Evolutionary Ecology 1998, 12, 855±870

Evolution of contest competition and its eect
on host±parasitoid dynamics
MIDORI TUDA1 * and YOH IWASA2
1
Department of Systems Science, University of Tokyo, Komaba, Meguro 153 and 2 Department of Biology, Faculty of Science,
Kyushu University, Fukuoka 812-8581, Japan

Summary
In experimental populations of the cowpea bean weevil Callosobruchus maculatus (Coleoptera: Bruchidae) anda parasitic wasp Heterospilus prosopidis (Hymenoptera: Braconidae), large changes in the abundances and the¯uctuations of both species occurred after approximately 20 generations. In this paper, we examine thehypothesis that this observed change in the dynamics may have been caused by an evolutionary shift in themode of competition among the bean weevils. A Nicholson-Bailey type model is developed using parameters
measured from the experiments. The host larvae can dier in the type of competitive behaviour that they
exhibit, which can be either of a contest type or of a scramble type. If a bean contains one or more larvae of thecontest type, only one of these will survive and any scramble-type larvae in the bean will be killed. If nocontest-type larvae are present within a bean, multiple individuals of the scramble type can emerge from asingle bean. The model assumes many genotypes, diering in the fraction of ospring of the two types. If ahigh per capita resource availability is maintained, then the scramble type is selected for, but if resources arelimited, then the contest type is selected for. The host population at the start of the experiment, taken from astock culture, was composed mostly of the scramble type. The model is successful in explaining the initial
quick increase in the host's abundance, followed by the evolutionary increase in the fraction of the contest type
among hosts, resulting in the more stable population dynamics of the host±parasitoid system, as observed in
the experiments. However, it predicts a parasitoid abundance much higher than that observed. We discussalternative hypotheses to explain the observed evolutionary shift in the population dynamics. We also examine
the eect of the dierence in size of the beans in the stock culture and those used in the experiments.
Keywords: Callosobruchus maculatus; evolutionarily stable strategy; evolutionary speed; Heterospilus prosopidis; laboratory system

Introduction
Populations of animals and plants in experimentally controlled environments sometimes show
long-term changes in dynamics that occur over many generations (Nicholson, 1957; Utida, 1957;
Pimentel and Stone, 1968). Some of these changes may simply be a result of long transients in the
dynamics while returning to an equilibrium state(s), but there are clear examples of outcomes of
evolutionary (or co-evolutionary) modi®cation in the component species of the system. Althoughsome pioneering models have analysed evolutionary processes in single-species populations (Stokes
et al., 1988; Toquenaga et al., 1994), few two-species systems have been subjected to experimental
tests of the mechanism leading to long-term changes in population dynamics (but see Pimentel etal., 1963; C.J. Briggs et al., unpublished).
In a laboratory host±parasitoid system consisting of the mung bean, the cowpea bean weevil anda parasitic wasp, Tuda (1996) demonstrated that the host and parasitoid populations showed three*Address all correspondence to Midori Tuda, Institute of Biological Control, Faculty of Agriculture, Kyushu University,
Fukuoka 812-8581, Japan.
0269-7653

Ó 1998 Chapman & Hall856

Tuda and Iwasa

large oscillations, and then they suddenly stabilized at about the twentieth host generation andsimultaneously the mean population size of the parasitoid was lowered (Fig. 1). By examining thepre- and post-experimental insects, Tuda (in press) found that the host had changed its larval
competition habit from the scramble type to the contest type, and the post-experimental hosts had
several properties distinguishable from the hosts in the stock culture. There was no change in theparasitoid in terms of the maximum attack rate and the duration of attacking host stages (or theperiod of host vulnerability).
In this paper, we examine the hypothesis that the change in the host±parasitoid dynamics wasprimarily due to the evolution of the competition type in the host larvae, rather than a change in
the nature of the host±parasitoid interaction. After examining the evolutionary model describing
the shift in the larval competition mode of the host during experiments, we incorporate random
removal of host adults to assess its impact on the rate of evolutionary change. The model is thenextended to study the eect of attack by the parasitoids, in a Nicholson-Bailey framework, host±parasitoid dynamics and the rate of host evolution. We also examine the eect of alternative timingof parasitization and the two modes of competition, and the eect of sizes of beans, to explain theobserved population dynamics.
The model
We ®rst consider the evolution of the host in the absence of the parasitoid. Consider two phenotypes of individuals ± contest type and scramble type ± diering in the behaviour of larval stages.
Contest-type larvae ®ght within a bean and at most one individual can emerge from a bean.
Scramble-type larvae do not attempt to kill others in the same bean but adults emerging from abean with many larvae are small, having lower fecundity than an individual which has grown singly
during the larval period.
We assume that females lay only a single egg onto each bean, but many larvae may exist in asingle bean if laid by multiple females. Based on this assumption, the larvae in a single bean are notrelated.

Figure 1. Population dynamics of a laboratory host±parasitoid system. The solid squares are the abundancesof the host, the cowpea bean weevil Callosobruchus maculatus, and the open squares are those of the parasitoid, a braconid wasp Heterospilus prosopidis. The method is described in Tuda (1996).

Evolution of contest competition

857

Since novel mutations occurring during the experiment are unlikely to be frequent enough to
explain the large change in the competitive behaviour, the initial population must have genetic
variability in terms of the propensity to produce contest-type larvae. We here assume that there is aseries of genotypes, each having a dierent probability of becoming larvae of the two types (i.e. thelarval competition type is controlled probabilistically by the genotype). We assume the simplest
possible genetic model to explain the observed evolutionary changes in bean weevil population: ahaploid population with multiple alleles at one locus controlling the probability q of being acontest-type larva, as is often assumed in evolutionary game theory (Maynard Smith, 1982). We
can easily extend it to the additive polygenic system controlling the fraction of contest-type larvae(Iwasa et al., 1991). We neglect new mutations, as we discuss events occurring in less than 100
generations.
Suppose that there are n genotypes indicated by i i  1; 2; . . . ; n, with the i-th type having aprobability of being a contest-type larva qi . In the numerical examples below, we useqi  i ÿ 1= n ÿ 1, where the ®rst genotype is a pure scramble-type larva (q1  0) and the n-th
genotype is a pure contest-type larva (qn  1), and all other n ÿ 2 types give mixed strategies ofdierent probabilities of being a contest-type larva.
Let xi be the number of adults of the i-th genotype. From x1 ; x2 ; . . . ; xn , we can compute the total
number of adults H, and the average fraction of the contest type q, as follows:
H
q 

n
X
i1
n
X

xi

1a

qi xi =H1bi1The average number of eggs per adult is denoted k, which is half of the number of eggs produced
per female, assuming a 1:1 sex ratio. The number of eggs becoming contest-type larvae and thenumber of eggs becoming scramble-type larvae are denoted by C and N, respectively. They aresimply:
Ck

n
X
i1

qi xi

N k

n
X

1 ÿ qi xi

2

i1

Let m be the number of beans. The numbers of eggs of the contest type and scramble type laid ona bean follow independent Poisson distributions with means C=m and N =m, respectively. The
hatchability of eggs and density-independent survivorship may dier between two types: theirproduct is hC for the contest type and hN for the scramble type. Then, among contest competitors,
only one larva per bean can survive to become an adult. The ®tness of a contest-type individual is
the product of fecundity k and the survivorship until maturity:
wC C  km 1 ÿ eÿhC C=m =C3

The term 1 ÿ eÿhC C=m  is the probability of a bean having at least one contest-type larva, whereeÿhC C=m is the zero-th term of the Poisson distribution with mean hC C=m. The product ofm 1 ÿ eÿhC C=m  is the number of adults from contest-type larvae. It is divided by the number ofcontest-type eggs C to give the survivorship from eggs to adults. Then it is multiplied by k to givethe ®tness wC in Equation (3). Note that the ®tness of contest-type individuals is independent of thepresence of scramble-type individuals.
The scramble-type larvae, on the other hand, can survive only in beans that lack contest-typelarvae. We use eÿb yÿ1 to denote the density-dependent survival among y scramble larvae per bean,

858

Tuda and Iwasa

where b is the strength of competition among scramble-type larvae. This function ®ts closely theobserved survival curve for larvae on mung beans (Tuda, in press). We assume that a scramble-type
individual has the same fecundity (k) as a contest-type individual. The probability of a bean having
y scramble-type larvae follows the Poisson distribution:hN N =my ÿhN N =mey!

The product of these factors, if summed over y up to in®nity, yields:eÿhC C=m1
X
hN N =myy1y!

eÿhN N =m ykeÿb yÿ1the number of the scramble type in the next generation. Finally, divided by N and multiplied by m,it becomes the ®tness (or per capita reproductive rate) of a scramble-type individual:wN C; N   khN expÿhC C=m ÿ hN 1 ÿ eÿb N =m

4

We estimated values for the host parameters from short-term experiments performed separatelyfrom the long-term census of the population dynamics (Tuda, in press). These values are listed inTable 1.
The evolutionarily stable fraction of contest-type larvae
In the next generation, xi , the abundance of the i-th genotype producing fraction qi of the contest
type, becomes:
xi; t1  fqi wC Ct   1 ÿ qi wN Ct ; Nt gxi;t5

The ®tness of the i-th genotype is an arithmetic average of the ®tness for contest-type larvae and the®tness for scramble-type larvae, as each egg of genotype i becomes contest and scramble type withprobability qi and 1 ÿ qi , respectively. Once xi i  1; 2; . . . ; n is known, we can calculate theaverage fraction of the contest type in the host population using Equation (1a) and the total adulthosts using Equation (1b).
Starting with an initial distribution with a sharp peak near q1  0, and hence a small averagefraction of the contest type, and using the estimated parameter values in Table 1, the number ofcontest-type adults rapidly increases at ®rst and then gradually saturates (Fig. 2). The number ofindividuals at saturation is about 90, the number of beans maintained in the experiment. This isquite close to the observed level of 94:4  1:4 (mean  S.E.) (Tuda, 1995). Changes in k do notaect the ®nal level much, but decreasing k slows the spread of the contest type.
In generating the initial distribution of xi we chose:,H0 eÿli

n
X

eÿlj

j1

where H0 is the initial population density of the host (H0  60). The variance of this distribution,
controlled by l, also in¯uences the speed of evolution (Figs 2a,b).
Equation (5) gives the full dynamics of genotypes, describing both the population dynamicchange in the total population size and the evolutionary change in the fraction of contest-typelarvae q. However, the following intuitive argument and the simple formulae are useful in calculating the evolutionarily equilibrium (see Appendix 1 for further argument): If an evolutionarily
stable population includes a mixture of larvae of both contest and scramble types, then the expected ®tnesses of the contest and scramble types must be the same; otherwise, producing a larger

Evolution of contest competition

859
aTable 1. De®nition of variables and parameters
Variable andparameterDe®nition

Host
H
C
N
qi
xi
k

Unit

total number of adult hosts
number of eggs for contest-type larvae
number of eggs for scramble-type larvae
proportion of i-th genotype becoming contest-type
number of adults of the i-th genotype
fecundity (per capita adult), half of fecundity
per female
hatchability of eggs multiplied by the densityindependent larval survivorship of contest type
hatchability of eggs multiplied by the densityindependent larval survivorship of scramble typestrength of density dependence in larval survival of
the scramble typeindividuals
individuals
individuals

Panumber of parasitoid adults
attack ratesP

larval survival rateindividuals
1/(generationindividual)
1/generation

Beanmnumber of beans

hC
hN
b

individuals
eggs perindividual

Parameter value

17.6
0.86
1.0
0.234

Parasitoida0.0125±0.03
0.990Parameter values for the host are estimated from independent short-term experiments (Tuda, in press).

(or a smaller) fraction of contest types would become more advantageous, which is in con¯ict withthe assumption of evolutionary stability. In addition, since the ®tness is the same as the population
multiplicative rate (as indicated in Equation 5), the ®tness of the type remaining in the populationmust be equal to 1. From these two considerations, we have:
wC C    wN C  ; N    1

if q is an intermediate value

6a

wC C  < wN C ; N   1

if q  0

6b

wN C  ; N   < wC C    1

if q  1

6c







from which we can calculate the evolutionarily stable fraction of the contest-type larvae.
Consider the case in which the evolutionarily stable population (or ESS) includes both contest
and scramble types. Let C  and N  be the values in the putative ESS solution. Then, from
Equations (3) and (6a), C  is a single positive solution of:

km 1 ÿ eÿhC C =m  ÿ C   0

7a

From Equations (4) and (6a), we have:N   m ln khN ÿ hC C  = hN 1 ÿ eÿb 

7b

860

Tuda and Iwasa

Figure 2. Population dynamics (H) and average fraction of the contest type (q) in the bean weevil withparameter values estimated from short-term
P experiments: k = 17.6, hC = 0.86, hN = 1.0 and b = 0.234(Equations 3, 4 and 5). We chose H0 eÿli = nj1 eÿlj to generate the initial distribution of xi , whose variance iscontrolled by l. The initial q values are (a) 0.03 and (b) 0.014.

The conditions for the two types to co-exist (i.e. C  > 0 and N  > 0) are:khC > 1

khN > 1m ln khN > hC C 

8For the parameter values listed in Table 1, the third inequality is not satis®ed, and thus the coexistence of the two competition types is impossible in the host-only population.
Random removal of the hostIn the stock culture, a large fraction of adults was removed every generation, to keep the availability of beans per individual suciently high. One of the potential reasons why the initial population of bean weevils was composed mostly of individuals engaging in scramble-type competition(rather than contest-type competition) is that removal during stock-keeping procedures might havefavoured scramble-type competition by maintaining a low weevil density per bean.
If adults of the host are removed randomly with rate R 0 < R < 1, the number of the i-th
genotype in the next generation is:Evolution of contest competition
xi; t1  xi; t fqi wC Ct   1 ÿ qi wN Ct ; Nt g 1 ÿ R

861
9

With this additional factor (1 ÿ R), we have modi®ed the equations for the ESS population as
explained in Appendix 2, from which we can calculate the evolutionarily stable population fordierent values of R.
As shown in Fig. 3a, for a wide range of R, the contest type is always selected for and thescramble type is predicted to be eliminated. However, for a suciently large R
R > 0:921 in Fig. 3a, the contest type and scramble type co-exist in the evolutionarily stable
population. As R increases further, the fraction of the contest type drops rapidly and is replaced by
the scramble type, the latter coming to dominate only at very large R R > 0:934 in Fig. 3a. At
even higher R, neither of the two types can persist in the stock (R > 0:943 in Fig. 3a). The range ofthe parameter R for the evolutionarily stable population to include both types is quite narrow(0:921 < R < 0:934), but the range of removal rate R for the ESS to be pure scramble type is evennarrower (0:934 < R < 0:943) (see Appendix 2 for the analysis).
Figure 3a shows that the ®nal value of q is 1 for most values of R, and Fig. 3b shows that, except
for very large R, the rate of increase in q is also insensitive to the removal rate. Figure 4 illustrates
several trajectories of q, which shows that large removal rates, especially R > 0:9, tend to slow
down the evolution of contest types.
This makes it dicult to explain why the initial host population derived from the stock culture iscomposed predominantly of scramble types, because the range of removal rate R for this to hold isvery restrictive. Later, we will consider an alternative mechanism to explain this, based on thepossibility for a large-sized bean used in the stock to support both scramble types and contest types
in the same bean.

Figure 3. Eect of random removal of bean weevil adults on (a) the evolutionarily stable fraction of thecontest type and (b) the time (the number of generations, in log scale) required for q to reach 0.5 (Equation 9).
The broken lines show the estimated removal rate caused by parasitoid attack in the experimental host±parasitoid system for days 60±390.

862

Tuda and Iwasa

Figure 4. Simulated dynamics of q for dierent values of R. A high random removal rate R slows the rate ofincrease in q, especially during the early phase of the increase (Equation 9; see also Fig. 3b).

Parasitoid±host interaction
Now we consider host evolution in the presence of parasitoids that attack hosts. The parasitoid
causes an additional mortality to the host population and thus works in a way similar torandom removal. We would expect the presence of parasitoids to cause a slower evolution ofcontest-type competition in hosts. In addition, parasitoid population dynamics are coupled withthose of host population dynamics to cause limit cycle oscillations or chaotic ¯uctuations, rather
than just a stable equilibrium, and these dynamical behaviours can also be modi®ed by hostevolution.
We assume that parasitoids attack hosts randomly, and irrespective of the competition types.
Hence, the number of the i-th genotype hosts in the next generation is expressed in a simple
Nicholson-Bailey form:
xi; t1  xi; t fqi wC Ct   1 ÿ qi wN Ct ; Nt geÿf Pt 

10

where eÿf Pt  is the escape rate of the host from parasitism andf Pt   aPt

11

Note that we can derive Equation (10) from Equation (9) simply by replacing 1 ÿ R with eÿf Pt  .
We assume that parasitoids attack hosts only after the completion of larval competition. Thus
the number of parasitoids in the next generation is:Pt1  sP 1 ÿ eÿf Pt  Ht1

12

where sP is the survivorship of the parasitoid larvae and Ht1 is the total number of vulnerable
hosts that survive competition. Ht1 is equal to the total number of adults at time t  1 prior to thestage vulnerable to parasitoids.
Although parasitoid attack slows down evolution towards the contest type, the contest typereaches a high fraction after 40 generations (in contrast to 20 generations without parasitoids) if all
the other parameters are the same (Fig. 5b). In the absence of the contest type, the host andparasitoid populations show unstable dynamics (Fig. 5a), while the contest-type-only population
stabilizes after short transients (Fig. 5c). The increase in the average fraction of the contest type isaccompanied by the stabilization of population dynamics of both host and parasitoid.

Evolution of contest competition

863

Alternative timing of parasitization and the two modes of competition
The above analysis assumes that scramble-type and contest-type competition occur simultaneously.
However, scramble-type competition is likely to occur at a later developmental stage than contesttype competition, rather than vice versa, because larval contest competition occurs in the earlystages before resources are depleted (Utida, 1975; Tuda, in press). In addition, in experimental
systems, parasitism is likely to occur just before scramble-type competition. We next assume thatthe parasitoid attacks host larvae at the stage after contest competition but before scramble
competition. This modi®cation leads to the following equations, instead of Equation (12):Pt1  sP 1 ÿ eÿf Pt  H~ t1

13a

where H~ is the number of vulnerable larvae. However, the de®nition of vulnerable larvae is now
contest-type larvae surviving competition and scramble-type larvae after suering contest competition but before scramble competition takes place:
H~ 

n
X

xi; t fqi wC Ct   1 ÿ qi khN eÿhC Ct =m g

13b

i1

Parasitoid abundance increases by attacking abundant scramble-type larvae just before, rather
than after, the scramble competition that reduces their number (Fig. 6). High parasitoid densities
slow down the evolution of the contest type, given that the parameter values are the same as those
applied in the previous section. This enables even smaller values of a or initial q to generate a few
large oscillations before the evolution of the contest type stabilizes the dynamics. The smaller alowers the parasitoid equilibrium density, while raising that of the host (Figs 5d and 6).
Size of beans
As shown earlier, a large random removal of hosts in the procedures maintaining the stock culture
population may in principle explain why the initial host population was composed predominantlyof scramble types. However, for this to hold in the basic model analysed, the removal rate must bewithin a very limited range. The removal rate during culture storage was approximately 0.8, which
is not consistent with the pure random removal explaining the initial scramble population. In thissection, we focus on the possible role of the dierence in size of the beans in the stock culture andthose used in the experiment.
Contest and scramble types dier with respect to their spatial feeding site within a bean: contesttype larvae feed at the centre of beans but scramble-type larvae feed at the periphery of beans(Umeya et al., 1975). Let k be the relative size of beans used in the stock culture to those used in theexperiment, which is larger than 1 (k > 1). Since contest-type larvae attempt to occupy the central
part of the bean, they compete among themselves; the remaining peripheral part, with volume(k ÿ 1), will be available for the scramble-type larvae. Thus, in a large bean, some scramble-typelarvae can survive when a contest-type larva is present. In beans without contest-type larvae, thewhole of the bean will be used by scramble-type larvae.
The ®tness of the contest type is the same as before and given by Equation (3). The density ofscramble-type larvae per bean is y=k; hence the density-dependent survival and size-dependent
fecundity becomes eÿb y=kÿ1 , where k is the relative size of beans, y is the number of scramble-typelarvae per bean, and b is the strength of scramble competition as before. The ®tness of thescramble-type larvae feeding on beans of size k is:

864

Tuda and Iwasa

Evolution of contest competition

865

Figure 6. Eect of dierent relative timings of competition to parasitism between the contest and scramble
types on the population dynamics (H and P) and the average fraction of the contest type (q) (Equations 10 and
13). The parameter values are those in Fig. 2 for the host and a = 0.0125 and sP  0:9 for the parasitoid.
Initial q  0:014.
~ N C; N   khN eÿhC C=m expfÿhN 1 ÿ eÿb=k N =m  b k ÿ 1=kgw
14
ÿhC C=m 1ÿe

ÿb= kÿ1expfÿhN 1 ÿ e

N =m  b k ÿ 2= k ÿ 1gThe ®rst term shows competition among the scramble-type individuals only and can be derived in
the same way as Equation (4) with a modi®ed density of scramble-type larvae. It is equivalent toEquation (4) when k  1. The second term describes scramble competition over the remaining bean
content, with volume (k ÿ 1), in beans with a contest-type larva occupying the central volume. The
expected fraction of the scramble type is simply the same as the ®rst term with k replaced by k ÿ 1.
Based on the competition curve measured for the scramble-type C. maculatus feeding on either
small or large mung beans (Toquenaga and Fujii, 1991), the parameter b was estimated, which did
not change with k.
Figure 7 shows the results of the analysis using Equations (4), (9) and (14) with dierent random
removal rates R. The average fraction of the contest type is reduced as k increases because it
increases the size of the refuge for scramble-type larvae. Compared to the cases with k  1, it ismuch easier for both types to co-exist in the population and also there is a relatively broad range ofremoval rate R that allows the scramble type to dominate in the evolutionarily stable population.
This eect outweighs that of adult removal unless the removal rate is extremely high.
Discussion
Our model shows that, in the absence of the parasitoid, the bean weevil population with an initialhigh fraction of the scramble type becomes rapidly dominated by the contest type (Fig. 2). Thisb

Figure 5. Eect of random attack by parasitoids on the evolutionary changes in the population dynamics(H and P) and the average fraction of the contest type (q) (Equations 10 and 12). (a) A scramble-type-only
population; (b) a mixed population of the two competition types, with the initial q = 0.03; and (c) a contesttype-only population. The parameter values are those in Fig. 2 for the host and a = 0.03 and sP  0:9 for theparasitoid. (d) A mixed population of the two competition types, with initial q  0:014 and a  0:0125.

866

Tuda and Iwasa

Figure 7. Eects of bean size and random removal rate on the evolutionarily stable fraction of the contest type
(Equation 14).

explains the results of experiments on a single-species C. maculatus population by Toquenaga et al.
(1994), in which, however, competition type was distinguished based on the resemblance of dynamical trajectories and not on the observation of competition outcome in a single bean. Theirstudy also indicated that the transition from scramble to contest type occurred on a time scaleconsistent with the prediction of the present model. Toquenaga et al. (1994) developed a genetic
algorithm model, assuming additive genetics, which exhibited a gradual increase in the averagefraction of the contest type; this parallels the result shown in Fig. 2 of our simple one-locus haploid
genetic model.
If the parasitoid has a mildly high attack rate, the introduction of a parasitoid does not aect thedirection of the selection pressure working on the larval competition type (Fig. 3). However, boththe parasitoid and random removal of host adults slow down evolution towards contest-type larvae(Figs 4 and 5b, in contrast to Fig. 2).
In our basic model (up to Equation 12), evolution of the host towards contest competition
stabilizes ± otherwise, there will be unstable oscillations of the host and parasitoid ± and this isconsistent with the reduced oscillations in the experimental system (Fig. 1). However, the basicmodel did not explain the following two characteristics of the observed dynamics: (1) the dominance of the scramble type in the founder population derived from the stock culture, and (2) the
drastic reduction in the initially high density of the parasitoid (Fig. 1).
The ®rst point stems from Fig. 3, which suggests that the ®xation of the contest type is the likely
outcome at all but high removal rates. This is because one individual of the contest type is enoughto exclude the scramble type at each bean of small size (i.e. k  1). With larger beans, however,scramble-type individuals survive competition with contest-type individuals because of refuge fromthe contest type at the periphery of beans (Fig. 7). Using this modi®cation, we can overcome the®rst problem. In fact, the stock population was maintained in beans about three times larger involume than those used in the experiment. Smith and Lessells (1985) incorporated the bean size

Evolution of contest competition867

dierence into a model for competition among bean weevils in terms of dierential encounter rateof larvae within a bean. We, however, chose not to use this formalism because, at present, theencounter rates of individual larvae of the two competition types inside beans are extremelydicult to measure, not only because they are morphologically indistinguishable but also because
opening beans inevitably kills the developing larvae (Tuda, 1995).
For the second point, we considered an alternative temporal order of competition and parasitism.
Indeed, if scramble competition occurs later than parasitism, the initial densities of the parasitoid
become much higher and evolution towards contest types brings the population to an equilibrium
which can be much lower than the initial densities depending on the values of a (Fig. 6, in contrast to
Fig. 5d). Theoretical studies have suggested that density-dependent mortality that occurs before
random parasitism is more stabilizing than when it occurs later (Smith and Mead, 1974; May et al.,1981). Therefore, if evolution from the scramble type to the contest type is accompanied by a shift of
the temporal order of competition and random parasitism, the stabilization eect of contest competition is two-fold, compared to scramble competition. The present study also shows that, during
the course of evolution and transients, the change in the temporal order of interactions can produce
even greater variety of dynamics than suggested theoretically (Fig. 6).
Although our model assumed a density-independent fecundity (k), a scramble-type individualfrom a crowded bean normally has a smaller body size and a smaller fecundity than k, the fecundityof an adult grown singly. A parasitoid emerging from a smaller host also has a smaller fecundity
than a parasitoid from a host grown singly. When density-dependent fecundity is important, we
can still use the same model if the combined eect of density-dependent larval survivorship anddensity-dependent fecundity are expressed as keÿb yÿ1 , and if the fecundity of a parasitoid from thehost is proportional to the same factor. We simply need to regard xi; t as the eective number ofadults of genotype i, de®ned as the number of eggs of genotype i divided by maximum fecundity k,
and H as the total eective number of adults. In fact, b in Table 1 was estimated from experiments
considering the combined eect of density-dependent fecundity and density-dependent larval
survivorship.
The possibility of parasitoid evolution, which was not examined in the present paper, is a processthat might, in principle, explain the change in the dynamics. However, we believe that it is lesslikely to be important than host evolution, because the genetic variability in the laboratory parasitoid population is likely to have decreased to a minimal level, as the population has been
cultured over 50 years since Professor Syunro Utida's time. The host, on the other hand, had been
kept for 2 years only in the laboratory. This reminds us of the gradual reduction in the parasitoid
density in Utida's host±parasitoid system. As stated above, however, laboratory populations kept
for generations also have less tendency to evolve (Sait et al., 1994; M. Boots, personal communication). In this sense, the population of H. prosopidis, in its early laboratory history, may still
have retained a potential to evolve as Utida suggested (Utida, 1957).
We conclude that the evolution of the contest-type host explains both the stabilization of the
population dynamics and the reduction in the parasitoid population size, which subsequently
changed the host±parasitoid interaction. Analyses of other long-term laboratory time-series data,such as those of Utida, will improve our understanding of the evolution of interacting species.

Acknowledgements
We thank Masakazu Shimada for pointing out the importance of bean size to us. We also acknowledge the following for their very helpful comments: M. Boots, C.J. Briggs, H. Caswell,
H.C.J. Godfray, B. Kendall, P.D. Taylor and Y. Toquenaga. Part of this study was carried out

868

Tuda and Iwasa

during M.T.'s stay at the Laboratory of Mathematical Biology, Kyushu University, and M.T.
thanks the members of the lab for useful discussion. This study was supported by a Grant-in-Aid
for JSPS Fellows (083895) to M.T. and by a Grant-in-Aid for International Scienti®c Program (Joint Research) from the Ministry of Education, Science and Culture (07044180) to M.
Shimada.
References
Iwasa, Y., Pomiankowski, A. and Nee, S. (1991) The evolution of costly mate preferences. II. The `handicap'
principle. Evolution 45, 1431±1442.
May, R.M., Hassell, M.P., Anderson, R.M. and Tonkyn, D.W. (1981) Density dependence in host±parasitoid
models. J. Anim. Ecol. 50, 855±865.
Maynard Smith, J. (1982) Evolution and the Theory of Games. Cambridge University Press, Cambridge.
Nicholson, A.J. (1957) The self-adjustment of populations to change. Cold Spring Harbor Symp. Quant. Biol.
22, 153±173.
Pimentel, D. and Stone, F.A. (1968) Evolution and population ecology of parasite±host systems. Can. Ent.
100, 655±662.
Pimentel, D., Nagel, W.P. and Madden, J.L. (1963) Space±time structure of the environment and the survivalof parasite±host systems. Am. Nat. 97, 141±167.
Roughgarden, J. (1979) Theory of Population Genetics and Evolutionary Ecology: An Introduction. Macmillan,
New York.
Sait, S.M., Begon, M. and Thompson, D.J. (1994) Long-term population dynamics of the Indian meal moth
Plodia interpunctella and its granulosis virus. J. Anim. Ecol. 63, 861±870.
Smith, R.H. and Lessells, C.M. (1985) Oviposition, ovicide and larval competition in granivorous insects. In
Behavioural Ecology: Ecological Consequences of Adaptive Behaviour (R.M. Sibly and R.H. Smith, eds),
pp. 423±484. Blackwell, Oxford.
Smith, R.H. and Mead, R. (1974) Age structure and stability in models of prey±predator systems. Theor.
Popul. Biol. 6, 308±322.
Stokes, T.K., Gurney, W.S.C., Nisbet, R.M. and Blythe, S.P. (1988) Parameter evolution in a laboratory
insect population. Theor. Popul. Biol. 34, 248±265.
Toquenaga, Y. (1993) Contest and scramble competitions in Callosobruchus maculatus (Coleoptera: Bruchidae). II. Larval competition and interference mechanisms. Res. Popul. Ecol. 35, 57±68.
Toquenaga, Y. and Fujii, K. (1991) Contest and scramble competitions in Callosobruchus maculatus (Coleoptera: Bruchidae). I. Larval competition curves and resource sharing patterns. Res. Popul. Ecol. 33, 199±
211.
Toquenaga, Y., Ichinose, M., Hoshino, T. and Fujii, K. (1994) Contest and scramble competitions in anarti®cial world: Genetic analysis with GA. In Arti®cial Life III (C.G. Langton, ed.), pp. 177±199.
Addison-Wesley, Reading, MA.
Tuda, M. (1995) Spatio-temporal population structures and host±parasitoid system dynamics. PhD thesis,
University of Tokyo.
Tuda, M. (1996) Temporal/spatial structure and the dynamical property of laboratory host±parasitoid systems. Res. Popul. Ecol. 38, 133±140.
Tuda, M. (in press) Evolutionary character changes and population responses in an insect host±parasitoid
experimental system. Res. Popul. Ecol.
Umeya, K., Kato, T. and Kocha, T. (1975) Studies on the comparative ecology of bean weevils. VI. Intraspeci®c larval competition in Callosobruchus analis (F.). Jap. J. Appl. Ent. Zool. 19, 47±53.
Utida, S. (1957) Cyclic ¯uctuations of population density intrinsic to the host±parasite system. Ecology 38,442±449.
Utida, S. (1975) Animal Population Ecology (in Japanese). Kyoritsu, Tokyo.

Evolution of contest competition

869

Appendix 1
The P
dynamics of genotypes given by Equation (5) include both the dynamics of total population
size ni1 xi;t and the evolutionary dynamics of average trait q, as is common to other densitydependent natural selection models (e.g. Roughgarden, 1979).
First, we note that the sum of Equation (5) over dierent i is:nXxi;t1 

i1



n
X

qi wC  1 ÿ qi wN xi;t

i1
n
X

xi;t qwC  1 ÿ qwN 

A1

i1

At the population dynamic equilibria,
1  qwC  1 ÿ qwN

n
P
i1

xi;t1 nPi1xi;t holds and Equation (A1) becomes:
A2

which indicates that the average ®tness must be equal to 1 at the population dynamic equilibrium.
Second, straightforward calculation from Equation (5) shows that the one-generation change in
the average fraction of contest type q, de®ned as Equation (1b), is:Dq var q
wC Ct  ÿ wN Ct ; Nt w

A3a

where var q is the additive genetic variance of contest type fraction q and w is the average ®tness:var q 
w

n
X

X

q2i xi.Xx i ÿ q2

qi wC  1 ÿ qi wN xi

A3b
X
n

i1

xi

A3c

i1

Equation (A3a) suggests to us that, as long as some additive genetic variance remains in the
population (var q > 0), the average fraction of the contest type tends to evolve to realize:
wC Ct   wN Ct ; Nt 

A4

if the evolutionarily stable q is an intermediate value 0 < q < 1. Then, Equations (A2) and (A4)give Equation (6a) in the text.
On the other hand, if the ®nal q is the lowest possible value q  0, the evolutionary stability
requires natural selection not to favour the increase in q. From Equation (A3a), this becomesEquation (6b) in the text. A similar consideration suggests the condition in Equation (6c) whenq  1 is evolutionarily stable.
Appendix 2
Random removal of the hostIf the host is randomly removed at rate R, Equation (6a) becomes:
wC C    wN C  ; N    1= 1 ÿ R

B1

From Equation (3), a numerical solution for C is obtained by solving:

km 1 ÿ eÿhC C =m  1 ÿ R ÿ C   0

B2a

Replacing Equation (4) we obtain:N   m ln khN 1 ÿ R ÿ hC C  =fhN 1 ÿ eÿb g

B2b)

870

Tuda and Iwasa

The conditions for two competition types to co-exist are:khC 1 ÿ R > 1

khN 1 ÿ R > 1

m ln khN 1 ÿ R > hC C 

B3

Parasitoid±host interaction
The equilibrium population size of the parasitoid is obtained from Equations (9) and (10) under thecondition of Equation (A1) with 1 ÿ R  exp ÿaPt1  andPt1  Pt

B4

where Pt1 is given by Equation (12).
With the estimated parameter values, simulations of the model show that 40 generations may not
be long enough for the host and parasitoid populations to reach equilibrium.