Adaptive Significance of Vertical Migration Behaviour

ADAPTIVE SIGNIFICANCE OF VERTICAL MIGRATION BEHAVIOUR

OF SKISTODIAPTOMUS OREGONENSIS

DAVID GHAN

B.Sc, McGill University, 1987 M.Sc, The University of Toronto, 1991

A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY

THE FACULTY OF GRADUATE STUDIES

(Department of Zoology)

We accept this thesis as conforming to the required standard

THE UNIVERSITY OF BRITISH COLUMBIA

March 1997

David Ghan, 1997 In presenting this thesis in partial fulfilment of the requirements for an advanced degree at the University of British Columbia, I agree that the Library shall make it freely available for reference and study. 1 further agree that permission for extensive copying of this thesis for scholarly purposes may be granted by the head of my department or by his or her representatives. It is understood that copying or publication of this thesis for financial gain shall not be allowed without my written permission.

Department of piD J\ Uy — zru~ The University of British Columbia Vancouver, Canada

Date lm/7srA .7 I'/fl"?

DE-6 (2/88) 11

Abstract

I have studied the adaptive significance of vertical migration of zooplankton in 2 populations of the copepod

Skistodiaptomus oregonensis that migrate and 2 populations that do not migrate. Vertical migration of the copepods is associated with the presence of pelagic sticklebacks. This observation is consistent with the hypothesis that the adaptive benefit of vertical migration by S. oregonensis is to avoid stickleback predators. The alternative hypotheses including avoidance of juvenile sockeye predators, foraging efficiency, bioenergetic efficiency, or combined foraging/bioenergetic efficiency are not supported by the comparisons of migratory behaviour of S. oregonensis in the 4 lakes.

Both the depth and timing of S. oregonensis migration are consistent with the hypothesis that copepods are avoiding predation by sticklebacks. Light intensities at the depth at which S. oregonensis reside during the day are sufficiently low to.reduce predation risk from visual foraging stickleback and the timing of ascent at dusk and descent at dawn are such that S. oregonensis remain at light intensities that reduce risk from stickleback. S. oregonensis are at the surface at dusk and dawn at the time that juvenile sockeye feed in the surface habitat.

Vertical migration appears to be a trade-off with resource acquisition. Phytoplankton are less concentrated in the deep habitat where S. oregonensis reside during the day. Furthermore, migrating copepods contain less phytoplankton as food in their guts than do non-migrating individuals. Ill

In vertical columns in the laboratory, the presence or absence of sticklebacks does not influence the vertical distributions of S. oregonensis collected from lakes with either migratory or non-migratory populations. This indicates that the migration phenotype is fixed rather than being a flexible behaviour induced by environmental cues. I developed a dynamic optimization model to predict the optimal depth decisions for S. oregonensis based on depth dependent lake food and temperature conditions, fish abundance and predation rates, and S. oregonensis bioenergetics. The model predicts that vertical migration should occur to avoid sticklebacks under a broad range of modelled conditions, but with a fitness cost due to feeding opportunity costs. This demonstrates quantitatively that it is tenable to hypothesize that vertical migration involves a trade• off between stickleback avoidance and feeding opportunity.

Taken together, these results are consistent with the view that different migration behaviours in these populations are a result of divergent evolution driven by environmental variation affecting the optimal solution to the predation risk/resource acquisition trade-off. iv

Table of Contents

Abstract ii Table of Contents iv

List of Tables v List of Figures vi Acknowledgements xii Chapter 1: General Introduction 1 Chapter 2: Testing hypotheses on the benefits and costs of vertical migration by Skistodiaptomus oregonensis by comparing populations 9 Introduction . 9 Methods 10 Results 19 Discussion 48 Chapter 3: The Timing and extent of vertical migration by Skistodiaptomus oregonensis relative to the temporal- spatial distribution of predation risk 58 Introduction 58 Methods 59 Results 63 Discussion . 98

Chapter 4: Vertical migration behavior of Skistodiaptomus oregonensis: constitutive or induced? . 103 Introduction 103 Methods 104 Results 108 Discussion 120 Chapter 5: A dynamic optimization model of Skistodiaptomus oregonensis vertical migration 128 Introduction 128 Model Description 129 Model Results 140 Summary 151

Chapter 6: Thesis Summary 153

References 158 V

List of Tables

Table 2.1: Physical conditions in the four study lakes. ... 37

Table 2.2: Biological conditions in the four study lakes. . . 3 8

Table 3.1: ANOVA results testing H0 that initial zooplankton densities in experimental feeding tanks did not differ among light intensity treatments 64 Table 3.2: ANOVA results for each prey type testing Ho that initial densities of the prey types did not differ among treatments 65 Table 3.3: ANOVA results testing Ho that initial zooplankton densities in experimental feeding tanks did not differ among days 69 Table 3.4: Regression results for the effect of light (X) on four Y variables where In(Y+l)=a*ln(X)+b, except for the capture/strike ratio where arcsin(sqrt (Y+l) ) =a*ln(X) +b 78 Table 4.1: Experiment 1 - univariate repeated measures analyses of variance for A) the effect of fishwater [+/-] treatments on the proportion of S. oregonensis below 100 cm during the day and B) the effect of fishwater [+/-] treatments on the change in the proportion of S. oregonensis below 100 cm from night to day 112 Table 4.2: Experiment 1 - nested analyses of variance for depths of individual S. oregonensis: tests of significance for fishwater [+/-] treatment effects and tube within treatment effects 114 Table 4.3: Experiment 2 - univariate repeated measures analyses of variance for A) the effect of fishwater [+/-] treatments on the proportion of S. oregonensis below 100 cm during the day and B) the effect of fishwater [+/-] treatments on the change in the proportion of S. oregonensis below 100 cm from night to day 118 Table 4.4: Experiment 2 - nested analyses of variance for depths of individual S. oregonensis: tests of significance for fishwater (+/-) treatment effects and tube within treatment effects 119

Table 4.5: Experiment 3 - nested analyses of variance for depths of individual S. oregonensis: tests of significance for fish (+/-) treatment effects and tube within treatment effects 123 vi

List of Figures Fig. 2.1: Location of the four study lakes in southwestern British Columbia 11 Fig. 2.2: Map of Great Central Lake showing sample location (X) and lake contours in meters. Depth contours taken from Rutherford et al. (1986) 12 Fig. 2.3: Map of Hobiton Lake showing location of sample site (X) and lake contours in meters 13 Fig. 2.4: Map of Kennedy Lake showing location of sample site (X) and depth contours in meters 14 Fig. 2.5: Map of Paxton Lake showing location of sample site (X) and depth contours in meters 15 Fig. 2.6: Day (hatched bars) and night (solid bars) vertical distribution for 5 metasome length classes of S. oregonensis in Kennedy Lake on August 25, 1993 20 Fig. 2.7: Day (hatched bars) and night (solid bars) vertical distribution for 5 metasome length classes of S. oregonensis in Kennedy Lake on November 12, 1992. ... 21 Fig. 2.8: A) Mean day and night depth of 750-850 um metasome length S. oregonensis in Kennedy Lake on 13 sample dates from 1992-1994. B) Mean day and night depth of 3-50 um size fraction of phytoplankton in Kennedy Lake from 13 sample dates from 1992 to 1994. C) Data in part A and B redrawn to compare mean day and night depth of S. oregonensis with mean day and night depth of 3-50 um size fraction of phytoplankton 22 Fig. 2.9: Vertical distribution of chlorophyll a from the 3-50 um size fraction of phytoplankton on 12 sample dates in Kennedy Lake 23 Fig. 2.10: Depth distribution of temperature (open circles) and of chlorophyll a from the 3-50 um size fraction of phytoplankton day (open squares) and night (solid squares) on six sample dates 25 Fig. 2.11: Changes in density of S. oregonensis in three depth strata of Paxton Lake during dawn of August 19, 1994. . 26 Fig. 2.12: Changes in density of S. oregonensis in three depth strata of Paxton Lake during dusk of August 19, 1994 27 Fig. 2.13: Day and night vertical distribution of chlorophyll a from the 3-50 um size fraction of phytoplankton in Paxton Lake, August, 1994 28 vii Fig. 2.14: Day (hatched bars) and night (solid bars) vertical distribution for 5 metasome length classes of S. oregonensis in Great Central Lake on July 7, 1992. . 30 Fig. 2.15: Day (hatched bars) and night (solid bars) vertical distribution for 5 metasome length classes of S. oregonensis in Great Central Lake on August 18, 1992. . • 31 Fig. 2.16: A) Mean day and night depth of 750-850 um metasome length S. oregonensis in Great Central Lake on 7 sample dates in 1992 and 1993. B) Mean day and night depth of 3-50 um size fraction of phytoplankton in Great Central Lake from 7 sample dates from 1992 and 1993. C) Data in part A and B redrawn to compare mean day and night depth of S. oregonensis with mean day and night depth of 3-50 um phytoplankton 32 Fig. 2.17: Day (hatched bars) and night (solid bars) vertical distribution for 5 metasome length classes of S. oregonensis in Hobiton Lake on August 5, 1992. ... 33 Fig. 2.18: Day (hatched bars) and night (solid bars) vertical distribution for 5 metasome length classes of S. oregonensis in Hobiton Lake on June 25, 1992 34 Fig. 2.19: Day (open circles) and night (solid squares) mean depth of 660-795 um metasome length class S. oregonensis and the 3-50 um size fraction of phytoplankton on June 25 and August 25, 1992 35 Fig. 2.20: Mean concentration of chlorophyll a from the 3-50 um size fraction of phytoplankton in the 4 study lakes 39 Fig. 2.21: Top: S. oregonensis weighted mean daytime depth versus metasome length classes in Kennedy Lake. Bottom: Difference between weighted mean daytime depth and weighted mean night time depth for each sample date 41 Fig. 2.22: Day (hatched bars) and night (solid bars) vertical distribution for 5 small metasome length classes of S. oregonensis in Kennedy Lake on April 14, 1993 42 Fig. 2.23: Day (hatched bars) and night (solid bars) vertical distribution for 5 small metasome length classes of S. oregonensis in Kennedy Lake on November 12, 1992 43 Fig. 2.24: Day versus night gut pigments in S. oregonensis in Kennedy.Lake (solid square) and Great Central Lake (open squares) on May 11-13, 1993 (top), June 22-23, 1993 (middle), and July 15-16, 1993 (bottom) 44 viii Fig. 2.25: Daytime S. oregonensis gut pigments versus depth on June 23, 1993 (top) and July 16, 1993 (bottom). ... 45 Fig. 2.26: S. oregonensis gut pigment changes at dawn and dusk in Great Central Lake and Kennedy Lake, August 25-27, 1993 46 Fig. 2.27: S. oregonensis gut pigment changes at dawn and dusk in Great Central Lake and Kennedy Lake, October 17-20, 1993. . 47 Fig. 2.28: Weighted mean daytime depth of S. oregonensis in Kennedy Lake versus mean chlorophyll a concentration of the 3-50 um phytoplankton size fraction in the top 10 m 49 Fig. 3.1: Total zooplankton densities broken down by taxa or size categories in each of 11 treatments for experiment date June 5 67 Fig. 3.2: Total zooplankton densities broken down by taxa or size categories in each of 11 treatments for experiment date June 7 68 Fig. 3.3: Mean zooplankton density across treatments for each experiment date. Vertical bars represent entire range of densities for each day 70 Fig. 3.4: A comparison of the relative density of prey types in one of the experimental tanks (solid bar) and in Kennedy Lake (open bar) on May 20, 1995 71 Fig. 3.5: A comparison of the size of prey types in one of the experimental tanks (solid square) and in Kennedy Lake (open squares) on May 20, 1995 72 Fig. 3.6: Number of S. oregonensis in stomachs of stickleback fed for 15 minutes at 11 light intensities. Top: Light intensity range 0.1-15.5 uE • s~x-m~2. Bottom: Enlargement of light intensity range from 0.1-1.6 uE-s~ 1-m-2 (bottom left corner of top figure) 73 Fig. 3.7: Number of prey in stomachs of stickleback fed for 15 minutes at 11 light intensities. Top: Light . intensity range 0.1-15.5 uE-s^-m"2. Bottom: Enlargement of light intensity range from 0.1-1.6 uE-s~ 1-m"2 (bottom left corner of top figure) 74 Fig. 3.8: Number of prey strikes taken by stickleback fed for 15 minutes at 11 light intensities. Top: Light intensity range 0.1-15.5 uE • s"1 -m"2. Bottom: Enlargement of light intensity range from 0.1-1.6 uE-s" 1'm"2 (bottom left corner of top figure) 75 ix Fig. 3.9: Ratio of captures/strikes for stickleback fed for 15 minutes at 11 light intensities. Top: Light intensity range 0.1-15.5 uE-s_1-rrf2. Bottom: Enlargement of light intensity range from 0.1-1.6 uE«s~ 1-m"2 (bottom left corner of top figure) 76 Fig. 3.10: Vanderploeg-Scavia index of electivity for S. oregonensis by stickleback fed for 15 minutes at 11 light intensities. Top: Light intensity range 0.1-15.5 uE-s^-nT2. Bottom: Enlargement of light intensity range from 0.1-1.6 uE-s^-m"2 (bottom left corner of top figure) 79 Fig. 3.11: Vertical migration of S. oregonensis relative to stickleback feeding rate thresholds in Kennedy Lake during dawn on May 20, 1995 80 Fig. 3.12: Vertical migration of S. oregonensis relative to stickleback feeding rate thresholds in Kennedy Lake during dusk on May 20, 1995 81 Fig. 3.13: Vertical migration of S. oregonensis relative to stickleback feeding rate thresholds in Kennedy Lake during dawn on June 24, 1994 82 Fig. 3.14: Vertical migration of S. oregonensis relative to stickleback feeding rate thresholds in Kennedy Lake during dusk on June 24, 1994 83 Fig. 3.15: Vertical migration of S. oregonensis relative to stickleback feeding rate thresholds in Paxton Lake during dusk on August 19, 1994 84 Fig. 3.16: Vertical migration of S. oregonensis relative to stickleback feeding rate thresholds in Paxton Lake during dawn on August 19, . 1994. . 85 Fig. 3.17: Summary of available data on time of the beginning of movement of juvenile sockeye toward the surface (X), the period of migration toward the surface (dotted lines) and the period of feeding near the surface (solid line) relative to sunset 89 Fig. 3.18: Summary of available data for juvenile sockeye on the time of juvenile sockeye feeding near the surface (solid line) and the time of the beginning of movement toward depth (X) relative to sunrise 90 Fig. 3.19: Maximum (1.0 ft.-c), half maximum (0.01 ft.-c), and minimum (0.0001 ft.-c.) feeding rate isolumes for juvenile sockeye (from Ali 1959) for clear sky conditions during dawn (top panel) and dusk (bottom panel) on June 23, 1994 91 X Fig. 3.20: Changes in vertical distribution of fish targets (top) and S. oregonensis (bottom) in Kennedy Lake at dusk on October 19, 1993 93 Fig. 3.21: Changes in vertical distribution of fish targets (top) and S. oregonensis (bottom) in Kennedy Lake at dusk on June 24, 1994 94 Fig. 3.22: Changes in vertical distribution of fish targets (top) and S. oregonensis (bottom) in Kennedy Lake at dusk on May 19, 1995 95 Fig. 3.23: Changes in vertical distribution of fish targets (top) and S. oregonensis (bottom) in Kennedy Lake at dawn on June 24, 1994 96 Fig. 3.24: Changes in vertical distribution of fish targets (top) and S. oregonensis (bottom) in Kennedy Lake at dawn on May 19, 1995 97 Fig. 3.25: Changes in vertical distribution of N. mercedis (top) and S. oregonensis (bottom) at dusk on October 20, 1993 99 Fig. 4.1: Light intensity depth profile in experimental tubes (primary axis) and corresponding depth of similar light intensities in Kennedy Lake at surface light intensity of 1000 uE-s^-m"2 and k=0.401 (secondary axis) 105 Fig. 4.2: Experiment 1 - typical day and night distributions of Kennedy Lake S. oregonensis in cyclinders in fishwater [ +/-] treatments 109 Fig. 4.3: Proportion of Kennedy Lake S. oregonensis below 100 cm during the day in experiment 1. Solid squares indicate fishwater [-] treatments and open squares indicate fishwater [ + ] treatments 110 Fig. 4.4: Experiment 1 - change in the proportion of Kennedy Lake S. oregonensis below 100 cm from night to day in fishwater [ + /-] treatments Ill Fig. 4.5: Experiment 2 - typical day and night distributions of Great Central Lake S. oregonensis in cyclinders in fishwater [ + /-] treatments 115 Fig. 4.6: Experiment 2- change in the proportion of Great Central Lake S. oregonensis below 100 cm from night to day in fishwater [ + /-] treatments 116 Fig. 4.7: Experiment 2 - proportion of Great Central Lake S. oregonensis below 100 cm during day 117 XI

Fig. 4.8: Experiment 3 - change in proportion of Kennedy- Lake S. oregonensis below 100 cm from night to day. Solid squares indicate fish [-] treatments and open squares indicate fish [ + ] treatments 121

Fig. 4.9: Increase in the proportion of Kennedy Lake S. oregonensis below 100 cm from night to day in fishwater [ + /-] treatments of experiment 3 122

Fig. 4.10: Day and night weighted mean depth of S. oregonensis in Kennedy Lake (top) and Great Central Lake (bottom) for multiple sample dates 124

Fig. 5-1: Cohort analysis of S. oregonensis in late winter/spring of 1993 (Kennedy Lake) 131

Fig. 5-2: Copepod filtering rates as a function body weight. General equation for copepods taken from Peters and Downing (1984), the values for mature S. oregonensis from Richman (1966) 135

Fig. 5-3: Model reactive distances of juvenile sockeye at night (top) and stickleback during the day (bottom) at each depth for 0.25 mm, 0.50, 0.75 mm and 1.00 mm size prey 139

Fig. 5-4: Model effect of stickleback and sockeye feeding on day (open squares) and night (asterisks) optimal growth and depths of S. oregonensis 141

Fig. 5.6: Model effect of phytoplankton cell density on (A) day and night optimal depths and growth of S. oregonensis and on (B) the final body size and lifetime survival probability 144

Fig. 5.8: Model effect of varying S. oregonensis filtering rate parameters between 90-110% of default values for four levels of phytoplankton food density 148

Fig. 5.9: Model parameter values that predict non-migration of smaller S. oregonensis 150 Xll Acknowledgement s

I gratefully acknowledge the support and patience of Paula

Gongalves, my wife, during the extended period of time it took to complete this thesis. Dr. J. D. McPhail supervised the thesis project with competence and wisdom. Drs. K. Hyatt, J. Myers, and

W.E. Neill provided useful input and guidance as committee members. Many early conversations with K. Hyatt were useful in the genesis and initial stages of the thesis project.

Assistance with equipment and field surveys was provided by

James Baxter, Leonard Ghan, Paula Gongalves, Leonardo Huato,

Chantal Ouimet, D.P. Rankin, Lynda Ritchie, Jordan Rosenfeld,

Lome Rothman, Ron Saimoto, Peter Troffe, and Olfe Zimmermann.

Research funding was provided by NSERC research grants to

Dr. J.D. McPhail, FOC Salmonid Enhancement Program funding to Dr.

K.D. Hyatt, a Provincial Fisheries grant, and NSERC postgraduate scholarships. Dr. K.D. Hyatt provided for the use of some FOC field equipment. 1

Chapter 1 General Introduction

Many pelagic organisms migrate vertically between shallower water at night and deep water during the day. Reverse vertical migrations (between deep water at night and shallower water during the day) are also observed. The literature on such vertical migrations is extensive and dates back more than a century (Ringelberg 1993). In this thesis I investigate three questions concerning vertical migration as an adaptive behaviour: what is the benefit of vertical migration, is there a cost to this behaviour, and is migration behaviour of individuals fixed or a flexible response to environmental factors that affect the benefit or cost? I have studied the vertical migrations of a freshwater lacustrine copepod, Skistodiaptomus oregonensis

(Pennak - formerly Diaptomus oregonensis). In this chapter, I review the background literature, outline the study system, and describe the research strategy.

Hypotheses concerning the adaptive nature of vertical migration

There are several hypotheses about the benefits of vertical migration (for reviews see Kerfoot 1985, Bayly 1986, Haney 1988,

Lampert 1989), and different selective factors may operate in different situations (eg. Bayly 1986). Three hypotheses that apply to lake dwelling zooplankton are described below.

One hypothesis, the foraging efficiency hypothesis, argues that vertical migration maximizes feeding rates. Alewives

(Janssen and Brandt 1980) and freshwater sardines, Limnothrissa miodon (Begg 1976) track the movements of their vertically migrating zooplankton prey. Carrillo et al. (1991) suggest that phytoflagellates migrate to follow nutrient patches generated by the excretions of similarly migrating herbivorous zooplankton. Heuch et al. (1995) propose that the parasitic copepod salmon louse, Lepeophtheirus salmonis, undertakes reverse migrations that are the opposite of their salmonid hosts to increase encounter rates with the host at dawn and dusk. A second hypothesis is the metabolic efficiency hypothesis. This hypothesis contends that growth benefits are attained by spending part of the day in deep water where cold temperature lowers the metabolic rate. Brett (1983), modelled the metabolism of sockeye salmon and suggested that vertical migration allows a larger fraction of ingested energy to be allocated to growth. McLaren (1963) proposed that migrating zooplankton move down into colder water to process food acquired at the surface and that this results in a decease in their mean metabolic rate. This, in turn, causes an upward shift in the equilibrium size at which intake rate equals metabolic rate and, thus, a larger body size and greater fitness through higher fecundity. Neither of these two hypotheses excludes the other, and a vertical migration strategy could be selected through growth maximization resulting from the combined effects of both depth- dependent foraging and metabolic rates. Bevelhimer and Adams (1993) describe a growth model for kokanee salmon in which vertical migration produces the highest growth through such combined effects. Enright (1977) and Enright and Honegger (1977) propose that zooplankton gain the greatest net energy through feeding at the surface at night when algae are more abundant, and 3 of higher quality, which increases feeding efficiency, and then moving to depth during the day to minimize metabolic costs. The third hypothesis is the predator avoidance hypothesis. This hypothesis argues that vertical migration is undertaken to decrease predation risk near the surface during daylight when diurnally foraging visual predators are active (Lampert 1993). Similarly, the reverse vertical migration could be to avoid nocturnal, surface-dwelling predators. Recent field comparisons and experiments provide support for the predator avoidance hypothesis for many species (Luecke 1986, Bollens and Frost 1989a, Bollens and Frost 1989b, Levy 1990, Neill 1990, Ohman 1990, Stirling et al. 1990, Tjossem 1990, Wright and Shapiro 1990, Bollens and Frost 1991, Dini and Carpenter 1991, Ringelberg 1991a, Ringelberg 1991b).

Opportunity cost of predator avoidance Food resources are often concentrated near the lake surface and vertical migration away from the surface to avoid predators or high temperature may thus result in a cost of lost feeding opportunity (Huntley and Brooks 1982, Dagg 1985, Gliwicz 1985, Johnsen and Jakobsen 1987, Pijanowska and Dawidowicz 1987, Gabriel and Thomas 1988, Mangel and Clarke 1988, Lampert 1989, Guisande et al. 1991, Dini and Carpenter 1992). There is some indirect evidence for such a cost. Field observations of Neocalanus plumchrus (Dagg 1985) and observations on Calanus pacificus in large deep marine water tanks (Huntley and Brooks 1982) and Daphnia in enclosures (Johnsen and Jakobsen 1987) all indicate that low food abundance is correlated with a decrease, or cessation of, downward migration during the day. These findings are consistent with the interpretation that vertical migration to depth results in a feeding opportunity cost and that as food becomes scarce, the cost becomes too high relative to the benefits and the organisms remain near the surface. Students of the relationship between diurnal feeding rhythms and diurnal vertical migration have variously argued both for and against a feeding opportunity cost. Some authors (eg., Gauld 1953) found that zooplankton do not feed if they vertically migrate to deep water during the day, but do feed over the entire diurnal period if they remain at the surface. Others find that the diurnal feeding rhythms persist whether migration occurs or not (eg., Stearns 1986). This suggests that migration and feeding rhythms are independent behaviours.

Fixed or flexible vertical migration Vertical migration patterns can vary among populations of a species (Neill 1992, Stewart and Sutherland 1993), over time within a population (Ohman 1990, Frost and Bollens 1992, Hays et al. 1995), and, at a given time, among individuals within a population (Stirling et al. 1990). The migration pattern of each individual may be fixed and differences among individuals may be due to different genotypes. If so, the various genotypes exist due to selective pressures that vary among habitats or that fluctuate over time in the same habitat. Alternatively, the variation in migration patterns could be due to flexible behaviour of individuals in response to different conditions both internal (hunger or energy) and external (predation risk) that 5 vary across time and place. Whether flexible or fixed vertical migration behaviour evolves may depend on the particular environmental conditions. Inducible defenses should evolve when predation risk varies unpredictably, when the time necessary to acquire the defensive trait is brief relative to the fluctuation in threat, when the fitness cost of maintaining the machinery to produce the induced defence does not exceed the benefits of the induced defence, when reliable and non-fatal cues are available, and/or when the fitness costs of defence offset some of the benefits of the defence (Harvell 1990, Pijanowska 1993). Recent experiments indicate that zooplankton migration is a flexible behaviour induced by the presence of predators, or predator cues, and suppressed when predators or their cues are absent. Examples include Acartia hudsonica avoiding stickleback predation (Bollens and Frost 1991), Daphnia avoiding fish predators (Dini and Carpenter 1992), Daphnia avoiding Chaoborus (Ramcharan et al. 1992), Diaptomus kenai avoiding Chaoborus (Neill 1990), and Chaoborus avoiding fish predators (Tjossem 1990 and Dawidowicz et al. 1990). Decreases in migration associated with decreases in food abundance (Huntley and Brooks 1982, Dagg 1985, Johnsen and Jakobsen 1987) suggest flexibility in migration behaviour as a response to foraging opportunities. Flexible migratory responses to predator abundance and food availability would be especially advantageous relative to fixed behaviour when there are costs associated with the behaviour.

There is evidence for within population genetic differences in the migration of zooplankton. For example, protein gel electrophoresis indicates five common genotypes in a Daphnia population (Stirling et al. 1990). One genotype was much more abundant in the hypolimnion during the day. This genotype was also most abundant in the winter and may be adapted to both cold water and low oxygen conditions. Another example are Daphnia magna clonal lines. Lines isolated from different populations showed genetically distinct phototactic responses (De Meester and

Dumont 1988) . Some clones were photopositive, others photonegative, and a third type were "gypsies" that migrate continuously between low and high light intensity environments.

Although these three types were isolated from different populations, clonal lines isolated from within a population also showed different vertical distributions in a vertical light gradient set up in aquaria (De Meester and Dumont 1989).

These same authors demontrated combined genetic (fixed) and environmental (flexible) effects on vertical distribution in

Daphnia. The amount of food supplied to each clonal line during culture affected their vertical distribution, and there was a significant interaction between clonal line and food supply effects. One clonal line isolated from a different population remained photonegative at all times, and never migrated upward at any feeding level. Similarly, Dodson (1990) showed that depth distribution responses to predators varied for different species of Daphnia collected from different lakes.

Study system

My investigation of vertical migration behaviour focusses on migratory populations of S. oregonensis in Kennedy and Paxton 7 lakes and on non-migratory populations from Great Central and

Hobiton lakes. These lakes provide a system to consider alternative hypotheses concerning the benefits of vertical migration, and to investigate the potential costs of this behaviour. Because all four lakes are located in south coastal

British Columbia they are easy to access, and are subject to similar climatic conditions. This facilitates comparison. The relatively simple aquatic communities and trophic structure in these lakes also simplifies analysis of potential species interactions. Low productivity in these lakes may select for vertical migration to maximize foraging and/or metabolic efficiency and if there are feeding opportunity costs associated with vertical migration they should be detectable.

Alternatively, predation pressure is potentially high on zooplankton in these lakes from feeding by juvenile sockeye

Oncorynchus nerka, stickleback Gasterosteus aculeatus, Neomysis mercedis, and phantom midge Chaoborus. High predation may select for vertical migration as a predator avoidance strategy.

Another advantage of studying these lakes is that Fisheries and Oceans Canada (FOC) research on the limnology and fish community composition in Kennedy, Great Central, and Hobiton lakes provides the background information necessary for interlake comparisons and modelling.

Research strategy

In Chapter 2, I use a comparative approach to evaluate the three hypotheses for the benefits and costs of vertical migration. I attempt to correlate interlake differences in 8 migration patterns with the density of predators, food abundance and distribution, temperature, and other environmental factors predicted by the various hypotheses to affect the benefits of vertical migration. I also compare the diurnal feeding rhythms of migratory and non-migratory S. oregonensis to test predictions made by the hypothesis that vertical migration results in a feeding opportunity cost.

In Chapter 3, I test the corollary of the predator avoidance hypothesis that vertical migration results in a decrease in the risk of predation by three potential predators (stickleback, juvenile sockeye, and Neomysis mercedis). This is accomplished by relating the timing and extent of vertical migration of S. oregonensis in Kennedy and Paxton lakes to estimated spatial- temporal distributions of predation risk from each predator. In

Chapter 4, I use laboratory experimental manipulations and field data to test whether individual S. oregonensis exhibit changes in vertical migration behaviour in response to changes in predation risk.

In Chapter 5 I use a theoretical dynamic optimization model, incorporating both a visual predation risk model and a bioenergetic growth model, to explore whether S. oregonensis vertical migration in Kennedy Lake can be represented quantitatively and realistically as a trade-off between maximizing feeding and minimizing predator risk. In Chapter 6, I summarize my work, attempt to place it in context, and outline further research opportunities. 9 Chapter 2

Testing hypotheses on the benefits and costs of vertical migration by Skistodiaptomus oregonensis by comparing populations

Introduction

Several hypotheses have been advanced to explain the adaptive significance of vertical migration by zooplankton

(reviewed by Kerfoot 1985, Bayly 1986, Lampert 1989). One, the predator avoidance hypothesis, proposes that migration to deeper, darker water during the day reduces vulnerability to diurnally foraging visual predators (Lampert 1993). Assuming food is less concentrated in deeper water, there may be a feeding opportunity cost associated with vertical migration to avoid predators. An alternative hypothesis, the bioenergetic hypothesis, proposes that cooler temperature in deeper water reduces metabolic costs and, thus, increases growth. A third hypothesis, the foraging efficiency hypothesis, argues that vertical migration increases food intake by following a migrating prey resource. If the metabolic advantage of residing in cool water during the day is coupled with higher energy intake rates when feeding at night (or during the crepuscular period when prey are more concentrated or of higher quality), there may be a combined foraging/bioenergetic benefit.

In this chapter I evaluate these hypotheses concerning the benefits and costs of vertical migration of the zooplankter

Skistodiaptomus oregonensis by comparing populations in four coastal lakes in British Columbia. Such interpopulation comparisons of copepods in lakes with relatively simple 10 vertebrate and invertebrate communities provide an opportunity, within the natural environment, to look for associations between vertical migration and factors hypothesized to affect benefits and costs.

Methods

Zooplankton Field Collections

The four study lakes are located in southwestern British-

Columbia (Fig. 2.1). Samples were collected at deep offshore locations in each lake (Fig. 2.2-2.5). To determine the vertical distribution of zooplankton in Kennedy, Great Central, and

Hobiton lakes zooplankton samples were collected simultaneously in each lake at 7 sample depths by towing conical 100 um nitex mesh plankton nets attached at intervals along a single rope.

Each net was 108 cm long with a 15 cm diameter opening. Tows were 20 minutes in duration at a speed of 50 cm per second.

During a tow, an angle of 50 degrees from the horizontal was maintained. A maximum of 40 seconds passed from the time the first net was released into the water until all nets were in place at the towing depth. Retrieval of the nets required a maximum of 1 minute. Thus, relative to the amount of water filtered from the sample depths, nets filtered only small volumes of water during descent and retrieval. Trigonometric calculations were used to estimate sample depths of 1, 3, 5, 7,

10, 17, and 24 m, assuming no curvature in the tow line.

Weighted mean depths (WMD) for S. oregonensis were calculated Fig. 2.1: Location of the four study lakes in southwestern British Columbia. Fig. 2.2: Map of Great Central Lake showing sample location (X) and lake contours in meters. Depth contours taken Rutherford etal. (1986). Fig. 2.3: Map of Hobiton Lake showing location of sample site (X) and lake contours in meters. Other details as in Fig. 2.2.

Fig. 2.5: Map of Paxton Lake showing location of sample site (X) and depth contours in meters. Other details as in Fig. 2.2. 16 from the stratified samples as

WMD= ^ n±Lid± , (2.1)

3 where nL is the abundance (individuals per m ) in the depth interval Ai with midpoint di (Osgood and Frost 1994). Borders between depth strata were defined as midway between subsequent sample depths. The total number of individuals within each stratum (TJ is expressed as the number under aim2 surface area and was estimated as

2i=i2iAi (2.2)

A depth sounder was employed from a second boat during one deployment of the sample nets to determine the exact depth of each net. Analysis of the echograms indicates a slight overestimate (1-2 m) of the depth of the deepest two sample nets.

The resulting bias in the calculations is too small to affect the overall patterns observed or conclusions drawn.

To track changes in S. oregonensis vertical distribution during dawn and dusk in Paxton Lake a series of vertically stratified zooplankton hauls were collected for the 9-5, 5-3, and

3-0 m strata. The strata were sampled from deepest to shallowest in rapid succession over approximately 8-12 minutes with a closable double-ringed Wisconsin-style 100 um nitex mesh plankton net 292 cm in length with a 55 cm diameter opening. A 20 minute interval separated the start of one series of stratified samples 17 and the start of the next series. Upon retrieval, samples were preserved in a solution of 4% sugared formaldehyde. In the laboratory, a subsample of each sample was counted under a Wild M-5 microscope. Species were identified using the key in Pennak (1989). Each sample was sub-sampled until either

100 S. oregonensis were counted or until the entire sample was counted. For some sample dates, subsampling ceased before counting 100 S. oregonensis. This happened when the subsample volume exceeded 10 times the volume required to count 100 S. oregonensis from samples at the other depths from the same sample tow. When lengths were measured these were recorded with an automated micro-computer based digitizer system described in Roff and Hopcroft (1986). Metasome lengths are used in most size class analyses because metasome length can be measured with greater accuracy than total length.

Measuring food available to SL_ oregonensis

To estimate the depth distribution of food available to S. oregonensis in the study lakes, I determined the concentration of chlorophyll a extracted from the 3-50 um size fraction of phytoplankton in lake water from discrete sample depths. This size fraction approximates the size of particles selected by S. oregonensis in feeding experiments on lake seston (Vanderploeg 1990) and lake phytoplankton (McQueen 1970). In my samples, lake water was first passed through a 50 um nitex mesh to remove larger particles. A measured volume (3 00-1000 ml) of the remaining filtrate was passed through a Poretics Corporation 47 mm diameter, 3 um polycarbonate membrane filter. The membrane 18 was placed in a petri dish, frozen on dry ice, and retained in the dark. Within one week of collection, chlorophyll a and phaeopigment were extracted and measured with a Turner model 10- AU spectrofluorometer and following the procedure described by Parsons et al. (1984). Weighted mean depth of chlorophyll a depth distributions were calculated using the same method used for zooplankton (equation 2.1). This estimate of available food does not include non- fluores'cing alternative food sources (e.g., ciliate protists, heterotrophic flagellates, and fine particulates; Stoecker and Capuzzo 1990, Gifford and Dagg 1991, Hartmann et al. 1993, Ohman and Jeffrey 1994, Cervetto et al. 1995). Presumably, in freshwater, these alternative prey are more abundant near the surface than below 10 m since marine ciliates are found almost exclusively within 5 m of the surface (Jonsson 1989).

S. oregonensis gut pigment analysis

To estimate feeding activity at the time of collection, the quantity of chlorophyll a and phaeopigment in the guts of field caught S. oregonensis was determined in Kennedy and Great Central lakes. To compare gut pigments across depth, zooplankton were collected from discrete depths with the horizontal tow method described earlier. To measure changes in gut pigment during dawn and dusk and, to compare day versus night gut pigments, vertical hauls from 24 m to the surface were made with the Wisconsin-style plankton net described above. On capture, S. oregonensis were collected onto 8 X 8 cm pieces of nitex mesh, placed in petri dishes and frozen on dry ice. In the laboratory, 19 samples were thawed in tap water and 10 individual adult S. oregonensis were randomly selected, rinsed in distilled water, and, for chlorophyll a extraction, placed into 5 ml of 90% acetone and stored overnight in the dark at 5°. Chlorophyll a and phaeopigment concentration in the extract were determined using the same method used for lake water chlorophyll a samples.

Results

Vertical distributions of S_^_ oregonensis and phytoplankton food resources in the study lakes-

Kennedy Lake and Paxton Lake both contain migratory populations of S. oregonensis. In Kennedy Lake all size classes of S. oregonensis larger than 450 um were consistent vertical migrators on all survey dates. Typical day and night vertical distributions for discrete size classes are displayed in Figure

2.6 and Figure 2.7. Mean depth of S. oregonensis in the 750-850

Vim metasome length class (Fig. 2.8A) was significantly deeper during the day than at night in samples from 1992 to 1994 (paired sample t-test: t=12.805, P<0.001, n=13).

The mean depth for the distribution of the 3-50 um size fraction of phytoplankton in Kennedy Lake is consistently located near the surface (Fig. 2.8B) and does not differ significantly from day to night (paired sample t-test: t=2.127, 0.10>P>0.05, n=8). Except in winter, when abundance is an order of magnitude lower and the phytoplankton are homogenously distributed down to

24 m (Fig. 2.9), the 3-50 um size fraction is consistently most abundant above 10. meters. During summer stratification, phytoplankton densities decline above the base of the 20

Fig. 2.6: Day (hatched bars) and night (solid bars) vertical distribution for 5 metasome length classes of S. oregonensis in Kennedy Lake on August 25, 1993. Densities are point estimates at the depths indicated on the vertical axis. Fig. 2.7: Day (hatched bars) and night (solid bars) vertical distribution for 5 metasome length classes of S. oregonensis in Kennedy Lake on November 12, 1992. 22

0 Nigh: 5 10" Q. 0) 15 Q 20

15-Jul-92 31-Jan-93 19-Aug-93 07-Mar-94 23-Sep-94 15-Jul-92 31-Jan-93 19-Aug-93 07-Mar-94 23-Sep-94

S. oregonensij Chlorophyll a

10fc 1c j| O O sz 8" 151 Q. Q 0) 15 P o o o o Q O mean day depth 201 o o oo 20 • mean night depth o o o 25 25" 15-Jul-92 31-Jan-93 19-Aug-93 07-Mar-94 23-Sep-94 15-Jul-92 31-Jan-93 19-Aug-93 07-Mar-94 23-Sep-94

Fig. 2.8: A) Mean day and night depth of 750-850 um metasome length S. oregonensis in Kennedy Lake on 13 sample dates from 1992-1994. B) Mean day and night depth of 3-50 um size fraction of phytoplankton in Kennedy Lake from 13 sample dates from 1992 to 1994. C) Data in part A and B redrawn to compare mean day and night depth of S. oregonensis with mean day and night depth of 3-50 um size fraction of phytoplankton. Error bars in A and B indicate standard deviations for each depth distribution. 23-Jul-92 12-NOV-92 24-Feb-93 14-Apr-93 13-May-93 23-Jun-93 1 3 CO 5

CD 7 c 10 1111111 Q. 17 m CD Q 24 1 —I 1 1 1 1 0 0.4 0 0.31 0 0.071 o 0.45 0 0.41 0 0.5

16-Jul-93 26-Aug-93 20-Oct-93 5-May-94 11-Jun-94 12-Jul-94

1 1 3

cti 5 i$Sm!fl$HtHtt! CD 7 •4—» C 10 Q. 17 CD Q 24 —i 0 0.3 0 0.51 0 0.38 0 1.1 0 0.62 0 1.0 Chlorophyll a (|jg/l)

Fig. 2.9: Vertical distribution of chlorophyll a from the 3-50 urn size fraction of phytoplankton on 12 sample dates in Kennedy Lake. All samples shown were taken during daytime except for July 12, 1994. 24 thermocline, which lies close to, or slightly below, 10 meters (Fig. 2.10). In spring, despite the absence of a strong thermocline, phytoplankton densities decrease at similar depths.

S. oregonensis migrate from a daytime depth below the thermocline where phytoplankton are less abundant to a night depth that is at or above the thermocline which brings them into close proximity to their phytoplankton food resource (Fig. 2.8C). Across sample dates from 1992-1994, mean daytime depth of S. oregonensis is significantly below the mean daytime depth of phytoplankton (paired sample t-test: t=9.757, P<0.001 ,n=ll); while at night, mean depth of S. oregonensis rises and does not differ from mean depth of phytoplankton (paired sample t-test: t=1.206, 0.5

Migration of S. oregonensis in Paxton Lake has been observed by biologists collecting zooplankton for laboratory experiments (Dolph Schluter, Department of Zoology, University of British Columbia, pers. comm.). These observations are verified by my samples. S. oregonensis is absent from strata above 12 meters during the day, rises to upper strata at dusk and then descends below 12 m again at dawn (Fig. 2.11 and Fig. 2.12). As in Kennedy

Lake, S. oregonensis migrate from daytime depths where food is less abundant to where food is more abundant in surface waters at night (Fig. 2.13). The density of phytoplankton in the 3-50 um fraction varied little from day to night. It peaked between approximately 5 to 11 meters and was somewhat lower both nearer the surface and below 11 meter to the bottom at 15 m.

Although S. oregonensis populations in both Kennedy and Paxton lakes are migratory, those in Great Central and Hobiton 0 10 20 30 0 10 20 30 Depth (m) Fig. 2.10: Depth distribution of temperature (open circles) and of chlorophyll a from the 3-50 um size fraction of phytoplankton day (open squares) and night (solid squares) on six sample dates. 0 15 30 I I I 3 2 # Diaptomus*10/ m 0.0-4.0 i i

CO > 4.0-9.0 CD i c I

CL CD 9.0-12.0 1

-1 1 1 1 3:10 3:50 4:30 5:10 5:50 Local Apparent Time

Fig. 2.11: Changes in density of S. oregonensis in three depth strata of Paxton Lake during dawn of August 19, 1994.

tSJ en 0 15 30 1 I I 3 2 # Diaptomus*10/m 0.0-4.0 I llll

CO 4.0-9.0 CD •»—• I I c I I I I

Q_ 0 9.0-12.0 Q PI J JI Ji

1 I I ~i r -1 r -I— 18:20 19:00 19:40 20:20 21:00 Local Apparent Time

Fig. 2.12: Changes in density of S. oregonensis in three depth strata of Paxton Lake during dusk of August 19, 1994.

M —I 28

4 3 2 1 0 1 2 3 4 Chlorophyll a (ug/l)

Fig. 2.13: Day and night vertical distribution of chlorophyll a from the 3-50 pm size fraction of phytoplankton in Paxton Lake, August, 1994. 29 lakes are not. Typical distributions of 5 size classes are shown for two sample dates in Figure 2.14 and Figure 2.15. In Great

Central Lake, the means of depth distributions of S. oregonensis in the 750-850 um metasome length class did not differ day versus night (Fig. 2.16A; paired sample t-test: t=0.552, P>.5, n=6). Vertical distributions in Great Central (Fig. 2.16A) were more variable both between and across dates, compared to Kennedy Lake (Fig. 2.8A). During February, April, and May sampling in

1993, when S. oregonensis densities were extremely low, a significant proportion of the population were found in the 17 and 24 m strata either during the day, during the night, or at both times. These results are not an artifact of low sample size: at least 40 S. oregonensis were counted at the depth of maximum density for each of these distributions. Neither the day nor night distributions were-consistently deeper. The 3-50 um size fraction of phytoplankton was also at the surface with no significant difference in mean depths between day and night (Fig. 2.16B; paired sample t-test: t=2.086, 0.2>P>0.1, n=5). Figure 2.16C illustrates the similar mean depth of S. oregonensis and the 3-50 um size class of phytoplankton both day and night.

In Hobiton Lake all sizes of S. oregonensis were non- migratory. Most individuals in all size classes remained at the surface both day and night (Fig. 2.17 and Fig. 2.18). The depth distribution of both large S. oregonensis and the 3-50 um size fraction of phytoplankton were near the surface day and night (Fig. 2.19). 30

1 3 , _ 5

sz 7 Q. CD 10 Q 17 450-550 um 24 40 20 0 20 40 60 t # individuals/m'

899999999993

B99999999]

650-750 um •

60 0 60 # individuals/m # individuals/m

# individuals/m

Fig. 2.14: Day (hatched bars) and night (solid bars) vertical distribution for 5 metasome length classes of S. oregonensis in Great Central Lake on July 7, 1992. 31

# individuals/m # individuals/m

250 125 0 125 250 300 150 0 150 300

# individuals/m # individuals/m

40 20 0 20 40

# individuals/m

Fig. 2.15: Day (hatched bars) and night (solid bars) vertical distribution for 5 metasome length classes of S. oregonensis in Great Central Lake on August 18, 1992. 32

o- 5' 5 • 10- E, 10 • x: a. 15- Q. 15 • CD CD Q Q 20' 20 •

25' Day 25- Night

26-May-92 3-Sep-92 12-Dec-92 22-Mar-93 30-Jun-93 26-May-92 3-Sep-92 12-Dec-92 22-Mar-93 30-Jun-93

0 5 ^ 10 j= 15 H g 20 25 H Night

26-May-92 3-Sep-92 12-Dec-92 22-Mar-93 30-Jun-93 26-May-92 3-Sep-92 12-Dec-92 22-Mar-93 30-Jun-93

0' S. oregonensis Chlorophyll a 5' O 10- " 1 O E. o" E. n 15- ° • • Q. O mean day depth 03 CD 20- o Q Q • mean night depth 25- 25 26-May-92 3-Sep-92 12-Dec-92 22-Mar-93 30-Jun-93 26-May-92 3-Sep-92 12-Dec-92 22-Mar-93 30-Jun-93

Fig. 2.16: A) Mean day and night depth of 750-850/vm metasome length S. oregonensis in Great Central Lake on 7 sample dates in 1992 and 1993. B) Mean day and night depth of 3-50 um size fraction of phytoplankton in Great Central Lake from 7 sample dates from 1992 and 1993. C) Data in part A and B redrawn to compare mean day and night depth of S. oregonensis with mean day and night depth of 3-50 um phytoplankton. Error bars in A and B indicate standard deviations for each depth distribution. 33

500 250 0 250 500 400 200 0 200 400 # individuals/m # individuals/m

500 250 0 250 500 2000 1000 0 1000 2000

# individuals/m # individuals/m

250 125 0 125 250

# individuals/m

Fig. 2.17: Day (hatched bars) and night (solid bars) vertical distribution for 5 metasome length classes of S. oregonensis in Hobiton Lake on August 5, 1992. 34

# individuals/m # individuals/m

1 3

E 5

E 10 CD Q 17 I 660-795 um 24 1000 500 0 500 1000 3500 1750 0 1750 3500 2 2 # individuals/m # individuals/m

350 0 350 700 2 # individuals/m

Fig. 2.18: Day (hatched bars) and night (solid bars) vertical distribution for 5 metasome length classes of S. oregonensis in Hobiton Lake on June 25, 1992. 35

Diaptomus Chlorophyll a

June 25 August 5 June 25 August 5

Fig. 2.19: Day (open circles) and night (solid squares) mean depth of 660-795 um metasome length class S. oregonensis and the 3-50 um size fraction of phytoplankton on June 25 and August 25, 1992. Bars indicate standard deviations of the population distribution. 36

Biological and physical comparison of study lakes The physical conditions do not differ in any way that is consistent with the differences in migration behaviour of S. oregonensis (Table 2.1). Light extinction values for Great Central and Hobiton (no vertical migration) fall between those for Paxton and Kennedy Lake (vertical migration). Also, temperature and pH values do not distinguish lakes where S. oregonensis migrate from lakes where they do not migrate. S. oregonensis migrate in large and deep Kennedy lake, but also in small and shallow Paxton Lake. Non-migratory S. oregonensis are also found in both large and small lakes. In Great Central Lake, where juvenile sockeye density is the highest among the lakes (Table 2.2), S. oregonensis do not migrate. In Hobiton Lake, where juvenile sockeye are present they also do not migrate; however, in Kennedy Lake (where sockeye and stickleback are present) they migrate, and in Paxton Lake (which contains stickleback but no juvenile sockeye) they also migrate. Zooplankton biomass and primary productivity are similar in Kennedy, Hobiton, and Great Central Lake. The density of the 3-50 um size fraction of phytoplankton is also similar for Kennedy, Hobiton and Great Central lakes, although it is higher in Paxton Lake (Fig. 2.20). Among biological factors (Table 2.2), only the presence of pelagic stickleback distinguish the two lakes where S. oregonensis migrate from the two lakes where they do not. Table 2.1: Physical conditions in the four study lakes.

elevation area depth light compensation lake (m) (km2) (m) ext. depth (m) pH

no migration: Great Central 82 51 2121 .44 18.5 7.0 Hobiton 15 3.6 361 0.44 10.4 6.8

migration: Kennedy 4 64 331 .38 12 .3 7.1 Paxton 61 0.162 162 501 unknown unknown

-"•mean depth 2maximum depth Table 2.2: Biological conditions in the four study lakes.

limnetic2 limnetic2 zooplankton annual sockeye stickleback biomass primary density density (mg dry production lake temp.1 (103/ha) (103/ha) wt/m3) (g C/m2)

no migration: Great Central 18.4 1.356 03 9.0 18.9 Hobiton 17 .8 0.775 0 11.0 28.7

migration: Kennedy - 18.1 0.555 0.957 5.4 16.5 Clayoquot Arm Paxton max=23 present4 unknown unknown

xmean temp. June 1 and Sept. 3 0 at 1 m 2mean values for 10 annual estimates from 1986-1995 via hydroacoustic and trawl surveys in late fall to early winter (K. Hyatt, FOC, unpublished data). Hyatt et al. 1984 and Hyatt and Stockner 1985 may be consulted for details of survey procedures and analytical methods, respectively. 3although stickleback are present in both GCL and Hobiton, FOC surveys indicate their virtual absence from open water. 4see McPhail 1993

00 39

Great Central Kennedy Hobiton Paxton

Fig. 2.20: Mean concentration of chlorophyll a from the 3-50 um size fraction of phytoplankton in the 4 study lakes. Each point represents the mean all samples in the top 10 m averaged across sample dates. Bars represent 95% confidence intervals. 40

Body size and vertical distribution of S\_ oregonensis in Kennedy

Lake

Both mean daytime depth of S. oregonensis in Kennedy Lake (Fig. 2.21A), and the change in mean depth from night to day (Fig. 2.21B), increase with metasome length up to approximately 450 um. Beyond this size there is little, if any, further effect. S. oregonensis in size classes 375 and 425 um are highly variable in mean daytime depth between sample dates and show considerable change in mean depth from night to day on some dates and not on others, although the change is not as great as it is for the larger size classes. Vertical distributions both day and night of small metasome length classes of S. oregonensis in Kennedy Lake for two dates are displayed in Figure 2.22 and Figure 2.23.

Gut pigments and diurnal feeding patterns of migratory and non- migratory oregonensis

Migrating S. oregonensis from Kennedy Lake contain more chlorophyll a and phaeopigment in their guts at night than during the day, while the non-migrating Great Central Lake population showed no diurnal feeding rhythm (Fig. 2.24). Within Kennedy Lake, daytime gut pigments decreased with the depth at which S. oregonensis were captured (Fig. 2.25). Gut pigments of the migrating Kennedy Lake population increase at dusk, the time of migration toward the surface, and decrease again at dawn at the time of descent. Non-migratory Great Central Lake S. oregonensis show no such pattern (Fig. 2.26 and Fig. 2.27) . 41

•ZP • CO c5 CP 20 - • EP Cl • • "=tb • • • Cl Q. CP • CD • cP • "D 15 - • cF Cl CD • E • cF CD • CO cP • "D 10 • • • C CO • CD CP • • • •

CP • «=*=• cP a 0 200 300 400 500 600 700 800 900 1000

c CD E CD O _cd CL w .c ••—> CL CD TJ c CO CD

200 300 400 500 600 700 800 900 1000 Length class midpoint (pm)

Fig. 2.21: Top: S. oregonensis weighted mean daytime depth versus metasome length classes in Kennedy Lake. Bottom: Difference between weighted mean daytime depth and weighted mean night time depth for each sample date. Positive differences indicate greater daytime mean depth. Depth (m) Depth (m) Depth (m) 43

1 S66666666&J466666666664J 1 >66663 3 3 5 5 7 7 'yyyyyyyyvyi 10 CL Q. 10 <250 urn CD 17 CD 17 250-300 um Q Q 24 24 30 15 0 15 30 200 100 0 100 200 f # individuals/m # individuals/m'

1 xxxxxxxxxxxxxxxxxxxxxxxi 1

AAAAAAAAA/yVvl 3 ^ 3 SAAAAAAAJ 5 £ 5 >W^AJtXXJl 7 CL CD 10 o 10 XXXXXXXXXXXJ

Q Q 17 300-350 Lim 17 350-400 um • 5553 24 24 • 320 160 0 160 320 360 180 0 180 360 # individuals/m' # individuals/m

3 XXXXXXXXJ 5 Q. CD 7 Q VVVVVVVAVVVVS/VVVWWVS 10 • .AAXAAAAAAAAAAAAAAAAAAA^ 17 400-450 um 24 340 170 0 170 340 # individuals/m'

Fig. 2.23: Day (hatched bars) and night (solid bars) vertical distribution for 5 small metasome length classes of S. oregonensis in Kennedy Lake on November 12, 1992. 44 0.8

0.7-

Night Day

Fig. 2.24: Day versus night gut pigments in S. oregonensis in Kennedy Lake (solid square) and Great Central Lake (open squares) on May 11-13, 1993 (top), June 22-23, 1993 (middle), and July 15-16, 1993 (bottom). Each point represents the mean of 10 mature individuals. Lines join grand mean at each time within each lake. 45

0 10 15 20 25 Depth (m)

10 15 Depth (m)

Fig. 2.25: Daytime S. oregonensis gut pigments versus depth on June 23, 1993 (top) and July 16, 1993 (bottom). Each point represents the mean of 10 individuals. Fig. 2.26: S. oregonensis gut pigment changes at dawn and dusk in Great Central Lake and Kennedy Lake, August 25-27, 1993. The dashed vertical lines indicate time of sunrise and sunset. Each point represents the mean of 10 individuals. 47

Fig. 2.27: S. oregonensis gut pigment changes at dawn and dusk in Great Central Lake and Kennedy Lake, October 17-20, 1993. Other details as in Fig. 2.26. 48

Relationship between weighted mean depth of oregonensis and chlorophyll a concentration in Kennedy Lake

The mean daytime depth of S. oregonensis in Kennedy Lake tends to decrease with decreasing mean chlorophyll a concentration from the 1,3, 5, and 7 meter depth (Fig. 2.28). If the two outliers (Jn93 and My94) are removed the mean chlorophyll a concentration in the 1, 3,5, and 7 m samples explains 61% of the variation in the mean depth of S. oregonensis and the least- squares linear regression is significant (P < .02).

Discussion

The adaptive benefit of vertical migration The only factor examined that distinguishes the two lakes in which S. oregonensis vertically migrate from the two in which they do not migrate is the presence of pelagic sticklebacks in the former. This is consistent with the hypothesis that the ultimate selective force for S. oregonensis vertical migration is avoidance of stickleback predation. If juvenile sockeye predation was driving vertical migration, migrations would be expected in Great Central Lake, where juvenile sockeye density is more than twice that of Kennedy Lake, and migrations would not be expected in Paxton Lake where there are no juvenile sockeye (Table 2.1). If foraging efficiency were the selective advantage for vertical migration, food abundance or food distribution should differ between the lakes where migration occurs and those where migration does not occur. However, neither food abundance nor food distribution separate lakes where S. oregonensis migrate from lakes where they do not migrate. In the same vein, under 49

-12 Jn93

-14 -j

-16

Q. CD •o CD -18 E JI92NV92 -I—» pLgo My93 co ~o -20 JI93 c JI94 My94 co CD Au93 -22 Oc93

Ap93 Jn94 -24 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 Mean chl a in top 10 m (pg/l)

Fig. 2.28: Weighted mean daytime depth of S. oregonensis in Kennedy Lake versus mean chlorophyll a concentration of the 3-50 um phytoplankton size fraction in the top 10 m. Dates (month/year) indicated for each sample point. 50 the bioenergetic hypothesis, temperature profiles in the two classes of lakes would need to differ in such a way as to provide a temperature-dependent bioenergetic advantage for vertical migration in the lakes where migration occurs. However, temperature regimes are similar in all four lakes.

Recently, evidence has accumulated for predator avoidance as the selective force driving vertical migration in many zooplankton species (eg. Ohman 1990, Dini and Carpenter 1991, Bollens et al. 1992, Neill 1992, Bollens et al. 1994). Interlake comparisons demonstrating a positive relationship between migration and predation risk exist for Cyclops abyssorum (Gliwicz 1986) and Diaptomus kenai (Neill 1992). Schmidt et al. (1994) found greater migration of Cyclops sp. and Diaptomus sp. in lakes with higher predation risk, although the species of zooplankton in this study were not reported and they may not have been the same in different lakes. Stewart and Sutherland (1993) report a strong vertical migration of S. oregonensis in McCargo lake in contrast to weak or absent migration of S. oregonensis in Lime Lake in western New York State. Data on predation risk in these lakes is lacking.

Within populations, many studies show seasonal onset, or changes, in the intensity of zooplankton migration that correspond to changes in predation risk. Examples include Acartia hudsonica (Bollens et al. 1992), Calanus pacificus (Bollens and Frost 1989b), Diaptomus sanguineus (De Stasio 1993), Pseudocalanus newmani (Ohman 1990), Cyclops abyssorum, Mesocyclops sp., Eudiaptomus gracilis, Daphnia hyalina, and Bosmina sp. (Stich 1989). 51

Stickleback predation pressure

The hypothesis that stickleback predation drives vertical migration by S. oregenensis in Kennedy and Paxton lakes requires that pelagic stickleback present a significant predation risk. O'Neill and Hyatt (1987) demonstrated that sticklebacks in

Kennedy Lake prefer copepods, including S. oregonensis. Stickleback and juvenile sockeye, either in allopatry or sympatry, in their lake enclosures were strongly size-selective and decreased the mean size of zooplankton in the enclosures from approximately 450-550 um (total length) to between 190-330 um in less than one month. Mature S. oregonensis range in length from approximately 800 to 1200 um and are the largest zooplankton species in Kennedy and Paxton Lake, with the exception of

Neomysis mercedis (in Kennedy) and Chaoborus sp. (in Paxton). N. mercedis and Chaoborus are strong vertical migrators themselves that are deep during the day and, thus, remain unavailable to stickleback. Such size-selective predation may cause vertical migration in the larger individuals within a prey species but not in the smaller individuals (eg. Neill 1992, Osgood and Frost 1994, Angeli et al. 1995). My data indicate that the total distance of vertical migration by S. oregonensis does, indeed, decrease with size (Fig. 2.21). This size effect is apparent for metasome length classes less than about 450 um (625 um total length). In comparison, O'Neill and Hyatt (1987) found that size-selective stickleback predation cropped the mean total length of zooplankton from 450-550 um to 190-33 0 um in enclosure experiments in Kennedy Lake. Thus, we might expect that below 52 this size range (190-330 um) the strength of the vertical migration in S. oregonensis will decline.

Juvenile sockeye predation pressure

Juvenile sockeye are also size-selective zooplanktivores, capable of exerting considerable predation pressure. O'Neill and Hyatt (1987) report that the size-selective cropping effect of juvenile sockeye in Kennedy Lake enclosures was similar to that exerted by stickleback. In Alaskan lakes Schmidt et al. (1994) observed vertical migration of diaptomids where there were unusually high densities of juvenile sockeye, and no vertical migration in lakes where densities remained at lower, historical levels. Thus, it is surprising that juvenile sockeye, unlike the stickleback, do not seem to be driving vertical migration in my study lakes. This apparent paradox may be related to differences in the timing of the predation risk from the two predators. The available evidence indicates that stickleback are diurnal predators (Manzer 1976) and that juvenile sockeye are primarily crepuscular feeders (Narver'1970, Barraclough and Robinson 1972, McDonald 1973). In Chapter 3, I examine in detail the temporal- spatial pattern of predation by both sockeye and stickleback relative to the timing of vertical migration.

Vertical migration, feeding rhythms, and the cost of lost feeding opportunity

In zooplankton, diurnal feeding rhythms showing higher food intake at night often correspond with vertical migration from a deep daytime habitat (low food concentration) to a night-time 53 surface habitat (high food concentration). Examples include Calanus finmarchicus (Gauld 1953 and Simard et al. 1985), Calanus pacificus (Hassett and Landry 1988), and Calanus hyperboreus (Head et al. 1985). This suggests a direct cause and effect relationship between vertical migration and feeding - a corollary of the hypothesis that vertical migration results in a cost of lost feeding opportunity. Contrary evidence suggests that DVM and feeding are controlled separately. Feeding rhythms in the absence of vertical migration are reported for Acartia tonsa (Durbin et al. 1990), for Calanus hyperboreus and Calanus glacialis (Head et al. 1985), for marine copepods (Morales et al. 1993), for Pseudocalanus sp. and Centropages hamatus (Nicolajsen et al. 1983), and for Paracalanus parvus, P. crassirostris, Acartia erythraea, and Eucalanus subcrassus (Tang et al. 1994). Also, the timing of feeding rhythms does not always correspond with vertical migration movements (Dagg et al. 1989, Atkinson et al. 1992a, Tang et al. 1994). Feeding rhythms are known where migration depth ranges within a homogenous food distribution (Haney 1985, Stearns 1986, Mourelatos et al. 1989, Atkinson et al. 1992a, Bollens and Stearns 1992, Cervetto et al. 1995), although a lack of feeding rhythm under these same conditions also occurs (Haney 1985, Lampert and Taylor 1985, Mourelatos et al. 1989) .

In Kennedy Lake, S. oregonensis feeding rhythms correspond to movement between a surface habitat where food is abundant and a deep habitat where food is scarce, and the timing of vertical migration and feeding rhythm are the same. The contrasting 54 absence of a feeding rhythm in a non-migratory Great Central S. oregonensis population, and the fact that on some dates some

Kennedy Lake S. oregonensis remained at the surface and fed during the day, provides stong evidence that vertical migration is, in fact, the cause of the feeding rhythm in S. oregonensis.

Similarly, Angeli et al. (1995) found that large Daphnia migrated across a vertical food gradient and displayed a feeding rhythm, while small Daphnia and mature' Eudiaptomus migrated only within a zone of homogenous food and did not display a feeding rhythm.

Gibbons (1992) found that an offshore population of Sagitta serratodentata tasmanica migrating between a food rich surface zone and a food poor depth displayed a feeding rhythm, whereas an inshore population of the same species migrating within a homogenous food zone fed continuously. Perhaps, both vertical migration and the cessation of daytime feeding are separate, complementary strategies that reduce daytime predation risk and co-occur in environments where predation risk is high. The cessation of daytime feeding may decrease predation risk by reducing movement and gut pigmentation that attract predators (Bollens and Stearns 1992) . Further observations are required to test this hypothesis. Migrators that feed less during the day may compensate with increased night time food intake in such a way that total intake over the diurnal period is equal in migrators and non-migrators (Angeli et al. 1995). Higher levels of gut pigment at night in Kennedy lake relative to both night and day values in Great Central in May, June, July and August of 1993 (Figs. 2.24 and

Fig. 2.26) suggest that migrating S. oregonensis may compensate 55 for lower daytime feeding during the day by feeding more at night. However, this clearly does not occur in October (Fig. 2.27). Lower gut fluorescence in Great Central Lake S. oregonensis may also result from the ingestion of non-fluorescing food types or may indicate less available food. Knowledge of the temporal scale of cycles of hunger and satiation is necessary to evaluate whether spending part of the diurnal period away from food decreases overall food intake. Bimodal feeding rhythms with dusk and dawn feeding maxima and low rates of feeding in the middle of the night are known to occur in other zooplankton (e.g., Starkweather 1983, Baars and Oosterhuis 1984, Atkinson et al. 1992a, Atkinson et al. 1992b), and this suggests satiation after dusk feeding may last until dawn. In

Kennedy Lake, however, S. oregonensis gut fluorescence measured near midnight on October 17, 1993 (Fig. 2.27) is nearly as high as the highest mean value recorded post-dusk on that date. Large differences in gut fluorescence are also detectable in samples taken near midnight in comparison to daytime samples (Fig. 2.24). Furthermore, reported gut evacuation rates for zooplankton are short: 38 minutes for Acartia tonsa (Cervetto et al. 1995), 24 minutes for Calanus acutus (Atkinson et al. 1992b), 2-3 hours for Calanus finmarchicus (Simard et al. 1985), 100 minutes for

Metridia spp. and Pleuromamma spp. (Morales et al. 1993), 24.1 minutes for Acartia tonsa, (Durbin et al. 1990). Given a high gut evacuation rate, S. oregonensis likely need to feed continuously to maintain high gut pigments through the night. This suggests they do not remain satiated during the long day period away from surface food resources. 56

Effect of food availability on S\. oregonensis daytime vertical distribution

Johnsen and Jakobsen (1987) showed a significant decrease in the daytime depth of vertically migrating Daphnia longispina in response to an experimentally depleted food supply in enclosures, and argued that this was a reflection of the optimal strategy to balance a trade-off between feeding and predator avoidance. The mean daytime depth of S. oregonensis in Kennedy Lake also shows a tendency to decrease as food supply in the top 10 m decreased. Although these results must be interpreted with caution, as sample size is low and outliers were removed, they do provide some evidence for a feeding opportunity cost associated with vertical migration.

Fitness consequences of the feeding opportunity cost of vertical migration

Direct measures of a feeding opportunity cost as a result of vertical migration, expressed as changes in fitness (survival, growth, and/or reproduction), have not been demonstrated for zooplankton. Johnston (1990) showed that migrating kokanee salmon fry grew more slowly than non-migratory fry in experimental enclosures. In chapter 5 I present a model that explores potential effects of vertical migration on growth and reproduction of S. oregonensis.

Summary

The hypothesis that vertical migration by S. oregonensis is driven by stickleback predation is supported by the comparison of 57 lakes. Alternative hypotheses, including the avoidance of juvenile sockeye predation, foraging efficiency, bioenergetic efficiency, and combined foraging/bioenergetic efficiency are not consistent with the between lake observations. The stickleback avoidance hypothesis is also supported by enclosure experiments which indicate that stickleback depredate the same size classes of S. oregonensis that vertically migrate in Kennedy Lake. Juvenile sockeye also exert strong predation pressure, but may not drive vertical migration because they are crepuscular feeders rather than daytime feeders. Vertical migration appears to result in a feeding opportunity cost. Phytoplankton are less concentrated in the deep habitat where S. oregonensis reside during the day. Gut pigments are less during the day than at night in migratory

Kennedy Lake S. oregonensis, while gut pigments in non-migratory

S. oregonensis from Great Central Lake do not differ between day and night. Within Kennedy Lake, S. oregonensis near the surface during the day contain more gut pigments than individuals in deep water. The decline in mean depth of S. oregonensis as food abundance decreases also suggests a feeding opportunity cost. 58 Chapter 3

The Timing and extent of vertical migration by Skistodiaptomus oregonensis relative to the temporal-spatial distribution of predation risk

Introduction Daytime vertical migration of zooplankton from the bright, near-surface habitat has been proposed as a strategy to decrease the risk from light-limited visual predators (Mangel and Clarke 1988, Bollens and Frost 1989a, Angeli et al. 1995). The interlake comparison presented in chapter 2 supports the hypothesis that vertical migration by S. oregonensis in the study lakes is an adaptation to avoid predation by visually feeding sticklebacks. In this chapter, I test predictions concerning the pattern and timing of diurnal vertical migration that are corollaries of the stickleback avoidance hypothesis. Specifically, the light intensity at the depth where S. oregonensis are located during the day should reduce the feeding rate of sticklebacks relative to their feeding rate in surface waters. Secondly, the timing of the vertical movements of S. oregonensis at dawn and dusk should keep them at a light intensity which reduces stickleback feeding rate. Juvenile sockeye are present in three of the four study lakes and, although the data presented in chapter 2 do not support the hypothesis that juvenile sockeye predation drives vertical migration in S. oregonensis, Schmidt et al. (1994) suggest that unusual abundance levels of juvenile sockeye in Alaskan lakes produced a shift in copepod behaviour from no 59 migration to migration. Furthermore, an enclosure study in Kennedy Lake (O'Neill and Hyatt 1987) demonstrated that juvenile sockeye and stickleback are both size selective planktivores that can strongly impact the zooplankton community. Consequently, I also test predictions that are corollaries of a juvenile sockeye avoidance hypothesis. Namely, that the light intensity at the depth where S. oregonensis are located during the day results in a decreased feeding rate by juvenile sockeye (relative to their feeding rate in the surface waters), and that the vertical movement of S. oregonensis at dawn and dusk are timed to avoid juvenile sockeye predation.

Methods

Field measures of zooplankton vertical movements at dawn and dusk

To track the timing of vertical migration by S. oregonensis during dawn and dusk, time series of vertically stratified zooplankton tows were collected at 24-12 m, 12-5 m and 5-0 m depth intervals with a closable double-ringed Wisconsin-style 100 um nitex mesh plankton net (292 cm in length and with a 55 cm diameter opening). The three depth strata were sampled in rapid succession, from deepest to shallowest, over approximately 8-12 minutes. A 20 minute interval was maintained between the start of one set of stratified samples and the start of the next set. Immediately upon retrieval, samples were preserved in 4% sugared formaldehyde.

In the laboratory, all S. oregonensis larger than 800 um total length were counted under a Wild M-5 microscope. The subsampling methodology was described in chapter 2. In each 60 stratum, abundance was estimated as the number of S. oregonensis occurring under aim surface area (see chapter 2 methods). In

October 1993, a number of Neomysis mercedis were captured in Kennedy Lake and these were ennumerated in each stratum as well.

Field measures of vertical distribution of fish at dawn and dusk In the intervals between each set of vertical zooplankton hauls described above, hydroacoustic measurements of the depth distribution of fish targets were determined with a Furuno FM-22 200 KHz sounder with 100 watts power. The sounder was mounted on a hydroplane lashed into position at 1 m depth alongside a boat moving at approximately 0.5-1.0 m-s"1 (see Hyatt et al. 1984 for further details). The time varied gain circuit, which controls for spreading and attenuation losses of the acoustic signal with distance, was inoperative on the sounder. This likely resulted in a depth-dependent bias in the estimated density of targets but the data still provide a measure of the movement of targets across depth over time. Fish targets on the echosounder traces were counted to determine the mean number of fish targets per second in each stratum during each time interval.

Light measurements

Light extinction was determined near mid-day on each sample date by measuring light intensity just below the surface and at 1 m depth intervals with a Li-cor 186A light meter. Light 61 intensity at depth is given by:

kz Iz=I0*e- (3.1)

where Iz=light extinction at depth z, Io=light intensity at the surface, and k=light extinction coefficient. This equation was rearranged to:

lnl0-lnlz=kz (3.2)

and a least squares regression was fit to the field measurements of Io, Iz, and z to determine the light extinction coefficient, k. This estimate of k was used to calculate light intensity depth profiles during dawn and dusk sampling from measurements of

light intensity at the surface (ID) . This method assumes that the light extinction coefficient does not change as light intensity changes over the dawn and dusk period. Levy (1989 - his Figure 5-5) demonstrated that k did not change during crepuscular periods in Cultus Lake and Great Central Lake. Light intensity is measured in quantum units of microEinsteins • second"1-meter-2 (uE-s-1-m"2) . One Einstein is equivalent to one mole of photons.

Stickleback feeding rate experiment

Kennedy Lake sticklebacks were collected in minnow traps on May 21, 1995, transported to the laboratory, and held in a 208 1 holding tank illuminated by two 40 watt Vita-Lite full spectrum fluorescent lights placed 40 cm above the tank. An automatic switch turned the lights off at sunset and on at sunrise each 62 day. Once per day, the stickleback were fed live zooplankton collected from Shirley Lake and/or Marion Lake in the UBC Research Forest. Every 2 to 3 days the stickleback were fed thawed Tubifex worms. Shirley Lake zooplankton consisted mainly of Hesperodiaptomus kenai, fourth instar Chaoborus trivittatus and Aglaodiaptomus leptopus. Marion Lake zooplankton consisted mainly of mature S. oregonensis (779 um mean metasome length), S. oregonensis copepodites (410 um mean metasome length) and a cyclopoid copepod (440 um mean metasome length). Twenty-four hours before the beginning of experimental trials for each day, 11 fish were transferred from the holding tank to a 56 1 starvation tank. The experimental feeding unit consisted of an outer clear plexiglass tank measuring 30 x 58 x 38 cm into which was placed a 27 x 51 x 32 cm inner tank which consisted of clear plexiglass vertical walls and a porous 100 um nitex mesh bottom. Lake water filtered through a 50 um mesh was added to the experimental feeding unit to a volume of 40 1 in the inner tank. A piece of non-reflective black araldite was placed over the mesh bottom during the experiment to reduce reflection and to reduce contrast of prey against the bottom background. The exterior surface of the bottom and 3 of the 4 vertical walls of the outer tank were covered with brown packing paper over which was placed light impermeable black plastic. For observation, one of the larger vertical walls of the outer tank was left open, but covered from the outside by a large black cloth blind attached along the top edge of the open vertical wall by velcro®. The observer, wearing dark clothing, sat motionless between the blind and the open wall. This allowed the observer 63 to see into the tank and prevented background light from entering the tank through the open side wall. Each day, for 6 days, 11 individual fish were fed at 11 different light intensity treatments. For each trial, Marion Lake zooplankton were added to the experimental feeding unit and briefly mixed. Following this, a single fish was transferred from the starvation tank into the, inner tank of the experimental feeding unit. A sheet of plexiglass was placed over the top of the experimental chamber and, depending on the desired light intensity, 1 to 11 sheets of grey, plastic Permascreen light filters were placed on top of this plexiglass sheet. All fish commenced feeding within 2-10 minutes of placement in the experimental feeding unit. Once feeding behaviour had begun, the number of feeding strikes were recorded for 15 minutes. The fish was then removed, anaesthetized and killed in 95% ethanol, and then fixed in 4% formaldehyde. Zooplankton remaining in the tank were collected by removing the araldite sheet from the bottom of the inner tank, lifting the mesh-bottomed inner tank out of the outer tank, and rinsing the contents of the inner tank into a jar of 4% sugared formaldehyde.

Results

Stickleback feeding rate experiments The total density of zooplankton did not differ among light intensity treatments (Table 3.1), nor did the initial densities of each of six prey categories (Table 3.2). Within each day, the total density as well as the proportion of each prey type in the experimental tanks were approximately equal across treatments Table 3.1: ANOVA results testing HQ that initial zooplankton densities in experimental feeding tanks did not differ among light intensity treatments.

Source Sum of Mean DF Squares Square F Value P>F Treatment 10 53.096 5.310 0.19 0.9967 Error 55 1577.650 28.685 Corrected Total 65 1630.746 Table 3.2: ANOVA results for each prey type testing Ho that initial densities of the prey types did not differ among treatments. For prey type Treatment DF=10 and Error DF=55.

Treatment Error Mean Prey Type Mean Square Square F P>F cyclopoids 0.930 6.471 0 .14 0 .9989 large S. oregonensis 0 .419 3 . 076 0 .14 0 .9991 small S. oregonensis 0.292 9.029 0 .03 1 .0000 Bosmina 1.896 23 .523 0 . 08 0 .9999 large cladocerans 0.024 0.068 0 .35 0 .9629 small cladocerans 0.006 0.020 0 .29 0 .9817 66

(values for 2 days shown in Fig. 3.1 and 3.2). There were significant differences among days (Table 3.3, and Fig. 3.3).

Zooplankton density in the laboratory experimental tank treatments ranged from 18.8 to 3 6.7 per liter with a mean of

26.0. The daily means ranged from 21.6-31.8 per liter. These values are on the order of 4-5 times higher than local Kennedy

Lake zooplankton concentrations of 6.2 per liter (May 1995) and

6.4 per liter (October 1993) estimated from the highest densities in vertically stratifed zooplankton samples.

The Marion Lake zooplankton prey used in the experimental treatments are comparable to the prey available in Kennedy Lake.

All zooplankton present in a sample collected from Kennedy Lake in May of 1995 are represented by four groups that include bosminids, cyclopoids, large S. oregonensis (>800 um total length), and small S. oregonensis (<800 um total length). Marion

Lake contained these same groups in similar proportions as well as only a small number of various other cladocerans (Fig. 3.4).

Furthermore, the sizes of the prey taxa were very similar for all prey types (Fig. 3.5).

In the experiment, the number of prey per stickleback stomach, the number of S. oregonensis per stomach, the number of strikes, and the capture/strike ratio all increase over a light intensity range of 0.1 to 1.6 uE-s^-m"2. After a light intensity of 1.6 uE-s^-m"2 is reached there is no further light effect

(Figs. 3.6-3.9). Natural log transformations were performed for each variable (with the exception of the capture/strike ratio, for which the arcsine square-root transformation was used) and then separate least-squares linear regressions were performed 67

Fig. 3.1: Total zooplankton densities broken down by taxa or size categories in each of 11 treatments for experiment date June 5. 68

Treatments

cyclopoids i large S. oregonensis 1 1 small S. oregonensis II11II bosminids cladocerans

Fig. 3.2: Total zooplankton densities broken down by taxa or size categories in each of 11 treatments for experiment date June 7. 69

Table 3.3: ANOVA results testing Ho that initial zooplankton densities in experimental feeding tanks did not differ among days.

Sum of Mean Source DF Squares Square F Value P>F days 5 1340.017 268.003 55.31 0.0001 error 60 290.729 4.846 corrected total 65 1630.746 70

June 4 June 5 June 6 June 7 June 10 June 11

Experiment Date

Fig. 3.3: Mean zooplankton density across treatments for each experiment date. Vertical bars represent entire range of densities for each day. 71

0.7

Fig. 3.4: A comparison of the relative density of prey types in one of the experimental tanks (solid bar) and in Kennedy Lake (open bar) on May 20, 1995. 900

800 -

700 "

600 -

CD 500 N '(fi 400 H C 03 CD 300 ii 200 -

100 -

0 1 r bosminids cyclopoids large S. small S. other oregonensis oregonensis cladocerans

Fig. 3.5: A comparison of the size of prey types in one of the experimental tanks (solid square) and in Kennedy Lake (open squares) on May 20, 1995. Vertical bars represent standard deviations for each size distribution.

to 73

118 •

98- o ECO o co i_ 78 CD CL C/> 13 E o 58 Q. CO b O 38 i CD • n • • E • • • 3 • 18 i5: b• • • • • B B B jo! • i 1 3 7 9 11 5 13 15 17 Light Intensity (uE-s 1-m

o CEO o CO t CD CL c/> E o » Q. CO b

£ is

Light Intensity (uE-s -m

Fig. 3.6: Number of S. oregonensis in stomachs of stickleback fed for 15 minutes at 11 light intensities. Top: Light intensity range 0.1-15.5 uE-s"1 m"2. Bottom: Enlargement of light intensity range from 0.1-1.6 uE-s~1-m"2(bottom left corner of top figure). 235

195

155

115

Light Intensity (uE-s'^m2)

115

Light Intensity (uE-s ^m"2)

Fig. 3.7: Number of prey in stomachs of stickleback fed for 15 minutes at 11 light intensities. Top: Light intensity range 0.1-15.5 uE-s"1 -m"2. Bottom: Enlargement of light intensity range from 0.1-1.6 uEs"1-nr2 (bottom left corner of top figure). 235

205 H

• 175 • • B U5 • B n P • • • 115 • • • a

85 • • 55 • • 25

-5 -1 3 5 7 9 11 13 15 17 Light Intensity (uE-s 1-m ^

Light Intensity (uE-s -m

Fig. 3.8: Number of prey strikes taken by stickleback fed for 15 minutes at 11 light intensities Top: Light intensitintensityy range 0.1-15.5 uEs -m"2. Bottom: Enlargement of light intensity range from 0.1-1.6 uE-s"1-m"2(bottom left corner of top figure). 1.2 1.1 1 0.9 0.8 0.7 • 0.6 • • • 0.5 • 0.4 • • 0.3 B 0.2 0.1 0

-0.1 -r- -1 5 7 9 11 13 15 17 3 Light Intensity (uE-s 1-m

-1 Light Intensity (uE-s -m •5

Fig. 3.9: Ratio of captures/strikes for stickleback fed for 15 minutes at 11 light intensities. Top: Light intensity range 0.1-15.5 uE-s"1 m"2. Bottom: Enlargement of light intensity range from 0.1-1.6 uE-s"1-m"2(bottom left corner of top figure). 77 using each variable as a dependent variable against the natural log of light intensity as an independent variable. These transformations were used to reduce heteroscedasticity. Regressions were performed separately for light ranges less than and greater than 1.6 uE'S_1*nf2 (Table 3.4). For all four dependent variables, the regressions were statistically significant for light intensity less than 1.6 uE-s_1-irf2 and non• significant for light intensity greater than 1.6 uE-s^'m"2. At all light levels, large S. oregonensis are selected by most of the stickleback in these trials (Fig. 3.10). The rate at which S. oregonensis are eaten is lowest at the two lowest light level treatments used in this experiment. Thus, the mean number of S. oregonensis per fish at the two lowest light levels was 1.45 (n=ll) compared to 23.42 (n=23) at light levels above 1.6 uE.

Timing of SL oregonensis vertical migration in relation to stickleback feeding rate Figures 3.11-3.16 plot the vertical distribution of S. oregonensis over the periods of rapid light change (dawn and dusk) in Kennedy and Paxton lakes relative to the 1.6 uE isolume and the 0.1 uE isolume. Based on my experiments, these light levels are defined as the maximum (MFRT) and the near-zero feeding rate thresholds (FRT) for stickleback. At dawn on May 20, 1995 (Fig. 3.11) light levels were below FRT at the surface before sunrise and S. oregonensis were mainly located between 5- 12 m. As the FRT isolume shifted downward into the 5-12 m stratum, S. oregonensis also moved downward, although some S. 78

Table 3.4: Regression results for the effect of light (X) on four Y variables where ln(Y+l)=a*ln(X)+b, except for the capture/strike ratio where arcsin(sqrt(Y+l))=a*ln(X)+b. A light intensities ranging from 0 1 to 1. 6 uE -1 -? • s -m : Dependent Variable a b n r2 F P>F number of prey in 1.06 3 .54 42 0 .37 23 .98 0 .0001 stomach number Diaptomus in 0.86 2 . 50 42 0 .40 26.18 0 . 0001 stomach number of strikes 1.05 4.33 42 0 .33 19.60 0 . 0001 capture/strike ratio 0.12 0.77 - 36 0 .20 8.48 0 . 02

B light intensities ranging from 1 6 uE tc > 15. 5 uE-s'1 •m"•2 .

Dependent Variable a b n r2 F P>F number of prey in 0.34 3 .44 24 0 .11 2.64 0 .1186 stomach number Diaptomus in 0.03 2.80 24 0 .00 0.02 0 .9033 stomach number of strikes 0.15 4.42 24 0 .04 0.91 0 .3510 capture/strike ratio 0.083 0.078 24 0 .20 1.51 0.50 7 9 11 17

1 Light Intensity (uE-s-1- m

0.6 0.9 1.2 1.8

Light Intensity (uE-s 1-m ^

Fig. 3.10: Vanderploeg-Scavia index of electivity for S. oregonensis by stickleback fed for 15 minutes at 11 light intensities. Top: Light intensity range 0.1-15.5 uEs"1m"2 . Bottom: Enlargement of light intensity range from 0.1-1.6 uE-s~1-m "2 (bottom left corner of top figure). Values above dotted horizontal line represent positive electivity and value below this line represent negative electivity. 0 5.5 11 I I I 3 2 # Diaptomus*10/ m sunrise

0.0-5.0

5.0-12.0 MFRT CO

CD •*—> C 12.0-24.0 Q_ CD Q

3:00 3:40 4:20 5:00 5:40 Local Apparent Time Fig. 3.11: Vertical migration of S. oregonensis relative to stickleback feeding thresholds in Kennedy Lake during dawn on May 20, 1995. Horizontal bar graphs represent total number of S. oregonensis under 1 m square surface in three depth strata. Curves represent depth isolumes for stickleback maximum feeding rate threshold (MFRT) and near-zero stickleback feeding rate threshold (FRT). 0 5.5 11 I I I sunset 3 2 # Diaptomus* 10 An

0.0-5.0

5.0-12.0

12.0-24.0 Q_ CD Q

18:40 Local Apparent Time

Fig. 3.12: vertical migration of S. oregonensis relative to stickleback feeding thresholds in Kennedy Lake during dusk on May 20, 1995. Details as in Fig. 3.11. 2:40 3:20 4:00 4:40 5:00 Local Apparent Time Fig. 3.13: Vertical migration of S. oregonensis relative to stickleback feeding thresholds in Kennedy Lake during dawn on June 24, 1994. Details as in Fig. 3.11. I I I I I I I I I 18:55 19;35 20:15 20:55 21:35 Local Apparent Time

Fig. 3.14: Vertical migration of S. oregonensis relative to stickleback feeding thresholds in Kennedy Lake during dusk on June 24, 1994. Details as in Fig. 3.11. 0 15 30 I I I 3 2 sunset # Diaptomus*10/ m MFRT

0.0-4.0

CO Z CD 4.0-9.0

Q. CD Q 9.0-12.0

18:20 19:00 19:40 20:20 21:00 Local Apparent Time

Fig. 3.15: Vertical migration of S. oregonensis relative to stickleback feeding thresholds in Paxton Lake during dusk on August 19, 1994. Details as in Fig. 3.11. Fig. 3.16: Vertical migration of S. oregonensis relative to stickleback feeding thresholds in Paxton Lake during dawn on August 19,1994. Details as in Fig. 3.11.

oo 86 oregonensis temporarily remained in the 5-12 m stratum. The FRT isolume levelled off at about 17 m during the day and very few S.

oregonensis remained above 12 m. Because of the sampling depth interval, their distribution within the 12-24 m stratum cannot be defined. It is clear, however, that most individuals are below the MFRT isolume. At dusk on the same date (Fig. 3.12), almost all S. oregonensis remained below 12 m until the FRT isolume rose above this depth and, again, most individuals remained below MFRT throughout the sample period.

On June 24, 1994 the pattern was similar. Before first light, light levels in the lake remained below FRT and S.

oregonensis were located near the surface (Fig. 3.13). As the

FRT isolume moved downward at dawn, S. oregonensis moved downward out of the 5-12 m stratum. Almost all individuals reached the 12-24 m stratum before the FRT isolume. At dusk (Fig. 3.14), most individuals remained below the MFRT isolume at all times and migration into the 5-12 m stratum corresponded closely to the time of movement of the FRT through this stratum. If we assume similar visual feeding thresholds apply to Paxton Lake sticklebacks, vertical migration in Paxton Lake S.

oregonensis also appears to be timed to remain below the MFRT, and the data are consistent with the notion that most individuals remain below the FRT isolume. Since the maximum depth of Paxton Lake is less than 15 m, it was not possible to sample below 12 m. During daylight hours, the FRT isolume was located at or just below 12 m. Thus, most S. oregonensis were below 12 m and inaccessible to the net samples. This explains both the low'' numbers of S. oregonensis above 12 m at 18:29 and the sudden 87 increase in numbers in the 9-12 m stratum at 18:49 just as the

FRT isolume rises above 12 m (Fig. 3.15), and the decrease in S. oregonensis caught after dawn as the FRT isolume shifts to below the 9-12 m stratum (Fig. 3.16).

The daytime depth distribution of S. oregonensis in Kennedy

Lake approximates the expectation of the stickleback avoidance hypothesis that they are at depths where light intensities reduce stickleback feeding rate. Discrete samples at 1, 3, 5, 7, 10,

17, and 24 m intervals indicate few S. oregonensis at 10 m or above, and peak abundances at 17 or 24 m (chapter 2). The vertically stratified samples indicate S. oregonensis are below the 12 m depth as dusk begins and dawn ends. In Kennedy Lake, during full sunlight (2000 uE-s^-nT2) the MFRT light intensity is estimated to be at 16.9 m and FRT light intensity at 23.8 m

(using the extinction coefficient of 0.401 measured in June of

1994). Under cloudy conditions (1000 uE-s^-m-2) , MFRT is estimated to be at 15.2 m and FRT at 22.1 m.

Timing of £\_ oregonensis vertical migration relative to sockeye vertical migrations

With the exception of glacially turbid lakes (Hyatt et al.

1989), information obtained from diurnal hydroacoustic sampling of fish target depth distribution, analyses of gut contents of juvenile sockeye sampled by open water trawl, and visual observations of surface feeding (Narver 1970, Barraclough and

Robinson 1972, McDonald 1973, Levy 1990) indicate that juvenile sockeye typically remain in deep water during the day and that, at this depth, their feeding rate is low. Ascent toward the 88 surface occurs at dusk and feeding may occur as they ascend (Barraclough and Robinson 1972). At the surface, active feeding continues for a period before the twilight fades. The juvenile sockeye then migrate down to the thermocline where they spend the night. Dense schooling, and the rarity of fresh food in gut samples at night, indicate that the feeding rate is low. As light intensity increases at dawn, sockeye may approach the surface and feed again before descending to deep water for the daylight period. The timing of migration and feeding is consistent relative to sunrise and sunset (Fig. 3.17). In 11 of 13 instances, the dusk ascent begins within 3 0 minutes of sunset, and by about 15- 2 0 minutes after sunset the juvenile sockeye arrive near the surface. They feed here for about 20-40 minutes before again descending to near the thermocline. Less data are available for the dawn period and the rise from the thermocline to the surface for feeding is harder to define than from the hypolimnion at dusk. Some juvenile sockeye do not feed at dawn. This suggests that at the time that some sockeye rise to feed at the surface, other sockeye descend to day time depths. This disperses the fish targets in echo sounder graphs and obscures the timing of these events. Nonetheless, the available information indicates that feeding starts and ends before sunrise (Fig. 3.18). Depth isolumes in Kennedy Lake for maximum, half maximum, and minimum feeding rate light intensities of juvenile sockeye over dawn and dusk periods (Fig. 3.19) indicate that juvenile sockeye have the visual capacity to feed near the surface up to an hour after sunset and an hour before N1 X ! t-

N4 X " r N5 X ? B1 x- - CO M1 CD x- - - h TJ C/)

I •150 •120 -90 -60 Minutes from sunset

Fig. 3.17: Summary of available data on time of the beginning of movement of juvenile sockeye toward the surface (X), the period of migration toward the surface (dotted lines) and the period of feeding near the surface (solid line) relative to sunset. Uncertainty about time that feeding begins or ends is represented by question marks. N1-N5 from Narver (1970) at Babine Lake, B1 from Barraclough (1972) in Great Central Lake, M1 from McDonald (1973) in Babine Lake, L1-L3 from Levy (1989) in Shuswap Lake, Babine Lake, and Quesnel Lake, and G1-G3 my data from Kennedy Lake. N1

N5 X B1

CO M1 CD T3 L1 Z5 •4—' CO 12

T T T i—h-r 1 -165 -140 -115 -90 -65 -40 •15 sunrise 10 35 Minutes from sunrise

Fig. 3.18: Summary of available data for juvenile sockeye on the time of juvenile sockeye feeding near the surface (solid line) and the time of the beginning of movement toward depth (X) relative to sunrise. Other details as in Fig. 3.17. 91

-60 -45 -31 -16 sunrise 12 27 Minutes from sunrise

-10 sunset 10 20 30 40 50 60 70 80 Minutes from sunset

Fig. 3.19: Maximum (1.0 ft.-c), half maximum (0.01 ft.-c), and minimum (0.0001 ft.-c.) feeding rate isolumes for juvenile sockeye (from AN 1959) for clear sky conditions during dawn (top panel) and dusk (bottom panel) on June 23,1994. Calculations based on average clear sky instantaneous surface light intensities on June 23 at 50 degrees Lat. (United States Navy Bureau of* Ships 1952) and an estimated light extinction coefficient of 0.401. 92 sunrise. Figs. 3.20-3.24 show timing of vertical movements of S. oregonensis and fish at dawn and dusk in Kennedy Lake. The interpretation of vertical movement of juvenile sockeye by hydroacoustics is complicated in Kennedy Lake by the presence of large numbers of stickleback. Stickleback do not vertically migrate and generally remain at the surface regardless of light level. Thus stickleback account for most of the targets near the surface during the day (Kim Hyatt, FOC, unpublished data). Therefore, sockeye movements can be inferred from the movement of fish targets from deeper strata toward the surface at dusk and from the surface stratum downward at dawn. At dusk on October 19, 1993 (Fig. 3.20), June 24, 1994 (Fig. 3.21), and May 19, 1995 (Fig. 3.22) some deep water fish targets, assumed to be juvenile sockeye, rose to < 12 m within 10-15 minutes after sunset. S. oregonensis arrived in the surface stratum shortly before juvenile sockeye on October 19, 1993 (Fig.

3.20) and June 1994 (Fig. 3.21). In May, S. oregonensis rose to the surface shortly after dusk and at about the same time as the juvenile sockeye (Fig. 3.22). Thus, S. oregonensis were vulnerable to post-sunset surface feeding by juvenile sockeye on all of these dates. If sockeye feed as they ascend, as reported for Great Central Lake sockeye (Barraclough and Robinson 1972), then on all three sample dates S. oregonensis were also exposed to sockeye predation from 10 minutes before sunset to 15 minutes after sunset. This was the time period when both S. oregonensis and juvenile sockeye were moving upward and present in the 5-12 meter stratum. 0 7 14 sunset I I I Fish targels/trin

0.0-5.0 b i 5.0-8.5

8.5-12.0 CO 12.0-15.5 CD c 15.5-19.0

Q. CD 19.0-22.5 Q 22.5-26.0 26.0+ • F P —n 1I 16:20 17:00 17:40 18:20 19:00

0 18.5 37

I I 1 3 2 # Diaptomi£*107m

0.0-5.0

5.0-12.0

CO iirrrr

12.0-24.0 CL CD Q

I 16:20 17:00 17:40 18:20 19:00

Local Apparent Time

Fig. 3.20: Changes in vertical distribution of fish targets (top) and S. oregonensis (bottom) in Kennedy Lake at dusk on October 19, 1993. Upper and lower dashed lines represent approximate timing of vertical movement of juvenile sockeye targets. 94

0 6 12 I I I Fish taigets/min sunset

0.0-5.0

5.0-8.5

8.5-12.0 "CO ^ 12.0-15.5 -*—CD1 — 15.5-19.0 SZ gj" 19.0-22.5 Q

22.5-26.0

26.0+

I I I I 18:55 r 19:35 20:15 20:55 21:35

0 13 26 1 I I 3 2 # Diaptomus'10/ m

0.0-5.0

5.0-12.0 ILL! f r CC

CD -*—< C 12.0-24.0 CL • I I I I I CD Q

I I i I i I 18:55 19:35 20:15 20:55 21:35

Local Apparent Time

Fig. 3.21: Changes in vertical distribution of fish targets (top) and S. oregonensis (bottom) in Kennedy Lake at dusk on June 24, 1994. Other details as in Fig. 3.20. 95

0 3 6 I I I sunset

Fish targets/min

0.0-5.0

5.0-8.5

J^, 8.5-12.0 "CO ^ 12.0-15.5 CD 15.5-19.0

19.0-22.5

22.5-26.0

26.0+ Ti 1— 1 1 18:40 19:20 20:00 20:40 21:20

0 5.5 11 1 \ \

# DiaptomiB*107 m 0.0-5.0 I |

5.0-12.0 I I I I I I

12.0-24.0 I I I

I I I 18:40 19:20 20:00 20:40 21:20

Local Apparent Time

Fig. 3.22: Changes in vertical distribution of fish targets (top) and S. oregonensis (bottom) in Kennedy Lake at dusk on May 19, 1995. Other details as in Fig. 3.20. 96

I I I

Fish targets/rrin sunrise

0.0-5.0

5.0-8.5

8.5-12.0

12.0-15.5 1

15.5-19.0

19.0-22.5

22.5-26.0

26.0+

"I 1— 2:40 3:20 4:00 4:40 5:00

0 13 26 I I I 3 2 # Diaptomus*10/ m

0.0-5.0

5.0-12.0

12.0-24.0 I

i i~ 2:40 3:20 4:00 4:40 5:00

Local Apparent Time

Fig. 3.23: Changes in vertical distribution of fish targets (top) and S. oregonensis (bottom) in Kennedy Lake at dawn on June 24, 1994. Other details as in Fig. 3.20. 97

0 3 6 , sunrise Fish targets/rrin

I 1 1 1 1—i 1 1 3:00 3:40 4:20 5:00

0 5.5 11 i i i 3 2 # Diaptomus*lO/ m ;

0.0-5.0 ;

-g- 5.0-12.0 • • 1 1 1 • •! i i terva l

12.0-24.0 CL 1 i 1 1 1 1 CD Q

- - - - • ;

i i i i i i i i i 3:00 3:40 4:20 5:00

Local Apparent Time

Fig. 3.24: Changes in vertical distribution of fish targets (top) and S. oregonensis (bottom) in Kennedy Lake at dawn on May 19, 1995. Other details as in Fig. 3.20. 98 At dawn on June 24, 1994 (Fig. 3.23) and May 19, 1995 (Fig. 3.24), juvenile sockeye began descending within 20 minutes of sunrise. S. oregonensis began to shift downward from the 5-12 to 12-24 m depth interval at about the same time, or later, and therefore after the juvenile sockeye feeding period.

Timing of £\. oregonensis vertical migration relative to N. mercedis vertical migrations N. mercedis, an invertebrate zooplankton predator, also occurs in Kennedy Lake (Cooper et al. 1992) . N. mercedis is also a strong vertical migrator, and it was captured in abundance during the dusk sampling of October 1993. On this date, S. oregonensis ascended to the 0-5 m stratum about 20-40 minutes earlier than N. mercedis (Fig. 3.25). Since S. oregonensis move upward well before the N. mercedis begin feeding near the surface, the timing of S. oregonensis movements has no significant effect on the amount of time they are vulnerable to the N. mercedis.

Discussion Timing of S\_ oregonensis vertical migration in relation to stickleback feeding rate As predicted by the stickleback avoidance hypothesis, as S. oregonensis move up at dusk and down at dawn they closely track the threshold light intensity for stickleback feeding. If there is a daytime feeding opportunity cost associated with vertical migration, the optimal strategy may be to tolerate predation risk greater than 0. This may explain the position of some S. 99

0 40 80 I I I sunset

#NeomySB / m

0.0-5.0

5.0-12.0 [ rrc

12.0-24.0 I I

i 1 I 1 1 16:20 17:00 18:20 19:00 17:40

0 18.5 37 I I I 3 2 # Diaptomus*! 0/ m

0.0-5.0 5.0-12.0 iirrrr

12.0-24.0 I I I I I

—r~ l I 1 I 16:20 17:40 18:20 19:00 17:00 Local Apparent Time

Fig. 3.25: Changes in vertical distribution of N. mercedies (top) and S. oregonensis (bottom) at dusk on October 20, 1993. 100. oregonensis at light intensities above FRT but below MFRT. The position of some S. oregonensis at light intensities above FRT also may be an artifact of underestimating FRT because of the higher prey densities in the feeding experiments than in Kennedy Lake. These higher densities elevate encounter rates and, thus, may cause feeding to be profitable at lower light intensity than it is in the lake. In turn, potentially, this underestimates feeding rate light thresholds and the extent to which S. oregonensis avoid threshold light levels for stickleback feeding. While FRT may be underestimated somewhat due to high experimental prey densities, the estimate of MFRT obtained from the laboratory experiments is likely to be accurate because prey densities were low enough that non-zero time intervals exist between prey encounters. Therefore, trends of feeding rate as a function of light intensity for each prey density should be identical in shape and differ only in elevation. Above a threshold prey density, one or more prey are always within view and feeding rates are determined only by light-independent pursuit, capture, and handling times. Below this threshold, feeding rate is affected by the average time increment between encounters which are determined by light dependent reactive distances (Ware 1973, Aksnes and Giske 1993). Under these conditions the reactive distance for each prey item, as a function of light intensity, will be independent of prey density and relative rates of feeding at different light intensity will, therefore, be independent of prey density as well.

Distinct time intervals between prey encounters were observed in the lab feeding experiments. This can be confirmed 101 with simple time allocation calculations. With one exception, all fish in the experiment pursued less than 180 prey over a 15 minute interval (Fig. 3.8), and all prey encountered appeared to be pursued. I conservatively estimate a mean combined pursuit, capture, and handling time per prey item of 3 seconds. Even at 180 encounters, this leaves an average 2 second time interval between encounters.

Timing of oregonensis vertical migration relative to sockeye vertical migrations

Clearly, S. oregonensis do not decrease daytime risk from sockeye predation by migration: sockeye are crepuscular feeders and S. oregonensis are at the surface at dawn and dusk when juvenile sockeye are feeding. In fact, vertical migration may increase risk from juvenile sockeye predation since descent of S. oregonensis to deep water during the day brings them closer to juvenile sockeye that also migrate downward. In Babine Lake, freshly eaten individuals of a vertically migrating copepod,

Heterocope septentrional is, were found in the stomachs of juvenile sockeye that occupied deep water during the day (Narver 1970) .

The conclusion that vertical migration by S. oregonensis is neither driven by, nor results in, juvenile sockeye avoidance contradicts the conclusions of Schmidt et al. (1994) for turbid Alaskan Lakes. Possibly, the turbid conditions in these lakes force juvenile sockeye to feed in daylight near the surface, rather than crepuscularly.and, thus, provide a daytime selective pressure for downward migration of zooplankton similar to that 102 provided by stickleback in the lakes we studied. Hydroacoustic and trawl surveys indicate that juvenile sockeye remain near the surface throughout the diel period in turbid Owikeno Lake (Hyatt et al. 1989). From hydroacoustic data, it has been inferred that juvenile sockeye in Nimpkish Lake undertake a nocturnal vertical migration rather than a typical diurnal migration and that daytime predation threat from these sockeye drove the observed diurnal vertical migration of zooplankton in that lake (Levy 1990) . However, pelagic stickleback are.also present in Nimpkish Lake and these may account for the zooplankton vertical migration. The sticklebacks may also account for the large number of surface fish targets in daytime hydroacoustic data that were interpreted as juvenile sockeye.

S. oregonensis vertical migration and separate juvenile sockeye and stickleback resource niches Stickleback and juvenile sockeye both utilize zooplankton resources that appear to be limited in many coastal lakes (Hyatt and Stockner 1985, O'Neill and Hyatt 1987) and are the only two common planktivores in many of these lakes (Hyatt and Stockner 1985). In lake enclosure experiments in Kennedy Lake the diets of both fish species were similar. Both preferred larger prey

(including S. oregonensis) and strongly impacted the size distribution and species composition of the zooplankton community (O'Neill and Hyatt 1987). In the lake, however, juvenile sockeye are able to exploit vertically migrating S. oregonensis, but stickleback are not. 103 Chapter 4

Vertical migration behavior of

Skistodiaptomus oregonensis: constitutive or induced?

Introduction I presented evidence in chapters 2 and 3 to argue that interlake differences in the vertical migration behaviour by S. oregonensis are associated with the presence, or absence, of pelagic sticklebacks. In this chapter I examine whether the migration phenotypes of individuals are fixed genetic (constitutive) characters or environmentally induced (flexible) behaviours. Many recent publications demonstrate that vertical migration in individual planktors can be induced by environmental cues. In most cases, exudates released by predators provide this cue (Dodson 1988, Dawidowicz et aT. 1990, Neill 1990, Tjossem 1990, Bollens and Frost 1991, Ringelberg 1991a, Ringelberg 1991b, Neill 1992, De Meester 1993, Forward and Rittschof 1993, Loose and Dawidowicz 1994), although in some cases direct mechanical or visual cues from the predator are necessary (Bollens et al. 1994). Also, genotype differences for different migration or vertical distribution phenotypes within populations of zooplankton are well known (Weider 1984, Weider 1985, De Meester and Dumont 1988). Interaction between genotype and induced effects on migration has been documented for. genetically distinct clonal groups of Daphnia magna (De Meester 1993) and for different species of Daphnia collected from different lakes (Dodson 1990) .

Here, I present laboratory experiments designed to directly 104 test the hypothesis that fish presence or absence affects the vertical distribution of individual S. oregonensis. Field evidence for variation in migration behaviour collected over three years of field sampling is also investigated. Individuals from both non-migratory (Great Central Lake) and migratory (Kennedy Lake) populations are considered.

Methods

Laboratory experiments Four cylindrical plexiglass columns 195 cm tall and 15 cm in diameter were used as microcosms to investigate the effect of stickleback presence or absence on the vertical migration behaviour of S. oregonensis. Each column was placed within a chamber 245 cm in height, 150 cm in length, and 120 cm in width. The ceiling and walls of each chamber consisted of light- impermeable black plastic. Twenty-five cm diameter photographer lamps fitted with standard incandescent 25 Watt light bulbs were suspended 22 cm directly above each tube. The lamps were also fitted with blue Westsun theatrical light filters to remove a large portion of the red light which is normally absorbed within the first few meters in lakes (Wetzel 1975) . The light intensity profile within the tubes is shown in (Fig. 4.1). An automated light switch turned the lights on at dawn and off at dusk each day.

S.• oregonensis were captured from the lake with vertical tows at depths from 3 0 m to the surface using a double-ringed Wisconsin-style 100 um nitex mesh plankton net 292 cm in length with a 55 cm diameter opening. Zooplankton were transported in 105

0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 Light intensity (uE)

Fig. 4.1: Light intensity depth profile in experimental tubes (primary axis) and corresponding depth of similar light intensities in Kennedy Lake at surface light intensity of 1000 uE and k=0.401 (secondary axis). 106 25 1 carboys to the laboratory where they were maintained under a diurnal light rhythm. Light was switched on at sunrise and turned off at sunset by an automated timer. Within 48 hours of capture, equal numbers of S. oregonensis were placed in each experimental tube. For a period of up to eight days and nights, the number of individuals in each of 11 depth intervals was recorded (once near noon and once near midnight). At night the tubes were surveyed using a narrow-beam flashlight fitted with a filter that allowed only far red light to pass. Diaptomus are reported to be insensitive to far red light (Ramcharan and Sprules 1989). Evasive hopping behaviour, on initial exposure to the light beam, occurred less than 5% of the time. Three separate experiments were performed. In experiment 1

Kennedy Lake S. oregonensis were placed into tubes filled with Kennedy Lake water. For fish water addition treatments (fishwater [+]) two Kennedy Lake sticklebacks, previously fed Kennedy Lake zooplankton, were placed for 24 hours in a dish containing 500 ml of Kennedy Lake water. The sticklebacks were then removed and the water added to the two fishwater [+] treatment tubes. I added equal amounts of Kennedy Lake water that had not held sticklebacks to the two fish water absent (fishwater [-]) treatment tubes.

Experiment 2 was conducted using S. oregonensis from Great Central Lake in tubes filled with Great Central Lake water. Fishwater [+/-] treatments were prepared as in experiment 1, except that Great Central Lake zooplankton were fed to the sticklebacks prior to the experiment.

Experiment 3 was conducted in Kennedy Lake water with S. 107 oregonensis from Kennedy Lake in Kennedy Lake water. In these fish [+] treatments two sticklebacks were placed into a nitex mesh cage and suspended in the top 10 cm of water in the tube. The mesh was flush with the interior walls of the tube and flat along the bottom. Similar cages, but without stickleback, were placed in the fish [-] treatments. Statistical analyses were performed using the SAS System software (Littel et al. 1991). Statistical tests on proportional data were performed for logit transformations of the proportion values (p'=ln[p/[1-p]], where p=proportion). Univariate repeated measures analyses of variance for the proportion of individuals below 100 cm during the day, and for the change in the proportion below this depth from night to day, were performed for the dependent time series measurements in each tube. This procedure performs an analysis of variance based on a single average measure for each time series (Littel et al. 1991). Because the low number of replicates (two tubes per treatment) yielded insufficient error degrees of freedom, it was not possible to use multivariate repeated measures analyses of variance to test for a time effect. For the univariate repeated measures analyses, the low number of replicates (only 1 error degree of freedom) limit the power of the test to detect treatment affects. To increase error degrees of freedom and the resulting statistical power, I also performed mixed-model nested analyses of variance for the depths of individual S. oregonensis within each sample time. These analyses increased error degrees of freedom and allowed for tests of both fixed treatment effects (fish or fishwater [+/-]) and random tube within treatment effects. 108

Field collections

Methods for determining zooplankton depth distribution from horizontal tows and for extraction of chlorophyll a from the 3-50 um phytoplankton size fraction as a measure of the food available to S. oregonensis are described in Chapter 2.

Results

Experiment 1

S. oregonensis collected from the migratory population in Kennedy Lake (see chapter 2) also migrated in the experimental tubes. Typical day and night distributions in all four tubes are shown in Figure 4.2. At night S. oregonensis in all four tubes were distributed relatively evenly across depths but, during the day, a large proportion of S. oregonensis were concentrated near the bottom. These distributions are comparable to typical day and night vertical distributions of S. oregonensis in Kennedy Lake (Fig. 2.3 and Fig. 2.4). Although a large proportion of S. oregonensis remained below 100 cm in the columns on all days (Fig. 4.3), the proportion of individuals below 100 cm increased from night to day on nearly all dates (Fig. 4.4). This suggests a net downward movement of individuals during the day. Neither the daytime vertical distribution nor the change in distribution from day to night were affected by fishwater [+/-] treatments. Univariate repeated measures analysis of variance indicates no significant fishwater [+/-] treatment effect for either the proportion of individuals below 100 cm during the day or the change in the proportion below this depth from night to day (Table 4.1). Mixed model nested analyses of variance for the 109

0-10 Night 10-20

20-40 no fish fish 40-60 E o 60-80

Q. 80-100 CD a 100-120 120-140

140-160

160-180 -I— 15 -10 0 To"

0-10 Day tube 1

10-20 tube 2 IWW1 tube 3 tube 4 20-40 no fish fish 40-60 ZZJ E o 60-80

CL 80-100 CD mm,„ Q 100-120

120-140

140-160

160-180 -1— -10 -5 0 5 10 Number of individuals

Fig. 4.2: Experiment 1 - typical day and night distributions of Kennedy Lake S. oregonensis in cyclinders in fishwater [ +/-] treatments. 110

0.9

CL 0.3 - * 11

0.2 J , , , , 18-Jul 20-Jul 22-Jul 24-Jul 26-Jul 28-Jul

Fig. 4.3: Proportion of Kennedy Lake S. oregonensis below 100 cm during the day in experiment 1. Solid squares indicate fishwater [-] treatments and open squares indicate fishwater [+] treatments. Lines join values from the same cyclinder through time. Ill

Fig. 4.4: Experiment 1 - change in the proportion of Kennedy Lake S. oregonensis below 100 cm from night to day in fishwater [+/-] treatments. Zero line indicates no change. Other details as in Fig. 4.3. 112

Table 4.1: Experiment 1 - univariate repeated measures analyses of variance for A) the effect of fishwater [+/-] treatments on the proportion of S. oregonensis below 100 cm during the day and B) the effect of fishwater [+/-] treatments on the change in the proportion of S. oregonensis below 100 cm from night to day. Analyses were performed using the logit transformation of the proportion data. A Source DF Type III SS Mean Square F Value Pr > F TREAT 1 0.63984722 0.63984722 0.97 0 .4281 Error 2 1.31666008 0*65833004

B Source DF Type III SS Mean Square F Value Pr > F TREAT 1 0.00026310 0.00026310 0.00 0 .9876 Error 2 1.70411574 0.85205787 113 depths of individuals, performed separately for each sample time, also indicate neither treatment effects nor effects of tubes nested within treatments for any day or night during the course of the experiment (Table 4.2)

Experiment 2

S. oregonensis from the non-migratory Great Central Lake population (see chapter 2) did not migrate as strongly in the experimental tubes as the Kennedy Lake S. oregonensis in experiment 1. Typical day and night distributions in all four

tubes are shown in Figure 4.5 (compare Fig. 4.2). r Compared to

Kennedy Lake S. oregonensis (experiment 1), both the change in the proportion below 100 cm (Fig. 4.6) as well as the proportion below 100 cm during the daytime (Fig. 4.7) is, on average, much smaller and the change in proportion below 100 cm from day to night is as often negative as positive. The fishwater [+] treatment appears to increase the proportion of S. oregonensis below 100 cm during the day (Fig. 4.7), although a univariate repeated measures analysis of variance detects no significant difference (Table 4.3). Despite s the apparent increase in the proportion of S. oregonensis in deep strata during the day in fishwater [+] treatments, there is no clear effect of fishwater [+/-] treatments on the change in vertical distribution from day to night (Fig. 4.6 and Table 4.3). Nested analyses of variance for depths of individual S. oregonensis show no significant treatment effects except on the second night and no significant tube nested within treatment effects (Table 4.4). Table 4.2: Experiment 1 - nested analyses of variance for depths of individual S. oregonensis: tests of significance for fishwater [+/-] treatment effects and tube within treatment effects. For all times, treatment df=l and tube within treatment df=2. tube treatment within

effect Ftreatment P>Ftreatment treatment Ftube P>Ftube time error df error df day 1 2 12 0 212 0 6878 31 0 466 0 6319 day 2 2 00 0 267 0 6565 33 0 278 0 7593 day 3 2 06 0 115 0 7659 35 0 894 0 4181 day 4 2 13 0 475 0 5582 33 0 326 0 7240 day 5 2 07 1 022 0 4151 33 0 247 0 7826 day 6 2 10 0 068 0 8179 33 0 653 0 5271 day 7 2 02 0 352 0 6127 32 1 329 0 2791 day 8 2 07 0 179 0 7118 33 1 659 0 2059 night 1 2 08 1 465 0 3458 34 0 368 0 6946 night 2 2 03 0 416 0 5840 33 0 905 0 4144 night 3 3 31 8 141 0 0578 33 0 011 0 9890 night 4 2 09 1 452 0 3470 34 0 588 0 5612 night 5 2 22 2 081 0 2740 33 0 400 0 6736 night 6 2 00 0 061 0 8282 35 1 286 0 2891 night 7 2 14 3 746 0 1841 34 0 789 0 4623 115

0-10 Night 10-20 20-40 no fish fish 40-60 60-80 80-100 100-120 120-140 140-160 160-180 •10 5 5 A 3 0 2 4 6 8 10

0-10 Day WWWWjip""'"""" tube 1 """" tubegR-^sl 10-20 [HH tube 3 •ttt(/f///t/\ V777A tube 4 20-40 no fish fish 40-60 60-80 80-100 100-120 120-140 140-160

160-180 -10 -4 -2 0 2 4 6 8 10 Number of individuals

Fig. 4.5: Experiment 2 - typical day and night distributions of Great Central Lake S. oregonensis in cyclinders in fishwater [+/-] treatments. 116

0.4

30-Aug 31-Aug 01-Sep 02-Sep 03-Sep

Fig. 4.6: Experiment 2- change in the proportion of Great Central Lake S. oregonensis below 100 cm from night to day in fishwater [+/-] treatments. Other details as in Fig. 4.3 117

0.35

0-1 , . . 1 30-Aug 31-Aug 01-Sep 02-Sep 03-Sep

Fig. 4.7: Experiment 2 - proportion of Great Central Lake S. oregonensis below 100 cm during day. Other details as in Fig. 4.3. 118

Table 4.3: Experiment 2 - univariate repeated measures analyses of variance for A) the effect of fishwater [+/-] treatments on the proportion of S. oregonensis below 100 cm during the day and B) the effect of fishwater [+/-] treatments on the change in the proportion of S. oregonensis below 100 cm from night to day. Analyses were performed using the logit transformation of the proportion data.

A Source DF Type III SS Mean Square F Value Pr > F TREAT 1 0.10654630 0.10654630 3 .61 0.1977 Error 2 0.05468853 0.02734426

B Source DF Type III SS Mean Square F Value Pr > F TREAT 1 0.02890008 0.02890008 0 . 01 0 .9322 Error 2 6.25834208 3 .12917103 Table 4.4: Experiment 2 - nested analyses of variance for depths of individual S. oregonensis: tests of significance for fishwater (+/-) treatment effects and tube within treatment effects. For all times, treatment df=l and tube within treatment df=2. tube treatment within

> ; treatment Ftube P>Ftube effect Ftreatment P -- 'treatment error df time error df day 1 2 02 0 . 640 0 5068 31 0 398 0 6750 day 2 2 31 0.530 0 5334 29 0 635 0 5370 day 3 2 01 7.913 0 1059 34 0 449 0 6419 day 4 2 00 2 .550 0 2512 32 0 404 0 6713 night 1 2 09 0.040 0 8598 32 0 360 0 7006 night 2 2 01 20.21 0 0459 30 0 128 0 8807 night 3 2 01 0.014 0 9157 28 0 981 0 3875 120

Experiment 3

The addition of fish directly into fish treatment cyclinders did not result in a higher proportion of S. oregonensis below 100 cm relative to either the fish [-] treatment (Fig. 4.8) nor the fishwater [+] treatments in experiment 1. Likewise, the change in the proportion of S. oregonensis below 100 cm from night to day did not increase with fish directly in the tank rather than fishwater treatment of experiment 1 (Fig. 4.9). Nested analyses of variance for depths of individual S. oregonensis indicate no significant treatment or tube within treatment effects (Table 4.5).

Temporal variation in vertical distribution in the lakes The means of the daytime depth distributions in Kennedy Lake are consistently deep and, through time, the distributions have a similar variance. At night, when the distributions are shallower, the variance of the distributions are greater and the mean depths more variable between sample dates. In Great Central Lake, mean depth (both day and night) are comparable to mean depth in Kennedy Lake at night, except that on some dates mean depths are deeper. The variances of each depth distribution are high for both day and night (Fig. 4.10).

Discussion The absence of an effect of fish treated water or caged fish on vertical migration behaviour of S. oregonensis suggests that in these lakes this species exhibits constitutive vertical migration behaviour. Neill (1992) also reported constitutive 121

Fig. 4.8: Experiment 3 - change in proportion of Kennedy Lake S. oregonensis below 100 cm from night to day. Solid squares indicate fish [-] treatments and open squares indicate fish [+] treatments. 122

0.78

0.76 E o 0.74 o o 0.72 0 _Q c 0.70 H o "•c o 0.68- CL o 0.66-

0.64 24-Oct 25-Oct 26-Oct

Fig. 4.9: Increase in the proportion of Kennedy Lake S. oregonensis below 100 cm from night to day in fishwater [+/-] treatments of experiment 3. Other details as in Fig. 4.8. Table 4.5: Experiment 3 - nested analyses of variance for depths of individual S. oregonensis: tests of significance for fish (+/-) treatment effects and tube within treatment effects. For all times, treatment df=l and tube within treatment df=2. tube treatment within effect ^treatment •P->Ftreatmen treatment Ftube P>Ftube error df time error df t day 1 2 00 0 156 0 .7308 26 0 436 0 6514 night 1 2 02 0 756 0 .4753 27 0 199 0 8210 night 2 2 03 1 154 0 .3937 31 0 983 0 3856

to Day Night

15-Jul-92 31-Jan-93 19-Aug-93 7-Mar-94 23-Sep-94 15-Jul-92 31-Jan-93 19-Aug-93 7-Mar-94 23-Sep-94

10 •

15 •

20 "

25 •

i i r -i r- 6-May-92 3-Sep-92 12-Dec-92 22-Mar-93 30-Jun-93 6-May-92 3-Sep-92 12-Dec-92 22-Mar-93 30-Jun-93

Fig. 4.10: Day and night weighted mean depth of S. oregonensis in Kennedy Lake (top) and Great Central Lake (bottom) for multiple sample dates. Vertical bars represent variance of each depth distribution for each date. 125 vertical migration in Diaptomus kenai exposed to cutthroat trout (Onchorhynchus clarki) predation. In contrast, most of the literature reporting experiments designed to test for inducible effects show such effects. These include studies of freshwater copepods (Neill 1990, Neill 1992), Acartia hudsonica (Bollens and Frost 1991), cladocerans (Dodson 1988, Ringelberg 1991a, Ringelberg 1991b, De Meester 1993, Loose and Dawidowicz 1994), Artemia larvae (Forward and Rittschof 1993), and chaoborid larvae (Dawidowicz et al. 1990, Tjossem 1990). The absence of seasonal changes in vertical migration behaviour of S. oregonensis provides further evidence that the behaviour is fixed. In winter, stickleback move to deep water (Dr. K.D. Hyatt, FOC, unpublished data). They likely reduce their feeding activity to a low level. Temperature throughout the water column is below 6o c, and, in laboratory tanks, stickleback at this temperature are nearly inactive (Dr. J.D. McPhail, Department of Zoology, University of British Columbia pers. comm. and Dr. K.D. Hyatt, FOC, pers. comm.). Despite the apparent decreased predation risk from stickleback, S. oregenensis in Kennedy Lake continue to migrate in the winter. In contrast, many zooplankton species exhibit decreased migration, or a complete absence of migration, during seasons when predators are reduced in numbers or inactive (Bollens and Frost 1989b, Ohman 1990, Frost and Bollens 1992, De Stasio 1993, Huang et al. 1993, Brancelj and Blejec 1994).

Inducible versus constitutive vertical migration behaviours are expected to be selected in different kinds of environments (Harvell 1990, Neill 1992, Pijanowska 1993), and in Kennedy Lake 126 three factors may favour the evolution of the latter. First, predation risk from stickleback may be invariant from year to year. In the absence of fluctuating risk, flexible behaviour would not be selected. Second, the absence of a cost to vertical migration also favours a fixed behaviour. Although evidence from the analysis of feeding rhythms in chapter 2 suggests a cost to vertical migration, this cost may be absent in winter when food abundance is low and its distribution is homogenous down to 24 m (Fig. 2.7 - February). This may explain continued vertical migration in winter when stickleback are relatively inactive. Third, environmental cues from stickleback may be too unreliable, making flexible vertical migration too risky. During the long summer breeding season, stickleback numbers offshore can fluctuate rapidly as they migrate in synchrony between littoral breeding zones and the offshore habitat (Hyatt and Ringler 1989). Cues that induce migration might disappear offshore when the littoral migrations occur. If so, when stickleback return to the pelagic habitat in large numbers, S. oregonensis dependent on such a cue, initially would not be migrating and thus (until the cue took effect) they would be vulnerable to predation.

The lack of a treatment effect in my experiments is possibly because of insufficient cues for the induction of migration. Although the caged fish were placed directly into the tubes to ensure a high, and constant, level of exudate, Bollens et al. (1994) showed that only direct mechanical or visual stimuli induce vertical migration in Acartia hudsonica. Free swimming fish in enclosures trigger vertical migration of Acartia hudsonica while caged fish are inadequate (Bollens and Frost 127 1989a). Nonetheless, in the experiments involving Kennedy Lake

S. oregonensis, lack of a treatment effect appears to be due to strong migration of most individuals both with and without fish, rather than the lack of sufficient stimulus to cause greater vertical migration relative to the non-fish treatment. Although the experimental results support the hypothesis that vertical migration behaviour by S. oregonensis is fixed at maturity, my experimental design did not test for developmental determination of the migration phenotype. Further experiments with laboratory reared individuals are required to determine if exposure to particular predation regimes during development determines the migration phenotype of mature individuals. Neill

(1992) showed that Diaptomus kenai from a lake containing predatory cutthroat trout displayed invariant, obligate vertical migration that was unaffected by exposure to the trout during ontogeny. 128 Chapter 5

A dynamic optimization model of Skistodiaptomus oregonensis vertical migration

Introduction In chapters 2 and 3 I present evidence consistent with two hypotheses: 1) that S. oregonensis vertical migration in Kennedy and Paxton lakes is driven by stickleback predation, and, 2) that this avoidance behaviour has a cost associated with lost feeding opportunities in surface waters. In this chapter I construct an optimal depth decision model for S. oregonensis in Kennedy Lake based on the physiological energetics of S. oregonensis, the temperature environment, the abundance and vertical distribution of food, and estimates of predation risk. I then use the model to examine the effect of predation on optimal depths, and the consequent feeding opportunity costs. This provides an assessment of whether the hypotheses (1 and 2, above) are tenable on the basis of the present knowledge of the biology of

S. oregonensis and relevant factors of the Kennedy Lake environment. To build the model, I use a dynamic optimization algorithm. This provides a technique to determine sequential behavioural decisions that maximize fitness over the entire life-history of an organism. Multiple factors affecting fitness are expressed in a common currency. This makes it possible to explore fitness trade-offs that may exist among factors (Mangel and Clarke 1988). In the model presented here, expected lifetime fecundity is used as a measure of fitness which, in turn, depends on both growth to maturity and the probability of surviving predation. I then 129 estimate the sequential depth choices necessary to optimize a combination of growth and the probability of survival through a lifetime. Although the dynamic optimization technique has been used previously to predict the occurrence of vertical migration as a trade-off between predator avoidance and food aquisition (Clarke and Levy 1988, Mangel and Clarke 1988), my model is the first to use realistic representations of growth and predation risk over the entire life-history of an organism.

Model Description

Overview My model predicts lifetime fitness-maximizing depth choices for discrete size classes of S. oregonensis for each day and night period for life durations ranging from 30-70 days. For each depth there are associated growth benefits determined by food intake (depends on food abundance which varies with depth) and metabolic rate (depends on temperature which varies with depth). Also, for each depth there are associated costs due to the risk of being eaten by either of two fish predators: juvenile sockeye or stickleback. Since these fish are visual predators, risk not only depends on depth but also time of day. This is because light intensity decreases with depth and varies with the time of day. Fitness is defined as the product of reproductive output at the final time period, T, multiplied by the probability of survival to the final reproductive stage. Animals must grow to reach a minimum reproductive size above which reproductive output 130 increases linearly with weight. However, increased fitness due to greater growth may trade off with survival if feeding near the surface increases predation risk. The algorithm first calculates the optimal choice at terminal time, T, then works recursively through time to calculate the optimal combination of choices to arrive at this final outcome. The resulting decisions yield the maximum lifetime fitness which maximizes the probability of survival from time = 1 to T multiplied by reproductive success at time T (Mangel and Clarke 1988). Once optimal depth choices for each size at each time are calculated, the growth trajectory from time t=l to t=T can be modelled for any size individual at t=l. First, growth at t=l is calculated for an individual S. oregonensis of size(t=l) residing at the optimal depth. This growth is added to the size(t) to become size(t+l). This process is repeated for each time step and the size at each time is stored in a growth trajectory array. Then lifetime survival is calculated as the product of the probabilities of survival at each time step from t=l to T.

Biological Components of the Model

Cohort analysis of samples from late winter/spring of 1993 indicate that growth from egg stage to maturity takes approximately 50 to 71 days (Fig. 5-1). The default model life history duration was set at 50 days, although a range of 30-70 days was modelled. In the model, vertical migration and growth of S. oregonensis are simulated each day and night, beginning April 15. One night period and one daytime period were modelled 24-02-93

eggs <.4 4.25 4.75 5.25 5.75 6.25 6.75 7.25 7.75 8.25 >8.5

Size class (10~1 mm)

Fig. 5-1: Cohort analysis of S. oregonensis in late winter/spring of 1993 (Kennedy Lake). 132 for each day. For simplicity, I assume S. oregonensis to be semelparous in the model, although after maturity a number of egg broods may be produced before death.

Metabolism Specific rates of oxygen consumption per individual (ug

02/hr) for 5 species in the genus Diaptomus (including S. oregonensis) were determined by Comita (1968) as function of temperature (T, °C) and weight (W, ug) :

log10 specific 02 = a*T-b* log10 W + c (5.1) with a=0.0364, b=0.3418, and c=0.6182. This is converted to total consumption per individual by taking the antilog and multiplying by weight:

10910 s ecific total 02 = 10 * °2 * w (5.2)

Total 02 is converted to carbon consumed in respiration using the conversion of Parsons et al. (1984):

Cresp = Total 02 * -^-j * RQ (5.3) using an RQ (respiratory quotient) equal to 1. Temperature for each time and depth are determined from field temperature depth profiles for three sample dates during the period modelled (15-04-93, 13-05-93, and 23-06-93). Values for each day between the sample dates were estimated by linear interpolation between dates for each depth. 133 Food Intake I measured the concentration of chlorophyll a in the 3-50 um size fraction (see chapter 2 for details of method) on three sample dates at Kennedy Lake (15-04-93, 13-05-93, and 23-06-93). The sample depths were 1, 3, 5, 7, 10, 17, and 24 m. Values at 1 m intervals to 24 m were estimated by linear interpolation. These were used to relativize the estimate by Stockner et al. (1980) of total epilimnetic phytoplankton cell density in Kennedy Lake (mean = 0.91 cells per ul) across depths on each sample date:

Pz = relative chl az * Pepllimn * 24 (5.4)

where Pz = phytoplankton cell concentration at depth z and Pepiiimn = phytoplankton cell concentration in epilimnion. Phytoplankton cell densities for each day between the three sample dates were then estimated from linear interpolation for each depth between dates. Based on the list of phytoplankton cell types, cell sizes, and qualitative abundance in Kennedy Lake (Stockner et al. 1980), I assumed an average cell volume of 750 um3. From Strathmann (1967) I estimated carbon content per cell (C) from cell volume (V) as:

log10 C = 0.866 * log10 V - 0.46 (5.5)

The amount of carbon per ml of lake water at each depth is 134 determined as:

C c (5.6) ml cell

Carbon intake can then be calculated as:

intake = F * — (5.7) ml where F = filtering rate (ml/animal/day). Peters and Downing (1984) used an extensive literature survey to determine a predictive equation for copepod filtering rates:

log10 F = -1.245 + 0.534 * log10 W + 0.683 * log10 R 2 (5.8) - 0.067 * (log10 R) + 0.0001 * C - 0.0002 * M where R = food particle volume, C = volume of the experimental container, and M = experiment duration. Temperature was not a significant factor according to their analysis. I set R=750 um3, and C and M at the median values reported by Peters and Downing (1984) for their literature survey (C = 500 ml, M = 1440 min). The equation thus simplifies to:

log10 F = -0 . 07315 + log10 W * 0 . 534 (5.9)

Reported maximum filtering rate for mature S. oregonensis (Richman 1966) fall precisely on the curve for this equation (Fig. 5-2).

Growth Carbon available for growth is the difference between total carbon intake and carbon used in respiration. Carbon available 135

Fig. 5-2: Copepod filtering rates as a function body weight. General equation for copepods taken from Peters and Downing (1984), the values for mature S. oregonensis from Richman (1966). 136 for growth is multiplied by 2 (Peters 1984) to estimate total growth:

growth = (Clntake - Cresp) * 2 (5.10)

Fecundity

The metasome lengths of the smallest egg-bearing female S. oregonensis in Kennedy Lake were approximately 800 um which corresponds to dry weight of 6.33 ug (length-weight conversion for S. oregonensis from Culver et al. 1985). In the model, fecundity of S. oregonensis less than 6.33 ug was set at 0 at time T. Above 6.33 ug, the number of eggs produced increases with weight according to the fecundity/weight relationship established for Lake Erie S. oregonensis (Davis 1961).

ln{eggs) = 0.193059 * dry weight + 0.592806 (5.11)

Survival

Survival is modelled as the probability of not being eaten by sockeye and stickleback. I use the visual predation model described by Aksnes and Giske (1993) and Clarke and Levy (1988).

Feeding rate of one fish predator (f) measured as number of prey taken per unit time is determined by:

2 f = T± * n * [RD * sin Q) * v * Nprey

where T1=search time, T2=handling time, RD=reactive distance,

8=reactive field angle, v=fish swimming speed, and Nprey=prey

density. Handling time (T2) was assumed to be 0, reactive field 137 angle to be 45s, v was set at 6 cm^s"1 for juvenile sockeye and 5

_1 3 cm*s for stickleback, and Nprey was set at 2000 per m. The probability of being eaten for each S. oregonensis is then determined as:

P^obmottality=^ * f (5.13) "prey

where Nfish = fish density. For juvenile sockeye, Nfish was set at 93 0 per hectare and for stickleback at 1400 per hectare. These values correspond to the means of 10 annual point estimates for Kennedy Lake (Kim Hyatt, Department of Fisheries and Oceans, unpublished data). Reactive distance is a function of several components which include ambient light intensity. Aksnes and Giske (1993) derive a theoretical function for RD as:

Iz * Tl * Ljrey * CQ (5.14! RD N is

where Iz = light level at depth z, C0 = inherent prey contrast,

= L Prey prey length, and *S = sensitivity threshold. Values for

C0 and *S are not known. Juvenile sockeye begin feeding at a light level of about 9.3 * 10"7 lux and feeding rate reaches a plateau at about 0.093 lux (Ali 1959, his Fig. 11). Constants of the above equation were adjusted to provide RD values that increase over these same range of light levels. *S was set at 4.5

7 * 10" , and C0 was set at 0.5. In chapter 3, evidence was presented that juvenile sockeye begin feeding shortly after sunset and continue for 40 minutes to 138 an hour after sunset. Thus, in the model, juvenile sockeye feed during the night period and not during the day. The surface light intensity during feeding was set at 0.224 lux, the approximate light intensity 22 minutes after sunset on a clear night. Light intensity at each depth is determined according to equation 3.1 using an extinction coefficient of 0.401. The reactive distances of sockeye at each depth resulting from this model are shown in Figure 5-3 (top). In contrast to juvenile sockeye, stickleback in the model feed during the day only. Chapter 3 provided evidence that stickleback do not feed at the light levels that occur after sunset and before sunrise. As in my laboratory experiments (Chapter 3), I model the effect of light intensity on stickleback feeding rate using quantum units, rather than the photometric units used for the juvenile sockeye model (Ali 1959), except that daytime surface light intensity was set at 1000 lux. Maximum light intensity at the lake surface at mid-day on a clear day is approximately 2000 lux. However, intensities are lower in the morning and afternoon and are approximately halved by thin clouds, and cut by a third in average cloudy conditions (United States Navy Bureau of Ships 1952). Default ±S was set at

5 1.0 * 10" and C0 at 0.5. Experimental data (chapter 3) show that feeding rate is maximum at 1.6 uE-s^-rrr2 and nearly 0 at 0.1 i^E'S"

1-m'2. Thus, where light intensity at depth exceeded 1.6 uE, I set light intensity at these depths to 1.6 jaE-s^-m"2, and at depths at which light intensity was < 0.1 laE-s^-m"2, light intensity was set to 0. The modelled reactive distance of the stickleback at each depth during the day are shown in Figure 5-3 (bottom) . 139

Fig. 5-3: Model reactive distances of juvenile sockeye at night (top) and stickleback during the day (bottom) at each depth for 0.25 mm, 0.50, 0.75 mm and 1.00 mm size prey. 140 Predation intensity due to stickleback and juvenile sockeye was altered in the model by specifying the total number of hours each day or night that each fish actively feed.

Model Results The model results predict vertical migration only when fish predation occurs (Fig. 5-4). When neither fish species feed

(panel a), maximum fitness is achieved when S. oregonensis remains near the surface both day and night over its entire life. This strategy maximizes growth, resulting in higher fecundity. When stickleback feeding is introduced into the model (panel b and c), maximum fitness is achieved when S. oregonensis of all sizes are at depth during the day and near the surface at night. Increasing the duration of stickleback feeding from 2 hours up to 10 or more has virtually no effect on optimal depth choice. When juvenile sockeye feed for one hour, and stickleback risk is not included in the model (panel d), maximum fitness is achieved when S. oregonensis remain deeper at night than during the day. This effect is due to the night time risk of juvenile sockeye predation. Under these conditions, S. oregonensis remain quite deep during the day until about 25-30 days, after which they rise to the surface during the day and, thereafter, grow rapidly to a large mature size. However, if stickleback feeding is included in the model along with sockeye feeding, S. oregonensis migrate to deep water during the day to avoid the stickleback and rise to the surface at night to feed, although they do not rise as high at night as they do when sockeye predation is absent (panel b and c). no stickleback stickleback feed 2 hours stickleback feed 4 hours

cd n CO 0 >> 0 0 o -5 CO -10 o q. -15 c cd Q -20 -25 I I I I I i J I L 5 10 15 20 25 30 35 40 45 50 5 10 15 20 25 30 35 40 45 50 5 10 15 20 25 30 35 40 45 50

cd n "D CO 0 & J 0 -L- ^ i— O q. cd o Q CO

5 10 15 20 25 30 35 40 45 50 5 10 15 20 25 30 35 40 45 50 5 10 15 20 25 30 35 40 45 50

Days

Fig. 5-4: Model effect of stickleback and sockeye feeding on day (open squares) and night (asterisks) optimal growth and depths of S. oregonensis. Dashed horizontal line indicates the minimum size of reproduction. Phytoplankton food cell density was set to 1900 * 10 phytoplankton cells per ml. Default values were used for other model parameters. 142 While the degree of stickleback predation risk has little effect on the optimal depths chosen, it does decrease fitness by decreasing final body size (and the resulting fecundity) and lifetime survival probability (Fig. 5-5). This decrease is greater if sockeye predation is included in the model. Interaction exists between predation risk and food density effects. At 1700 phytoplankton cells per ul, probability of survival for S. oregonensis approaches 0 as predation risk increases, while at 1900 phytoplankton cells per ul, lifetime survival probability remains near 0.4. In order to reach the minimum size of maturity at the lower food density, S. oregonensis is required to increase predation risk in surface waters. Like predation risk, food density does not effect the predicted optimal depths (Fig. 5-6A). Optimal daytime depth is below 20 m for all sizes and night depth is near the surface. At

1500 phytoplankton cells/ul, S. oregonensis is unable to grow to maturity, at 1700 cells/ul the minimum size for maturity is reached but the probability of survival is very low (Fig. 5-6B). Between 1700-2500 phytoplankton cells per ul both final size and probability of survival increase. The lack of an effect of food density on mean daytime depth in the model is inconsistent with observations of such an effect by Huntley and Brooks (1982), Dagg (1985), and Johnsen and Jakobsen (1987) and the suggestion of this effect for S. oregonensis (Fig. 2.28). In the model, the optimal strategy as food density decreases is to stay deep during the day and sacrifice growth, rather than to rise toward the surface and no sockeye

sockeye feed 1 hour

Hours per day stickleback feed Hours per day stickleback feed

Fig. 5-5: Model effect of stickleback and juvenile sockeye feeding on final body size and lifetime survival probability of S. oregonensis at 1700 (solid squares) and 1900 (open squares) phytoplankton cells per pi. Dashed horizontal line indicates the minimum size of reproduction. Default values were used for other model parameters. A 15 15 _ 1.7 cells/Ml 10 _ 1.9 cells/ul

CD N 5 fi i i CO f 0

0 -5 -*—*—*— -10 Q_ -15

3 CD Vi c < £D

N O O" "to

1500 1700 1900 2100 2300 2500 Food density (cells per ul)

Fig. 5.6: Model effect of phytoplankton cell density on (A) day and night optimal depths and growth of S. oregonensis and on (B) the final body size and lifetime survival probability. Dashed horizontal line indicates the minimum size of reproduction. Juvenile sockeye and stickleback hours feeding were set to 1 and 6 respectively. Default values were used for other model parameters.

t-1 145 maintain growth at increased predation risk. In the lake, food density may increase more rapidly and/or risk of stickleback predation may increase less rapidly as depth decreases than modelled. If so, the trade-off between feeding and predator avoidance would be less driven by the latter factor than in the model, and the true optimal depths might thus decrease as food density decreases.

In the model, the minimum food density S. oregonensis require to grow to maturity is almost double the estimated food density in Kennedy Lake (Stockner et al. 1980). Estimates of energy requirements based on respiration rates also exceed estimates of energy intake for zooplankter Bythotreph.es cederstroemi (Sprules et al. 1990, Lehman and Caceres 1993,

Vanderploeg et al. 1993). For S. oregonensis, estimated energy intake assumed phytoplankton consumption only. This may be an underestimate since alternative prey types are also available (Stoecker and Capuzzo 1990, Gifford and Dagg 1991, Hartmann et al. 1993, Ohman and Jeffrey 1994, Cervetto et al. 1995). Alternatively, short-term laboratory respiration rates may overestimate long term respiration in situ. To test the sensitivity of the model predictions to S. oregonensis metabolism and feeding parameters, each was varied ± 10% of the default value while holding other parameters at default values (the effect of temperature on metabolism was varied ± 20%). Optimal depths were insensitive to variation in either metabolic rate or filtering rate parameters of S. oregonensis. Lifetime survival, as well as final body size, were 146 affected by both metabolism (Fig. 5-7) and filtering rate (Fig. 5-8) parameters. The sensitivity of the model results to the fecundity/body size relationship of S. oregonensis was tested by rotating the slope ± 50% through the mean natural log of egg number (y) and mean body size (x). Across this range, optimal depths, final body size and lifetime survival were identical. For each defined fecundity/body size relationship modelled, increases in fitness for any given increase in growth were offset by the effect of decreased lifetime survival. The default model also was insensitive to changes in the relative amount of predation for different sizes of S. oregonensis. In the default predation risk component of the model, body size of S. oregonensis affects predation risk only through its effect on the reactive distance of the predator. However, smaller sizes may also experience decrease risk through active size selection of predators that choose not to pursue smaller, less profitable, prey. Furthermore, small S. oregonensis may be at less risk than larger conspecifics due to a greater number of other small prey available in Kennedy Lake.

To test if decreased risk to small S. oregonensis would affect model results, the probability of mortality of S. oregonensis in weight classes less than 75 (corresponding to a dry weight of 0.3 87 ug and total length of 3 00 um) was multiplied 147

0.5563 0.5811 0.6058 0.6305 0.6552 0.68 0.5563 0.5811 0.6058 0.6305 0.6552 0.68 Metabolism intercept Metabolism intercept

e 1.7 cells/pi -•• 1.9 cells/Lil -A- 2.1 cells/Ml -B 2.3 cells/Ml

Fig. 5.7: Model effect of changes in S. oregonensis metabolic rate parameters at four levels of phytoplankton food density. The weight coefficient and intercept were varied ± 10% and the temperature coefficient ± 20%. Dashed horizontal line indicates the minimum size of reproduction. For each parameter varied, all other parameters set at default values. Juvenile sockeye and stickleback hours feeding were set to 1 and 6 respectively. Fig. 5.8: Model effect of varying S. oregonensis filtering rate parameters between 90-110% of default values for four levels of phytoplankton food density. For each parameter varied, all other parameters set at default values. Juvenile sockeye and stickleback hours feeding were set to 1 and 6 respectively. 149 in each time period by a factor of:

1 {7 5/weightclass)3

This alteration did not affect depth choices in any significant manner. This contrasts with the hypothesis that non-migration by the smaller individuals in migrating species is due to very low predation risk for these smaller individuals (Neill 1992, Osgood and Frost 1994 Angeli et al. 1995).

In the model system, migration by larger S. oregonensis, but not by smaller individuals could only be produced through fine tuning of certain parameters (Fig. 5.9). For instance, decreasing the metabolism weight coefficient by 6% or increasing the metabolism intercept by 2% results in non-migration of smaller S. oregonensis, but this result only occurs if sockeye predation is not included. Decreasing the filtering rate intercept by 10% or the filtering rate size coefficient by 2% also stops migration of smaller S. oregonensis, but, again, only when sockeye predation is not included in the model. In all these cases, lifetime survival probability is unrealistically low, ranging from 7.83*10~4 to 1.30*10"3. Furthermore, non- migration of the smaller sizes is only predicted when food is set at 1700 cells/ul. At higher food levels, all sizes migrate, and at lower food levels mature body size cannot be achieved. Because life history duratin is fixed in the model, smaller individuals may remain migratory to avoid higher in the surface habitat which would increase total time at larger body size and thus increase predation risk. I tested if the addition of higher predation risk for smaller individuals would cause them to stop a weight metabolism coefficient=0.3212 (6% decrrease) metabolism intercept=0.6305 (2% increase) 15 15

"55 10 3 10 13. • 1.1 i • • w 0) 5 - ^»^--t—i—

Q. CD Q

5 10 15 20 25 30 35 40 45 50 5 10 15 20 25 30 35 40 45 50 Days Days

tittering rate intercept=-0.08046 (10% decrease) filtering rate weight coefficient=0.523 (2% decrease)

(D N CO

Q. (D Q

5 10 15 20 25 30 35 40 45 50 5 10 15 20 25 30 35 40 45 50 Days Days

Fig. 5.9: Model parameter values that predict non-migration of smaller S. oregonensis. For panel a-d, phytoplankton cell densities were 1700 per pi, and stickleback feeding was set to 6 hours. For panel a and b, sockeye predation was not included, while in panel cand d, sockeye fed for 1 hour. Dashed horizontal line indicates the minimum size of reproduction. 151 migrating as a way of growing larger to avoid such risk. In

Kennedy Lake, small S. oregonensis may be under such risk from cyclopoid copepods and/or N. mercedis. However, multiplying the mortality to small individuals (weights less than 0.3 87 ug and total length of 3 00 um) by 1.5,. 2, or 4 did not cause smaller individuals to cease migrating. The inability to produce a model in which smaller individuals migrate less is puzzling since such an effect is observed for S. oregonensis and other migrating zooplankton species. Feeding and respiration of smaller S. oregonensis were calculated from rates measured for mature S. oregonensis and scaling body size effects according to inter-specific relationships available for calanoid copepods (feeding) and diaptomids (respiration). These interspecific relationships may not be accurate for different life-history stages within the species S. oregonensis. Further investigation of the feeding and respiration of immature stages of S. oregonensis may be required to understand why the smallest individuals do not migrate.

Summary The dynamic optimization model presented above demonstrates that the stickleback avoidance hypothesis is a tenable explanation for vertical migration by S. oregonensis given the conditions in Kennedy Lake. The model also predicts that this avoidance behaviour results in a lost feeding opportunity cost that lowers growth and fecundity. Because of this trade-off, remaining near the surface at all times is predicted to be optimal in the absence of predation. These model results are 152 insensitive to a wide range of variability in model parameters. Under realistic survival probabilities, the model does not produce a result consistent with the observed effect of body size on migration pattern in Kennedy Lake S. oregonensis in which small individuals tend to remain near the surface day and night and then switch to migrating only above a certain body size. 153

Chapter 6

The sis Summary (Hinde 1975) defined "function" as a beneficial consequence of a character selected and maintained through natural selection. Hinde identified three requirements for natural selection of a character and three types of evidence that support hypotheses for the function of a character. An effective summary of this thesis is provided by evaluating two hypotheses with respect to the requirements and types of evidence identified by Hinde: (1) the function of vertical migration by S. oregonensis is to avoid stickleback predation and (2) the function of remaining near the surface at all times (no migration) is to maximize food intake and growth. The first requirement for the natural selection of a character is that the character varies. Chapter 2 demonstrates that vertical migration is variable in S. oregonensis: a migratory form dominates in populations from two study lakes and a non-migratory form dominates in two other lakes. The depth distribution of individuals within lakes is also variable, particularly in the non-migratory populations. The second requirement for natural selection of a character is that this variation has a genetic basis. There is evidence that differences in vertical migration behaviour in S. oregonensis are genetic (Chapter 4). In the laboratory, when held in similar conditions, differences in vertical migration behaviour of individuals from migratory and non-migratory populations persist and neither type change their vertical distribution in response to stickleback presence/absence 154 treatments. However, these experiments do not eliminate the possibility that vertical migration behaviour is determined during development by environmental conditions (canalized). In order to test this, it is necessary to obtain egg-stage S. oregonensis from non-migratory and migratory populations and raise both types to maturity in environments with and without stickleback before comparing vertical migration behaviour. A third requirement for the natural selection of a character is that fitness consequences exist within the range of variation of the character. Although direct measures of fitness (transmission of genetic material to future generations) or closely related measures (lifetime reproductive success) were not obtained for S. oregonensis, the quantitative model presented in Chapter 5 predicts fitness effects of vertical migration behaviour based on estimates of predation risk and the physiological energetics of S. oregonensis in a simulated Kennedy Lake environment. The models predicted higher fitness for vertical migrators relative to non-migrators in the presence of stickleback due to lower lifetime probability of stickleback predation. When stickleback are absent, the model predicts higher fitness for non-migratory S. oregonensis because they do not incur the opportunity cost of lost feeding that migratory individuals do and, thus, achieve greater growth and higher fecundity. The model shows that it is tenable to hypothesize that migration behaviour affects fitness through its effect on predation risk and food intake.

One type of evidence for hypotheses concerning the function of a character is an association between the state of the 155 character and environmental factors. Vertical migration of S. oregonensis populations is associated with the presence of pelagic stickleback (Chapter 2). Alternative hypotheses for vertical migration, including juvenile sockeye predation avoidance, foraging efficiency, bioenergetic efficiency, and combined foraging/bioenergetic efficiency, are not supported by such associative evidence. The hypothesis that vertical migration results in a feeding opportunity cost (i.e. remaining near the surface at all times maximizes food intake) is supported by the association between decreased daytime mean depth of the migratory Kennedy Lake population and decreased food abundance (chapter 4). A second type of evidence for hypotheses for the function of a character are field observations that individuals that possess a character obtain a benefit relative to similar individuals lacking the character. Evidence that vertical migration of S. oregonensis is beneficial because stickleback are avoided is provided by the measurement of the timing and extent of vertical migration with respect to light-dependent stickleback feeding rates determined in laboratory experiments (Chapter 3).

Migratory S. oregonensis occupy depths during the day at which light intensity is low enough to decrease the rate of stickleback predation. Furthermore, the timing of S. oregonensis migration (upward at dusk and downward at dawn) causes them to remain below light levels at which stickleback feeding rate is maximum. A similar examination of the extent and timing of migration with respect to juvenile sockeye predation risk suggests that vertical migration does not result in a beneficial decrease in risk. 156 The hypothesis that the strategy of remaining near the surface at all times maximizes growth is also supported by observational evidence for a feeding benefit (Chapter 2) . Phytoplankton food is less concentrated in the deep habitat where migratory S. oregonensis reside during the day and S. oregonensis from migratory populations contain less gut pigments during the day than at night, while gut pigments of non-migratory S. oregonensis do not differ between day and night. Furthermore, within the migratory Kennedy Lake population, S. oregonensis captured near the surface during the day contain more gut pigments than individuals in deep water. A third type of evidence for hypotheses for the function of a character consists of experimental comparison of benefits for individuals expressing the character relative to those that do not. Ideally, such experiments allow one to relate the hypothesized function of a character to a resulting benefit through direct observation in the natural setting. The laboratory experiment in Chapter 3, which measured stickleback feeding rate as a function of light intensity, demonstrates the benefit of migration relative to non-migration by extrapolating light-dependent relative predation rates of stickleback, determined in the laboratory, to the field situation. A more direct field experiment would be to assess predation risk of S. oregonensis at different depths directly in the lake, perhaps through the use of submerged fine-mesh cages stocked with lake zooplankton and stickleback.

I did not pursue an experimental approach to test the hypothesis that remaining near the surface at all times maximizes 157

S. oregonensis growth. This could perhaps be tested by experimentally manipulating the depth of submerged cages containing S. oregonensis, constructed of fine mesh that prevents escape of S. oregonensis but allows passage of food particles.

Growth of S. oregonensis could be compared in cages that are positioned deep during the day and shallow at night versus cages that are kept near the surface and cages that are kept in deep water. If the experiment could be maintained over an entire life history of S. oregonensis, time to maturity and fecundity could also be compared. This type of experiment would also directly test a prediction shared by the bioenergetic- efficiency hypothesis and the combined foraging/bioenergetic efficiency hypothesis: growth is higher for migrators than for non- migrators . This thesis demonstrates the utility of integrating field observation, field comparisons, laboratory experiments, and modelling to evaluate competing hypotheses for the function of characters. Through this approach, it has been possible to demonstrate that the hypotheses that the function of vertical migration by S. oregonensis is to avoid stickleback predation and that the function of remaining near the surface night and day is to maximize food intake are consistent with most of the requirements and types of evidence identified by Hinde. Furthermore, alternative hypothesis are demonstrated to be inconsistent with some of the associative and observational evidence. 158 References

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