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3
Kinship, Greenbeards, and Runaway
Social Selection in the Evolution of
Social Insect Cooperation
PETER NONACS
Social Hymenoptera have played a leading role in development and
testing of kin selection theory. Inclusive fitness models, following from
Hamilton’s rule, successfully predict major life history characteristics,
such as biased sex investment ratios and conflict over parentage of male
offspring. However, kin selection models poorly predict patterns of
caste-biasing nepotism and reproductive skew within groups unless kin
recognition constraints or group-level selection is also invoked. These
successes and failures mirror the underlying kin recognition mecha-
nisms. With reliable environmental cues, such as the sex of offspring or
the origin of male eggs, predictions are supported. When only genetic
recognition cues are potentially available, predictions are not supported.
Mathematical simulations demonstrate that these differing mechanisms
for determining kinship produce very different patterns of behavior.
Decisions based on environmental cues for relatedness result in a robust
mixture of cooperation and noncooperation depending on whether or not
Hamilton’s rule is met. In contrast, cooperation evolves under a wider
range of conditions and to higher frequencies with genetic kin recognition
as shared greenbeard traits. This “excess of niceness” matches the exist-
ing patterns in caste bias and reproductive skew; individuals often help
others at an apparent cost to their inclusive fitness. The results further
imply a potential for greenbeard-type kin recognition to create arbitrary
runaway social selection for shared genetic traits. Suggestive examples
Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA
90095. E-mail: pnonacs@biology.ucla.edu.
49
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50 / Peter Nonacs
in social evolution may be alloparental care and unicoloniality in ants.
Differences in kin recognition mechanisms also can have consequences
for maintenance of advantageous genetic diversity within populations.
S
eemingly overtly altruistic behavior, such as individuals accept-
ing sterility, has puzzled evolutionary biologists since the time of
Darwin. The first truly predictive framework for how reducing one’s
own reproduction could be adaptive came from the seminal work of W. D.
Hamilton (1964a). His key insight was that fitness is “inclusive” of both
an individual’s direct reproduction and indirect gains arising through
help provided to genetic relatives. Gains in indirect fitness, often labeled
as “kin selection,” recast altruism as an ultimately selfish act. Help rela-
tives if the benefit provided (b), prorated by the genetic relatedness of the
recipient (r), exceeds the cost to self (c). This is Hamilton’s rule: Helping
is adaptive if br > c.
More than any other taxonomic group, social Hymenoptera (ants,
bees, and wasps) sit at an apparent peak of kin selection, with many
species having morphologically sterile workers. Kin selection and appli -
cations of Hamilton’s rule, however, extend far beyond the evolution of
sterile castes to examine many aspects of cooperative (and noncoopera -
tive) behavior (Bourke and Franks, 1995). Thus, social insects have had a
pivotal role in the development of kin selection theory and its elevation
to being the dominant evolutionary paradigm for the study of coopera -
tion and conflict. To date, there have been hundreds of tests of kin selec-
tion predictions in social insects (Abbot et al., 2011). However, despite
this track record of remarkable utility, kin selection theory has recently
become embroiled in controversy. The mathematics of inclusive fitness
modeling have been directly challenged (Nowak et al., 2010). The evolu -
tion of cooperation is argued as better explained by group-level selection
than by nepotism toward kin (Wilson and Wilson, 2007). Finally, the status
of social insects as being a paramount example of kin selection has been
questioned, with kin selection relegated to being a dissolutive force that
primarily selects against cooperation and sociality (Wilson and Hölldobler,
2005). The response to these criticisms from defenders of inclusive fitness
modeling and kin selection has been simultaneously vigorous and dismis-
sive (Foster et al., 2006; Lehmann et al., 2007; West et al., 2007c, 2008; Abbot
et al., 2011; Herre and Wcislo, 2011; Strassmann et al., 2011b).
The current conceptual maelstrom offers an opportunity for a criti-
cal appraisal of the effects of kin selection in the social Hymenoptera.
Considering a model or hypothesis as either a failure or success is highly
subjective. No single model can be expected to be 100% accurate for all
taxonomic groups and in all situations. It is nevertheless fair to categorize
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Kinship, Greenbeards, and Runaway Social Selection / 51
a model as failing when a strong majority of studies reject its predictions.
Conversely, models that are consistently supported by data are valued
for accurately tracking evolutionary outcomes. By such standards, and
contrary to its critics, kin selection theory has had major successes. How -
ever, contrary to its apologists, kin selection theory also has had some
major failures. I will briefly review within the social Hymenoptera two
successes, (i) sex investment ratios and (ii) conflict over reproduction by
workers (i.e., worker policing), and two failures, (i) caste-biasing nepotism
and (ii) reproductive skew theory. I will thereafter consider the mechanism
for how kin are recognized as the driving force for the observed pattern
of success and failure.
These four topics are chosen because I believe the underlying theory
for the kin selective predictions is sound and that the possibility for kin
nepotism to evolve is at least potentially present. This differs from two
other cases, where kin selection predictions are suggested to have failed:
the haplodiplody and monogamy hypotheses (Nowak et al., 2010). First,
cooperative breeding has repeatedly evolved in the haplodiploid Hyme -
noptera. Haplodiplody creates a genetic asymmetry, such that a female is
more related to her full sister (r = 0.75) than she is to her own offspring
(r = 0.5). Therefore, if a singly mated mother produces a female-biased
offspring sex ratio, it is genetically more advantageous for a daughter to
help her mother raise more sisters. However, the balance of evidence from
existing species where cooperative breeding is facultative finds that such
species are not monogamous, do not predictably bias sex ratios toward
females, or both (Bourke and Franks, 1995). Hence, the haplodiploidy
hypothesis is not a robust test of kin selection because the required pat -
terns of genetic relatedness likely did not exist in the putative ancestors
of eusocial species (Nonacs, 2010). The second example is the “monogamy
hypothesis,” where cooperative breeding is predicted to be more likely to
evolve in species where family groups are full siblings because of monog -
amy (Boomsma, 2009). However, a gene-based model for the evolution
of cooperation found that helping actually often tended to spread more
rapidly through populations with polygamy (Nonacs, 2011). This may be
an instance where the underlying kin selection model actually produces
erroneous predictions [as postulated by Nowak et al. (2010)].
SUCCESSES: BIASED SEX INVESTMENT RATIOS AND
PARENTAGE OF MALES THROUGH WORKER POLICING
Another genetic consequence of the asymmetrical relatedness patterns
attributable to haplodiploidy is that with one singly mated queen (i.e.,
monogynous with monandry), workers are more closely related to full sis-
ters than to their brothers. This preference should drive female investment
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52 / Peter Nonacs
bias to the point where it is exactly offset by the relative mating advantage
of the rare male sex (Trivers and Hare, 1976). Thus, if workers control sex
investment ratios, a 3:1 female-to-male investment bias should result. Over
3 decades of evidence has solidly supported the core of the Trivers and
Hare hypothesis (Nonacs, 1986; Bourke and Franks, 1995; Chapuis and
Keller, 1999; Strassmann and Queller, 2007). Female-biased investment
occurs frequently in species where the sister-brother relatedness asymme-
try is present and far less often in species where it is absent. Within some
species, there are both monogynous, monandrous colonies and others in
which the relatedness difference between females and males is reduced or
absent because of having multiple laying queens or one queen that uses
sperm from multiple males. Extending Trivers’ observation predicts that
such populations should exhibit split sex ratios, with the monogynous,
monandrous colonies favoring females and the others favoring males
(Boomsma and Grafen, 1990). A recent review (Meunier et al., 2008) found
that within-colony relatedness asymmetries do significantly affect bias in
sex investment as predicted by kin selection.
Conflict over male parentage in Hymenoptera can also be present
because workers retain the ability to produce haploid eggs in many spe-
cies, and therefore can produce sons (Bourke and Franks, 1995). Although a
worker’s sons and nephews (r = 0.375) are more closely related than broth-
ers (r = 0.25), males produced by half sisters are less related (r = 0.125).
Thus, when more than 50% of the workers are half sisters, a nonlaying
worker is more related to a queen-produced male than to the average
worker-produced male. Maximization of inclusive fitness would there-
fore predict that workers replace (i.e., police) worker-produced eggs with
queen-produced eggs (Ratnieks et al., 2006). Policing occurs in all exam-
ined species where workers are more related to the queen’s male offspring
than to the average worker-produced male (Wenseleers and Ratnieks,
2006a). Contrary to expectations generated from the relative genetic value
of brothers vs. nephews, however, worker policing also occurs in species
where workers are more related to worker-produced males than to queen-
produced males (Hammond and Keller, 2004). Thus, worker policing may
also often reflect group-level advantages, such as the replacement of less
viable worker eggs with more viable queen-laid eggs (Nonacs, 2006a).
Despite these notable exceptions, extensive phylogenetic analyses support
broad predictions of kin selection theory (Ratnieks et al., 2006; Wenseleers
and Ratnieks, 2006b): (i) Worker policing occurs more frequently in species
where queen-produced males have higher mean relatedness to workers;
(ii) frequencies of worker-produced males correlate to increasing relat-
edness between worker-produced males and workers; (iii) frequency of
worker laying negatively correlates to effectiveness of policing; and (iv)
worker policing is less prevalent after queen death in colonies with lower
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Kinship, Greenbeards, and Runaway Social Selection / 53
between-worker relatedness [i.e., a reversal of the pattern found in ( ii) in
the presence of viable queens].
FAILURES: PATRILINE NEPOTISM IN CASTE
BIAS AND REPRODUCTIVE SKEW
In the eusocial Hymenoptera, sterile female workers primarily raise
the offspring (Bourke and Franks, 1995). These offspring can have a wide
range of relatedness to the tending females as a result of queens mating
with multiple males or multiple fertile queens in colonies. The former
creates patrilines of full sisters within the colony, and the latter can create
worker cohorts ranging in relatedness from nieces (if queens are sisters)
to totally unrelated. Therefore, any worker cohort that manages to have
its full sisters preferentially raised as the future reproductives should
significantly increase its fitness. Careful observation, however, has yet to
find any significant conflict or favoritism over care giving under a wide
range of scenarios. Honey bees (Apis mellifera), whose queens mate with
many males, have been studied most extensively for evidence of queen-
rearing nepotism, but none has been conclusively demonstrated (Tarpy et
al., 2004; Ratnieks et al., 2006). Similar studies in other social Hymenoptera
have also failed to find nepotism in colonies with multiply mated females
or multiple queens (Keller, 1997; Gamboa, 2004).
If facultatively cooperative groups are more productive than the
expected cumulative output of all their individual members, it is possible
for reproduction to be shared so that all individuals have higher fitness
through cooperation (Nonacs and Hager, 2011). A fitness-maximizing divi-
sion of the reproduction (i.e., the reproductive skew within the group) can
be predicted through an inclusive approach. Groups can be stable if all
individuals accrue fitness that is equal to or greater than their expected
fitness from reproducing on their own (Nonacs, 2006b). Although there
are numerous variants of skew models, all share the general features that
predicted skew within groups ought to be affected by the genetic related-
ness of the group members, their relative ability to compete for reproduc-
tive shares, and the relative productivity of groups vs. solitary individuals
(Nonacs and Hager, 2011). In an extensive review of experimental tests
of skew theory, none of these predicted relationships were consistently
found (Nonacs and Hager, 2011). In 21 of 27 studies, there was no sig -
nificant correlation between genetic relatedness and skew across groups
within populations. In 13 of 18 cases, correlates with competitive ability
had no significant effect on skew, and in only 3 of 18 cases did skew sig -
nificantly correlate to factors likely to cause ecological constraints. Finally,
3 of 4 studies estimating inclusive fitness of group members and solitary
individuals found it unlikely that cooperation was favorable for all group
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members. Individuals of low relatedness would probably gain higher
fitness by reproducing solitarily rather than being subordinate group
members. Therefore, the overall evidence suggests that individuals rarely
modulate reproductive shares in response to the intrinsic characteristics
of other group members, such as relatedness (Nonacs, 2006b; Port and
Kappeler, 2010; Nonacs and Hager, 2011).
The failure of reproductive skew models to predict the behavioral
dynamics between group members within populations contrasts with
more accurate predictions at the population or species level. In these com-
parisons, differences in mean within-group relatedness or differences in
environmental constraints for being solitary do accurately predict which
population or species should exhibit the greater reproductive skew (Reeve
and Keller, 1995; Nonacs and Hager, 2011). For example, if two popula -
tions significantly differ in mean within-group relatedness, subordinate
individuals in low-relatedness populations stand to gain more fitness by
reducing reproductive skew. Thus, there would be greater selective pres -
sure with overall low relatedness to share reproduction more equally,
independent of whether individual-level relatedness can be recognized
(Reeve and Keller, 1995).
MECHANISMS OF KIN SELECTION
“Failure” is a semantically loaded word and should not imply that
there are no evolutionary explanations for the observed outcomes in
caste rearing and reproductive skew. However, these explanations invoke
elements that are added to kin selection theory and do not follow from
it. For example, caste-rearing nepotism would be absent if workers are
constrained by an inability to distinguish their own patrilines from others.
Without some means of kin recognition, kin selection could not “fail” as a
hypothesis because it simply would not be relevant to the phenomenon at
hand. Alternately, caste-rearing nepotism could create such within-colony
conflict that overall colony productivity or survival is seriously reduced.
Hence, conflict would not be selectively advantageous. This alternative
explanation, again, does not follow from kin selection theory. No mat -
ter the overall cost, successful nepotists would always have a selective
advantage relative to nonnepotists within colonies. It is only selection on
the across-group level that could favor this ergonomic efficiency explana -
tion for the absence of nepotism. The same two possibilities, constraint
or ergonomics, could also explain why reproductive skew models do not
adequately predict patterns of cooperative breeding (Nonacs and Hager,
2011). Nevertheless, recent work casts doubt on the constraint hypothesis
as a broadly viable explanation. For example, individual ants produce
genetically heritable hydrocarbon profiles that could, theoretically, be
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Kinship, Greenbeards, and Runaway Social Selection / 55
used to identify kin (van Zweden et al., 2010). However, such markers
are readily transferred to create effective nestmate recognition rather than
within-nest nepotism. This leaves only the group selection hypothesis as
a plausible, if unsatisfying, explanation. It is unsatisfying because it is
untestable in many cases; that is, if species A never exhibits caste-rearing
nepotism, how can it be shown that it is because such behavior reduces
overall colony productivity? Therefore, instead of relegating the solu -
tion as only explainable by difficult-to-test group selection, it is useful to
reexamine kin selection predictions relative to the mechanistic aspects of
exactly how individuals recognize or define other group mates as genetic
kin. In essence, kin selection theory may accurately predict the outcomes
for caste rearing and reproductive skew, but the predictions themselves
may differ from earlier expectations.
There are only two ways that kinship can be assigned, either through
recognizing genetic similarity or by using environmental cues that accu -
rately predict genetic similarity. The latter can lead to simple and relatively
effective rules-of-thumb for cooperation. For example, in a population
where most females mate with only one male, two female wasps matur-
ing at the same time on a nest are likely to be full sisters and can behave
according to predictions from Hamilton’s rule. However, such rules-of-
thumb are not absolutely reliable: The females could also be half sisters,
cousins, or unrelated because of multiple mating, multiple foundresses,
or nest usurpation. Errors in estimation of relatedness could be common
(Nonacs, 2006b).
In contrast to using environmental cues, individuals could recognize
kin through a shared phenotypic trait that uniquely represents the pres-
ence of identical alleles. To function as an effective kin selective mecha -
nism, genetic recognition must have three elements: expressed phenotypic
trait(s), an ability to recognize traits in other individuals, and the proclivity
to direct aid toward those others if a suitable opportunity arises (Gardner
and West, 2010). These three elements can either be genetically linked as
a single “greenbeard” system or be a set of genetic markers monitored
by a single perception locus that triggers cooperative behavior (Lacy and
Sherman, 1983). In the second scenario, recognition and action need not
be linked to any cue alleles. Although the basic premise of greenbeard kin
selection is sound, functioning greenbeards have been thought likely to be
rare for several reasons (Gardner and West, 2010). A greenbeard system
must always co-occur within individuals. For example, if the willingness
to aid becomes decoupled from the phenotypic trait, a “falsebeard” indi -
vidual would result. Such individuals would receive benefits from other
greenbeards but would never provide benefits (and thus never incur any
costs for being helpful). Under a wide range of conditions, cheating false -
beards could be at a selective advantage over true greenbeards and pre-
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vent widescale cooperation (Gardner and West, 2010). A second problem
is that successful greenbeard genetic systems would encounter Crozier’s
paradox (Crozier, 1986). As the greenbeard system increases in frequency,
it becomes less useful for identifying kinship (Rousset and Roze, 2007). As
it approaches fixation, it can no longer function for kin nepotism because
almost all individuals in the population would be viewed as identically
related. A final problem for a greenbeard system, but not for phenotype
matching, is that individuals are either highly related at a locus (both have
identical alleles) or totally unrelated. Thus, if the rest of the genome is
Hamiltonian in the sense of estimating relatedness relative to environmen-
tal cues, this could lead to different estimates of r as well as intragenomic
and interlocus conflict. Assuming that disproportionally more loci are
Hamiltonian in driving behavior, this is predicted to lead to suppression
of any greenbeard favoritism (Helanterä and Bargum, 2007); however, an
alternative argument is supported by Gardner and West (2010).
Despite the theoretical objections, more examples of greenbeard
behavior have been found recently in hydrozoans (Grosberg et al., 1985),
slime molds (Queller et al., 2003), yeast (Smukalla et al., 2008), and ants
(Keller, 2007). The most compelling example is in side-blotch lizards ( Uta
stansburiana), where blue-throated males preferentially establish territories
next to each other (Sinervo et al., 2006). These aggregations form with
respect to the blue-throat trait and are not predicted by whole-genome
relatedness. Neighboring blue-throats are more successful at mate guard -
ing against larger aggressive orange males. However, these benefits accrue
only to blue males not next to an orange male; blue males adjacent to
orange males suffer a cost. Possibly in reaction to a perception that such a
greenbeard system could not be evolutionarily stable, Sinervo et al. (2006)
insightfully comment, “A proximate explanation for kin altruism is not
that kin share a fractional number of genes; rather, kin altruists share key
genes for signal, self-recognition, and donation behavior” (p. 7376). In this
context, it is seen that kin nepotism through genetic recognition differs
from existing models of greenbeard nepotism not in process but simply
in the number of genes involved. This view argues that kin selection can
result from a collaboration of multiple greenbeards sharing a common
interest.
SIMULATING DIFFERENT PATHWAYS FOR
THE EVOLUTION OF COOPERATION
Although the evolutionary dynamics of single greenbeard systems
have been extensively examined (Gardner and West, 2010), multiple green-
beards evolving synchronously have not received similar attention. I con -
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Kinship, Greenbeards, and Runaway Social Selection / 57
sider this latter situation by simulating the evolution of helping behavior
under three scenarios:
(i) Help is allocated so as to maximize inclusive fitness as predicted
by Hamilton’s rule.
(ii) Help is allocated relative to recognized shared alleles, with the
helper and helped having the same greenbeard allele(s). In this scenario,
falsebeard mutants can also arise that induce cooperation from greenbeard
alleles but never extend help.
(iii) A mixed system exists where some loci favor cooperation as
predicted by Hamilton’s rule and others behave as greenbeards or false -
beards. This tests the degree to which interlocus conflict can suppress or
mask greenbeard effects.
Phenotype matching (Lacy and Sherman, 1983) is a hybrid version
of greenbeard and Hamiltonian kin recognition, where a number of cues
act as greenbeards but there is only one recognition locus. This locus col-
lates matches from all the cues to generate an estimate of r that is used in
Hamilton’s rule to determine if cooperation occurs. I do not specifically
evaluate phenotype matching, although scenario (i) can be viewed as a
version of the model that is completely accurate for estimating relatedness.
The model is written in TrueBasic.
All simulations assumed a diploid population and started with 500
mothers, each mating with two males. All mothers produced two off-
spring, a potential helper and helped offspring that could be full siblings
or half siblings. All offspring genotypes were randomly determined with
respect to father and which allele was contributed by each parent. Loci
were not linked and segregated independently. Only offspring and no
mothers, helpers, or helped survived to the next generation. For the first
two scenarios, all offspring had 1–15 loci (depending on the simulation)
at which helping behavior could independently evolve. All alleles at these
loci were initially “null” and neutral with respect to whether help was
offered. Helping alleles were randomly mutated into the population at
the rate of 0.01 mutations per offspring. If no cooperation occurred, both
offspring mated twice and produced two offspring of their own, which
were added to the pool from which the next generation’s mothers and
fathers were chosen. Thus, the inclusive fitness of noncooperation (IF NC)
equaled 2(0.5) + 2r, where r is the relatedness of the sibling’s future off-
spring calculated at the level of the entire genome. If cooperation occurred,
the helper did not reproduce and its sibling produced 2–12 offspring (b)
depending on the conditions of the simulations (Table 3.1). This results in
IFC = rb. A Hamiltonian allele would vote “yes” if IFC > IFNC and “no”
otherwise. (Note that to be completely consonant with Hamilton’s rule,
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58 / Peter Nonacs
TABLE 3.1 Payoffs for Helping Behavior
Hamiltonian Greenbeard
Mean
Half Sib Full Sib Helper/Helped
Benefit (b)
Levels r = 0.125 r = 0.25 1/1 1/2 2/1 2/2
Good
Low: b = 4 −0.75 −0.5 0 1 –1 0
Medium: b = 8 −0.25 0.5 2 5 1 4
High: b = 12 0.25 0.5 4 9 3 8
Moderate
Low: b = 3 −0.875 −0.75 −0.5 0 −0.5 −1
Medium: b = 6 −0.5 0 1 0
3 2
High: b = 9 −0.125 0.75 2.5 6 1.5 5
Poor
Low: b = 2 −1 −1 −1 −1 −2 −2
Medium: b = 4 −0.75 −0.5 0 –1 0
1
High: b = 6 −0.25 0 0
1 3 2
Notes: The mean number of offspring produced by helping (b) varies from good to poor,
with a lower, medium, or higher payoff equally likely under each overall condition. For Ham-
iltonian loci, relatedness (r) to the offspring of potential helped individuals is calculated at
the level of the entire genome. The inclusive fitness of noncooperation (IFNC) always equals
two own offspring plus two nieces or nephews, and the inclusive fitness of cooperation (IF C)
always equals rb. Hamiltonian loci vote to provide help (shown in bold) whenever IFC – IFNC
> 0. For greenbeard loci, potential helpers can have either one or two greenbeard alleles (first
number in pair). They may help only individuals that also have one or two identical green -
beards or the matching falsebeard alleles (second number). Greenbeard loci vote to help (in
bold) only when the expected number of alleles transmitted by a helped individual, minus
the sum of helper and helped reproducing noncooperatively, exceeds zero. Therefore, a “yes”
or “no” vote can depend on the zygosity of both potential helper and helped individuals.
the number of offspring raised by the helped offspring without a helper
ought to be subtracted from both IF values. For mathematical simplicity,
I allow this value to cancel out during calculations.) I assume that Hamil -
tonian alleles are completely accurate in discriminating full sibs and half
sibs. This could occur as a modified greenbeard system where a single
recognition/action system simultaneously monitors multiple phenotypic
or environmental cues (unspecified in this model) to estimate genetic
relatedness reliably. Unlike a single greenbeard, the components would
not have to be linked to each other. Similarly, I assume that although b
varies stochastically, the level is always recognized. Thus, Hamiltonian
alleles vote identically across all loci, giving either a 100% yes or no vote
for helping among themselves. Therefore, depending on whether overall
environments were good, moderate, or poor for producing benefits from
cooperation, Hamiltonian alleles would favor helping in ~50%, 17%, or
0% of the possible cases (Table 3.1).
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Kinship, Greenbeards, and Runaway Social Selection / 59
In contrast, at each greenbeard locus, there are four different possible
greenbeard alleles (each producing a hypothetical unique phenotypic cue)
that can mutate into the population. For each greenbeard allele, a match-
ing falsebeard allele can also mutate into the population. A greenbeard
allele in a helper could vote yes if the helped sib had identical green -
beard or matching falsebeard allele(s) at the same locus. It would vote
yes, however, only if a helped individual would be expected to transmit
more greenbeard alleles to the offspring generation than the combined
reproduction of noncooperating helpers and helped (Table 3.1). It would
vote no if noncooperation was expected to transmit more alleles. Thus,
the vote of a greenbeard locus depended on b and the heterozygosity or
homozygosity of the helper and helped with respect to greenbeard and
matching falsebeard alleles. Different greenbeard alleles at the same locus
do not help each other and would vote no. Falsebeard alleles in a helper
always vote no. Thus, across greenbeard loci, there could be a mixture of
yes and no votes and probability of helping occurs relative to the propor-
tion of yes votes (e.g., 12 yes votes and 3 no votes would result in an 80%
probability of helping).
In the third scenario, five loci evolved cooperation as Hamiltonian
and one to five loci evolved as greenbeards, both as described above
(resulting in a range of a 5:1 advantage for Hamiltonian loci to 5:5 equal
weighting). Helping occurs with a probability that is the proportion of yes
votes across all votes by Hamiltonian and greenbeard loci. All scenarios
were simulated for 2,500 generations with 20 replicates. Random mutation
was present for the first 2,000 generations to allow all possible alleles to
enter the population. For the last 500 generations, greenbeard alleles were
prevented from mutating into the population. Therefore, at the end of the
simulations, the frequency of greenbeard alleles was more reflective of
their relative selective advantage (i.e., they could be selectively eliminated
from populations).
RESULTS
The invasion of helping is charted as the proportion of mothers (out
of 500) that produced pairs of offspring that decided to cooperate. Hamil -
tonian alleles rapidly invade a noncooperative population when coopera -
tion is at least sometimes advantageous (Fig. 3.1). The resulting level of
sociality is commensurate with how often IFC > IFNC (e.g., 50%, 17%, or
0%). The number of loci that could be involved has no effect on the rate
of spread of helping behavior. Overall, the system consistently evolves
rapidly to maximize inclusive fitness.
Sociality also often evolves with only greenbeard loci but differs
from Hamiltonian patterns. Unlike with Hamiltonian alleles, a signifi -
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60 / Peter Nonacs
FIGURE 3.1 Increase in sociality
with Hamiltonian alleles that help
if IFC > IFNC for full or half sibs,
as measured by the proportion of
offspring pairs that help each other.
The upper set of lines is for simula-
tions where helping often produces
large benefits (b = 4-12), and the
lower set is for simulations where
helping has moderate benefits (b
= 3–9). No sociality results under
conditions where helping provides
poor benefits (b = 2-6). Lines in
each set represent 1, 3, 7, 11, or 15
loci and are shown for only the first
1,000 generations of the simulation.
cant fraction of the population can exhibit cooperation under conditions
where helping never produced higher inclusive fitness at a genome level
(Fig. 3.2A). Although this level of cooperation was often enhanced through
continual input of greenbeard alleles by mutation, greenbeards continued
to persist for many generations in the population when their entry by
mutation was turned off (Fig. 3.2). Moreover, higher levels of cooperation
evolved and greenbeard alleles persisted longer in the absence of mutation
as the number of greenbeard loci increased across all levels of b.
At most loci, a single greenbeard allele was strongly numerically dom-
inant in frequency no matter the level of b or the number of loci involved.
Thus, Crozier’s paradox (Crozier, 1986) often occurs at individual loci,
where one greenbeard allele rises to high frequency at the expense of all
other possible alleles. Although falsebeard alleles occasionally reached
high frequency, they did not predominate at the majority of loci for any
combination of b and loci number. This result is somewhat surprising
because falsebeards contribute to producing nonhelping phenotypes by
always voting against cooperation. Thus, conditions where cooperation
was never beneficial at a whole-genome level, IFNC ≥ IFC (Table 3.1),
might have been expected to tip the balance of selection toward a false -
beard allele, but this happened only at a minority of loci. As more loci are
interacting or b becomes moderate or good, allele populations are almost
uniformly dominated by a single greenbeard allele.
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Across most individual simulation trials, there appeared to be little
interaction between greenbeard and falsebeard alleles at a given locus.
Occasionally, an increase in the frequency of a matching falsebeard could
tip the balance of selection from one greenbeard allele to another and lead
to a replacement as the most frequent allele in the population .
The high frequency of greenbeard alleles under many conditions
results in more cooperative behavior between siblings than predicted by
Hamilton’s rule for any given b value. For example, even with a large
FIGURE 3.2 Proportion of social pairs with loci that favor helping if individuals
share the same greenbeard alleles or matching falsebeards. Simulations are where
helping provides poor benefits (A, b = 2-6), moderate benefits (B, b = 3-9), or large
benefits (C, b = 4-12). For the last 500 generations, no mutations that produce
greenbeard alleles were allowed.
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mean payoff to cooperation, applying Hamilton’s rule predicts that only
~50% of the helpers’ decisions ought to be to cooperate (Fig. 3.1). Com-
pared with this prediction, cooperation through greenbeards results in
many “mistakes” (Fig. 3.3). Most of the errors are of individuals being
helped when IFC < IFNC predicts no helping.
The results also show that there can be interlocus conflict across
Hamiltonian and greenbeard loci. These two regions of the simulated
genomes can disagree as to whether cooperation is advantageous. The
FIGURE 3.3 Outcome of decisions made by individuals with greenbeard loci.
“Correct” and “incorrect” are determined for 500 pairings relative to whether IFC
> IFNC at the whole-genome level holds with half (r = 0.125) or full (r = 0.25) sibs.
For the last 500 generations, no mutations that produce greenbeard alleles were
allowed. Only the situation with seven greenbeard loci and a large level of benefit
(b = 4–12) is graphed.
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Kinship, Greenbeards, and Runaway Social Selection / 63
FIGURE 3.4 Proportion of social pairs when individuals have both Hamiltonian
and greenbeard loci. The three sets of lines represent conditions with good (top
series, b = 4-12), moderate (middle series, b = 3-9), or poor (bottom series, b =
2–6) benefits for helping. In all simulations, there are five Hamiltonian loci. From
the lowest to highest line in each set, the numbers of greenbeard loci are one,
three, or five. For the last 500 generations, no mutations that produce greenbeard
alleles were allowed. In the absence of greenbeard loci, the three levels of benefit
predict that a pure Hamiltonian population would have approximated 50%, 17%,
and 0% social pairs.
resulting levels of sociality appear to be an approximate balance between
the relative number of loci that select for Hamiltonian or greenbeard lev -
els of cooperation (Fig. 3.4). Thus, cooperation sometimes occurs under
conditions where combinations of sibling relatedness and benefit predict
it should not; however, cooperation also sometimes does not happen in
the presence of shared greenbeard loci across offspring.
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DISCUSSION
Kin Recognition Mechanism and the Expression of Cooperation
In predicting patterns of life history traits, robust theory must com -
bine with a realistic mechanism for action. The distribution of success
and apparent failure in past kin selection predictions for social insects
illustrates the importance of this connection. Thus, genetic mechanisms
for identifying kin (e.g., a hypothetical series of greenbeard loci) are less
likely to maximize an actor’s inclusive fitness than environmental cues
that provide only a probability level of sharing genotypes. That kin selec -
tion theory is accurate only with probabilistic environmental cues helps
to explain patterns of behavior within social insects. For example, the sex
of a given offspring may be hidden for some time through development,
but it must eventually become recognizable (Nonacs and Carlin, 1990).
This gives workers a clear cue for biasing investment toward females
and away from males. Similarly, having multiple matrilines or patrilines
within a single colony may give out an unmistakable diversity signal (van
Zweden et al., 2010). Therefore, kin selection models for optimal sex ratio
investment have usable proximate cues and function well in predicting
ultimate allocation patterns at both the colony and population levels.
Conflict over and suppression of worker laying similarly have an
available proximate mechanism. Although both workers and queens can
produce male eggs, an increasing body of evidence shows that queen eggs
are recognizably different from worker eggs in morphology and chemical
signatures (Ratnieks et al., 2006; van Zweden et al., 2009; Meunier et al.,
2010). As a result of nutritional differences, queens may always be able
to imbue their eggs with specific signals that cannot be faked by work-
ers. Thus, workers can discriminate between eggs and maximize their
inclusive fitness through manipulating which individuals will produce
the males.
In comparison, there is almost no supportive evidence for within-
colony nepotism in the production of new queens (Keller, 1997; Gamboa,
2004; Tarpy et al., 2004; Ratnieks et al., 2006). This is despite a potentially
huge boost in inclusive fitness for eusocial Hymenoptera (e.g., the replace-
ment of an unrelated female, r = 0, or half sister, r = 0.25, with a full sister,
r = 0.75). From a mechanistic perspective, however, the only cues that
workers could use to behave nepotistically would be through recognizing
one or more shared alleles. Similarly, reproductive skew models require
that group members estimate kinship in apportioning reproductive shares.
Although unstated in the models, this assumes a type of greenbeard
kin recognition and may be why they fail to predict skew across groups
within populations. There is no obvious nongenetic cue that would, for
instance, be able to differentiate emerging adults on the same nest as full
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Kinship, Greenbeards, and Runaway Social Selection / 65
sisters rather than cousins. However, evolved patterns of reproductive
sharing at population or species levels ought to reflect the expected mean
levels of relatedness or ecological constraints, regardless of any ability for
individual-level recognition of genetic relatedness. Hence, skew models
are relatively more successful at predicting population-level differences
in reproductive sharing (Nonacs and Hager, 2011).
An interesting result from the simulation models is that greenbeard
nepotism results in seemingly overly cooperative populations (Fig. 3.3),
which is exactly how caste nepotism and reproductive skew appear to fail.
In both cases, individuals are too nice. In caste determination, matrilines
do not discriminate across females in how they are treated. Close kin, dis-
tant kin, and nonkin are equally helped. Reproductive skew on wasp nests
tends to be very high, indicating that subordinates willingly cooperate to
their apparent fitness detriment (Nonacs et al., 2006). Most paradoxically,
fertile unrelated wasps join (and are allowed to join) groups with no differ-
ential treatment (Queller et al., 2000; Leadbeater et al., 2010). Relatedness
has no predictive role in establishing aggression patterns or dominance
hierarchies on nests (Nonacs et al., 2006; Leadbeater et al., 2010).
Runaway Social Selection Through Greenbeard Nepotism
The significance of greenbeard kin nepotism in evolutionary biology
is controversial (Gardner and West, 2010; Leigh, 2010). However, in the
models presented here, two of the three major objections to greenbeards
often fail to prevent the evolution of helping. A falsebeard cheating geno -
type that accepts cooperation but does not reciprocate rarely destabilizes
a greenbeard kin recognition. The inability of a falsebeard to predominate
may result from several simultaneous processes. First, positive kin assort -
ment into sibling pairs often imposes a cost onto cheating. Although there
is the probability of drawing benefits from unrelated greenbeards, there
can be the relatively greater chance of not helping siblings that share iden -
tical falsebeard alleles when such help would increase allele frequencies.
A second process occurs as a greenbeard allele reaches higher frequencies.
At this point, more of the helper/helped pairings involve homozygous
individuals, which increases the net gain for helping (Table 3.1). This may
generate positive feedback in more helping and continued increases in
allele frequency. Finally, when greenbeard alleles predominate at multiple
loci, they will increase commonality of interest. This could result in green -
beard alleles forming a “voting block” as regards cooperation and depress
the selective advantage of a falsebeard at any individual locus. Altogether,
the results are strongly suggestive that models of greenbeard recognition
systems based on single-locus dynamics (Gardner and West, 2010) may
predict very different outcomes from multilocus situations. These rami-
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fications need to be explored more extensively in future work. Also, the
models here assume idealized versions of Hamiltonian and greenbeard
alleles in that all alleles “know” the payoff for helping, know the cost for
abandoning direct reproduction, and properly identify shared alleles or
correctly measure r. The effects of mistakes in these estimates could be
valuable to consider (Nonacs, 2006b).
The second objection is that greenbeards will sometimes function to
the detriment of the much larger nongreenbeard genome, and therefore are
expected to be suppressed (Helanterä and Bargum, 2007). However, sup -
pression is only partial in this model. Shared greenbeard alleles increase
in populations and raise levels of cooperation proportional to their abun -
dance relative to Hamiltonian loci (Fig. 3.4). This supports the view that
greenbeard alleles are not intragenomic “outlaws” but are under similar
selection pressures as the rest of the genome (Gardner and West, 2010).
An effect of greenbeard nepotism is that it quickly increases the fre-
quency of arbitrary phenotypic traits in social settings in what is very
much a “runaway” process (i.e., in the absence of social interactions, the
traits convey no benefit to their bearer). This outcome is relevant to West-
Eberhard’s (1983) proposal that parents might allocate resources biased
toward offspring with particular traits that have no effect other than being
“attractive.” If such attractive traits are greenbeards, their bearers would
benefit from the genetic correlation between trait and preference as in
runaway sexual selection. The process could be further enhanced by the
feedback between the commonness of an allele and increased payoffs for
cooperation. Such runaway social selection is proposed for bright color-
ation and plumage in young birds, which appears to function in attracting
parental care (Lyon et al., 1994; Ligon and Hill, 2010) but, interestingly,
not in identifying kin (Shizuka and Lyon, 2010). Moreover, rapidly reach-
ing Crozier’s paradox (i.e., fixation at the loci involved) may leave no
trace in present-day behavior of past genetically based favoritism across
offspring. This suggests that some morphological and behavioral traits
in social species without clear adaptive value may have evolved through
greenbeard nepotism.
In this suite of traits arising from greenbeard nepotism could be the
initial evolution of cooperative breeding itself. Specifically, greenbeard
traits can produce low levels of social behavior under conditions where
Hamilton’s rule would predict no cooperation (Fig. 3.2). If, for exam-
ple, offspring dispersal is limited, positive kin assortment would result
among neighboring individuals. This would create preconditions where
greenbeard alleles producing alloparental behavior could be selectively
favored. If alloparental care is as simple as feeding a nearby hungry
mouth (Jamieson, 1989), a greenbeard trait for feeding a “mouth like
mine” could evolve even if it did not appear to increase kin selective
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Kinship, Greenbeards, and Runaway Social Selection / 67
inclusive fitness (Emlen et al., 1991; Komdeur, 1996). Once social groups
are established, more elaborated forms of cooperation could evolve with
enhanced benefits provided to helped individuals that are potentially in
line with Hamilton’s rule.
Another trait that could result through runaway social selection is the
phenomenon within ants of unicoloniality. Unicoloniality occurs when
adjacent nests show atypically low or no aggression toward each other and
is commonly associated with invasive ant species, where supercolonies
can arise that extend over thousands of kilometers (Helanterä et al., 2009).
Unicolonial associations are genetically homogeneous, with the majority
of ants having low relatedness to each other. The reduction in intraspe-
cific aggression appears to be attributable to a loss of genetic diversity at
recognition loci (Suarez et al., 2008). Although unicolonial behavior may
be enhanced by genetic bottlenecks, it is also present in situ in native habi-
tats and apparently can evolve within large populations (Pedersen et al.,
2006; Wang et al., 2010). In other words, unicoloniality can be selectively
favored and is not simply always a byproduct of genetic bottlenecks from
introductions. Interestingly, unicoloniality could be categorized as work -
ers showing excessive cooperation by accepting and raising unrelated
individuals, exactly as predicted by the model of greenbeard cooperation.
The suggestion would be that if greenbeard alleles arise in a species at their
recognition loci, it would be possible for such alleles to sweep through a
population, carrying unicoloniality in their wake. This would lead to high
genetic similarity at recognition loci in populations where within- and
across-nest relatedness is almost identical [which is indeed observed in
unicolonial ants (Brandt et al., 2009)]. Finally, it is a suggestive coincidence
that one of the known greenbeard allele systems (Gp-9 in fire ants) appears
to have arisen in an exotic species as that species was simultaneously
evolving a unicolonial population social structure (Keller, 2007).
Genetic Diversity, Relatedness, and Social Heterosis
Controversies about kin selection often concern the best methods to
model the effects of genetic relatedness (Wilson and Hölldobler, 2005;
Foster et al., 2006; Lehmann et al., 2007; West et al., 2007c; Wilson and
Wilson, 2007; Nowak et al., 2010). This tends to obscure the more salient
point of how important the level of relatedness is for favoring cooperation
(Nonacs, 2011). The dynamics of social groups can be dominated by either
their genetic relatedness or their genetic diversity, because both bring
evolutionarily selective advantages. High relatedness means that group
benefits will tend to be exclusively shared by alleles identical by descent.
It becomes relatively less important which individuals are the reproduc-
ers and which individuals are the helpers (Nonacs and Hager, 2011). In
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contrast, higher genetic diversity can create social heterosis, or the ability
to exploit a wider range of resources more effectively, and thus increase
total group benefits (Nonacs and Kapheim, 2007). Although more restric-
tive on the possible skew between reproducers and helpers, within-group
outcomes become less important relative to across-group competition. The
evolutionarily inescapable point is, however, that nepotism, as predicated
on Hamilton’s rule, must come at the expense of genetic diversity. Simi-
larly, selection for genetic diversity may require behavioral biases against
closer genetic relatives. Relatedness and diversity have an unavoidable
tradeoff between them.
The model presented here gives no advantage to genetic diversity;
therefore, cooperation evolves to maximize population-level genetic simi -
larity. Alleles go to high frequency or fixation acting either as greenbeards
or to maximize genome-level inclusive fitness. Nevertheless, one might
expect that the diversity/ relatedness tradeoff could be different for green-
beard or Hamiltonian alleles. Any natural system where the benefits of
cooperation are primarily directed to close relatives would strongly select
against genetic diversity. In contrast, cooperation could evolve with con -
siderably less of a tradeoff with a greenbeard kin recognition mechanism.
The benefits of cooperation would not necessarily only flow to the closest
relatives. As argued above in the case of ant unicoloniality, selection for
nepotism based on greenbeard similarity could potentially affect only a
limited part of the genome. Social heterosis could simultaneously select
for genetic diversity at the remainder of the genome, with the result being
a patchwork genome of regions of low and high genetic diversity (Nonacs
and Kapheim, 2007). It is difficult to imagine how such opposing selective
processes could simultaneously operate when one or more traits are being
selected relative to their probabilities of being shared. Kin nepotism fol -
lowing Hamilton’s rule will always work to reduce genetic diversity. It is
the dynamic evolutionary consequences of selection for kin vs. selection
for genetic diversity that should draw the future attention of both theoreti-
cians and experimentalists.
ACKNOWLEDGMENTS
I thank J. Field, D. C. Queller, T. Wang, and an anonymous reviewer
for helpful comments on the manuscript.
