Interrelationships Between Prey Body Size and ...

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Interrelationships Between Prey Body Size and Growth of Age-0 Yellow Perch a

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Edward L. Mills , Michael V. Pol , Ruth E. Sherman & Teresa B. Culver

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Department of Natural Resources, Cornell University, Ithaca, New York, 14853, USA Version of record first published: 09 Jan 2011.

To cite this article: Edward L. Mills, Michael V. Pol, Ruth E. Sherman & Teresa B. Culver (1989): Interrelationships Between Prey Body Size and Growth of Age-0 Yellow Perch, Transactions of the American Fisheries Society, 118:1, 1-10 To link to this article: http:// dx.doi.org/10.1577/1548-8659(1989)1182.3.CO;2

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TRANSACTIONS of the AMERICAN FISHERIES SOCIETY Volume 118

January 1989

Number 1

Downloaded by [MBLWHOI Library] at 10:06 15 October 2012

Transactions of the American Fisheries Society 118:1-10, 1989 © Copyright by the American Fisheries Society 1989

Interrelationships Between Prey Body Size and Growth of Age-0 Yellow Perch EDWARD L. MILLS, MICHAEL V. POL, RUTH E. SHERMAN, AND TERESA B. CULVER l Department of Natural Resources, Cornell University Ithaca, New York 14853, USA Abstract. — We conducted laboratory experiments in the summers of 1986 and 1987 to examine the effects of Daphnia pulex body size and ration level on growth of age-0 yellow perch Perca flavescens. Daphnia pulex rations were set at 25 and 40% of yellow perch dry weight. Specific growth rate tended to be higher for smaller fish and decreased with fish size at both ration levels. For the 25% ration, the highest growth rates, 0.023 to 0.024 g/d, were observed when yellow perch were fed meals of D. pulex between 1.4 and 1.8 mm long; growth declined for prey sizes outside this size range. For the 40% ration, no relationship was found between body length of D. pulex and specific growth rate; the mean specific growth rate for the 40% ration was the same as the peak rate for the 25% ration. Multiple-regression analysis was used to examine the dependence of specific growth rate of yellow perch on initial fish length, prey size, and temperature. For the 25% ration, prey size and the square of prey size were the only variables that contributed significantly (P < 0.05) to the prediction of specific growth rate. For the 40% ration, initial fish length was the only significant predictor (P < 0.05) of specific growth rate. Our results clearly indicate linkages between prey selection and growth and demonstrate the importance of prey size to growth of age-0 fish. Fish ecologists often seek to define conditions that are optimal for growth and reproduction of fish populations. For age-0 fish, rapid growth is critical for survival (Milinski 1986) and is dependent on many factors including food supply and availability. Adequate densities of suitable prey, for example, have been shown to be crucial to the growth and survival of larval Atlantic herring Clupea harengus harengus (Werner and Blaxter 1980) and age-0 yellow perch Perca flavescens (Noble 1975; Mills and Forney 1981). However, the

availability of prey to age-0 fish is moderated by a variety of factors including prey size (Wong and Ward 1972; Furnass 1979; Hansen and Wahl 1981), prey vulnerability (Vinyard 1980), prey visibility (Zaret and Kerfoot 1975; Hairston et al. 1982; Breck and Gitter 1983), and prey motion (Zaret 1980). These factors influence the energy costs associated with capture and have an indirect effect on fish growth. An interrelationship among prey body size, predator body size, and growth efficiency has been demonstrated for adult planklivorous fish (Palo———— heimo and Dickie 1965, 1966a, 1966b; Kerr 1 Present address: Department of Civil Engineering, 1971 a, 1971 b). In these studies, the energy gained Cornell University, Ithaca, New York 14853, USA. by large fish eating large prey outweighed the costs


MILLS ET AL.

associated with the capture and ingestion of smaller prey. Age-0 fish show a high degree of prey selectivity based on prey body size (Feller and Kaczynski 1975; Furnass 1979; Mathias and Li 1982) and select small- to intermediate-sized (0.81.4 mm) zooplankton (Hansen and Wahl 1981). Preference for small- to intermediate-sized prey occurs even though data on capture success, handling time, and reaction distance indicate that young fish should select larger prey (Mills et al. 1984a). A recent study of age-0 yellow perch has also shown that growth of these fish varies when the fish are fed diets of different zooplankton species (Confer and Lake 1987). Although much is known about the patterns and factors that influence prey selection, little is known about the interrelationships between prey body size, fish size, and growth of age-0 fish. We hypothesized that selection of intermediate-sized prey by age-0 fish optimizes growth. To test this hypothesis, we conducted laboratory experiments to evaluate the effects of prey body size and ration level on the growth of age-0 yellow perch fed Daphnia pulex of different sizes. Methods Growth experiments on age-0 yellow perch were conducted in summer 1986 and 1987. An experiment began in mid to late June and continued until the end of August. Each experiment consisted of a series of feeding trials; each trial employed eight growth chambers that were maintained for a 9-10-d feeding period. A single chamber was considered to be an experimental unit. Growth chambers. —We used cylindrical 71-L and 76-L Plexiglas growth chambers to study the growth of age-0 yellow perch (Figure 1). Two chambers were immersed in each of four 800-L

fiberglass tanks filled with filtered Oneida Lake water. The fiberglass tanks acted as water reservoirs and temperature baths for the growth chambers. Growth chambers operated as static systems during feeding periods and as flow-through systems to flush uneaten prey from the chambers at the end of a feeding period. In the static mode, all inlet and outlet tubes were corked, and an aeration line and air stone were run through an air vent. As a flow-through system (i.e.. during pumping), the air vent was corked, tygon tubing was attached from the outlets to a pump, and the inlets were uncorked to allow water to be pulled through the chamber. Uneaten prey items were collected by pumping the chamber water through a bucket with

AIR

VENT-

SUPPORT ROD WING NUT-

WATER OUTLETS

WATER

INLET

60 cm

50 cm FIGURE 1.—Growth chamber used in growth experiments for age-0 yellow perch.

100-/Ltm-mesh net sides; this usually took 20 min. Water was recycled in a single trial by pumping it out of a growth chamber and back into the 800L water reservoir for reuse. In this way, the same water was used throughout a 9- to 10-d trial with occasional replenishment from Oneida Lake. Environmental conditions.—-We measured the water temperature of each 800-L tank daily before we flushed the chambers and again at feeding time. Light intensity was measured in each tank at feeding time with a Protomatic cell at or near the surface of the water. Turbid water was avoided because it reduced light levels in the chamber. Throughout the experiments, we maintained a photoperiod of 15 h of fluorescent light per day, which was roughly equivalent to the natural day length. Treatments.—We fed each group of age-0 yellow perch in a chamber a diet of different-sized Daphnia pulex for 9-10 d. The daily ration in dry weight of D. pulex was either 25 or 40% of the estimated dry weight of yellow perch in each chamber. The 25% ration approximated the daily ration for growth of age-0 yellow perch in Oneida Lake (Mills and Forney 1981); the 40% ration was selected to test the fish's response to high food densities. Initial dry weights of experimental fish were estimated from dry weight-wet weight regressions determined from the control fish. Dry weight of D. pulex fed to yellow perch was increased daily to match expected growth and to maintain rations at the 25 and 40% ration levels. Smaller fish ( 1.7 mm). Consequently, to maintain equal biomass per fish and equal density among chambers, we varied the number offish per chamber in proportion to the biomass of/), pulex in the chamber. For example, a chamber receiving 2.0-mm D. pulex at a 25% ration might contain 100 prey/L. A chamber containing a 0.9-mm D. pulex diet with the same density (100 prey/L) would contain only Vhlh the dry weight of the 2.0-mm D. pulex chamber. To maintain a 25% ration per fish in both chambers, the chamber with 0.9-mm D. pulex contained V(,th the number offish in the chamber with 2.0-mm D. pulex. The number of yellow perch used in chambers varied between 2 and 18 and was constrained by the availability of live prey. Each trial consisted of four prey sizes and two ration levels distributed over eight growth chambers. The si/e of prey chosen for a trial reflected the availability of the different sizes of D. pulex. We assigned treatments to chambers by using a table of random digits (Snedecor and Cochran 1980). Experimental prey.— Daphnia pulex used in the experiment were collected from Oneida and Caxcnovia lakes. New York, placed in 800-L laboratory tanks, and maintained on spinach ground in a blender. Periodically during the summer, samples of D. pulex were sieved and dried for calorimetry. To prepare the daily rations, we separated D. pulex according to body size by washing the laboratory cultures through a series of six soil sieves (mesh sizes: 2.1. 1.2, 1.0, 0.75,0.5, and 0.25 mm). This arrangement of sieves was chosen to provide a broad array of prey sizes that age-0 yellow perch are capable of ingesting (Mills et al. 1984a). The lengths of individual D. pulex for feeding generally was provided in three size categories: greater than

1.7 mm (retained on the 1.2-mm sieve), 1.1-1.7 mm (retained on the 0.5-mm sieve), and less than 1.1 mm (retained on the 0.25-mm sieve); each sieved size category was distributed into a separate 70-L aerated aquarium. The experimental ration was prepared daily from these single sizeclass stocks. To determine the volume of D. pulex stock necessary for an experimental ration, we took a 1 -L sample from each stock after dead prey were allowed to settle out for about 2 h. Counts and lengths were determined and recorded by means of an overhead projector and electronic calipers interfaced with a microcomputer (Mills and Confer 1986). The density, biomass, average length, and average weight of zooplankton were determined for each aquarium. The lengths of D. pulex were measured from the anterior margin of the head to the base of the tail spine. Zooplankton weights and biomass were calculated from known length-to-weight regressions (present authors, unpublished data). We determined the volume of stock required for experimental feedings from biomass and density estimates. Feedings were pipetted into the growth chambers through the air vents. The fish were allowed to feed for about 18 h (midafternoon until late next morning). The chambers were then pumped for 20 min to remove uneaten prey which were then preserved in a sucrose-formalin solution. We estimated the biomass consumed as the difference between biomass fed and biomass recovered. Experimental'fish.—Age-0 yellow perch for each trial were seined from inshore areas of nearby Oneida Lake and transported to a holding tank filled with lake water. The fish were treated with a fungicide (0.1 mg Prefuran/L) for 48 h and fed D. pulex. Fifty yellow perch (controls) were randomly selected from the holding tank, and both wet weight (g) and total length (mm) were measured. These fish were dried at 60°C for at least 48 h to determine dry weight (g) and then frozen for later caloric analysis. We calculated length-wet weight and dry weight-wet weight regressions. Experimental fish were weighed and were deemed acceptable if their wet weight fell within 15% of the mean wet weight of the controls. The initial length and initial dry weight of experimental fish were estimated from regressions determined for the control fish. Selected fish were placed in growth chambers, fed a maintenance ration of D. pulex, and acclimated for 24 h. Fish growth.—We determined mean wet and dry

weights, length, and caloric densities at the end of

MILLS ET AL.

each trial for each growth chamber and measured specific growth, gross assimilation, and caloric assimilation. We calculated specific growth rate (SGR) by the equation, SGR

Xf is final dry weight, Xt is initial dry weight, and dis number of days (Ricker 1975). We calculated gross assimilation and caloric assimilation of prey

by


A = 100

f

- X, R

A is percent assimilation, Xf is final mean caloric content or dry weight of yellow perch for each chamber, Xt is the initial mean caloric content or dry weight, and R is the total ration consumed in joules or weight. Calorimetry.—Conirol fish, experimental fish, and D. pit/ex were dried immediately after collection for at least 72 h and frozen for later analysis. For caloric analysis, we pulverized fish and daphnids, compressed them into pellets, and redried them at 60°C for at least 72 h. We weighed pellets to the nearest 0.001 g and determined caloric contents with a Parr adiabatic bomb calorimeter equipped with a semimicro bomb and standardized with benzoic acid. We calculated caloric values from combustion of three or more replicate pellets. Standard deviations of caloric samples averaged 2.3% (range, 0.6-6.3) of the means. The mean initial caloric content of the experimental fish was assumed to be the same as for the controls. Caloric values of D. pulex collected from Oneida and Cazenovia lakes were assumed to reflect the caloric content of the experimental diet. Daphnia pulex samples for caloric analysis were not taken as often as prey were collected for the experiment; the caloric content of prey was estimated from the average caloric content of samples taken just before or during feeding trials. Because of the difficulty of collecting sufficient biomass of D. pulex less than 1.1 mm long, only one sample of this size category was used each year to determine caloric content. Data analysis.— Chi-square tests were used to test the similarity of size distributions of D. pulex before and after they were pumped from individual growth chambers (Snedecor and Cochran 1980). Student's /-distribution was used to assess differences in zooplankton caloric values. Polynomial and multiple linear regression techniques

(Feldman and Gagnon 1986) were used to examine the effect of prey body length on growth of age-0 yellow perch. Age-0 yellow perch were sorted according to ration (25 and 40%), and data from both years were included in the regression analysis. Results

Prey Recovery. Size Separation, and Caloric Content of Experimental Meals We conducted 21 recovery experiments during 1986 and 1987 to evaluate the effectiveness of our system for removing uneaten prey from individual growth chambers. Daphnia pulex were introduced into a fishless growth chamber in an amount equivalent to a typical feeding and pumped out 24 h later. Analysis indicated that pumping damaged D. pulex larger than 1.1 mm, and consequently, we estimated lengths only of individual daphnids with more than 50% of their carapace remaining. Prey less than 1.1 mm long were not affected by pumping, and only whole small organisms were counted. We compared the size distribution of D. pulex before and after pumping to assess length estimates of reconstructed organisms in 14 growth chambers. Chi-square analysis revealed no significant differences (P > 0.05) in length distributions before and after pumping (\2 = 9.7, df = 13); the mean size of prey added to all 14 fish growth chambers was 1.77 mm and the mean size recovered was 1.70 mm. Recovery efficiencies of D. pulex ranged from 85 to 97% for individual prey sizes and were used to estimate the dry-weight biomass consumed by age-0 yellow perch. The biomass of a feeding added to each chamber was known in all cases, and the uneaten prey was estimated from the recovery efficiency. The dry weight biomass added, less the uneaten biomass, equalled the biomass consumed. The uneaten biomass was calculated by dividing the amount of recovered biomass by the recovery efficiency. For example, in trial 1, 1987, 0.540 g of zooplankton was added over the course of the trial, and 0.027 g was recovered. We divided 0.027 g by the 85.2% recovery efficiency determined for 0.87-mm D. pulex and estimated the uneaten biomass to be 0.032 g. Therefore, the biomass consumed by age-0 yellow perch was 0.508 g. The mean body length of D. pulex for all trials ranged from 0.80 to 2.20 mm. The average purity of D. pulex in fish diets was 90, 97, and 99% for size-groups representing less than 1.1 mm (range,

PREY BODY SIZE AND YELLOW PERCH GROWTH


73-100%). 1.1-1.7 mm (range, 81-100%), and greater than 1.7 mm (range, 84-100%), respectively. Mean caloric content of D. pulex from Ca/enovia Lake increased over the summer of 1987 (F = 30.76, df = 1. 12: P = 0.005), whereas the caloric values of prey from Oneida Lake did not change significantly (F = 0.12, df = 1, 12; P = 0.07). There were no significant differences between caloric densities for size categories of l.l1.7 mm and greater than 1.7 mm in Oneida (/ = -2.31, df = 8: P > 0.05) and Ca/enovia (/ = -1.32, df = 14; P > 0.05) lakes; differences between prey less than 1.1 mm and other prey sizes could not be tested because of insufficient sample si/e. Growth Trials Growth trials began when yellow perch reached a length of 30-35 mm TL; mean fish size increased during the summer and ranged from 31.2 mm to 58.3 mm TL in all trials for both years. Mortality rates varied among trials, and in most cases, mortality resulted from fish becoming caught between the lid and body of the growth chamber. Growth chambers that experienced greater than 15% mortality were excluded from analyses. A total of 40 growth chambers, 18 at the 25% ration and 22 at the 40% ration, provided data for analysis. Average water temperature ranged between 19 and 22°C in all growth trials except one when average water temperature was 16.4°C. Light levels were high and ranged between 387 and 646 Ix. Caloric content of D. pulex less than 1.1 mm, 1.1-1.7 mm, and greater than 1.7 mm averaged over the 2-year study period were 18,552. 18,648, and 18,732 J/g of D. pulex, respectively. The actual ration (biomass of prey added/final biomass of fish at each feeding) averaged 25.6% (range, 23.6-28.7; SD = 1.6; N = 18) for the 25% ration and 40.5% (range, 33.5-47.2; SD = 3.23; N = 22) for the 40% ration. The average percentage of D. pulex biomass consumed by yellow perch varied among

trials but was higher for the 25% ration level (mean, 89.4; range, 39.4-98.5%; N = 18) compared to 40% ration (mean, 85.4; range, 62.9-94.7%; N = 22). In effect, the actual ration ofD. pulex biomass consumed by yellow perch averaged 22.9% in the 25% ration compared with 34.6% in the 40% treatment. Specific growth rate of age-0 yellow perch varied from loss of weight to a gain of 0.05 g/d and tended to be higher for smaller fish and decreased with fish size. For example, specific growth rate for yellow perch 30-40 mm TL averaged 0.037 g/d for

the 40% ration, whereas fish exceeding 40 mm TL had an average specific growth rate of 0.012 g/d. A similar trend was evident for the 25% ration. Log-transformed data, exclusive of those yielding negative specific growth rates, were pooled from the 25 and 40% ration levels; a significant linear relationship was observed between specific growth rate and initial fish size (N = 37, F = 17.67, r- = 0.34, P = 0.002), and specific growth rate declined with increasing fish size. Untransformed data followed a simple power function as displayed in Figure 2. There was a significant linear relationship between specific growth rate and gross assimilation (GA): GA = 0.849 + 340.5SGR (N = 40, F = 122.3, r2 = 0.76, P = 0.0001). A similar relationship was found between specific growth rate and caloric assimilation (CA): CA = —0.995 + 388.8SGR (N = 40, F = 170.8, r- = 0.82, P = 0.0001). Both slopes were positive and thus, indicated that specific growth rate increased proportionately with gross and caloric assimilation.

Prey Size, Specific Growth Rate, and Assimilation We examined specific growth rate, gross assimilation, and caloric assimilation in relation to mean size of D. pulex at 25 and 40% ration levels. For the 25% ration, the highest growth rates, 0.0230.024 g/d, were observed when yellow perch were fed prey between 1.4 and 1.8 mm long, whereas growth declined for zooplankton sizes less than or greater than this size range. Both the X (prey size) and X2 terms in the polynomial regression used to predict specific growth rate from prey size for the 25% ration were significant (N = 18, F = 4.62, R2 = 0.38, P = 0.03; Figure 3A). Similar relationships were observed for the 25% ration level between prey size (PS) and GA: GA = -27.53 + 52.54PS - 17.64PS2 (N = 18, F = 4.36, R2 = 0.37, P = 0.03) and between PS and CA: CA = -34.33 4-59.2IPS- 19.56PS 2 (W= 18,F=6.72, R2 = 0.47, P = 0.008). For the 40% ration, specific growth rate ranged between 0 and 0.05 g/d across all prey sizes, and the mean specific growth rate was equivalent to the peak rate for the 25% ration. However, there was no significant relationship between prey size and specific growth rate when the data were fitted to either a linear (/V = 22, F = 0.0004, r2 = 0.00, P = 0.98) or a polynomial model (N = 22, F = 0.048, R2 = 0.005, P = 0.95; Figure 3B); therefore, prey size did not modify growth of age-0 yellow

perch at an elevated ration level. A similar lack of relationship for the polynomial model was ob-

MILLS ET AL.

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0.02

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30

35

40

45

50

55

60

X = Initial Fish Length (mm) FIGURE 2. —Relationship between initial fish length and specific growth rate for age-0 yellow perch fed rations of Daphnia pulex equivalent to either 25 or 40% of yellow perch dry weight.

served at the 40% ration between prey size and gross assimilation^ =22, ^ = 0.141,/* 2 = 0.015, P = 0.87) and between prey size and caloric assimilation (N = 22, F = 0.146, R2 = 0.02, P = 0.86). Multiple Regression Analysis To predict age-0 yellow perch specific growth rate according to ration level (25 and 40%), we used a multiple regression model and included the variables in the form

specific growth rate = a + bX\ + cX2 + d(X2)2 4- ..." + b,,Xn + bn(Xnra. / ? , c , . . . , and bn are empirical constants, and AV X2, . . ., and Xn represent continuous variables, which in some cases were linearized by transformation. Specific growth rate decreased curvilinearly with initial fish length but linearly with initial fish length raised to the —2.814 power (Figure 2). Consequently, we incorporated the latter expression into the multiple regression model. Temperature is a critical determinant of fish growth (Brctt 1979), and in our trials, average water temperature ranged between 16.4 and 22°C. Therefore, we included temperature in the regression model to determine if this factor masked the effect of other variables on specific growth rate. Because we used a quadratic model to describe the relationship between prey size and specific growth rate (Figure 3), both prey size and the square of prey size were used in the multiple

regression model. For the 25% ration, prey size (partial F — 8.82) and the square of prey size (partial F — 8.05) were the only variables that contributed significantly (P < 0.05) to the prediction of yellow perch specific growth rate (Table 1). The equation explained 59% of the variance in yellow perch specific growth rate. For the 40% ration, initial fish length was the only significant (P < 0.05) predictor (partial F— 9.02) of specific growth rate. Similarly, according to the multiple regression model, prey size for the 25% ration and fish size for the 40% ration were also the only significant factors (P < 0.05) in the prediction of gross assimilation and caloric assimilation. Discussion The existence of prey selectivity implies a mechanism for optimizing foraging efficiency to maximize digestible-energy intake. Thus, it might be expected that interrelationships exist between prey body size, predator body size, and growth. Several studies have shown that these variables are interrelated for adult planktivores and that the energy gain of eating large prey outweighs the energy cost of capture. For juvenile Atlantic salmon

Salmo salar that were fed commercial pellets differing in particle size, growth rates were closely related to particle size, and the optimum prey size for maximum growth increased with fish length (Wankowski and Thorpe 1979). Our results for age-0 yellow perch fed live D. pulex indicated that specific growth and prey size were related when fish were fed a ration of 25% of fish dry weight.


A 2 rr £

0.03 n Y = -0.049 + 0.092 (X) - 0.030 (X)2 B

S "go 0.02-

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0.00

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X = Prey Size (mm) FIGURE 3,—Specific growth rate for age-0 yellow perch (30-60 mm total length) fed different size categories of Daphnia pulex at rations amounting to 25% (A) and 40% (B) of yellow perch dry weight.

Under these conditions, young yellow perch exhibited maximum growth when fed l.4-l.8-mm D. pulex. When the ration was increased to 40%, prey size no longer influenced ftsh growth and as-

similation, and instead, the interrelationship between fish length and growth became more evident. Seemingly, at a high ration level when ample densities of different sized prey were available,

TABLE I.—Summary of coefficients used to predict specific growth rate (SGR) of age-0 yellow perch fed Daphnia pulex rations of 25 and 40% offish dry weight in a multiple regression of prey size (mm), initial fish length (IFL, mm), and temperature (°C). Nonsignificant (NS) variables (P > 0.05) were excluded from actual predictions. Ration level 25 40

Independent variable

Dependent variable

df

Prey size

(Prey size)2

(IFL)-2-81

Temperature

Intercept

SGR SGR

17 21

0.087 NS

-0.029

NS 729.9

NS NS

0.002 0.092

NS

0.59 0.56


8

MILLS ET AL.

yellow perch were able to capture and consume enough prey smaller and larger than the preferred 1.4-1.8-mm animals. These findings are consistent with the work of LeBrasseur (1969) who also found that the growth of juvenile chum salmon Oncorhynchus keta was not influenced by the body size of available prey at abnormally high prey densities. However, the peak specific growth rate at the 25% ration for 1.4-1.8-mm D. pitlex was the same as the mean specific growth rate across all prey sizes at the 40% ration. Apparently, at lower ration levels when prey density limits growth, young yellow perch 30-60 mm TL must optimize foraging efficiency by consuming intermediatesized prey to achieve maximum growth observed at higher ration levels. Fish growh depends on several factors, and the results of our study indicate the importance of prey size and ration. The daily prey ration of 25% of yellow perch dry weight used in our experiments reflects a ration that these fish might obtain in nature (Mills and Forney 1981). Our laboratory results indicated a linkage between prey size and predator growth that was consistent with observations of prey selection in the field. Relationships between the lengths of D. pulex and age-0 yellow perch established by Hansen and Wahl (1981) in Oneida Lake indicate that these fish select 1.11.7-mm prey. In our experiments, age-0 yellow perch exhibited the highest specific growth and assimilation rates for prey in the 1.4- to 1.8-mm size range. These findings suggest that a linkage exists between prey size selection and fish growth and that prey size regulates the growth of age-0 fish. For age-0 fish that depend on zooplankton for food and pass prey through the digestive tract as whole organisms, the best strategy might be to process as many prey as possible to maximize growth. When prey is abundant and fish-prey encounter rate is high (i.e., time per encounter is low), as was the case in our 40% ration trials, prey density is not limiting. Consequently, young fish can process large numbers of prey and mask linkages between prey size and differential growth. During times of restricted prey availability, young fish must select prey that maximize their ability to process prey efficiently. In evacuation experiments with age-0 yellow perch, the number of prey in stomachs was dependent on meal size and was inversely related to prey size; an increase in the number of prey in stomachs generally increased the evacuation rate (number egested per hour; Mills et al. 1984b). As a result, fish may net less energy

per prey when prey abundance is in excess and prey consumption is high, because residence time is short. In our experiments, growth of yellow perch at the 25% ration was highest for 1.4- to 1.8-mm prey, but the differences in growth rate apparently were not due to differential caloric content among prey size-classes because they were nearly equal. This suggests that factors in addition to caloric content affect fish growth. For age-0 fish, it is possible that prey 1.1-1.7 mm long allow maximum processing capability and have a surface-to-volume ratio that is optimal for digestibility and assimilation. Although we found that prey size accounted for 38% of the variance in specific growth rate when the ration was set at 25% offish dry weight, other factors associated with prey organisms can modify growth rates of age-0 fish. The availability of suitable organisms is critically important to the growth of young fish, as indicated by the influence of prey size on the growth of age-0 yellow perch in our experiments. Additional factors can influence the availability and conversion efficiency of energy from food to growth. Zooplankton species differ in caloric (Schindler et al. 1971) and lipid content (Tessier et al. 1983), and invertebrates have been shown to vary in their digestibility (Windell 1966). Prey type has recently been shown to influence growth of age-0 yellow perch (Confer and Lake 1987). Further, numerous field studies have shown that age-0 fish growth is modified when fish switch to alternative prey (Mills and Forney 1981; Guma'a and Yassin 1984). Finally, Elliot (1972, 1976) has shown that the assimilable energy and the digestive response of a predator varies with the type of prey organism. Our use of live prey facilitated the field testing of inferences drawn from laboratory experiments. Our experimental results agree with current analyses of field data from Oneida Lake that suggest linkages between prey selection and growth and

demonstrate the importance of prey size to the growth of age-0 fish (Mills et al., in press). Consequently, models designed to predict growth of age-0 fish in the natural environment must consider not only the more familiar modifiers offish growth such as food abundance, food availability, and temperature (Blaxter 1969) but should also consider the importance of zooplankton body size as an additional factor influencing fish growth. Acknowledgments Funds for this study came from the National Science Foundation (BSR: 8516274) and Cornell


regimes. Journal of the Fisheries Research Board of Canada 26:1631-1645. Mathias, J. A., and S. Li. 1982. Feeding habits of walleye larvae and juveniles: comparative laboratory and field studies. Transactions of the American Fisheries Society 111:722-735. Milinski, M. 1986. Constraints placed by predators on feeding behaviour. Pages 236-252 In T. J. Pitcher, editor. The behaviour of teleost fishes. Croom Helm, London. Mills, E. L., and J. L. Confer. 1986. Computer proReferences cessing of zooplankton—application in fisheries Blaxter. J. H. S. 1969. Development: eggs and larvae. studies. Fisheries (Bethesda) 1 l(l):24-27. Pages 177-252 in W. S. Hoar and D. J. Randall, Mills, E. L., J. L. Confer, and R. C. Ready. 1984a. Prey editors. Fish physiology, volume 3. Academic Press, selection by young yellow perch: the influence of New York. capture success, visual acuity, and prey choice. Breck. J. E., and M. J. Gittcr. 1983. 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Fish vision and the detection of planktonic prey. Ricker, W. E. 1975. Computation and interpretation Science (Washington, D.C) 218:1240-1242. of biological statistics offish populations. Fisheries Hansen. M. J., and D. H. Wahl. 1981. Selection of Research Board of Canada Bulletin 191. small Daphnia pulex by yellow perch in Oneida Lake, New York. Transactions of the American Fisheries Schindler, D. A., A. S. Clark, and R. J. Gray. 1971. Seasonal calorific values of freshwater zooplankton, Society 110:64-71. as determined with a Philipson Bomb calorimeter Kerr, S. R. 197 la. A simulation model of lake trout modified for small samples. Journal of the Fisheries growth. Journal of the Fisheries Research Board of Research Board of Canada 28:559-564. Canada 28:815-819. Kerr, S. R. 1971 b. Prediction of fish growth efficiency Snedecor, G. W., and W. G. Cochran. 1980. Statistical in nature. Journal of the Fisheries Research Board methods, 7th edition. 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University. We gratefully acknowledge John Forney. Mark Prout, John Confer, and three anonymous reviewers who made valuable contributions to the manuscript. Russell Lloyd's counsel in statistics was gratefully appreciated. This paper is contribution number 103 of the Cornell Biological Field Station.

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