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The origin and development of individual size variation in early pelagic stages of fish. Magnus Huss Æ Lennart Persson Æ Pär Byström. Received: 22 August ...
Oecologia (2007) 153:57–67 DOI 10.1007/s00442-007-0719-x

POPULATION ECOLOGY

The origin and development of individual size variation in early pelagic stages of fish Magnus Huss Æ Lennart Persson Æ Pa¨r Bystro¨m

Received: 22 August 2006 / Accepted: 6 March 2007 / Published online: 6 April 2007  Springer-Verlag 2007

Abstract Size variation among individuals born at the same time in a common environment (within cohorts) is a common phenomenon in natural populations. Still, the mechanisms behind the development of such variation and its consequences for population processes are far from clear. We experimentally investigated the development of early within-cohort size variation in larval perch (Perca fluviatilis). Specifically we tested the influence of initial variation, resulting from variation in egg strand size, and intraspecific density for the development of size variation. Variation in egg strand size translated into variation in initial larval size and time of hatching, which, in turn, had effects on growth and development. Perch from the smallest egg strands performed on average equally well independent of density, whereas larvae originating from larger egg strands performed less well under high densities. We related this difference in density dependence to size asymmetries in competitive abilities leading to higher growth rates of groups consisting of initially small individuals under high resource limitation. In contrast, within a single group of larvae, smaller individuals grew substantially slower under high densities whereas large individuals performed equally well independent of density. As a result, size variation among individuals within groups (i.e. originating from the same clutch) increased under high densities. This result may be explained by social interactions or differential timing of diet shifts and a depressed resource base for the initially smaller individuals. It is concluded

Communicated by Anssi Laurila. M. Huss (&)  L. Persson  P. Bystro¨m Department of Ecology and Environmental Science, Umea˚ University, 901 87 Umea˚, Sweden e-mail: [email protected]

that to fully appreciate the effects of density-dependent processes on individual size variation and size-dependent growth, consumer feedbacks on resources need to be considered.

Keywords Perca fluviatilis  Larval fish  Within-cohort size variation  Cohort competition  Growth

Introduction Most organisms undergo substantial growth and development during their life cycle (Sebens 1987; Werner 1988). Furthermore, individual growth and development is generally strongly dependent on resource availability and the following plasticity in growth may result in a weak relationship between age and size (Pfister and Stevens 2002; De Roos et al. 2003). Size variation between individuals is therefore a common phenomenon both between individuals of different ages as well as among even-aged individuals as a result of differences in their present and historical environment (Huston and DeAngelis 1987; Sebens 1987; Ebenman 1988; DeRoos and Persson 2001; Pfister and Stevens 2002). Differences in size among evenaged individuals within populations have been reported in a number of empirical studies (Van Densen et al. 1996; Fraser et al. 2001; Pfister and Stevens 2002; Vadas et al. 2002). Such within-cohort size variation has been related to mechanisms that produce size- and time-dependent growth rates (DeAngelis and Huston 1987; Huston and DeAngelis 1987; DeAngelis et al. 1993a; Pfister and Stevens 2002, 2003). These mechanisms include both inherent factors, such as genetic differences and maternal effects, and extrinsic factors related to the interaction

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between individual life histories and the environments, such as unequally distributed resources and environmental heterogeneity. In combination with initial variation and size-dependent mortality, above-mentioned factors may influence the degree of size variation observed within cohorts (Huston and DeAngelis 1987; Pfister and Stevens 2002; Pfister and Peacor 2003). Such variation among individuals has been suggested to have major consequences not only for individual performance but also for population stability and persistence (DeAngelis et al. 1993b; Kendall and Fox 2002). The importance of initial size variability for the development of size variation within cohorts was recognized early on (Uchmanski 1985; DeAngelis and Huston 1987; Latto 1992). One factor, which potentially could affect initial variability, is maternal effect (Roff 1992; Bernardo 1996; Johnston and Legget 2002). An example is initial offspring size, which often is positively related to female age and size in fish and hence varies within and between spawning populations (Johnston 1997). For many species egg size has been shown to have a substantial influence on early development. For example, a positive relationship between egg mass and larval mass and length has been observed, which, in turn, may translate into differences in developmental rates and survival (Collazo 1996; Johnston 1997; Einum and Fleming 1999; Heyer et al. 2001; Einum 2003). Besides egg size, fecundity may also influence the degree of size variation within cohorts as a result of density-mediated effects. Variation in traits related to individual growth rates may be expressed differently depending on cohort density. Increased variation and skewed size distributions have been suggested to correlate with increasing density (Uchmanski 1985; Ziemba and Collins 1999; Pfister and Stevens 2002; Pfister 2003; Peacor and Pfister 2006) which, in turn, has been suggested to be related to intense competition (Rubenstein 1981; Weiner 1985; Schmitt et al. 1986; Huston and DeAngelis 1987; Lekve et al. 2002). However, it has also been suggested that increased density may result in decreased size variation because small individuals catch up in size with initially larger individuals as a result of their lower critical resource demands (Latto 1992; Persson et al. 1998; Pfister and Peacor 2003). Fish have been extensively studied regarding the effects of density on size development and recruitment variation, and have also been the subject of modelling studies concerning size variation within cohorts (Miller et al. 1988; DeAngelis et al. 1993a, b). Individual young-of-the-year (YOY) fish can differ in a number of important characteristics, such as hatching date and encounter rates with prey and predators, which, in turn, may lead to differential growth and hence changes in size distribution and size variation over time (Miller et al. 1988; Post et al. 1998). To

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increase our understanding of the development of withincohort size variation in early stages of size-structured populations we investigated potential mechanisms behind size variation from egg through early ontogeny of the teleost perch (Perca fluviatilis). Specifically we first investigated initial offspring size variation in relation to egg strand size, which can be used as a proxy for female size. Secondly, we experimentally studied size development of initially differently sized cohorts (i.e. individuals originating from differently sized egg strands) as well as development of individual size variation (i.e. variation among individuals from the same egg strand). The development of size variation was studied in large-scale mesocosms at two different densities of larval perch to enable an examination of the combined effects of density and maternal effects/initial size variation on early size development.

Materials and methods Study species Eurasian perch is often a numerically dominant species and is found over most of Eurasia (Johansson and Persson 1986). Perch spawn in spring in nearshore areas in the vegetation or on fallen branches. Egg strands differ substantially in size and their width is proportional to the size of the reproducing female (Gillet et al. 1995; Dubois et al. 1996). The larvae hatch in the littoral zone but soon after hatching they move out to the pelagic zone. After initially feeding on rotifers and copepod nauplii, perch larvae start to feed on larger zooplankton, such as copepods and cladocerans. After a gradual development into juveniles, they shift habitat to the littoral area (at a size of 15–25 mm) where they continue to feed on zooplankton, but at a size of 30–80 mm they also start to feed on benthic macroinvertebrates. Finally, at a large enough size (commonly at a size over 130 mm), perch become piscivores (Persson 1988; Treasurer 1988; Wang and Eckmann 1994; Bystro¨m et al. 1998, 2003). Experiment The experiment was carried out in a small lake of low productivity (Lake Abborrtja¨rn 3) in central Sweden (64˚29¢N. 19˚26¢E) in early summer 2005. Detailed information on the lake is given in Persson et al. (1996). We used 32 enclosures made out of transparent plastic (polyethylene) bags with a diameter of 1.6 m, a depth of 9 m and a total volume of 18 m3. Each bag was attached to an iron ring with a diameter of 1.6 m, which, in turn, was attached to a wooden frame with polystyrene floating

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devices. Each bag was anchored to the bottom of the lake with a weight. The enclosures were placed in the lake and filled with unfiltered lake water during 16–20 May. The enclosures were placed in rows of four, and the distance between rows was approximately 3 m. To ensure that a natural zooplankton community developed before the start of the experiment, each enclosure was inoculated with a filtered lake sample of zooplankton on 27 May corresponding to a volume of 1,000 l of lake water. Estimates of the numbers and sizes of egg strands in Lake Abborrtja¨rn 3 were conducted by snorkelling along the shore line on 23–24 May. The width of all visible egg strands were measured to the nearest 0.5 cm. Sixteen egg strands, with widths of either 3.5, 6, 8.5 or 11 cm (four of each size) were subsequently taken out from the lake on 31 May and were transferred to 20-l indoor aquaria (one egg strand per aquaria). Immediately after collecting the egg strands, a subsample from each egg strand was preserved in Gilsons’s fluid for later egg size measurements (Bagenal and Braum 1978). The bottom and walls of the aquaria were covered with black plastic and the temperature was held between 16 and 18C. The perch larvae hatched in the aquaria on 1–5 June. On the first day of hatching, a subsample of larvae was sampled and conserved in Lugol’s solution. Remaining larvae were held in the aquaria for 3 days. Prior to introduction to the enclosures the larvae in each aquaria were fed with a natural zooplankton mixture taken from the lake, sampled from approximately 1,000 l of lake water. Three days after hatching (4–8 June), the larvae were transferred and stocked in the enclosures, thus mimicking the natural hatching pattern in the lake (Bystro¨m et al. 1998). On the day of stocking, a subsample of larvae was again preserved in Lugol’s solution. The enclosures were stocked with larvae from one individual egg strand each, with the densities of either 20 or 60 larvae per enclosure corresponding to a density of 10 or 30 individuals/m2. Each treatment was replicated 4 times and randomly assigned to enclosures. The experiment was terminated on 30 June– 2 July when the enclosures were sampled for fish in random order with a large dipnet. The hauling of each enclosure was stopped when two subsequent hauls had resulted in no captures. Sampled fish were preserved in Lugol’s solution. In the laboratory, the egg diameter of 30 eggs from each egg strand was measured to the nearest 0.1 mm under a stereomicroscope. Thirty larvae from each of the sampling periods (day of hatching, start and end of the experiment) were measured to the nearest 0.1 mm (total length) under a stereomicroscope and were thereafter blotted dry and weighted to the nearest 0.01 mg (wet weight). Growth rates of the larvae were expressed as specific growth rate:

59

G ¼ 100 

ln w2  ln w1 t2  t1

where G is the specific growth rate and w1 and w2 are weights at the start (t1) and end (t2) of the experiment. To study how size distributions of perch changed over time, the coefficient of variation (CV) and skewness were calculated to obtain measures of the size distributions. To further investigate which size class of individuals potentially had the largest impact on shifts in size distributions, we compared the observed and predicted maximum final weights of the smallest and largest individual, respectively, at the start and end of the experiment in each replicate. The predicted maximum final weight was calculated starting with the initially smallest and largest individual in each enclosure. Data for maximum specific growth rate (Gmax) was derived from Wang and Eckman (1994) and Bystro¨m and Garcı´aBertho´u (1999) including both size and temperature dependence (see Persson et al. 2000). As temperature was only measured on three occasions during the experiment, daily temperatures were estimated from interpolations assuming a linear relationship in temperature between dates. The water temperature in the enclosures varied between 12 and 18C during the experimental period. From each enclosure, the five smallest, the five mean sized and the five largest individuals (all, if fewer than 15 individuals, were present) were analysed for diets. Stomach contents were identified to species or taxa and ten (all, if fewer than ten) of each prey item were length measured Lengths were transformed to biomass using length–weight regressions (Bottrell et al. 1976). Zooplankton were sampled on 3, 18 and 30 June with a 100-lm-mesh net with a diameter of 25 cm, drawn vertically from the thermocline to the surface with an approximate speed of 0.5 m/s. Zooplankton were sampled from the epilimnion to the surface as perch larvae are rarely caught below the thermocline (Post and McQueen 1988; Wang and Eckman 1994). To test that the zooplankton community in the enclosures developed similarly to the natural community in the lake, two zooplankton samples were also taken from the pelagic area in the lake on each sampling occasion. Zooplankton samples were preserved in Lugol’s solution. Zooplankton were classified by species or taxa and counted and the lengths of 15 individuals (all, if fewer than 15) of each sample were measured under an inverted microscope. Lengths were transformed to biomass using length–weight regressions (Bottrell et al. 1976). To investigate the potential effects of gape-limitation on prey availability, the fraction of Holopedium (which was the only zooplankton species large enough to induce gape-limitation in perch) available for the smallest and largest perch larvae, respectively, at the middle and end of the experiment was estimated using a function describing the maximum

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Holopedium size available, with respect to gape size, for differently sized perch larvae (Bystro¨m et al. 2003). Perch lengths at the middle of the experimental period for each replicate were calculated from initial and final sizes by assuming exponential growth over the experimental period.

originating from small egg strands hatched later compared to larvae from larger egg strands. Egg diameter increased asymptotically with egg strand width (r2 = 0.64, P = 0.0002, Fig. 1b) as did larval weight at hatching (r2 = 0.76, P < 0.0001, Fig. 1c).

Statistical analyses

Survival, growth and final larval weight

The relationships between egg strand size and egg diameter, initial larval weight and hatching date were estimated using nonlinear regression analyses with asymptotic functions of the form y = a(1 – exp–bx) if increasing and by y = a(exp–bx) if decreasing. These regressions were based on individual replicates (egg strands), i.e. the means of each clutch. All other analyses were performed on enclosure means. Effects of egg strand width and density on final weight, total biomass and growth were analysed using univariate analysis of covariance (ANCOVA). Density was considered as a categorical variable (fixed factor) whereas egg strand width was considered as a continuous variable (covariate). Also the combined effects of density and initial larval size were analysed by ANCOVA with density as fixed factor and initial size as covariate. The interaction term was used to test whether the slope of the relationships between egg strand width or initial size and the dependent variables differed between density treatments. If the interaction term was not significant it was dropped from the model and we then tested for an effect of density or egg strand width on the dependent variables. Effects of egg strand width and density on survival were analysed using a generalized linear model with binomial error structure. The effects of egg strand size and density on diet was determined using multivariate analysis of covariance (MANCOVA). To evaluate whether certain prey were selected for we used Jacobs’ selectivity index (D) (Jacobs 1974). The index ranges from –1 (negative selection) to +1 (positive selection). When analysing data using ANCOVA and MANCOVA, egg strand size was log-transformed and proportions were arcsine square root transformed. The effects of egg strand size and density on CV, skewness and zooplankton biomass were investigated using repeatedmeasures ANOVA. In one of the low-density replicates (with larvae originating from an egg strand of the width 8.5 cm) a hole was present in the enclosure. Hence, this replicate was removed from further analyses.

YOY perch had a lower survival at high density (GLM, Z28 = 2.32, P = 0.020). There was also a negative relationship between egg strand width and survival (GLM, Z28 = –2.70, P = 0.007) (Fig. 2a). The relationship between egg strand width and specific growth rate differed between densities, being negative at high densities (r2 = 0.53, P = 0.0013) but not at low densities (r2 = 0.047, P = 0.44) (interaction term, ANCOVA, F1,28 = 4.84, P = 0.036) (Fig. 2b). There was also a difference in the relationship between final weight and egg strand width between high and low densities (interaction term, ANCOVA, F1,28 = 4.70, P = 0.039) (Fig. 3a). Final weight increased with egg strand width at low density (r2 = 0.47, P = 0.0047) but not at high density (r2 = 0.073, P = 0.31). A similar pattern was found for initial larval weight versus final weight (interaction term, ANCOVA, F1,28 = 4.99, P = 0.034). Initial and final weight were strongly correlated at low density (r2 = 0.56, P = 0.0014) but not at high density (r2 = 0.074, P = 0.31) (Fig. 3b). Zooplankton resources Initially copepods dominated the zooplankton resource but their importance decreased as their levels fell over time in all treatments, and more so at high than at low YOY perch density (Table 1). Furthermore, copepod biomass and the relationship between copepod biomass and time differed depending on egg strand width, but these differences were very small in terms of actual biomass. No zooplankton category apart from copepods showed any significant changes over time. Neither was there any difference in total zooplankton biomass as a function of density, egg strand width or time (Table 1). The mean zooplankton biomass during the experimental period in the enclosures, 27.3 ± 5.83 lg/l (mean ± 1SE), did resemble that in the lake, 18.8 ± 13.2 lg/l (mean ± 1SE) and all zooplankton taxa found in the enclosures were also found in the lake. Diets

Results Hatching date, egg diameter and initial larval weight Hatching date decreased exponentially with increasing egg strand width (r2 = 0.75, P < 0.0001, Fig. 1a), i.e. larvae

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Diets of perch differed between density treatments (Table 2). More copepods were found in the diets of perch from the low-density treatments whereas small cladocerans and Holopedium were more common in the diets of perch from the high-density treatments. Egg strand width had no

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5

1.0

a) Proportion survival

a)

Hatching date

4

3

2

1

0.9

0.8

0.7

0.6

0.5 2

4

6

8

10

12

2

4

Egg strand width (cm)

10

12

10

12

14

b)

b)

2.5

2.0

1.5

13

12

11

10

9 2

4

6

8

10

12

2

Egg strand width (cm)

4

6

8

Egg strand width (cm)

1.0

Fig. 2 The relationships between egg strand width and a survival and b specific growth rate at low (open circle) and high (filled circle) densities. Regression lines (if significant) and means (±1 SE) are shown. Sample size: n = 15 for the low-density treatments, n = 16 for the high-density treatments

c) Weight at hatching (mg)

8

Egg strand width (cm)

Specific gr owth rate (%)

Egg diameter (mm)

3.0

6

0.9

0.8

0.7

0.6

0.5 2

4

6

8

10

12

Egg strand width (cm) Fig. 1 The relationships between egg strand width and a hatching date, b egg diameter and c weight at hatching. Regression lines (if significant) and means (±1 SE) are shown. Sample size: n = 16 for all regressions

items in the diets. There was a positive prey selection (D > 0) for copepods and small cladocerans in all treatments and a negative prey selection for Holopedium (D < 0) (Table 3). The fraction of Holopedium available for YOY perch was close to zero in all treatments on 18 June even though a small fraction of Holopedium had become available for the largest individuals in most treatments at this time. At the end of the experiment, on 30 June, up to 44% of Holopedium was available for the largest individuals compared to a maximum of 11% for the smallest individuals, causing a large difference in prey biomass available to the largest and the smallest individuals during the second half of the experiment (Table 4). Size distributions

effect on the proportion of different prey items in the diet, neither was there any interaction effect between density and egg strand width on the proportion of different food

The CV of final perch weights increased relative to initial values at both low and high density, but more so at high

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Oecologia (2007) 153:57–67 50

a) Final weight (mg)

40

30

20

10

0 2

4

6

8

10

12

Egg strand width (cm) 50

b) Final weight (mg)

40

30

20

(Table 5; Fig. 4b). At low density there was instead a tendency for final perch weights to be more negatively skewed compared to initial skewness. Overall, the changes in CV and skewness resulted from low growth of some individuals, whereas other individuals had substantial growth, resulting in an increased size variation over time (Fig. 5). We could not follow the growth trajectories of individual fish. However, by using the smallest and largest individuals at the start of the experiment, we estimated the final sizes of those individuals when growing at maximum rates. The final size of the initially smallest individuals within replicates was 37–64% of what was expected from the predicted maximum growth rate, whereas that of the largest individual was almost 100%. Furthermore, whereas the growth rate, and hence the final size, of the smallest individuals decreased with density (ANOVA, F1,28 = 10.62, P = 0.003) this was not the case for the largest individuals (ANOVA, F1,28 = 0.62, P = 0.44) (Fig. 6). As a result, size variation among individuals increased at high density.

Discussion

10

Initial offspring variation

0 0.4

0.6

0.8

1.0

1.2

Initial weight (mg) Fig. 3 The relationship between a egg strand width and final weight and b initial weight and final weight at low (open circle) and high (filled circle) densities. Regression lines (if significant) and means (±1 SE) are shown. Sample size: n = 15 for the low-density treatments, n = 16 for the high-density treatments

density, irrespective of egg strand width (Table 5; Fig. 4a). Changes in skewness in response to density and egg strand width showed a similar pattern, that is, final perch weights were more positively skewed at high density compared to at low density. Furthermore, final weights were more positively skewed than initial weights at high density

First of all our study demonstrated an initial size variation in perch eggs that was related to variation in egg strand size and hence to female size. Second, this variation in egg size translated into variation in larval size, which in turn, affected both developmental rates and individual survival. Similar to what has been found for many other fish species, we found that the size of perch eggs was positively related to egg strand width (i.e. female size) and that large eggs gave rise to larger offspring (Roff 1992; Gillet et al. 1995; Bernardo 1996; Johnston 1997; Einum sand Fleming 2000). In addition to differences in egg and offspring size, we also found that egg strand size influenced hatching time. Delayed hatching was observed for offspring originating from small egg strands relative to large egg strands. One

Table 1 Repeated-measures ANOVAs (F-values given) of the effects of density, egg strand width and time on the zooplankton communitya Source of variation

df

Total biomass

Holopedium

Other cladocerans

Copepods

Time

2,56

0.69

0.89

0.10

1.49

Density

1,28

0.38

0.07

0.25

25.79**

Width of egg strand

1,28

0.30

0.46

0.00

8.50**

Time · Density Time · Width of egg strand

2,56 2,56

0.29 0.37

0.02 0.09

2.52 1.06

5.43** 3.15*

* P £ 0.05, ** P £ 0.01 a

Biomasses were log transformed prior to analysis

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Table 2 Multivariate (Wilks’ k) tests of the effect of density (factor) and egg strand width (covariate) on the diet of larval perch and the following univariate tests by group (F-values)a Wilks’ k

Source of variation

df

F

Density

3,28

4.85**

Width of egg strand

3,28

0.74

Density · Width of egg strand

3,28

1.08

Univariate df

Holopedium

Other cladocerans

Copepods

1

6.14*

5.84*

13.29**

* P £ 0.05, ** P £ 0.01 a

Data were arcsine square root transformed prior to analysis

Table 3 Jacobs’ (1974) selectivity index (D) for different zooplankton taxa. Means (±1 SE) are shown

Density Low

High

Egg strand (cm)

Holopedium

Other cladocerans

Copepods

3.5

–0.94 ± 0.032

0.11 ± 0.24

0.66 ± 0.096

6

–0.99 ± 0.090

0.48 ± 0.36

0.68 ± 0.22

8.5

–0.88 ± 0.071

0.79 ± 0.092

0.52 ± 0.026

11

–0.95 ± 0.048

–0.067 ± 0.42

0.62 ± 0.27

3.5

–0.73 ± 0.23

0.74 ± 0.098

0.33 ± 0.34

6

–0.98 ± 0.0078

0.85 ± 0.087

0.45 ± 0.15

8.5

–0.80 ± 0.088

0.52 ± 0.24

0.59 ± 0.15

11

–0.63 ± 0.17

0.26 ± 0.26

0.79 ± 0.084

Table 4 The proportion of total Holopedium biomassa available for the smallest and largest perch larvae, respectively, on 18 and 30 June Egg strand (cm) Date 18 June 30 June a

3.5

3.5

6

6

8.5

8.5

11

11

Density

Low

High

Low

High

Low

High

Low

High

Smallest

0.00

0.00

0.00

0.00

0.02

0.00

0.00

0.00

Largest

0.02

0.00

0.07

0.02

0.08

0.05

0.00

0.00

Smallest

0.02

0.00

0.08

0.04

0.11

0.00

0.02

0.00

Largest

0.28

0.18

0.15

0.24

0.44

0.33

0.34

0.27

Values are based on pooled data within treatments

Table 5 Repeated-measures ANOVAs (F-values given) of the effects of density, egg strand width and time on the coefficient of variation (CV) and skewness Source of variation

df

CV

Skewness

Time

1,28

7.32*

2.62

Density

1,28

19.14**

8.12**

Width of egg strand

1,28

3.21

2.32

Time · Density

1,28

17.50**

12.83**

Time · Width of egg strand

1,28

0.014

2.29

* P £ 0.05, ** P £ 0.01

consequence of this was a reinforcement of size differences, that is, offspring from large females both hatched earlier and were born larger. One mechanism behind such a pattern could be size-related differences in

spawning time. An extended hatching period is a common feature for many fish species, and often much more so than what we observed for perch in our study (Johnson and Post 1996; Ludsin and DeVries 1997; Post 2003; Ozen and Noble 2005). In contrast to our results, many other studies show no difference in time of hatching between large and small eggs or that small eggs hatch earlier than larger eggs (Ludsin and DeVries 1997; Einum and Fleming 1999; Nathanailides et al. 2002). Unfortunately we have no information on egg laying dates. However, Gillet et al. (1995) observed that large female perch spawn later compared to smaller ones. Consequently, the observed pattern in our study is probably not a consequence of larger eggs being laid earlier. Instead it can be hypothesized that the observed pattern is related to size-dependent differences in maternal investment in eggs generating differences in developmental time.

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1

a) Proportion of max

Coefficient of variation (CV)

60

40

0.5

a

20

0

smallest

0

3.5

6

8.5

largest

Fig. 6 Proportions of observed final weights relative to estimated maximum weights for the smallest and largest individual within each replicate. White bars Proportion of the estimated final weight under low density, black bars proportion of the estimated final weight under high density. All high- and low-density replicates, respectively, have been collapsed into one histobar. Means (+1 SE) are shown. Sample size: n = 15 for the low-density treatments, n = 16 for the highdensity treatments

11

Egg strand width (cm) 1.5

b)

Skewness

1

Size development, individual variation and environmental condition

0.5

To fully evaluate the importance of initial size variation on growth and development, the combined effects of time and environmental condition need to be considered (e.g. Einum and Fleming 1999). However, most studies on the influence of maternal phenotype and initial size differences have been performed in artificial small-scale experiments under near optimal conditions (e.g. Reznick 1991). In contrast, our study was performed at a more realistic scale under seminatural conditions, including resource dynamics. Furthermore, our results first of all suggest that whether initial size differences between cohorts, related to maternal effects, are sustained over early development or not depends on the

0

-0.5

-1

3.5

8.5

6

11

Egg strand width (cm) Fig. 4 The effects of egg strand width and density on a the coefficient of variation (CV) and b skewness. Grey bars Initial values, white bars final values under low density, black bars final values under high density. Means (±1 SE) are shown. Sample size: n = 4 for all treatments except low density/8.5 cm egg strand (n = 3)

0.3

0.3

P r o p o r t io n

Fig. 5 The weight frequency distributions of larval perch originating from differently sized egg strands. White bars Final weights under low density, black bars final weights under high density. All replicates within treatments have been collapsed into the same weight distributions

3.5 cm egg strand

6 cm egg strand

0.2

0.2

0.1

0.1 0

0 0

8

16

24

32

40

48

56

P r o p o rt i o n

0.3

8

16

24

32

40

48

56

64

0.3

8.5 cm egg strand

11 cm egg strand

0.2

0.2

0.1

0.1

0

0

0

8

16

24

32

40

Weight (mg)

123

0

64

48

56

64

0

8

16

24

32

40

Weight (mg)

48

56

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intensity of within-cohort competition. Differences in average size between groups of larvae (originating from differently sized egg strands) at the end of the experiment was positively related to initial size differences, but only under low densities. Secondly, whereas we found that the differences in average size between larvae originating from differently sized egg strands decreased under high densities, the opposite was the case for size variation among individuals within replicates. Consequently, intense competition can magnify initial size variation within a cohort and thus lead to growth depensation. Our results concerning whether initial size differences between different cohorts are sustained over early development or not contrast with several other studies in that offspring from smaller eggs on average were favoured relative to offspring from larger eggs under harsh conditions (Reznick 1991; Einum and Fleming 1999; Heath et al. 1999). The higher growth rates of smaller-sized groups of perch under resource limitation can be explained by taking size-related competitive abilities into account. The density of the preferred food items, copepods, was very low under high densities which, in turn, suggests that resources were limited. Given the size-scaling relationships for foraging capacity and metabolic demands experimentally found for fish in general, and perch specifically, smaller individuals are competitively superior in exploitative competition in that they can tolerate lower resource levels for maintenance and uphold positive growth rates where larger individuals have negative growth rates. Smaller individuals may therefore compensate for their small size by higher growth rates relative to initially larger individuals (Persson et al. 1998; Bystro¨m and Garcı´a-Berthou 1999). Correspondingly, that the difference in size at the end of the experiment was positively related to initial size differences under low densities can be explained by near maximum growth rates and, therefore, a low degree of asymmetric competition between differently sized individuals (Persson et al. 2000). On the other hand, the observed growth depensation within groups of perch contrasts with the expected superiority of small individuals regarding exploitative competition. Consequently, mechanisms other than exploitative competition for a shared resource need to be taken into account. Clearly some individuals grew much more slowly than the expected maximum growth rates. In the highdensity treatments, the observed growth rates of the smaller individuals were less than half of the estimated maximum growth. As the growth rates of the largest individuals decreased to a smaller extent, the larger size variation under high densities thus was due to the fact that larger individuals performed equally well independent of density, whereas smaller individuals grew substantially less at high densities. These results are in agreement with previous

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studies that have shown that competition magnifies initial size variability (Rubenstein 1981; Uchmanski 1985; Ziemba and Collins 1999; Peacor and Pfister 2006). A number of mechanisms that produce size- and time-dependent growth rates have been put forward to explain growth depensation. Positive size-dependent growth may explain development of size variation. This is particularly likely for light competition among plants, but has also been evoked as a potential mechanism behind growth depensation in animal populations. Still, in the latter case, the argument has been based on specific assumptions about ontogenetic niche shifts or has not taken population feedbacks via resources into account (Harper 1977; DeAngelis et al. 1993b; Persson and Bro¨nmark 2002). Individual variation in growth may also result from positive correlations in growth independent of size, i.e. autocorrelation in growth, related to, for example, genetic or maternal effects (Pfister and Stevens 2002; Pfister and Peacor 2003, Fujiwara et al. 2004). In our study genetic differences and maternal effects are less likely explanations as all individuals within groups (replicates) had the same maternal origin. Instead, positive size-dependent growth can be advanced to explain the observed pattern. Positive size-dependent growth within groups (replicates) of perch could be related to unequal prey availability between individuals. Especially the largest prey species, Holopedium, was only accessible for the largest perch larvae as a result of gape-limitation causing a substantial time lag between when the first individuals could start to feed on Holopedium to when the slowest growing individuals could do so. The larger size variation observed within replicates at high densities may hence be explained by an early diet shift by the initially largest individuals which depressed the future resource base for the initially smaller individuals. Small differences in growth rates during one stage may thereby develop into large differences in growth and development if some individuals make a shift to another exclusive prey type potentially leading to increased size variability (Werner and Gilliam 1984; Huston and DeAngelis 1987; Post 2003). Hence, feedbacks on the consumer cohort via resources are crucial to better understand the mechanisms behind growth depensation in natural environments, especially when considering a heterogeneous resource base. A similar outcome as for differential timing of ontogenetic niche shifts, i.e. positive size-dependent growth, may emerge as a result of social interactions, also in the absence of effects of exploitative competition. Effects of social interactions are obviously expected to express themselves only within replicate comparisons. It has, for example, been shown that suppression of small individuals within groups of animals due to size-specific interference can lead to increased size variation over time. However, it is unclear whether

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non-exploitative interactions are expressed differently depending on cohort density (Ziemba and Collins 1999; Ziemba et al. 2000). Development of size variation among individuals, as observed in our experiment, can have important implications for individual fitness as well as population level processes. Recruitment success, population stability and population persistence can all potentially be affected by individual variability (DeAngelis et al. 1993b; Ludsin and DeVries 1997; Kendall and Fox 2002; van De Wolfshaar 2006). Several studies point to the importance for YOY individuals to reach a large enough size at the end of the first growing season to survive winter because of a sizedependent capacity to withstand starvation (cf. Post and Evans 1989). Hence, variability in life history among individuals can be crucial in terms of whether a total recruitment failure will take place or whether some larger individuals of a YOY cohort can survive (DeAngelis et al. 1993b; van de Wolfshaar 2006). Variability among individuals may also influence recruitment variation via its effects on intra- and interspecific interactions. It has, for example, been shown that intra-cohort cannibalism can develop in YOY perch if a broad enough size distribution develops early in the season (Brabrand 1995). Cannibalism may, in turn, affect growth and size distributions because of accelerated growth of cannibals (Post 2003) and relaxed competition (Persson et al. 2000) leading to increased growth rates and survival of the remaining cohort. Hence, a better understanding of mechanisms behind development of size variation within cohorts, such as the positive correlation between individual variability and competitive intensity as demonstrated in our study, is important for our ability to predict and understand recruitment variation in size-structured populations such as fish. Acknowledgements We thank Ma˚rten So¨derquist and Christian Tideman for field and laboratory assistance. This study was supported by grants from the Swedish Council for Forestry and Agricultural Sciences to L. Persson. The experiment in this study complies with current laws of Sweden and was approved by the Ethnical Committee at Umea˚ University.

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