5 μm2 for sagitta and lapillus, respectively) was so small compared with standard errors for the combinations (Table 3) that the mean of the two otolith pairs is used in all analyses. The use of egg diameter as a measure of egg size proved defective. Due to the benthic nature of herring eggs, their shape is not spherical but, rather, oval with major depressions at points where they touch a surface (the plate or other eggs). Hence, a linear measure is not representative of actual egg size and, consequently, the trait was omitted from all analyses. Most of the early life history traits were positively correlated (Table 4). However, due to the very

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conservative nature of the Dunn–Sidák correction when many comparisons are performed only a few correlations are significant. Generally, the same pattern emerged whether testing individual values or family means but the critical values for the individual correlations were rather low compared to the family mean correlations (Table 4). Both levels showed a strong correlation between yolk-sac volume and freezedried weight. At the individual level there were correlations between larval length and sagittal area as well as between sagittal and lapillar area. The correlation between lapillar and sagittal area and RNA : DNA ratio was deemed marginally non-significant by the Dunn–Sidák correction, but since these were a priori hypotheses they are considered significant at the 5% level. Accordingly, lapillar area was positively correlated with the RNA : DNA ratio both at the individual as well as at the family level (individual values, P = 0.036; family values, P = 0.025). The correlation between sagittal area and RNA : DNA ratio was only significant at the individual level and the correlation was negative (individual values, P = 0.006; mean values, P = 0.136). 3.3. Components of ELH trait variance The relative amount of variation within a single parental combination and between different parental combinations was investigated by a one-way ANOVA on the full dataset (Table 5). For freeze-dried weight and yolk-sac volume most of the variation was between groups, while variation for the other traits was predominately within groups. There were parental effects on all of the examined traits (Table 6). A sire effect was evident on standard length, yolk-sac volume, RNA : DNA ratio and lapillar area, while the effect on dry weight was nearly significant. Explained variance for yolk-sac volume (3.9%) and dry weight (1.2%) was, however, very small compared to the female contribution. A dam effect was evident on standard length, yolk-sac volume, dry weight, and lapillar and sagittal area with females explaining a particular large part Table 2 Matrix of fertilization and hatching percentages for the 15 parental combinations Parent

Female 1

Female 2

Female 3

Female 4

Female 5

Male 1 Male 2 Male 3

84, 87 95, 80 83, 78

94, 86 81, 78 96, 82

35, 81 75, 80 39, 80

83, 86 64, 93 83, 91

96, 99 55, 98 99, 82

Numbers before and after commas represent fertilization and hatching percentages, respectively.

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A. Bang et al. / Journal of Experimental Marine Biology and Ecology 334 (2006) 51–63 1.0

(a)

600

(d)

500

Sagitta area (µm2)

Yolk-sac volume (mm3)

0.8

0.6

0.4

400

300 0.2

0.0

(b)

700

8.6

8.2

7.8

500

400

7.4

300

7.0

200

0.25

(e)

600

Lapillus area (µm2)

Larval standard length (mm)

9.0

200

2.6

(c)

(f)

2.2

RNA:DNA

Freeze-dried weight (mg)

2.4 0.20

0.15

2.0

1.8

0.10

1.6 0.05 1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

Parental combination

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

Parental combination

Fig. 1. Box-plots of (a) yolk-sac volume, (b) larval standard length, (c) freeze-dried weight, (d) sagitta area, (e) lapillus area, and (f) RNA : DNA ratio. The top and bottom of the box represent the upper and lower quartiles, respectively. The solid and dashed horizontal line within the box represents the median and mean value of the data, respectively. The upper and lower limit of the whiskers represents the largest and smallest value within 1.5 interquartile ranges of the top and the bottom of the boxes, respectively. Data outside the whiskers are considered outliers and represented by solid circles. Parental combinations as defined in Table 3, vertical dotted lines separate male combinations.

of the variation for yolk-sac volume (66.3%) and dry weight (77.4%). An interaction effect was only evident for the RNA : DNA ratio, while the interaction for lapillus area was nearly significant. For the RNA : DNA ratio the interaction term could be explained by apparently consistent higher ratios of the progeny from the younger females

3–5 in combination with males 1 and 3 (Fig. 1). For lapillus area no clear tendency explained the interaction effect but differences in mean areas were larger among females than among males. The variance was partitioned into its components and larval length, yolk-sac volume, RNA : DNA ratio, and

A. Bang et al. / Journal of Experimental Marine Biology and Ecology 334 (2006) 51–63

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Table 3 Mean phenotypic characteristics (±S.D.) of herring larvae from the 15 parental combinations at hatch Male

Female

Combination

n

Standard length (mm)

Yolk-sac volume (mm3)

Freeze-dried weight (mg)

RNA : DNA

Lapillus area (μm2)

Sagitta area (μm2)

1 1 1 1 1 2 2 2 2 2 3 3 3 3 3

1 2 3 4 5 1 2 3 4 5 1 2 3 4 5

F1 F2 F3 F4 F5 F6 F7 F8 F9 F10 F11 F12 F13 F14 F15

25 21 25 25 25 25 23 25 25 25 25 24 25 25 25

8.32 ± 0.152 8.25 ± 0.161 8.30 ± 0.148 8.37 ± 0.135 8.37 ± 0.176 8.26 ± 0.179 8.33 ± 0.138 8.41 ± 0.162 8.43 ± 0.142 8.36 ± 0.104 8.36 ± 0.153 8.49 ± 0.119 8.41 ± 0.133 8.53 ± 0.128 8.53 ± 0.133

0.44 ± 0.048 0.39 ± 0.033 0.48 ± 0.046 0.58 ± 0.057 0.42 ± 0.040 0.45 ± 0.074 0.42 ± 0.032 0.55 ± 0.050 0.66 ± 0.059 0.44 ± 0.036 0.43 ± 0.045 0.38 ± 0.031 0.50 ± 0.048 0.65 ± 0.053 0.43 ± 0.039

0.160 ± 0.0131 0.154 ± 0.0065 0.178 ± 0.0131 0.204 ± 0.0110 0.157 ± 0.0093 0.157 ± 0.0100 0.156 ± 0.0079 0.176 ± 0.0090 0.206 ± 0.0085 0.154 ± 0.0061 0.148 ± 0.0123 0.154 ± 0.0061 0.178 ± 0.0083 0.201 ± 0.0066 0.150 ± 0.0054

2.03 ± 0.096 2.00 ± 0.111 1.99 ± 0.080 2.16 ± 0.109 2.08 ± 0.076 2.02 ± 0.090 2.00 ± 0.067 1.99 ± 0.088 2.00 ± 0.098 2.01 ± 0.053 2.05 ± 0.082 2.02 ± 0.147 2.07 ± 0.092 2.14 ± 0.113 2.07 ± 0.077

450 ± 39.7 452 ± 40.8 471 ± 35.8 494 ± 44.3 448 ± 24.6 437 ± 34.8 432 ± 33.2 467 ± 31.1 450 ± 45.7 432 ± 33.6 459 ± 27.5 458 ± 37.7 483 ± 30.8 488 ± 31.8 446 ± 23.2

387 ± 44.4 411 ± 45.5 436 ± 33.7 428 ± 43.8 402 ± 30.4 380 ± 33.5 405 ± 54.3 418 ± 31.9 409 ± 39.2 400 ± 30.8 401 ± 31.4 413 ± 33.9 441 ± 31.4 414 ± 45.0 400 ± 37.5

Sagitta and lapillus area are the mean of both right and left otolith.

lapillar area showed significant heritability, h2 (Table 7). Maternal effects were high but not significant for yolksac volume and dry weight (F2,4 = 0.109, P = 0.899 and F2,4 = 0.0328, P = 0.968, respectively). However, caution should be exhibited when looking at absolute values of the variance components due to their high standard errors. 4. Discussion 4.1. Parental fish, incubation and hatching The applied experimental temperature (9.8 °C) is close to the temperature at catch for the given stock

Table 4 Partial Pearson product-moment correlations, r, between early life history traits of herring larvae Trait

(1)

(2)

(1) Standard length – 0.13 (2) Yolk-sac 0.33 – volume (3) Freeze-dried −0.27 0.91⁎ weight (4) RNA : DNA 0.29 − 0.06 (5) Lapillus area −0.04 0.06 (6) Sagitta area 0.17 − 0.38

(3)

(4)

(5)

(6)

0.05 0.25⁎

0.10 − 0.02 0.19⁎ 0.12 0.10 − 0.07

–

0.11

0.02 0.11 0.37

0.12

(10.4 °C) and also corresponds well with the natural conditions generally experienced by herring larvae in autumn with common temperatures in the North Sea and Skagerrak being 10–11 °C in October (Johannessen et al., 2000). Furthermore, the parental fish represented the natural size range of autumn-spawning herring (approx. 25–37 cm) and included both inexperienced (4 year old) and experienced spawners (Table 1). Fertilization and hatching success was somewhat variable but generally very high (Table 2) and comparable to other laboratory studies (Høie et al., 1999b). Parentage had no effect upon egg mortality, with the exception of a nearly significant female effect on hatching success. Also, there was no obvious effect upon average larval viability indicating that none of the parental combinations were incompatible. Eggs in the 24-well plates had a mean hatch day a day later than remaining eggs on the glass plates, which is most likely due to the different

0.15

0.11 − 0.15 0.67 – 0.28⁎ − 0.48 0.69 –

Table 5 Relative amount of variation for early life history traits of herring larvae Trait

Within a single parental combination

Between different parental combinations

Standard length Yolk-sac volume Freeze-dried weight RNA : DNA Lapillus area Sagitta area

75.6%

23.4%

30.5%

69.5%

26.3%

73.7%

83.9% 76.9% 84.6%

16.1% 23.1% 15.4%

–

Correlations above the diagonal are based on individual values (n = 349–368) and correlations below the diagonal are based on family mean values (n = 15). Statistically significant correlations are marked ⁎P b 0.05. Table-wide significance levels are adjusted using the Dunn– Sidák correction. Critical values for the correlations prior to Dunn– Sidák are r = 0.11 (individual values) and r = 0.51 (family mean values).

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A. Bang et al. / Journal of Experimental Marine Biology and Ecology 334 (2006) 51–63

Table 6 Paternal, maternal and interaction influences on early life history traits at hatching for herring larvae Trait

Source

df

SS

Standard length

Sire Dam Interaction Error Sire Dam Interaction Error Sire Dam Interaction Error Sire Dam Interaction Error Sire Dam Interaction Error Sire Dam Interaction Error

2 4 8 285 2 4 8 285 2 4 8 285 2 4 8 285 2 4 8 285 2 4 8 285

1.046 0.664 0.291 6.395 0.0683 1.253 0.00324 0.721 0.00164 0.100 0.00155 0.0314 0.225 0.251 0.202 2.559 26773 57244 14555 230896 2.989 39.66 6.042 192.01

Yolk-sac volume

Freeze-dried weight

RNA : DNA

Lapillus area

Sagitta area

F

P

14.36 4.561 1.623

0.002 0.033 0.118

8.441 77.47 1.599

0.011 b0.001 0.125

4.238 128.7 1.762

0.056 b0.001 0.084

4.457 2.491 2.809

0.050 0.127 0.005

8.541 9.131 1.953

0.010 0.004 0.055

1.979 13.13 1.121

0.200 0.001 0.349

Variance * 10− 3 (±S.E. * 10− 3)

Relative contribution (%)

4.87 (±3.70) 2.16 (±1.62) 0.699 (±0.819) 22.4 (±1.87) 0.301 (±0.242) 5.15 (±3.01) 0.0757 (±0.0912) 2.53 (±0.211) 0.00628 (±0.00588) 0.413 (±0.240) 0.00420 (±0.00436) 0.110 (±0.00919) 0.868 (±0.803) 0.627 (±0.632) 0.812 (±0.566) 8.98 (±0.750) 118 * 103 (±95.0 * 103) 212 * 103 (±138 * 103) 37.8 * 103 (±40.8 * 103) 810 * 103 (±67.6 * 103) 7.39 (±11.0) 153 (±95.6) 4.08 (±17.1) 674 (±56.2)

16.2 7.2 2.3 74.3 3.9 66.3 1.0 28.8 1.2 77.4 0.8 20.6 7.7 5.6 7.2 79.6 10.0 18.0 3.2 68.7 0.9 18.2 0.5 80.4

Table shows values from two-way ANOVA with sire and dam as random effects and offspring trait as dependent variable. Dataset was randomly reduced to 20 measurements per parental combination to achieve a balanced design.

microenvironment with better oxygen supply and no contact with conspecifics. 4.2. Early life history traits and their correlation For yolk-sac volume and freeze-dried weight most of the variation occurred between parental combinations, while larval length, nucleic acid ratio, and otolith areas, predominately showed variation within parental combinations (Table 5). The former two traits are predominately affected by (non-genetic) maternal investments and it is therefore not surprising that they tend to vary

more between crosses or different females than traits, which are not immediately influenced by egg size. There was a strong positive correlation between larval weight and yolk-sac volume (Table 4). This is to be expected considering the yolk sac in newly hatched herring larvae contribute significantly to its weight (Blaxter and Hempel, 1963). Due to the inefficiency of egg diameter as a reliable measure of egg size in this study, larval weight is the best available measure of maternal investment. The absence of a relationship between larval weight and length is surprising, since this is generally well established (Pepin, 1995). A low overall

Table 7 Causal components of phenotypic variance, heritability and maternal effect for early life history traits for herring larvae Trait

VP (⁎ 103)

VA (⁎ 103)

VM (⁎ 103)

VD (⁎ 103)

VE (⁎ 103)

h2

Maternal effect

Standard length Yolk-sac volume Freeze-dried weight RNA : DNA Lapillus area Sagitta area

30.1 7.80 0.533 11.3 118 * 10− 2 838

19.5 1.20 0.0251 3.47 472 * 10− 3 29.6

− 2.71 4.85 0.406 − 0.241 94.1 * 10− 3 146

2.80 0.303 0.0168 3.25 151 * 10− 3 16.3

18.3 6.94 0.508 7.12 828 * 10− 3 811

0.65⁎ 0.16⁎ 0.047 0.31⁎ 0.40⁎ 0.035

−0.090 0.62 0.76 −0.021 0.080 0.17

Significant heritabilities and maternal effects are marked ⁎P b 0.05. VP, total phenotypic variance; VA, additive genetic variance; VM, maternal effects; VD, dominance effects; VE, environmental variance; h2, heritability.

A. Bang et al. / Journal of Experimental Marine Biology and Ecology 334 (2006) 51–63

variation in larval length (CV = 2.0%, Table 3) may have added to this inconsistency, since correlation methods are vulnerable to sample truncation effects (Meekan et al., 1998). Length at hatching correlates positively with age or incubation time (Chambers et al., 1989) and since all larvae were from the same modal hatch day, variation in length may have been reduced. This may also have created the somewhat irregular relation with otolith areas, in that larval length was correlated to sagitta but not lapillus area (Table 4). A consistent correlation between larval length and otolith area at hatch does not seem to exist, Meekan et al. (1998), Høie et al. (1999a,b) and Bang and Grønkjær (2005) found poor correlations between the two, while Miller et al. (1999) did find a positive relationship between otolith size and larval standard length at hatching. These findings add to the notion that otolith growth may not always be governed by somatic growth (see below). The sizes of the two pairs of otoliths, lapillus and sagitta, were positively correlated (Table 4). This correlation is commonly observed (Miller et al., 1999) and not surprising, since their growth seems to be governed by the same fundamental physiological processes (Morales-Nin, 2000). In this study, lapillus was the bigger otolith at hatch (Table 3), which is the case for many species of fish (e.g. Campana, 1989). However, the relationship between sizes of sagitta and lapillus at hatch has been shown to depend on temperature for Atlantic herring (Høie et al., 1999b) with sagitta being the larger otolith at higher temperatures and, consequently, the observed otolith sizes should not be extrapolated to temperatures other than the one used in this study (10 °C). In the present study, the RNA : DNA ratios at hatch had a mean value of 2.0 (Table 3). Using similar fluorimetric techniques Clemmesen (1994) found a mean value of 3.0 for Baltic Sea herring eggs, while Høie et al. (1999a) found values between 2.8 and 3.8 for newly hatched Norwegian herring. Although methodological differences (e.g. different standards) may contribute to this discrepancy, the reported higher values are most likely due to biological differences. Both earlier studies were conducted with spring spawning stocks from which both eggs and newly hatched larvae are significantly larger and supposedly in better condition than from autumn spawning stocks such as the one studied here (Hempel and Blaxter, 1967). Furthermore, spring spawners typically experience lower temperatures at incubation than autumn spawners and RNA concentrations generally are higher at lower temperatures (Bergeron, 1997; Høie et al., 1999a). Whether the reported differences in RNA : DNA ratios reflect environmental influences or adaptive responses is unclear.

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The a priori hypothesis of a positive relationship between otolith size at hatch and relative RNA content was confirmed with the correlation between lapillar area and RNA : DNA. Possibly owing to the larger size of the lapillus, this relationship was more robust than the relationship between sagittal area and RNA : DNA. This was a negative one, which is peculiar considering the strong positive relationship between sagittal and lapillar area. Examining the correlations more closely it was evident that the relationship between sagitta and RNA : DNA was only driven by a few families, which could explain the negative result. Furthermore, the process of performing partial correlations can produce spurious results when two variables, such as lapillus area and sagittal area, co-vary strongly. This is supported by the fact that sagittal area and RNA : DNA ratio became positively correlated when simple as opposed to partial correlations were performed. The RNA : DNA ratio is an index of a cell's metabolic rate and has been proven to be a sensitive measure of protein synthetic capacity and growth rate in larval fish (Ferron and Leggett, 1994; Buckley et al., 1999; Belchier et al., 2004). The connection with otolith size lends additional support for the growing body of evidence that otolith growth is more related to metabolic rate than to somatic growth rate (Mosegaard et al., 1988; Wright, 1991). This provides a further rationale for using otolith size at hatch as a proxy trait for estimating the predetermined basal metabolic level of individual larvae whose measurement is otherwise very difficult to obtain (Bang et al., 2004; Bang and Grønkjær, 2005). 4.3. Parental effects and components of variation All of the traits examined showed a large amount of variation and a significant part of this variation was explained by both female and male influences (Table 6). Our findings suggest that in Atlantic herring, female effects are expressed in larval length and weight, yolksac volume, lapillus and sagitta size, while male effects are expressed in larval length, yolk-sac volume, RNA : DNA ratio, and lapillar area. For RNA : DNA ratio a female effect was also revealed through interaction with respective males and the male–female interaction term was equivalent to the male effect (7.2% and 7.7%, respectively). Consequently, the RNA : DNA ratio of progeny of a male can be significantly influenced by the female parent. Interestingly, none of the female effects translated into significant maternal effects (Table 7). However, we believe that the absence of maternal effects on yolk-sac volume and dry weight are due to

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large standard errors, since females explained more than 2/3 of the variance for these traits (Table 6). It is important to note the traits that failed to show an effect of paternal or maternal origin. No maternal effect was evident on the larval length. This is otherwise commonly seen between species due to the shared connection of female size and larval length with egg size (Chambers, 1997). However, within a species this relationship is generally more weak and dependent on having a wide range in larval lengths. Consequently, the absent maternal effect in this study may result from the truncation effect as previously discussed. Furthermore, there was no maternal effect on the RNA : DNA ratio, which is somewhat unexpected since the egg receives all of its initial RNA from the mother together with the yolk. However, the period over which maternal RNA is functional in fishes is unknown and almost nothing is known about gene expression and/or mRNA translation in fish embryos (Brooks et al., 1997). The finding of a male influence on RNA : DNA ratio in this study suggests that the embryos' own genes are being activated well before hatching. The few studies conducted on parental effects on nucleic acid content support the results found in this study. In a pilot study on Atlantic herring, Høie et al. (1999a) found a male but no female effect on RNA : DNA ratio, while Heyer et al. (2001) failed to find maternal effects on RNA : DNA ratios in yellow perch. Conversely, sagitta area and freezedried weight at hatch were not influenced by different males. For dry weight this is not surprising since it is strongly correlated to egg size which is largely determined by the maternal investment (Chambers and Leggett, 1996). Regarding sagitta, it seems that the larger lapillus better reflects the physiological processes of the embryo (as seen by its relation to RNA : DNA) and, hence, better reflects the paternal effect. In addition to this study, paternal effects on standard early life history traits of fish have only been demonstrated in a few instances; larval length (Panagiotaki and Geffen, 1992; Rideout et al., 2004), nucleic acid content (Høie et al., 1999a), otolith size (Yamamoto and Reinhardt, 2003) and growth rate (Vollestad and Lillehammer, 2000). Aside from the effects of different and improper experimental designs, we believe that the generally equivocal results concerning paternal effects on the early life history traits of larval fish are mainly due to the traits chosen for analyses. At first, any sire effect is expected to appear at the physiological level. Then, depending on the magnitude of the maternal influence through egg deposits only later should it manifest itself in actual size related traits. Indeed, most studies are unable to detect paternal effects before maternal effects diminish and, since few studies follow individuals that long, paternal effects are not detected or assumed to

be of minor value (Heath and Blouw, 1998). Incorporation of physiological traits, on the other hand, allows for detection of sire effects within the time frame of most crossing experiments. The large male effect on a number of the early life history traits translated into a large genetic contribution and, hence, heritability for larval length, lapillus area, RNA : DNA ratio and yolk-sac volume (Table 7). Laboratory estimates of heritabilities have been shown to generally provide reasonable estimations of both the magnitude and the significance of heritabilities in nature (Weigensberg and Roff, 1996), however, as in this study, heritability estimates frequently possess large standard errors (Mousseau and Roff, 1987) and, hence, the absolute values should be treated cautiously. Furthermore, in general, the heritability of a trait is different in each population and in each set of environments; extrapolating the values from this study to other populations and sets of environments should be done with great care. The significant heritabilities for the given traits imply that they all have the ability to respond to natural selection. The high level of relative additive genetic variability may be explained by a large number of genes affecting the selected traits or by a lack of a stabilizing selection to reduce their phenotypic variance (Houle, 1992; Merilä and Sheldon, 1999). Alternatively, it is suggested that additive genetic variance can be maintained, even under strong stabilizing selection, when there is unpredictable spatio-temporal variation in different abiotic and biotic factors affecting traits (Blanckenhorn, 2000). This is certainly the case for marine larvae that experience large environmental variability in space and time during early life especially with regards to prey availability and predator occurrence (Bailey and Houde, 1989). A genetic basis of metabolic rate in fishes has previously been suggested through variation in allozyme (Paynter et al., 1991) and enzyme activity (Patterson et al., 2004). Huuskonen et al. (2003) assessed the influence of parental background directly on metabolic rate of newly hatched Arctic charr (Salvelinus alpinus L.), but were unable to detect an effect due to a very large individual variation. The metabolic rate of a larva is highly susceptible to environmental influences and the embryonic period offers a tractable way of reducing environmental effects. Although indirect, the heritability of RNA : DNA and lapillar otolith area, their correlation with one another and their hypothesised connection with metabolic rate lends support to the notion that metabolic level is heritable in young fish larvae (Yamamoto and Reinhardt, 2003).

A. Bang et al. / Journal of Experimental Marine Biology and Ecology 334 (2006) 51–63

4.4. Implications for the early life history Evaluating early life history traits expressed at hatch as opposed to later in larval life reduces environmental influences which would otherwise impair understanding of the underlying maternal, genetic and environmental sources of variation. There has been a great deal of debate about how long maternal effects persist and when or if paternal effects come into play. Although not found in this study (probably due to a benign laboratory environment), undoubtedly the mother has a large influence on early survival until first-feeding and end of the yolk-sac stage through her variable allocation of protein, vitamins, minerals etc. to the yolk (Brooks et al., 1997; Nagler et al., 2000). Also, there is consensus regarding a maternal effect on initial size differences among offspring, which may translate into variation in offspring fitness (Einum and Fleming, 1999). However, often only a transient effect is observed and evidence is equivocal of the duration of this effect (Reznick, 1991; Bromage et al., 1992; Heath and Blouw, 1998). It is suggested that the durations of maternal effects through size differences are dependent on the environment and that they persist longer in competitive than in benign environments (Einum and Fleming, 1999). Regarding paternal effects (additive genetic components) it is important to differentiate between traits that are likely to be a consequence of egg size (e.g. dry weight and yolk-sac volume) and traits more directly influenced by the physiological properties of the larvae. In this regard it is especially interesting that we found some of the largest paternal effects on traits connected to metabolic rate (otolith size and RNA : DNA ratio) and, although highly influenced by the environment once hatched, the individual genotype will limit the degree to which environmental factors affect the metabolic capacity of individuals (Patterson et al., 2004). Together with temperature and feeding rate, metabolic rate determines the growth rate of a larva and our study is thus in line with Vøllestad and Lillehammer (2000) who found sire but no dam effects on growth rate and development time of larval brown trout. Additionally, growth rate is well established as a heritable trait in fish and is incorporated via selection and breeding into many aquaculture improvements programmes (Panagiotaki and Geffen, 1992). Sires have an influence on the metabolic level as early as hatching and this effect is likely to continue by affecting the future growth potential of their offspring. Higher metabolic capacities predispose feeding larvae to grow faster by potentially allowing for faster protein synthesis These differences in protein synthesis are

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likely to be less evident in the yolk-sac stage where the larvae do not yet grow at their full potential (Kamler, 1992). Here initial size differences due to maternal effects are more visible. Acknowledgements We thank Frank Midtøy and Julie Skadal for supplying brood fish and for technical assistance during rearing of herring eggs. We thank Helgi Mempel for technical assistance with the nucleic acid analyses. The project was supported by grants from the Oticon and Højgaard Schultz Foundation and by a PhD grant to A. Bang from the SLIP research school under the Danish Network for Fisheries and Aquaculture Research financed by the Danish Ministry for Food, Agriculture and Fisheries and the Danish Agricultural and Veterinary Research Council. [RH] References Bailey, K.M., Houde, E.D., 1989. Predation on eggs and larvae of marine fishes and the recruitment problem. Adv. Mar. Biol. 25, 1–83. Bang, A., Grønkjær, P., 2005. Otolith size-at-hatch reveals embryonic oxygen consumption in the zebrafish, Danio rerio. Mar. Biol. 147, 1419–1423. Bang, A., Grønkjær, P., Malte, H., 2004. Individual variation in the rate of oxygen consumption by zebrafish embryos. J. Fish Biol. 64, 1285–1296. Bekkevold, D., Hansen, M.M., Loeschcke, V., 2002. Male reproductive competition in spawning aggregations of cod (Gadus morhua L.). Mol. Ecol. 11, 91–102. Belchier, M., Clemmesen, C., Cortes, L., Doan, T., Folkvord, A., Garcia, A., Geffen, A., Høie, H., Johannessen, A., Moksness, E., de Pontual, H., Ramirez, T., Schnack, D., Sveinsbo, B., 2004. Recruitment Studies: Manual on Precision and Accuracy of Tools. ICES Techniques in Marine Environmental Sciences, vol. 33. 35 pp. Bergeron, J.P., 1997. Nucleic acids in ichthyoplankton ecology: a review, with emphasis on recent advances for new perspectives. J. Fish Biol. 51, 284–302. Blanckenhorn, W.U., 2000. The evolution of body size: what keeps organisms small? Q. Rev. Biol. 75, 385–407. Blaxter, J.H.S., Hempel, G., 1963. The influence of egg size on herring larvae (Clupea harengus L.). J. Cons. - Cons. Perm. Int. Explor. Mer 28, 211–240. Bochdansky, A.B., Grønkjær, P., Herra, T.P., Leggett, W.C., 2005. Experimental evidence for selection against larvae with high metabolic rates in a food limiting environment. Mar. Biol. 147, 1413–1417. Bromage, N., Jones, J., Randall, C., Thrush, M., Davies, B., Springate, J., Duston, J., Barker, G., 1992. Broodstock management, fecundity, egg quality and the timing of egg production in the rainbow trout (Oncorhynchus mykiss). Aquaculture 100, 141–166. Brooks, S., Tyler, C.R., Sumpter, J.P., 1997. Quality in fish: what makes a good egg? Rev. Fish Biol. Fish. 7, 387–416.

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