Sperm Cornpetition and Alternative Mating Tactics in Bluegill Sunfish

Peng Fu

A thesis submitted in conformity with the requirements for the degree of Master of Science Graduate Deparûnent of Zoology

Ontario Institute for Studies in Education of the University of Toronto

@3 Copyrighted by Peng Fu 2000

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Sperm Cornpetition and Alternative Mating Tactics in Bluegill Sunfish

Abstract of a thesis submitted in confonnity with the requirements for the degree of Master of Science, Department of Zoology

University of Toronto

Peng Fu, 2000

ABSTRACT

Sperm competition is one of the most active areas of research in mating systems and behavioural

ecology. This thesis examines sperm cornpetition in the context of the alternative male mating

tactics in bluegill sunfish (Lepomis macrochinïs), and contains two chapters. Chapter one

examines the fertilization success of alternative mating tactics under sperm competition, and

tests the hypothesis that sneaks win under sperm competition, as predicted by the Sneak-Guard

rnodel. Using microsatellite DNA fingerprinting, statistical models, and behavioural mesures in

the field, 1 provide the fiat confirmation of this prediction. Chapter two examines the sperm

investment strategies and mechanisms by which sneaks win. 1 identify differences between the

male mating tactics in their investrnent in gonads, sperm characteristics, ejaculate sperm density,

and competitiveness. Overall, this thesis provides a mesure of fertilization success under sperm

competition and an explanation as to how this success c m be obtained.

I thank my supervisor, Mart Gross, who was instrumental in my academic development

for the past five years. 1 am extremely gratefùl for his direction and support during both my

undergraduate and graduate studies. His passion for science and nature has left an indelible mark

on me, and 1 will always chensh the learning expenence that I have had both in the lab and in the

field. I also thank Joe Repka for his time, knowledge, guidance, and most of all, stimulating

discussions. 1 thank Bryan Neff for being both an invaluable colleague and a dear friend.

Finally, I thank Peter Abrams and Maydianne Andrade for their time and cornrnents on this

thesis.

The work on bluegil l benefited fkom the facilities of the Queen's University Biological

Station at Lake Opinicon, Ontario, and 1 thank Frank Phelan and Floyd Conner for their

assistance and expertise. 1 also thank my field assistants, Anna Lawson and Tracy Michalak, for

al1 the hard work and a fabulous field season, and Karin von Ompteda, Cory Robertson, and

Michael Berends for their assistance with laborartory analyses.

During the past year, 1 have had the benefît of several great fnends. 1 thank Julian Olden,

Trevor Pitcher, and Pedro Peres for stimulating conversations, fun-filled shenanigans, and

mernorable outings. Graduate school would not have been the same without these guys. Finally,

I would like to thank my family for their constant support and advice.

Absti-act

Acknowledgements

Table of Contents

List of Figures

List of Tables

List of Appendices

Chapter one. Who wins under sperm competitioo? The Sneak-Guard mode1 in

bluegill sunfish.

Summary

Introduction

Calculating who wins in sperm cornpetition

Methods

Results

Discussion

References

Appendices

Chapter two. Alternative male mating tactics and sperm investment in bluegill

sunfish

Fo n;v ard

Summary

Introduction

Methods

Results

Discussion

v

vi

vii

Chapter Figure Title Page

One

Two

1 A demonsiration of the importance of both behavioural and genetic 22

data in evaluating sperm competition success.

Distributions of probabilities associated with estimates of the

relative egg number and cuckolder fertilization successes.

Scbematics of the Monte Carlo simulation used to solve for the

average fertilization success of different categories of males under

sperm competition.

The relationship between testes weight and body weight in male

bluegill sunfish.

The average spem longevity and ejaculate spcrm density of male 64

bluegill sunfish.

Tne relationship between ejaculate sperm density and testes weight

in male bluegill sunfish.

Chapter Table Title Page

One 1 Summary of variables and parameters used in the maximum 28

likelihood model.

Input data for the Monte Carlo simulation analysis of the success of 34

sneaken and satellites under sperm competition with parentals and

paternity of parentals in their broods.

Chapter Appendix Title Page

One 1 Description of the Monte Carlo simulation used for the 26

determination of sperrn competition success.

Procedure for the selection of an optimal number of loci for

usage in microsatellite DNA fingerprinting of parental broods.

Input data for the Monte Carlo simulation analysis of the

success of sneakers and satellites under sperm competition with

parentals and paternity of parentals in their broods.

CWTER ONE

Who wins under sperm cornpetition? The Sneak-Guard Mode1 in Bluegill Sunfish

SmmlARY

Sperrn competition is a major force of sexual selection, but its implications for mating

system and life history evolution are only beginning to be understood. An important model for

understanding sperm competition is the Sneak-Guard model of Parker (1 990, 1998). The mode1

rnakes two key predictions: (1) sneaks will have greater ejaculate expenditure than guards; and

(2) sneaks will win in sperm competition. Only the first of these has been adequately tested.

We now test the second prediction in bluegill sunfish (Lepomis macrochirz~s). Bluegill have

both cuckolder (sneak) and parental (guard) males. Parentals make nests, court females, and

provide solitary parental care for the embryos. Small cuckolders, termed 'sneaken', dart in and

out of nests to ejaculate during female egg releases (dips). Larger cuckolders, termed 'satellites',

mimic females and ejaculate behveen the parental and his h i e female mate. Using field

behavioural data and genetic patemity analyses, we suggest that cuckolders fertilize more eggs

than parentals when they engage in sperm competition. This confims the second prediction of

the Sneak-Guard model: sneaks win in spem cornpetition.

1. LNTRODUCTION

Sperm competition is widespread in nature (Birkhead & Mdler 1998). Parker (1998)

defmes sperm competition as the "competition between the sperm fiom two or more males for

the fertilization of a given set of ova". The ramifications of sperm competition in the evolution

of mating systems and life histones are only beginning to be understood. Parker (1990, 1998)

developed the "Sneak-Guard" model to undentand sperm strategies in breeding systems where

g a r d e s (typically larger and older males) attempt to monopolize females against sneaks

(typically smaller and younger males), which attempt to steal fertilizations. Sneak-Guard

breeding systems are widespread among animal species and have often evolved into alternative

male mating tactics and strategies (Gross 1996, Tabonky 1998). The model makes two major

predictions: (1) the sneak male should have greater ejaculate expenditure than the guard male;

and (2) the sneak male should have higher patemity per ejaculate than the guard male. Several

studies have confirmed the first prediction by showing that sneak males make larger investments

than guard males in testes mass and other correlates of expenses, such as ejaculate volume,

sperm activity, and sperm longevity (e.g., Gage et al. 1995, Taborsky 1998, Peterson & Wamer

1998, Simrnons et al. 1999). However, the second prediction has proved dificult to test. It

requires an assessment of who wins on a per ejaculate or per mating basis, which requires

observations of these events and specific analyses ofpatemity. The only test of the differential

sperm competition success of sneaks and guards, performed in the laboratory using irradiated

beetles, did not report any difference (Tomkins & Simmons 2000). We now provide a test of

the Sneak-Guard model in bluegill sdsh in the wild using genetic markers and suggest that

sneaks do win the competition.

a) The Sneak-Guard model

Sperm competition is an evolutionary game between rival males for which the solution

will be an evolutionarily stable strategy (ESS) since the probability of winning depcnds on the

shategies played by other males in the population (reviewed in Parker 1998). Parker (1990,

1998) recognized that many mating systems will have asymmetries in information or spenn

competition nsk, and developed the Sneak-Guard rnodel (and the EPC model) to provide

conceptual and predictive underpinnings. In the Sneak-Guard model, males are either sneaks or

guards but not both. It is assumed that either a small proportion of males, or a small proportion

of matings, involve sneaks. It is also assumed that there is a fair rafle, without any pre-

determined advantage to each male's ejaculate (each spem counts equally), but that one male

has more information about the probability of sperm competition than the other. The asymmetry

in information is that guards only know the mean probability of sperm competition (p) but not

exactly when it will occur, while sneaks always know when they will face competition. The

asymrnetry in risk is that guards will face cornpetition in only a portion of their matings (p c 1.0)

while sneaks will always face cornpetition (p = 1.0). Thus, the strategy of the guard is shaped by

the mean risk while the strategy of the sneak is shaped by the guaranteed isk. The ESS

outcome is that (Parker 1998): (1) the sneak, because of his perfect information about sperm

competition, will invest more in competition than the guard; and (2) the sneak, assuming equal

costs of sperm, will obtain higher patemity under the matings where sperm competition occurs

because of the greater investment.

b) Maüng system and sperm competition in bluegiil sunfish

Alternative male reproductive tactics and sperm competition are very comrnon in fishes

(Gross 1984; Taborsky l998), and many species match the behavioural assumptions of the

Sneak-Guard model. A case in point is the mating system of bluegill sunfish (Lepomis

macrochinis) (Gross 1982, 1991). "Parental" (guard) males breed from ages seven to ten years

and compete in densely packed colonies for nesting sites. They attract and spawn with multiple

females sequentially and provide sole parental care to the developing embryos in their nest.

Females release eggs in distinctive actions called "dips", and they dip hundreds of times in a nest

with each dip containing a batch of eggs. Precociously maturing "cuckolder" (sneak) males

employ two alternative mating tactics termed "sneaker" and "satellite". Sneakers fint mature at

age two years and steal fertilizations From parentals by hiding near the edge of nests and darting

in and out to get beneath the spawning pair where they release sperm dunng female dips. Once

sneakers reach age four, they switch ro the satellite tactic and rnirnic females to hold a temporary

position in the nest, directly between the parental and female, during multiple female dips. Thus,

whiie sneakers have a somewhat disadvantaged position during sperm competition relative to

both parentals anci satellites, satellites have an advantaged position. Parental males actively

chase sneakers and aiso satellites when these are detected. The alternative life histories of

cuckolden and parentals are part of a single conditional strategy with both genetic and

environmental influences on the decision process detemining which life history trajectory to

follow (Gross 1996; Gross & Repka 1998).

Sperm competition only occurs when a cuckolder (sneaker or satellite) successfully

inmides into a dip. Less than 20% of dips (Gross, long term data in Lake Opinicon, Ontario) are

accompanied by successful cuckolder intrusions, and therefore matings by parentals are typically

without sperm competition @ < 0.20). In contrast, mating by cuckolders is alrnost always with

sperm competition @ = 1) (Gross 1982, 199 1).

In this paper, we set out to test the Sneak-Guard model by determining the patemity of

sneakers, satellites, and parentals under sperm competition. The first prediction of the model,

that cuckolders will invest more in sperm production, is already known through their relatively

larger testes and greater ejaculate sperm density (Gross 1982; Chapter 2). The second prediction,

that cuckolders will have higher success, has not previously been tested because such tests are

extremely dificult to conduct methodologically. A single bluegill nest has many thousands of

embryos resulting From the spawning of multiple fernales and males including the parental and

several cuckolden. Although Our lab has previously determined, using molecular markers, that

the overall patemity of parentals in nests ranges ffom 40-100% (Philipp & Gross 1994; Neff

200 l), determining the success of an individual cuckolder per dip was an outstanding empirical

and theoretical challenge.

2. CALCULATING WFIO WINS IN SPERM COMPETITION

Many challenges exist in evaluating the fertilization success of males in a mating system

like that of the bluegill. First, the success of cuckolders under sperm competition cannot be

readily evaluated from the overall patemity in a parental's brood since they only participate in a

fraction of the matings (Figure 1). Second, offspring cannot be assigned to specific dips since

thousands occur and eggs cannot be collected from dips without disturbing spawning. Third,

only the genotype of a single male, the parental, is available for parentage analyses as cuckolders

and females disperse after spawning. Fourth, the large number of cuckolden and females make

it dificult to use conventional methods of parentage analysis such as exclusion (e.g.,

Chalcraborty et al. 1988) to detemine even simple estimates such as the total success of

cuckolden in a nest (Neff et al. 2000u, b). Fifth, the large number of putative parents erodes the

resolving power orgenetic markers since a parental male is likely to share allrles with females as

well as cuckolders (Neff et al. 20004 b).

We now recognize that the calculation of who wins in spenn competition will generally

require both behavioural and genetic data (Figure 1). The behavioural data provide the

frequency at which sperm competition occun, the genetic data provide the overall outcorne, and

a statistical mode1 will link the behavioural data to the success achieved per mating to arrive at

competitive success. A useful statistical procedure is a Monte Carlo simulation (see Manly

1997) that can be used to solve for maximum likelihood solutions given the challenges descnbed

above such as the incomplete sarnpling of candidate parents and uncertainties in genetic

offspring assignments (e.g., Neff 200 1). We have therefore developed a Monte Car10 simulation

to calculate the competitive success of each of sneakers, satellites and parentals in bluegill.

The Monte Car10 simulation generated a distribution of the probability of observing the

proportion of offspring that were compatible with the putative parental male genetically (i.e.,

share at least one allele at each loci genotyped) given the cuckolder intrusion frequency and al1

possible sneaker and satellite successes in each dip under sperm cornpetition with parentals

(Appendk 1). The most likely sneaker and satellite successes were chosen as ones that had the

highest probability value. The 95% confidence interval for the sneaker success estimate was

then calculated as the value that cut-off the lower and upper 2.5% of the area under the

probability distribution given the most likely satellite estimate. The 95% confidence interval for

the rnimic success estimate was calculated analogously while holding constant the most likely

sneaker success value. Both the success and confidence calculation assumed that the a priori

probability distribution of the observed intrusion frequencies is uniform, and is the least biaçed in

the absence of additional information (for an analogous discussion, see Neff 2000, Neff et al.

20000, b).

3. METHODS

(a) Behavioural data

Behavioural data were collected by divers at natural bluegill colonies in Lake Opinicon

and by observers at an experimental pool facility near the shore during the breeding season of

1999 (late May - early July; near Chaffey's Lock, Ontario, Canada). The pools were stocked at

the begiming of the breeding season with mature cuckolders, parentals, and fernales from Lake

Opinicon at densities sirnilar to the lake (Gross 1982, 199 1).

Three to four divers hovered over each nest and collected data on female dips and the

types of males that were in the nest during the dip. Satellites were distinguished from females

since they are smaller in size and cannot accuntely emulate the dipping motion associated with

female egg releases (Gross 1982). Nests with females were nndomly chosen for data collection

and observed continuously until spawning ceased. Due to the constraint on the ability of the

observers to watch more than one nest at a tirne while accurately recording data, not al1 spawning

within a nest was recorded. However, every effort was made to record as much behavioural

observations as possible from single nests. Just before the fky dispersed some seven days later,

the parental and his brood were collected using SCUBA. The f ry and adult tissue samples were

presented in 95% ethanol for genetic analyses. The same procedure was followed in the pool

facility, except that al1 mating behaviours were recorded, by either direct observation or videos

taken fiom elevated platfoms above the water.

(b) Genetic data

Analyses were carried out on 28 nests including 5 fiom the pools. Three criteria were

used to select these nests from a total of 44: (1) a minimum of 50 dips was observed; (2)

cuckolder intrusions were observed; and (3) the parentals raised the offspring to the dispersal

stage, at which point they were collected. Each parental male was genotyped at 1 1 microsatellite

loci using the methods of Neff et al. ( 2 0 0 0 ~ ) . Following Neff et al. (2000a), the parental's allele

frequencies within the breeding population were used to determine the optimal number of loci to

be used in genotyping 46 fry randomly chosen from each brood (details in Appendix 2). In total,

5700 genotypes were generated for 13 16 individuals.

Each parental's patemity was calculated using the Two-Sex Patemity model, which

allows for the contribution of multiple fathen and mothen in a single brood (Neff et al. 2000a).

Statistical confidence (95% confidence interval) in each patemity estimate was calculated with

the Monte Car10 simulation presented in Neff (200 l) , which approximated the Two-Sex

Confidence mode1 (Neff et al. 2000b). The Monte-Carlo simulation was used to expedite the

calcuIations presented in the confidence model, which would bave been too computationally

intense to solve for today's computen given the large number of loci used.

(c) Simdafion anaiysis

A feature of the simulation model is that there is a trade-off between the number of eggs

released by fernales in matings with sperm competition and that this influences the success of

cuckolders. In a brood of a fixed size, the more eggs released in rnatings with sperm competition

relative to that without, the lower the cuckolder success value. Therefore, without knowing a

prion' the value of the relative number of eggs released under spem cornpetition (Er, assuming

females do not discriminate within cuckolden - E, = Em), we fint calculated the possible range

of Ec by nmning the simulation model while assuming that the fertilization success of cuckolders

in a single dip under competition is either 0.5 or 1.0. The solution of the value of Ec in each

simulation is the one that has the highest probability of occurrence. This calculates the threshold

Ec values for which cuckolders win under sperm competition. A biologically reasonable Ec value

was then chosen as a parameter in the mode1 From which the patemity of parentals, sneakers and

satellites under sperm competition was estimated. In al1 simulations, the relative s d v o r s h i p of

cuckolder offspring, S, or Sm, was set at 1.6, as they are 60% more likely to survive to become

mature Fry than offspnng From parentals (Neff2000; Neff & Gross in prep).

4. RESULTS

(a) Behaviorrrai &ta

A total of 8625 female dips were observed in 20 houn and 18 minutes of active spawning

in 44 nests fiom 7 colonies in both the lake and pools. On average, 10.3% of female dips

included sperm cornpetit ion, where both cuckolders and parentals spawned over the released

eggs. Sneakers participated in 8.4% and satellites in 1.9% of dips. The lake and pool

environment did not differ significantly in inmision frequencies (Me: average of 9.5%; sneakers

6.3%, satellites 3.2%; pool: average of 6.2%; sneakers 6.0%, satellites 0.2%; Kniskal-Wallis test:

sneaker - 2 = 1.28, d.f. = 1, p = 0.26; satellite - 2 = 2.08, d.f. = 1, p = 0.15). The behavioural data from the 25 nests genotyped are in Appendix 3.

(b) Geneîic data

The average patemity of parentals and cuckolders per brood is 0.8 1 k 0.15 (SD) and 0.19

2 0.15 (SD) respectively. Each patemity estimate had high precision as a result of a narrow

confidence interval (Appendix 2). The patemities are not significantly different in the lake and

pools (lake: 0.83 + 0.16 (SD) and 0.1 7 f 0.16 (SD); pools: 0.73 2 0.10 (SD) and 0.27 + 0.10 (SD); t-test: t = 1.3 1, d.f. = 26, p = 0.20). The genetic data, including compatible offspnng,

parental allele frequencies, and patemities and confidence values, are also in Appendix 3.

(c) Simrilation anaipis

If both sneaken and satellites have a competitive success of 1 .O, then fernales would have

to release 1.4 (95% CI: 1.2 - I .7) times as many eggs in dips with sperm cornpetition than

without (Figure 2a). If both sneakers and satellites have a competitive success of 0.5, then

females would have to release 4.3 (95% CI: 3.3 - 5.2) times as many eggs in dips with sperm

competition than without (Figure 2a). Therefore, when Ec = 2 - 4, cuckolders win over parentals

in sperm competition. When Ec > 4, parentals win over cuckolders in sperm competition.

However, given that an average of 10 - 12 eggs rnay be released by females in a dip alone with

parentals (Gross, unpublished data), it rnay be unlikely that females cm physically release more

than 4 tirnes as many eggs (-40) in dips accompanied by cuckolder intrusions. This large

quantity of eggs released in a single dip, which rnay be conspicuous to observes, has not been

previously documented or observed. Therefore, it rnay be much more reasonable to assume that

females can release a maximum of about 20 eggs per dip (Ec = 2), and thus cuckolders probably

win over parentals in sperm cornpetition.

Assuming the Ec = 2, cuckolders on average fertilize 76% of the eggs in a dip and

parentals fertilize the remaining 24%. More specifically, sneakers fertilize 89% of the eggs in a

dip (95% CI: 0.74-0.98; Figure Zb), which is significantly more than the 64% (95% CI: 0.42-

0.83; Figure 2b) obtained by satellites (t-test: t = 22.9, d.f. = 26,p c 0.001). Even though the

satellite success estimate rnay be largely dependent on three nests with intrusion fkequencies

above 0.1, enough resolving power exists to detect the significant difference in competitive

success between sneaken and satellites. Further, since satellites are outnumbered three times by

sneakers (Gross 1982), it is expect that fewer nests would be intnided by satellites. nius, the

few parentals cuckolded by satellites rnay not be atypical, and within cuckolders, sneakers rnay

be more successfùl than satellites in competing against parentals on a per dip bais.

Finally, as the simulation mode1 presented has not been thoroughly tested with known

data sets, and the true value of the relative egg aumber is still unlaiown (E,), the conclusions are

bea interpreted qualitatively rather than quantitatively. Additional support for the validity of the

simulation results is provided by the biological knowledge of the mating system and the sperm

investment patterns of sneakers, satellites, and parentals (see Discussion).

S. DISCUSSION

We have now confirmed the second prediction of Parker's (1 990, 1998) Sneak-Guard

model. Cuckolders, both sneakers and satellites, may be superior to parentals in sperm

competition. A cornpanion paper (Chapter 2) provides detailed biological information on the

sperm and ejaculate investment strategies of alternative tactics and shows that cuckoldea invest

more in total spermatogenesis and ejaculate sperm density, supporting the first prediction of the

Sneak-Guard model. Thus, the predictions of Parker's theoretical model have empirical support.

The only other study testing the outcome of Sneak-Guard sperm competition is the recent

investigation by Tomkins & Simmons (2000) in internally fertilizing Onthophagus beetles that

have alternative male reproductive tactics. The dimorphic males include fighters (major males -

hamed) and sneakers (minor males - homless). In the species where the Sneak-Guard mode1

applied (0. binodis), they confirmed that sneakers invest more in sperm competition than

fighten (guards). However, they did not find suppon for the prediction that sneakers would have

greater ferti k a t ion success than guards. The y acknow Iedged the arti ficial nature of the

experiment (only two matings per female, irradiation to measure patemity, laboratory setting)

and encouraged hrther studies using molecular marken and natural conditions. We have done

so here.

An assumption of the Sneak-Guard model is that sperm competition is a 'fair raffle',

namely that a male's fertilization success is proportional to his relative contribution to the spem

pool competing for a batch of eggs (Parker 1990, 1998). Elsewhere we show that cuckolden

and parentals have a fair raffle when their milt is given equal proximity to eggs, as their

fertilization success was directly proportional to the relative number of sperm in ejaculates of

equal volume (Chapter 2). However, there are interesting positional differences in the mating of

sneakers and satellites in competition with parentals (and probably in most species with

competing males) that results in "loaded raffles", where some males are 'favoured' and others

'disfavoured' . Parker ( 1990, 1998) predicts that males who are always disfavoured will

compensate by producing more sperm per ejaculate. In bluegill, sneaken are disfavoured by

their position below the parental and female, as the female dips toward the parental and their

urogenital pores corne in close contact. In contrast, satellites are favoured since they ejaculate

between the female and parental, as the female dips her urogenital pore toward the satellite.

Despite this positional advantage, satellites are infenor sperm competitors to sneakers.

We have attributed this contradiction to the greater number of mating opportunities that

satellites obtain (Chapter 2). Even though satellites may fertilize fewer eggs per mating, the

transition fiom the sneaker tactic to the satellite tactic is associated with obtaining higher

reproductive success (Chapter 2). Thus, the suprnor body position of satellites may require them

to release fewer sperm under competition but allow them to allocate their ejaculate expenditure

in more matings. Sneaken invest more in sperrn production by having larger GSIs

(gonadosomatic index) than satellites since they are in a disadvantaged mating position (Parker

1990, 1998). Their lesser number of mating opportunities rnay require them to release more

spenn under competition since their reproductive success is more dependent on out-competing

parentals. In contrast to cuckoldea, parentals have a low risk of sperm competition (p < 0.20)

and an advantaged position except in the rare cases when satellites intrude (2% of dips).

Therefore they invest the least in sperm production as measured by GSI (Chapter 2). Since they

also fertilize 4-7 tirnes more eggs than both sneaken and satellites (Gross & Charnov 1980,

Phîlipp & Gross 1994, Neff 200 1, this paper), they are the poorest sperm competitors because

they may budget the least arnount of spem per mating.

We have discovered that more eggs are release by females in dips with cuckolder

intrusions. The effect of this on the overall patemity of cuckolders in a parental brood is

equivalent to the scenario that cuckolders may be fertilizing unfertilized eggs released by

females in previous dips alone with parentals. If this is me , then cuckolders are avoiding sperm

cornpetition by fertilizing eggs abandoned by parentals, and the fertilization success of

cuckolders in dips under direct competition with parentals would decrease as a result. However,

this scenario is unlikely to be tme. First, the magnitude of sperm limitation in mating systems

such as bluegill, where males and females are in close proximity during mating, is very small

(reviewed in Yund 2000). As such, parentals rnay fertilize most of the eggs released in a female

dip and cuckolders may not be able to detect and fertilize the few eggs that may be lefi over from

previous dips. Second, cuckolder intrusions always coincide with female dips and cuckolders

specifically aim for the location of egg release (Gross 1980, 1982). This indicates that

cuckolders target new eggs releases rather than the unfertilized eggs from previous dips.

Therefore, it is unlikely that cuckolden are fertilizing unfertilized eggs abandoned by parentals.

Our finding that more eggs released by females in dips with cuckolder intrusions could either

indicate the presence of female preference or cuckolder selection for more fecund dips. We do

not yet know which process is o c c h n g , or whether both are occuriing, or whether sneaken and

satellites in fact both experience exactly the same number of eggs in each dip. However, this

does provide the start to a new avenue of research in this mating system. Finally, our model for

calculating patemities in sperm competition may have broad usage for comparative testing of the

Sneak-Guard model in the many mating systems where females release batches of eggs over

which males compete (e.g., insects, amphibians, fish).

ACKNOWLEDGEMENTS

This work was supported by grants fiom NSERC of Canada. We thank Bryan Neff,

Anna Lawson and Tracy Michalak for help with the field work

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55-75. London: Academic Press.

Gross, M.R. 199 1 Evolution of alternative reproductive strategies: fiequency-dependent sexual

selection in male bluegill sunfish. Phil. Tram R. Soc. Lond. B 332, 59-66.

Gross, M. R. 1996 Alternative reproductive strategies and tactics: diversity within sexes. Trend.

Ecol. Evol. f l,92-98.

Gross, M. R & Charnov, E. L. 1980 Alternative male life histores in bluegill sunfish. Proc. Nati.

Acad. Sci. USA 77,6937-6940.

Gross, M.R. & Repka, J. 1998 Stability with inheritance in the conditional strategy. J. Theor.

Biol. 192,44543.

Manly, B.F.J. 1997 Randornizution. bootstmp and Monte Carlo methods in biology. New York:

Chapman and Hall.

Neff, B.D. 2000 Genetic markers and breeding success: theoretical and empirical investigations

in fish. Ph.D. dissertation, University of Toronto, Toronto, Ontario.

Neff, B.D. 200 1 Genetic patemity analysis and breeding success in bluegill sunfish (Lepomis

macrochirus). J. Hered. In press.

Neff, B.D., Repka, J. & Gross, M.R. 2000a Parentage analysis with incomplete sampling of

parents and O ffspring. Mol. Ecol. 9 , 5 1 5-528.

Neff, B.D., Repka, J. & Gross, M.R. 2000b Statistical confidence in parentage analysis with

incomplrte sampling: how many loci and offspnng are needed? Mol. Ecol. 9, 529-540.

Ne& B. D., Fu, P., & Gross, M. R. ZOOOc Microsatellite multiplexing in fish. Trans. Am. Fish.

Suc. 129: 584-593.

Parker, G.A. 1990 Sperm compeiition games: sneaks and extra-pair copulations. Proc. R. Soc.

Land. B 242, 127-133.

Parker, G.A. 1998 Spem competition and the evolution of ejacalates: towards a theoiy base. In

Sperm competition and se-mal selection (ed. T.R Birkhead & A.P. Meller), pp. 3-54. London:

Acadernic Press.

Petersen, C.W. & Warner, R.R. 1998 Sperm competition in fishes. In Sperm competition and

seruol selection (ed. T.R. Birkhead & A.P. Mialler), pp. 435-464. London: Academic Press.

Sirnmons, L.W., Tornkin, J.L. & Hunt, l. 1999 Sperm competition games played by dimorphic

male beetles. Proc. R. Soc. Lond. B 266: 145-150.

Taborsky, M. 1998 Sperm competition in fish: "bourgeois" males and parasitic spawning.

Trend. Ecol. Evol. 13,222-227.

Tomkins, J.L. & Simmons, L.W. 2000 Sperm competition games played by dimorphic male

beetles: fertilization gains with equal mating success. Proc. R. Soc. Lond. B 267, 1547- 1553.

Yund, P.O. 2000 How severe is sperm limitation in natural populations of marine fiee-spawners?

Trend. Ecol. Evol. 15, 1 0- 13.

Figure 1. In order to determine the 'kinner" of sperm competition in complex rnating

systems, behavioural data that differentiate matings with and without sperm competition and

genetic data that differentiate the relative genetic contributions of sperm cornpetitors in a brood

are both needed. This is a figure of a hypothetical brood resembling a nest of bluegill sunfish in

which females release eggs in multiple dips (P = parental; C = cuckolder). (a) Genetic analysis

reveals that P fertilized 75% of al1 the eggs in the brood while C fertilized the remaining 25%.

The paternities could result from either scenario (b) or (c). in (b), 33% of the dips involved

sperm competition and C fertilized 75% of the eggs per dip. In (c), 100% of the dips involved

sperm competition and C fertilized only 25% of the eggs in those dips. Although (b) and (c) are

clearly not equivalent scenarios, either could result in the same overall patemities of P and C in

the brood. ï'herefore, behavioural data on the frequency of sperm competition must be known in

order to calculate who is the supenor sperm cornpetitor and test the Sneak-Guard model.

Figure 1.

(a) Brood

lndividual matings

Figure 2. (a) The distribution of probabilities associated with estimates of the range of

possible values of the relative egg number (Ec) for which cuckolders win in sperm competition.

Two probabiiity distributions were calculated, one with an assumed cuckolder competitive

success of 0.5 (m) and the other with a success of 1 .O (+). @) The distribution of probabilities

associated with estirnates of sneaker (a) and satellite (+) fertilization success under sperm

competition with parentals with Ec = 2.

Figure 2.

O 2 4 6 8 10

Relative Egg Number (E,)

Patemity under spem cornpetition

APPENDIX 1

The variables in our mode1 are defined in Table 1. Generally, the simulation involves

three randomization routines that are based on a defined parameter set and a variable set. The

parameter set includes the behavioural data and the genetic data, and the variables set includes

quantities that the mode1 calculates (e.g., relative cornpetitive success of each category of males).

The simulation is repeated 10,000 times for each nest from which the most-likely success of each

male category is calculated (Figure A ln, b).

The first routine in the simulation randomizes the intrusion kquencies based on the

observed data. This routine accounts for variance among nests in the number of rnatings

observed and hence the precision of the intrusion frequency estimates. The second routine

randomizes the genotypes of the cuckolden and fernales that have genetically contnbuted to the

offspring within the nest (Neff et ni. 2000~. b). This routine accounts for the incomplete

sampling of the putative parents in the genetic analysis. The third routine is the rnost complex

and is described in detail (Figure A 16). Briefly, it randornizes the genotypes of the offspnng

genetically sampled from the nest based on the results of the previous two routines and the

variable set, and determines the proportion of these offspring that are genetically compatible with

the parental male. This proportion is then compared to the observed proportion obtained from

microsatellite DNA fingerprinting. The likelihood or probability of the variable set can be

determined as the number of matches out of the 10,000 simulated. For example, if very few of

the 10,000 offspring samples at any of the nests do not match the observed proportion of

compatible offspring, then the given variable set is unlikely. Conveaely, if most of the 10,000

samples at each of the nests match the observed proportions, then the given variable set is likely.

A global maximum solution c m be found by considering al1 possible combinations of variable

sets (i.e., the variable space).

Table 1. Sumrnary of variables and parameters used in the maximum likelihood model. Parameters are known quantities inputted into the simulation while variables are quantities outputted from the simulation. A quantity cm be either input or output depending on whether or not it is known. A quantity can be neither input nor output if it is calculated exclusively in the simulation fiom the input.

Name De finition Inputlûutput

Number of dips obse~:ed for nest E Input Number of intrusions by sneaken observed in nest n hput (expressed as a proportion of D.) Number of intrusions by satellites observed in nest n Input (expressed as a proportion of D.) Effective number of fernales genetically contributing to Input offspnng in nest n Effective number of males genetically contributing to offkpring Input in nest n Number of offspring sarnpled from nest n Input Number of O ffspring genetically compatible with putative Input father in nest n

Survivorship of sneaken' offspnng from fertilization to E ither sample collection Swivonhip of satellites' offspnng from fertilization to Either sample collection Sunrivonhip of parentals' offspring from fertilization to Either sample collection

Relative number of eggs released in presence of sneaker Either Relative number of eggs released in presence of satellite E i ther Relative number of eggs released in presence of parental Either

Probability that a sneaker fertilized the egg during offspnng Neither assignment in the simulation Probability that a satellite fertilized the egg during offspring Neither assignment in the simulation Proportion of eggs in a single dip (E,) fertilized by a sneaker Output during spem competition Proportion of eggs in a single dip (E,) fertilized by a satellite Output dunng sperm competition Proportion of eggs in a single dip (E,) fertilized by a parental Output dirring sperm competition

Figure Al. Schematics of the Monte Car10 simulation used to solve for the average cornpetitive

success of different categones of males under spem cornpetition. (a) The simulation involves

seven steps. In step 1, the behavioural and genetic data are inputted. Steps 3-5 involve three

randornization routines and are repeated 10,000 times for each of the N broods and each possible

parameter set. The maximum likelihood solution is determined from the parameter set with the

highest probability of matching the observed genetic data. (b) Schematic of steps involved in

Step 5. For each of the C. offspring sarnpled from the brood, a cuckolder intrusion is

probabilistically simulated based on the behavioural observations of intrusions. If a cuckolder

does not intrude then the offspring is genetically assigned to the parental male. If a cuckolder

partakes in the mating, then Equation A l is used to determine if the cuckolder or parental

successfùlly fertilizes the egg. The calculation of who fertilizes the egg using Equation A l

incorporates the intrusion frequencies of sneakers and satellites, the relative number of eggs

released by the female, and the differential survivorship of cuckolder and parental offspnng. If

the cuckolder is successful at fertilizing the egg then a genotype is generated for the offspring

based on those generated in Step 4. The offspring genotype is compared to the parental male and

if genetically compatible (offspring shares at least one allele with the parental male at each

locus) then it is assigned to the parental male. This emulates the error in offspnng assignments

as a result of the possible similar genetic profiles of putative fathers. The routine is repeated for

each of the C. offspring.

Step 1

Step 2

Step 5

Step 6

Input Parameter Set

Setup Variable Set

Step 3

Step 4

Randomize Intrusion Frequencies - for each of D, dips randornly generate a number between O

and 1 - randomized intrusion frequency is the proportion of these

numbers that are < (I,'" + I,")

Randomize Cuckolder and Female Genotypes

- for each of M cuckolders and F mothers randomly generate multiIocus genotypes based on breeding population al1eIe fiequenc ies and assuming Hardy- Wein berg equil ibrium genotype ratios

I Randomize Offspring Genotypes

Figure Ala.

1 Caleulate Probability of Observing Genetic Data

- brised on variable set and results of steps 3 & 4 generate Cn offspring genotypes (see Figure A 1 b)

- proportion of 10,000 samples that have k, of C,, offspring compatible with the putative father (see Figure A 1 b)

-

Step 7 Determine Maximum Likelibood Solution

- variable set with highest probability of matchhg the observeci number of compatible offSpring

Figure Alb.

Step 4

Determine if Egg Release is Accompanied by Cuckolder Intrusion

- generate randorn number between O and 1 - compare number to randornized cuckolder intrusion rate (from Step 3)

I

* Determine if Cuckolder or Parental

Fertilizes Egg Under Sperm Cornpetition - generate mndom number between O and 1 - determine if number < Pr, or Pr, (depending on

if intruding cuckolder is s n d e r or satellite); Pr is calculated according Equation A 1 (bottom).

cuckoIder wins

parental wins

Generate Offspring Genotype

- mdomIy select cuckolder's and rnother's genotypes ( h m Step 4)

- generate offspnng genotype based on Mendefian inheritance

* Y= Increment Number of Offspring that are

Compatible with the Putative Father I

Step 6

Equation A 1 : Pat,. Ii -4 -Si Ri =

(1-1, -I,)- E;S, +r; Esn*Ssn +[ , -AT, -Ssu 1 i can either be sn or sa.

APPENDIX 2.

The loci selection process for each parental, developed in accordance with the Two-Sex Paternity

mode1 presented in Neff et al. (2000a), is as follows. First, the expected proportion of the total

next generation individuals (NGIs) that is genetically compatible with the putative parental by

chance (NGdud) is calculated for each locus. The lower the NGdd value, the greater the resolving

power of that locus in excluding non-compatible offspring from the putative parental. Second,

al1 loci were ranked based on their NGdad values for each parental. A cumulative AGdud value

was then calculated as a multiplicant across al1 loci for each parental. The lower the cumulative

NGddd value, the greater the resolving power of that combination of loci in excluding non-

compatible offspring From the putative parental. A cumulative NGUd value of 0.1 was chosen as

the threshold of acceptable resolving power for a combination of loci. Finally. the physical

properties of each locus were exarnined for their appropriateness to be genotyped in a multiplex

(see Neff et al. 2000~). Generally, combinations of loci with high resolving power and non-

overlapping alleles were selected to genotype the brood of each parental.

APPENDIX 3.

Exact input data for the Monte Carlo simulation analysis of the success of sneakers and satellite

under sperm cornpetition with parentals and the paternity of parentals in their broods. The

behavioural data are compnsed of the total number of dips observed in a parental nest and the

cuckolder intrusion Frequencies, expressed as a proportion of al1 dips in a nest accompanied by

sneaker and satellite intrusions. The genetic data is compnsed of the number of offspring out of

the 46 sampled that appear to be compatible with the brood guarding parental and the parental's

combined allele frequencies at each of the microsatellite loci used. The combined allele

frequencies are calculated according to Neff et al. (2000a). The patemity and confidence

analysis was conducted following Nef€ et al. (2000a, b).

ci-

;=. I b ci- p? O d ;=.

O ci cn c?- e O' mi' - (O m' \o' vr 00' 2 2 2 22 22 C? ? V!99. '=? '? C O O O O O C

CHAPTER Two

Alternative male mating tactics and sperm investment in bluegill sunfish

FORWARD

Chapter Two includes some data and analyses from my ZOO 499Y independent research

project, Department of Zoology, University of Toronto (September 1998 - May 1999). These

are described in sections (b), (c), (4, and V) of Materials and Methods. Sections (b) and (4

were modified andor re-analyzed for this thesis. The Introduction and Discussion of these

sections are entirely new. Al1 other data analyses are original, and were performed during my

residency as a M.Sc. graduate student (September 1999 - October 2000).

SUMMARY

Although alternative mating tactics are found in the males of many species, little is

known about their adaptations to sperm cornpetition and the mechanism by which they obtain

fertilization success. We now report on the sperm investment strategies of parental, sneaker, and

satellite male bluegill sunfish (Lepontis macrochirus). We find that different investments in

testes, sperm characteristics, ejaculate sperm density, and competitiveness can be explained by

tactic-specific differences in fertilization behaviour, tradeoffs behveen somatic and gonadal

investment, sperm competition risk, and total mating opportunities. We show that there is

disruptive selection on body size in cuckolden and that sneakers make the transition to satellites

because the latter obtain more mating opportunities and greater reproductive success. Parentals

have absolutely larger testes than both sneakers and satellites, while sneakers and satellites have

larger testes relative io body size. Although the relationship behveen testes size and body size is

positive in al1 three mating tactics, they are linearl y discontinuous and there fore allometry cannot

explain the difference in absolute testes size among parentals, sneakers, and satellites.

Furthemore, while the size of sperm did not differ between the three mating tactics, parentals

had longer lived sperm than both sneakers and satellites. Finally, the ejaculate sperm density of

satellites was greater than that of sneakers, which in ni was greater than that of parentals. We

find that the success of males under competition is at least in part attributed to the number of

sperm released in the ejaculate and thus provide confirmation to the theoretical assumption that

sperm cornpetition may operate as a "rafle".

1. INTRODUCTION

In many species, males have alternative mating tactics (Gross 1996). These males often

engage in sperm competition, with the ejaculates from males with different tactics competing to

fertilize the same egg(s) (Parker 1998; Taborsky 1998). Parker (1 990, 1998) proposed the

Sneak-Guard mode1 of sperm competition in which certain males, the guarders, are paired

permanently to females while other males, the sneakers. specialize at stealing fertilizations. He

predicted that sneaks should be supenor sperm competiton because they typically experience

much higher levels of sperm cornpetition than the guards. In a cornpanion paper, we provide the

first confirmcition of this prediction by demonstrating that, in bluegill sunfish (Lepomis

macrochinrs), the sneak-like cuckolders are superior spem competi tors to the guard-li ke

parentals (Chapter 1). We now address the mechanism by which supenor fertilization success

can be obtained.

Sperm and ejaculate investment by males with alternative mating tactics has been studied

in only a few systems. Gage et al. (1995, 1998) compared precocious parr (sneakers) and

anadromous males (guarders) in Atlantic salmon (Salmo salar) and found that parr invested more

in total spermatogenesis, which was measured by testes size and sperm number relative to body

size in stripped ejaculates. The sperm morphology of the two mating tactics was similar, but pan

sperm lived longer. Stockley et al. ( 1 996) f o n d that fertilization success in the common shrew

(Sorer araneus) was higher among guarders with absolutely larger testes and sneakers with

greater sperm counts. Taborsky (1998) suggested that the investment in testes versus body mass

differed between sneakers and guarders in the European ocellated wrasse (Symphodus ocellutus),

with the relationship being negative in sneakers but positive in guarders. Schiirer & Robertson

(1999) found that, in bluehead wrasse (Tholassoma bifasciatum), the srnaller and more

promiscuous initial phase (IP) males had greater ejaculate sperm density and invested more in

daily ejaculate expenditure than the Iarger and more solitary terminai phase (TP) males. The

sperm of these two tactics did not differ in size. Overall, these studies suggest that the sneak

tactic typically invests more in sperm and ejaculates than the guarder tactic, and that this

elevation in investment is typically conelated w-ith the higher level of sperm competition

experienced by sneakers. However, as implicitly assumed in the Sneak-Guard mode1 of Parker

( 1990, 1998), the trade-off between obtaining mating opportunities and fertilization success

within matings rnay also effect sperm and ejaculate investments. In this paper, we investigate

the iactic specific differences in sperm and ejaculate investrnent in male bluegill sunfish and

address the relationship between mating opportunities. sperm investment, and competition

success.

Bluegill mating system

Male bluegill sunfish have a discrete polymorphism in life histones termed "parental"

and "cuckolder", and both spawn in the same nests (Gross 1982). While parentals are

specialized nest and mate guarders, cuckolders are specialized sperm competitors that gain entry

into parental nests as either "sneakers" or "satellites". Sneakers are cryptic and satellites are

female mirnics. Male bluegill, therefore, are characterized by three mating tactics (parental,

sneaker, and satellite), and sperm competition occurs when sneakers or satellites intrude upon

matings between parentals and females. The characteristics of the mating tactics that are

relevant to this study are: (1) parentals experience sperm competition in less than 20% of

matings while cuckolders experience spem competition in nearly 100% of matings (Gross, long

term estimate in Lake Opinicon, Ontario); (2) parentals fertilize 4-7 times more eggs than

cuckolders in a breeding season and thus have greater mating opportunities (Gross & Chamov

1980; Philipp & Gross 1994; Neff 200 1); (3) larger parentals obtain more mating opportunities

and eggs than smaller parentals (Gross & MacMillan 198 1); (4) cuckolders are superior spenn

competitors than parentals shce they fertilize more eggs in a "dip*' or rnating (Chapter 1); (5)

sneakers may be better sperm competitors than satellites (Chapter 1); (6) satellites gain closer

proximity to fernales during spawning since they ejaculate directly between the parental and

female while sneakers are usually undemeath (Gross 1980, 1982; Gross, unpublished data); and

(7) sneakers and satellites do not usually compete against each other, as sirnultaneous nest

intrusions by multiple cuckolden are rarely observed (Gross 1980; Gross, unpublished data).

Predictions

We formulate a number of predictions fiom the literature and our earlier work regarding

the spem and ejaculate investment strategies of parental, sneaker, and satellite male bluegill.

These predictions are empirically tested, and several are confirmed while others are rejected. We

evaluate the significance and ments of these predictions in the Discussion.

(a) Cuckolder mating opportunities

We predict that (i) intermediate sized cuckolders should be the least successful in

obtaining mating opportunities. Dimptive selection (e.g., Gross 1985) should favour smaller

sneakers and larger satellites. Smaller sneakers are more cryptic while larger satellites more

closely match fernales in size (Gross 1982).

We predict that (ii) parentals will have absolutely larger testes than cuckolders, and that

(iii) parental gonad sue will positively correlate with body size. These predictions are based on

the knowledge that parentals may optimize gonadal investment (Shapiro et al. 1994) so as to

fertilize the 4-7 tirnes more eggs that are available to them, and that larger parentals fertilize

more eggs than smaller ones (Gross 1982; Philipp & Gross 1994; Neff 200 1). Within

cuckolders, we predict that (iv) satellites should have absolutely larger gonads than sneakers,

since the developmental transition fiom sneaker to satellite implies that satellites fertilize more

eggs (Gross 1982). Gonads should (v) decrease in size with increasing body size in sneakers and

should (vi) increase in size with body size in satellites. This is due to the reduced nurnber of

mating oppominities for cuckolders of intermediate sizes.

We predict that (vii) cuckolders have a larger gonadal-somatic index (GSI) than

parentals, sincc cuckolders are specialized parasites that use their soma more purely as a vehicle

to deliver spem, while parentals use their soma also to constnict nests, guard mates. and provide

care to the offspnng (Gross 1982; Taborsky 1998). Parker's (1 990, 1998) Sneak-Guard mode1

also predicts that cuckolden will have a larger GSI, since cuckolders almost always mate under

spem competition while parentals only rarely mate under sperm competition. Within

cuckolders, (viii) sneakers will have a larger GSI than satellites since sneakers must compensate

for their relatively disadvantaged body position (Gross 1982; Parker 1990; Gage et al. 1995).

(c) Sperm morphology

We predict that (k) cuckolders and parentals will ciiffer in sperm morphology. It has

previous been docurnented that sperm competition favours the production of larger sperm, which

may be faster or more cornpetitive (e.g., Radwan 1996; Otronen et al. 1997; LaMunyon & Ward

1999; Simmons et al. 1999). Therefore, as cuckolders experience more sperm competition than

parentals, cuckolder sperm should be larger. However, it should be noted that two other shidies

in fish failed to fmd a difference (e.g., Gage et al. 1995, 1998; Schiirer & Robertson 1999).

(d) Sperm longeviv

We predict that (x) cuckolders will have longer lived sperm, reflecting a cornpetitive

advantage of greater spem energetics (e.g., Gage et al. L 995, 1998).

(e) Sperm qiiantity

We predict that (xi) cuckolders will have greater sperm density in their ejaculates than

parentals. Cuckolders, but not parentals, are Iimited in body cavity for the storage of milt (Gross

1982). Furthemore, since cuckolden are almost always under spem cornpetition, they may

require denser ejaculates to release a larger nurnber of sperm more quickly, as suggested by

Scharer & Robertson (1999). Within cuckolders, (xii) sneaken will have the greatest sperm

density since they are most constrained for body cavity space, and higher densities may be

required to release sperm more quickly due to the short of amount of time that they spend in

nests.

fl Ejacit late competitiveness

We predict that (xiii) the competitiveness of bo!h cuckolder and parental ejaculates

should be correlated with the number of sperm released. This relationship has been assumed

(e.g., Parker 1998) but never demonstrated.

2. MATERIALS AND METHODS

Behavioural observations at colonies, and CO llections of breeding bluegill including

cuckolders, parentals, and gravid females, were made in Lake Opinicon, Ontario dunng the

breeding seasons of 1984, 1996 and 1999 following the methods described by Gross (1980,

1982). Data from different years of collection were not combined in subsequent analyses.

(a) Cuckolder mating opportzmities

Mating observations were made at 36 nests in five colonies in three spawning bouts.

Female dips were counted, and the number and types of males that partook in spawning were

recorded. Each spawning cuckolder was visually classified as either small or large sneaker and

small or large satellite. Small sneakers and large satellites were assumed to be ages 2 and 5

yean respectively (Gross 1980, 1 982). Since intermediate sized cuckolders are known to adopt

either the sneaker or satellite tactics, large sneakers and srna11 satellites were both assumed to be

of ages 3-4 years old (Gross 1980, 1982). The ratio of the number ofindividuals in each of the

four size category of sneakers and satellites is 1 : 0.42 : 0.40 : 0.069 (Gross 1982, Table 5). The

total intrusions Frequency, and hence the relative number of mating opportunities, for each

cuckolder size class was caiculated as the number of successfbl inmision divided by the total

number of dips observed, The relative intrusion frequency per individual for each cuckolder size

category was calculated as the total intrusion fiequency divided by the relative size of the age

cohort. Assuming equal mortality rates and a constant population size over rime, the theoretical

average reproductive success for individuals who remain as small sneakers throughout their

reproductive lifespan (RS,) and those who make the transition from sneakers to satellites (Rli,)

c m be calculated as:

Here, FS' and FS, are the average per dip fertilizadon success of sneakers (0.89) and satellites

(0.64) when they intrude into parental nests and engage in sperm competition (Chapter l), and

I.,, 6 , I,,, and b are the relative, per individual intrusion Frequencies of small sneakers, large

sneakers, srnall satellites, and large satellites respectively .

The behavioural data were collected by P. Fu and field assistants during the field season

of May - M y 1999.

(b) Gonadal invesmeni

Forty-eight sneakers, 27 satellites, and 69 parentals collected at colonies before spawning

were weighed, and their testes were removed and also weighed. The gonadosornatic index (GSI)

for each tactic was calculated as GSI = (gonad weightftotal body weight) x 100.

The body and testes measurement data were collected by P. Fu, B.D. NeE, and field

assistants during the field season of May - July 1996.

(c) Sperm morpltology

Milt fiom live males was obtained, preserved, and filmed using scanning electron

microscopy (Hyat 1974; Bovola & Russell 1992). Three sperrnatozoa images were measured

for each of 10 males (five cuckolders and five parentals) using a digitizîng tablet and AutoCad

R12. Spermatozoa head and rnidpiece were identified following Wicker & Huish (1982) and the

length and width of each were measured as cross-sectional distances. The flagellurn was traced

as a hi&-resolution polyline sketch. Each sperm was measured three times to increase precision

and the means were used in the subsequent analysis. Sperm morphology was compared between

the cuckolder and parental life histories, and sperm from sneakers and satellites were analysed

together due to the srnall sarnple size.

The spenn specimens were collected by P. Fu and B.D. Neff during the field season of

May - July 1996, and the sperm morphology data were collected by P. Fu in Septernber 1997 -

May 1998.

(d) Spem longevity

Equai volumes of milt were collected from 7 sneaken, 6 satellites, and 10 parentals with

graduated syringes and mounted on glass slides. The spermatozoa were "dilution-activated"

(Scott & Baynes 1980) with lake water and observed under a compound light microscope with

400x magnification. Sperm longevity was estimated as the time from activation until 80% of

. the spematozoa within the field of view were no longer motile. Measurements were repeated

four times for each male, twice by each of two observers. There was high consistency among

observations and between the two observers (ANOVA: FJ2, = 1.65, p = 0.2 1 ).

The sperm longevity data were collected by P. Fu and B.D. Neff durhg the field season

of May - July 1996.

(e) Spem quantity

Ten microlitres of fiee-flowing milt were collected from 22 sneakers, 26 satellites, and 76

parentais. Two microlitres per male were diluted in 1 millilitre of water and thoroughly mixed.

Six microlitres of the dilution were injected into a Bright-line hemacytometer (American

Optical), and the sperm were counted in five 0.2 mm x 0.2 mm grids under a compound light

microscope at 400~ magnification. Spem density was calculated by multiplying the mean

spenn count per grid by the dilution factor and volume. The gonads of the males were then

removed and weighed. The weight change in gonads due to the removal of milt was negligible.

The sperm longevity data were collected by M.R. Gross and assistants during the field

season of May - July 1984.

If) Ejacdate competitiveness

Milt and eggs were sûipped from 4 cuckolders, 4 parentais and 3 fernales. Equal

volumes of milt from a cuckolder and a parental were mixed, dilution-activated, and the paired

milt was released over a sample of 30 - 100 eggs from each femaie. The containers with milt

and eggs were placed in an aquarium of lake water maintained at ambient temperature for

incubation. The embryos were reared for a week and then preserved in ethanol. Rearing was

not successful in 6 of the 16 trials (4 cuckolders 4 parentals) but the remaining 10 trials still

represented a thorough combination of cuckolder-parental cornpetition pairs as eac h individual

was used in either 2 or 3 trials. DNA was isolated from the adults and fry, and microsatellite

fingerprints were obtained using multiplex genotyping (Neff et al. 2000). Up to five primer sets

(presented in Colbume et al. 1996; Neff et al. 1999) were simultaneously amplified and al1

competing parental and cuckolder offspnng were unambiguously identified using exclusion

methods (e.g., Chakraborty et al. 1988).

The experimental fertilization trials were carried out by P. Fu, B.D. Neff and assistants

during the field season of May - July 1996, and the DNA fingerpnnting was performed by P. Fu

in September 1997 - May 1998.

Statistical calculations were performed with SPSS (version 9.0). Al1 mean values are

expressed with plus or minus one standard deviation and al1 statistical testes were performed

with two-tailed levels of significance. AI1 regression dope cornparisons were performed using

Student's t-tests (Zar 1996) and a11 ANOVAs were perfonned assuming an unbalanced design

with Type III sum of squares. Specifically the numbers of mating opportunities were compared

among al1 size categories using X' tests with the expected values calculated as the total number of

mating oppominities obtained by al1 categones divided by the relative size of the age cohorts

(based on body size, as reported in Gross (1982)). The relationships between gonad weight and

body weight within parentals, sneakers, satellites, and cuckoldes as a whole were tested with

both linear and n a m l logarithmic regressions. A natural logarithmic regression was used when

analysis of residuals from a linear regression revealed deviations from homoscedasticity (Zar

1996). The GSI and absolute gonad weight of the life histories were compared using an

ANOVA and Tukey's post hoc analysis. Sperm morphology was compared between life

histories with an ANOVA with measurements of different sperms for the same individual as

repeated measures. Sperm longevity between mating tactics was tested using an ANOVA with

the four observations from each individual as repeated measures. Sperm quantity between

mating tactics was tested using an ANOVA with Tukey's post hoc analysis. The relationship

between sperm density and gonad weight within the three mating tactics was investigated with

linear regressions. The proportional paternity data were arcsine square root transformed to

eliminate mean-dependent variation (Zar 1996). The relationship between absolute gonad

weight and fertilization success was examined with Spearman's non-pararnetric statistics with 2-

tailed measures of significance on z-scored values. For example, when testing the effect of

parental gonad weight on parental fertilization success, ranking parental patemity and gonad

weight within trials with the same cuckolder using z-scores controlled differences among

individual cuckolders.

3. RESULTS

(O) Cuckolder mating opportunities

In total, 7471 dips were observed in the nests of parentals. Cuckolders attended 766

(10.3%) and the parental was alone in the remainder. The opportunities for cuckolders varied

with their size and tactic. Small sneakers, large sneaken, srnall satellites, and large satellites

attended 6.0% (450 dips), 1.3% (98), 1.2% (92), and 1.7% ( 1 26) of dips, respectively. The

relative intrusion ftequency per individual cuckolder in each category was &O%, 3.1%, 3.0%,

and 25% respectively. Therefore, on an individual basis, satellites obtained about three times as

many matings as sneakers. Cuckolden of intermediate sizes were the least successful at

obtaining mating opportunities while large satellites were the most successful. If cuckolden

were to remain as small sneaken for their entire reproductive life span (4 years), their relative

average reproductive success would be 0.053. When cuckolders rnake the transition from

sneakers to satellites, their relative average reproductive success would be 0.065. Therefore,

sneakers become satellites because the latter is more successfùl.

(b) Gonadal hvestment

Testes size differed significantly between parentals ( 1.82 * 0.56 g), satellites (0.62 * 0.19 g), and sneakers (0.20 0.10 g) (ANOVA: Fzlw = 249.90, p < 0.001). The GSI of sneakers

(3.66 * 1.45) and satellites (3 -74 1 .O6) did not differ (ANOVA: Ft = 106.44, p = 0.93), but both were significantly greater than that of parentals ( 1.32 * 0.29) @ost hoc: p < 0.00 1). There was a positive linear relationship between parental gonad weight and body weight (r' = 0.60, d.f.

= 67, p < 0.00 1; Figure la). In cornparison, there was a positive natural logarithmic relationship

between cuckolder male gonad weight and body weight (r2 = 0.83, d.f = 73, p c 0.001; Figure

Ib). More specifically, there was a positive linear relationship within sneakers (2 = 0.48, d.f. =

46, p < 0.001) and within satellites (2 = 0.54, d.f. = 25, p c 0.001). The slope of the regressions,

or the rate of increase of gonad weight with body weight, was significantly greater for sneakers

than satellites (t-test: t = 2.92, d.f. = 7 1, p c 0.005).

(cl Sperm morphologv

No significant difference was detected between the morphology of parental and

cuckolder sperm (ANOVA - tail length: Fi,s = 0.37, p = 0.56; head width: FiVs = 1.07, p = 0.33;

head length: FI,8 = 0.18, p = 0.68; mid-piece length: = 1.86, p = 0.32; mid-piece width: Fi.s =

0.053, p = 0.83). There was little variation within the measured morphological characten (rnean

coefficient of variance - cuckolders: 0.1 1 * 0.06; parentals: 0.16 * 0.07), and there was high repeatability among the three measurements for each morphological chancter (the standard

deviations did not exceed 5 percent of the mean), which gives confidence to the measurement

technique.

{d) Sperm Longevity

Parental sperm lived 40% longer than the sperm of cuckolders (parentals: 159s k 30s,

sneakers: 109s * 19s, satellites: 120s * 33s; ANOVA: FZt3 = 7.66, p = 0.003; Figure 2a). There was no significant difierence within cuckolden, between sneakers and satellites @ = 0.75).

(e) Spem quantiîy

In equal volumes of ejaculate, cuckolders had more spem than did parentals. The

density of sperm produced by satellites exceeded that of sneakers which in tum exceeded that of

parentals (satellite: 2 . 0 ~ 107 0 . 4 ~ 10' per mm3; sneaker 1 . 4 ~ 107 * 0 . 2 ~ 107; parental: 9 . 0 ~ 1 o6 k 1 .0~10~ ; ANOVA: FZ,12d = 290.25, p < 0.001; Figure 26). Sperm density was linearly related to

gonad weight in cuckolders (cuckolders: # = 0.57, d.f. = 46, p < 0.00 1; Figure 36). Sneakers and

satellites had similar relationships (sneakers: 2 = 0.26, d.f. = 20, p = 0.02; satellites: r? = 0.50,

d.f. = 24,p < 0.001; t-tesr: t = 0.38, d.f. = 44, p > 0.50). There was no significant relationship in

parentals (7 = 0.0 L 5 , d.f. = 74, p = 0.29; Figure 30).

fl Ejaczrlate competitiveness

There was a significant positive correlation between patemity and gonad weight in

cuckoldes (p = 0.82, n = 10, p = 0.004). There was no such relationship in parentals (p = 0.26,

n = 10, p = 0.46 1). Since cuckolder gonad weight c m be used to predict their ejaculate spem

density, the patemity of cuckolders is correlated with the number of sperm present in the snipped

ejaculate.

4. DISCUSSION

We have tested 13 predictions from the literature and our earlier work regarding the

mating opportunity and sperm investment strategies of the alternative male mating tactics in

bluegill sunfish. Of these, 8 were confirmed and 5 were refuted.

(a) Ciickolder mating opportunities

As predicted, small and large cuckolders had more mating opportunity than did

intermediate sized cuckolden relative to their age-cohort size. This may be because intermediate

size cuckolders could not sneak as well as smaller sneakers or mirnic females as well as larger

satellites. In addition, we found that satellites were the most successful individuals in gaining

access to matings and in obtaining reproductive success. This confirms the assumption that

sneakers malce the transition to satellites because the latter tactic fertilizes more eggs (Gross

1982). Disruptive selection that is associated with the extreme body sizes of different mating

tactics is also found in salmon, where large males fight and small males sneak (Gross 1985;

Flemming & Gross L 994). To our knowledge, this study is the first to repon disruptive selection

within a single reproductive life history.

itals had absolu

(b) Gonadal investment

As predicted, paren itely larger gonads than cuckolders. This is may be due

to the greater number of matings that parentals have access to since they fertilize 4-7 times more

eggs than cuckolders. We can reject the notion that the difference in testes size arnong

alternative tactics are due to allometry alone, since the relationship between testes size and body

size is linearly discontinuous between sneakers, satellites, and parentals. In addition, as

predicted, satellites have absolutely Iarger testes than sneaken, possibly a result of the larger

number of matings that they have access to and the greater number of eggs that they fertilize.

Gage et al. (1995) and studies in Tabonky (1998) have also shown that guarding males have

absolutely larger testes than sneakers. The total number of eggs available to males of alternative

tactics may explain the differences in absolute gonadal investment between alternative mating

tactics.

As predicted by Parker's (1990, 1998) Sneak-Guard mode1 of sperrn competition,

cuckolders have a larger GSI than parentals. For cuckolders, Parker's prediction implies that the

return in reproductive success fiom investing in testes, and therefore higher success in sperm

competition, outweighs the reduced retum fiom investing in soma and rnating opportunity.

Although not confirmed in this study, Gross (1982) in fact found that sneakers do have a greater

GSI than satellites, as predicted by their more disadvantaged mating position (Gage et al. 1995;

Parker 1998). This suggests that the reproductive success of sneaken Iargely depends on their

success under sperm competition in a fewer number of rnatings, while that of satellites and

parentals rnay depend more upon their total mating oppominities.

As predicted, parental testes size increased with body size (also Gage et al. 1995,

Taborsky 1994). Contrary to prediction, testes size did not decrease with body size in sneakers.

Since large sneakers have fewer mating opportunities than small sneakers, we expected that the

testes of large sneaker would actually be smaller. The increase in testes size with body size in

sneakers may be a result of adaptive compensation in gonadal investment since meaken have a

disfavoured mating position under sperm competition (Parker 1990, 1998; Gage et al. 1995). In

addition, since large sneakers obtain few mating oppomuiities than srnall sneakers, the value of

each mating increases as sneakers increase in body size. Thus, Iarger sneakers may invest in

absolutely larger testes to increase their fertilization success per mating. As predicted, large

satellites have larger testes than srnall satellites, but this may be due to either their increased

mating opportunity. Overall, the relationship between testes size and body size was logarithmic

in cuckolders, with satellites having a lower rate of increase than sneakers. The difference in the

relationship between testes size and body size between the alternative tactics could be a result of

the different renims in reproductive success gained by alternative tactics in somatic versus

gonadal investment. Larger parentals invest in larger testes since they obtain more eggs than

srnalier parentals (Gross & MacMillan 1984), and satellites may have a lower rate of investment

in testes than sneakers since increased investment in somatic development make them more

convincing female mimics.

(c) Sperm rnorpllology

Contrary to the prediction that cuckolders rnay have larger sperm, there was no difference

in the sperm morphology of cuckolden and parentals. Although it is thought that sperm size

should decrease with competition in extemally fertilizing fishes (Stockley et al. 1997). a lack of

difference in the sperm size between alternative mating tactics was also f o n d in Atlantic salmon

(Salmo salar, Gage et al. 1995) and bluehead wrasse (Thalassoma bifmciatum, Schiirer &

Robertson 1999). This could indicate that the cross-species trend in sperm size may not be

dependent on sperm competition but other correlated aspects of mating systems such as egg size

or the ecology of the aquatic environment in which fertilization takes place (e-g., Stockley et al.

1996; Petersen & Warner 19%).

(d) Sperm l o n g w

Contrary to the predictions that cuckolders have longer lived sperm, as f o n d for the

precocious parr in Atlantic salmon (Gage et al. 1993, we found that parental males have the

longer lived sperm. This contradiction rnay be due to differences in the two mating systems. in

Atlantic salmon, both anadramous males and precocious parr rnay experience similar intensities

and risks of sperm competition as several anadromous males and precocious pan typically

participate in a single spawning (Fleming 1996). The precocious parr in Atlantic salmon was

thought to have a disadvantaged mating position and this rnay select for greater sperm longevity

(Gage et al. 1995). In contrast, parental bluegill experience a relatively low intensity and risk of

sperm competition as compared to cuckolders. The longer fertilization window available to

parentals rnay select for the release of relatively fewer longer lived sperm. Cuckolden, since

they always experience sperm competition, rnay release more shorter-lived sperm. As there rnay

also be a trade-off in sperm longevity and speed, cuckolders rnay produce faster sperm that could

also out-compete parental sperm by fertilizing eggs faster (Levitan 2000). Sperm speed,

however, remain to be investigated. Overall, we propose that longer lived spem is not

exclusively a characteristic of sneaker tactics, but that sperm longevity may be correlated with

the availability of unfertilized eggs.

(el Sperm quantity

As predicted, cuckolders have greater ejaculate spem density than parentals. This is

consistent with the finding in bluehead wcasse (Schiirer & Robertson 1999), where the

cuckolder-like initial-phase (P) males have greater ejaculate sperm density than the parental-like

terminal-phase (TP) males. The higher spem density of cuckolders may be due to their

limitation in body cavity for sperrn storage (Gross 1982) or selection for the ejaculation of sperm

at a greater rate when under spenn competition (suggested by Schiirer & Robertson 1999).

Contrary to prediction, satellites had greater ejaculate sperm density than sneakers. This may be

because, given their decreased investrnent in gonadal development, satellites require a tighter

packaging of sperm so as to meet the demands on sperm output for the four times more mating

opportunities that they obtain.

(B Ejacdute competitiveness

As predicted, we found that fertilization success was correlated with the number of sperm

released in an ejaculate. Although this result is only explicitly demonstmted in cuckolders, the

same should hold tme for parentals, although we were not able to manipulate their ejaculate

spenn number. Since the fertilization experiment eliminates the effect of proximity, it

demonstrates that ejaculate sperm number plays a role in determining a male's fertilization

success under spem competition. This confirms that sperm competition in extemally fertilizing

species may operate as a raffle, which has been assumed in several theoretical models (reviewed

in Parker 1998).

ACKNOWLEDGEMENTS

We thank Silvia D'Arnelio, Luca Cargenelli, Tamara Janasik, Anna Lawson, Tracy Michalak,

and Jemifer Moran for help with data collection, and Bruce Smith of Ithaca College for the use

of his microscopy equipment. This work is supported by gants from NSERC of Canada.

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