1.3 Fitness and inclusive fitness

Defining fitness

Fitness is a central concept in evolutionary biology that measures an individual's ability to survive and reproduce in a given environment. In animal behavior, fitness explains why certain behaviors evolve and persist in populations over time.

Fitness as reproductive success

Fitness is often equated with reproductive success: the number of offspring an individual produces that survive to reproductive age. Individuals with higher reproductive success are considered more fit, and their genes are more likely to be passed on to future generations.

Behaviors that increase reproductive success include effective foraging strategies (lions hunting cooperatively in prides to take down larger prey) and successful mate attraction (a peacock's elaborate tail display signaling genetic quality to peahens).

Direct vs. indirect fitness

• Direct fitness refers to an individual's own reproductive output.
• Indirect fitness accounts for the reproductive success of genetic relatives that an individual helps along.

Behaviors boosting direct fitness include securing resources and attracting mates. Indirect fitness increases through behaviors that help relatives survive and reproduce, such as meerkat sentinels giving alarm calls that put themselves at risk, or African wild dog helpers assisting with pup-rearing at the den.

Genotype frequency changes

Fitness ultimately drives changes in genotype frequency across generations. Genotypes linked to higher fitness increase in the population; those linked to lower fitness decline. This differential survival and reproduction is the engine behind evolutionary change.

Measuring fitness

Quantifying fitness is essential for understanding how behaviors evolve and for making predictions about future evolutionary trajectories. Several metrics exist, each with trade-offs.

Absolute vs. relative fitness

Absolute fitness is the total number of surviving offspring an individual produces over its lifetime. Relative fitness compares an individual's reproductive output to the population average.

Relative fitness is usually more informative because it accounts for population context. For example, producing 10 offspring sounds impressive, but if the population average is 20, that individual's relative fitness is only 0.5, meaning it's being outcompeted.

Fitness components

Fitness can be broken into components:

• Survival (living long enough to reproduce)
• Mating success (securing mates)
• Fecundity (number of offspring produced)

Studying these separately reveals which specific factors drive an individual's overall fitness. In many bird species, for instance, both survival (evading predators) and mating success (attracting mates through colorful plumage or song) contribute, but their relative importance can differ between populations or seasons.

Challenges in quantifying fitness

Measuring fitness in wild populations is difficult. Researchers must track individuals across their entire lifetimes and accurately assess reproductive success, which is rarely straightforward. Fitness is also context-dependent: it can shift across environments, seasons, or life stages.

Long-term field studies and genetic markers (like microsatellites for paternity analysis) have helped overcome some of these obstacles, but comprehensive fitness measurement remains a complex task.

Inclusive fitness theory

Inclusive fitness theory, proposed by W.D. Hamilton in 1964, extends classical fitness by incorporating the effects of an individual's actions on the fitness of genetic relatives. This framework explains the evolution of seemingly altruistic behaviors that benefit others at a cost to the actor.

Concept of inclusive fitness

Inclusive fitness is the sum of an individual's direct fitness and indirect fitness. An individual can increase its inclusive fitness by enhancing the reproductive success of close relatives, even at personal cost.

In many social insect colonies, for example, workers never reproduce. Instead, they help raise the queen's offspring. Because those offspring share a large proportion of the workers' genes, the workers gain indirect fitness through this arrangement.

Direct fitness benefits

Direct fitness benefits come from behaviors that increase an individual's own reproductive success, such as gaining access to resources, securing mating opportunities, or improving survival. Male lions, for instance, defend territories to maintain exclusive access to females, directly boosting their own reproductive output.

Indirect fitness benefits

Indirect fitness benefits come from helping genetic relatives reproduce. These benefits scale with the degree of relatedness between the helper and the beneficiary: the more genes shared, the greater the indirect payoff.

Examples include:

• Cooperative breeding in meerkats: Helpers guard and feed pups that aren't their own offspring but are siblings or nieces/nephews.
• Food sharing in vampire bats: Bats regurgitate blood meals for roostmates, often close kin, who failed to feed that night.
• Alarm calls in Belding's ground squirrels: Females give alarm calls more frequently when close kin are nearby, despite attracting predator attention to themselves.

Kin selection

Kin selection is the evolutionary process by which traits benefiting genetic relatives are favored by natural selection, even when those traits are costly to the individual performing them. It's the mechanism through which inclusive fitness operates.

Genetic relatedness

Genetic relatedness ($r$) is the proportion of genes two individuals share due to common ancestry. Relatedness is central to kin selection because individuals gain more indirect fitness by helping close relatives who share more of their genes.

Common relatedness values in diploid organisms:

• Parent to offspring: $r = 0.5$
• Full siblings: $r = 0.5$
• Half-siblings: $r = 0.25$
• Grandparent to grandchild: $r = 0.25$
• Cousins: $r = 0.125$

In many bird species, siblings cooperate to defend shared territories or help raise each other's offspring precisely because of this high relatedness.

Hamilton's rule

Hamilton's rule provides a simple inequality for predicting when altruistic behavior will be favored by natural selection:

$rB > C$

Where:

• $r$ = genetic relatedness between actor and recipient
• $B$ = reproductive benefit to the recipient
• $C$ = reproductive cost to the actor

A behavior evolves when the benefit to the recipient, weighted by relatedness, exceeds the cost to the actor. This is why you see more altruism directed toward closer relatives: higher $r$ makes the inequality easier to satisfy.

As J.B.S. Haldane reportedly quipped, he would lay down his life for two brothers (each $r = 0.5$) or eight cousins (each $r = 0.125$), since the genetic math works out.

Altruism vs. selfishness

• Altruism: behaviors that benefit others at a cost to the actor.
• Selfishness: behaviors that benefit the actor at the expense of others.

Kin selection explains how altruism can evolve when directed toward genetic relatives, because indirect fitness gains outweigh personal costs. Social insect workers that forgo reproduction to raise the queen's offspring are a classic example of kin-selected altruism. In contrast, individuals in many species selfishly hoard resources or monopolize mates when the fitness payoff from helping relatives is too low.

Evolutionarily stable strategies

Evolutionary game theory is a mathematical framework for studying how behavioral strategies evolve in populations. It identifies strategies that, once common in a population, resist invasion by alternatives.

Game theory in animal behavior

Game theory models interactions between individuals as strategic decisions, where outcomes depend on what everyone else does. In animal behavior, it's used to analyze the evolution of cooperation, aggression, and mating tactics.

The hawk-dove game is a classic example. "Hawks" always fight over resources; "doves" always back down. If everyone plays hawk, injuries are frequent and costly. If everyone plays dove, a rare hawk invader wins every contest. The stable outcome is typically a mixed population of both strategies.

Nash equilibrium

A Nash equilibrium is a set of strategies where no individual can improve its fitness by unilaterally switching to a different strategy. In animal behavior, this represents a stable state where everyone is already using the best available strategy given what others are doing.

In the producer-scrounger game, producers search for food while scroungers steal from producers. A Nash equilibrium is reached when the ratio of producers to scroungers stabilizes at a point where neither strategy yields higher fitness than the other. If scroungers become too common, there's nothing left to steal and producing becomes more profitable, pushing the ratio back.

Evolutionarily stable strategies (ESS)

An evolutionarily stable strategy (ESS) is a Nash equilibrium that also resists invasion by rare mutant strategies. Once a population adopts an ESS, no alternative strategy can spread because individuals using the ESS always have equal or higher fitness.

Examples of ESS in animal behavior:

• Fisher's principle: The roughly 1:1 sex ratio in many species is an ESS because any deviation creates a fitness advantage for the rarer sex, pushing the ratio back.
• Cooperation vs. defection dynamics: In repeated social interactions (modeled by the iterated prisoner's dilemma), strategies like tit-for-tat can be evolutionarily stable.

Inclusive fitness in eusocial insects

Eusocial insects (ants, bees, wasps, and termites) display some of the most extreme social organization in the animal kingdom. Their complex caste systems and cooperative behaviors have been central to testing inclusive fitness theory.

Haplodiploidy hypothesis

The haplodiploidy hypothesis proposes that the unusual genetics of hymenopteran insects (ants, bees, wasps) predisposes them toward eusociality. In haplodiploid species, males develop from unfertilized eggs and are haploid (one set of chromosomes), while females develop from fertilized eggs and are diploid (two sets).

This creates an asymmetry in relatedness:

• Sisters share $r = 0.75$ on average (they get identical genes from their haploid father, plus overlap from their mother).
• A mother shares only $r = 0.5$ with her daughters.

Because sisters are more related to each other than a mother is to her own offspring, workers can gain more inclusive fitness by raising sisters (the queen's daughters) than by reproducing themselves. This asymmetry is thought to have favored the evolution of sterile worker castes.

However, haplodiploidy alone doesn't fully explain eusociality. Termites are eusocial but diploid, and many haplodiploid species are not eusocial. Other factors like ecological constraints and colony defense also matter.

Worker policing

Worker policing occurs when workers destroy eggs laid by other workers, ensuring that only the queen's offspring are reared. This behavior makes sense through kin selection: in colonies where the queen mates with multiple males, workers are more closely related to the queen's sons ($r = 0.25$) than to other workers' sons ($r = 0.125$ on average with multiple paternity).

In honeybees, workers actively detect and eat eggs laid by other workers, maintaining the queen's reproductive monopoly. This policing keeps the colony's genetic interests aligned.

Queen-worker conflicts

The interests of queens and workers don't always align, creating queen-worker conflicts. A major area of conflict is the sex ratio of offspring.

• Workers in haplodiploid species are more related to sisters ($r = 0.75$) than to brothers ($r = 0.25$), so they prefer a female-biased sex ratio.
• The queen is equally related to sons and daughters ($r = 0.5$), so she prefers an equal sex ratio.

In many ant species, workers manipulate the sex ratio toward females by selectively destroying male larvae or allocating more resources to female brood. The observed sex ratios in these colonies often fall between the queen's optimum and the workers' optimum, reflecting an ongoing tug-of-war.

Criticism and limitations

Inclusive fitness theory has been enormously influential, but it has also faced substantive criticism. Understanding these limitations gives you a more complete picture of how behavioral evolution is studied.

Challenges to inclusive fitness theory

Some researchers, notably Martin Nowak, Corina Tarnita, and E.O. Wilson (2010), have argued that inclusive fitness theory is unnecessarily complex and that standard population genetics models or multilevel selection theory can explain altruism more simply. Others have questioned key assumptions, such as the additivity of fitness effects and whether relatedness can always be accurately estimated in natural populations.

Empirical studies have sometimes failed to find the predicted relationship between relatedness and altruistic behavior. Eusociality in termites (which are diploid, not haplodiploid) is one case where relatedness asymmetry alone can't explain the evolution of sterile castes.

Alternative explanations for altruism

• Reciprocal altruism (Trivers, 1971): Individuals help others expecting future reciprocation. This doesn't require kinship. Vampire bats share blood meals with unrelated roostmates who have shared with them before, and they refuse to share with individuals who haven't reciprocated.
• Group selection / multilevel selection: Traits benefiting the group can be favored even if costly to individuals, provided between-group selection is strong enough to override within-group selection against altruists.

These alternatives don't replace inclusive fitness theory but complement it. Different mechanisms can operate simultaneously.

Importance of non-additive interactions

Inclusive fitness theory assumes that the fitness effects of genes are additive, meaning an individual's fitness equals the sum of each gene's contribution. In reality, non-additive interactions complicate this picture:

• Epistasis: Interactions between genes at different loci can produce fitness effects that aren't predictable from individual gene effects alone.
• Genotype-by-environment interactions: The same genotype may produce different fitness outcomes depending on environmental conditions.

In some social insects, the expression of altruistic behaviors depends on the interaction between genotype and environmental factors like colony size or resource availability. Ignoring these non-additive effects can lead to inaccurate predictions about when and where altruism should evolve.