Posts Tagged ‘ animal ’

Evolution of Animal Fighting Behaviour

It is recommended that you read ‘An Introduction to the Evolution of Animal Fighting Behaviour‘ before you read this, as there are some concepts explained in the earlier article which are used without explanation in this article.


Success in fighting behaviour is frequency dependent i.e. as the population size increases fighting success decreases. Fighting behaviour amongst a species is often explained in terms of roles, for example we have previously looked at the fairly simplistic Hawk/Dove model which gives animals the role of either hawk or dove.

When determining which strategy will be dominant amongst a population we check it against the ‘standard conditions’ of Maynard Smith. If a strategy is adopted amongst the majority of a population we call it an evolutionarily stable strategy (ESS). An ESS is a strategy which, if adopted by most members of a population, cannot be invaded by a mutant strategy which is initially rare. The standard conditions to determine if a strategy (e.g. strategy I) is an ESS are:


1 – E (I, I) > E (J, I)


2 – If E (I, I) = E (J, I) then E (I, J) > E (J, J)

E (I, I) is the payoff of strategy I against strategy I. Therefore by the conditions of 1, strategy I is an ESS if the payoff of I vs. I is greater than the payoff J receives from fighting I i.e. E (J, I).

The Hawk/Dove/Retaliator Model

The Hawk/Dove model makes certain assumptions:

  • Animals fight with equal ability
  • Animals fight in pairs
  • Animals can only display, escalate or retreat
  • Encounters are random

Due to the limitations of the Hawk/Dove model an additional strategy was added – retaliator

  • Hawks (H)– Escalate immediately, retreat if injured
  • Doves (D)– Display immediately, retreat if opponent escalates
  • Retaliators (R)– Immediately display, escalate if opponent escalates and retreat if injured

The payoff matrix looks like this:

Vs. > H D R
H (V-C)/2 V (V-C)/2
D 0 V/2 (V/2)x 0.9
R (V-C)/2 (V/2)x 1.1 V/2
  • V = Value of resource.
  • C = Cost paid attempting to gain resource.
  • The reason for the x1.1 is that retaliators do slightly better than doves (10%) as they sometime escalate so their payoff is increased.
  • The reason for the x0.9 is the same as above, but because the doves sometimes lose, their payoff is reduced by 10%.

When V>C: Hawk is not an ESS, doves are unable to invade and therefore retaliator is an ESS.

When V<C: Hawk is not an ESS, doves are unable to invade and therefore retaliator is an ESS.

The War of Attrition

When 2 animals meet in a contest for a resource, the amount of energy they are willing to invest to win that resource are predetermined. The animal will therefore display until this time/energy is up. This value is not modified during the display. In the contest, the animal which wins is therefore the one who invested the most predetermined energy. We can model this:

  • Rate of cost accumulation: c
  • Contest length: T
  • Cost of contest: cT
  • Resource value: V
  • Animal A persistence time: TA
  • Animal B persistence time: TB

In this example TA > TB

Payoff to animal A = V – cTB (Animal A wins the resource V but still has to pay the cost, c for the length of the contest, the length of the contest would therefore be TB as the contest ended when animal B gave in.)

Payoff to animal B = – cTB (Animal B does not win any resource, but must still pay the energy that was used during the contest)

A population does not evolve a constant persistence time, however:

  • If cT < V it is worth persisting longer for a resource as the payoff is greater than the cost.
  • If cT > V then a persistence time of 0 spreads amongst the population as to engage in contest for the resource will mean a loss of energy (even if winning). It is therefore better to not engage and lose nothing.

The length animals choose as their persistence time follows a negative exponential distribution, i.e. many choose short times and a very limited number choose long times. The length of contests will therefore also follow this distribution. The log of the number of contests plotted against the length of the contests will give a straight line.


  • Damselfly larvae compete for perching space. Intruders encroaching on perching space will be warned by a ritualised display of the abdomen. The intruder may either leave or contest against the perch space owner. The contests are slow, but their duration follows the negative exponential predicted earlier, however 70-80% of the contests are won by the original occupant and not the 50% you would expect.
  • The fighting of male dungfly over female dungfly (which can be considered a resource) follows the same negative exponential pattern.

The assumption that all contests are fought symmetrically (equal chances of winning) is false, we can assume asymmetry because:

  • Resource Value – Resources are worth more or less to different animals, e.g. a piece of food may be worth more to a hungry animal than a recently fed animal.
  • Resource Holding Power (RHP) – The fighting ability of the animal, this will vary amongst the population, those with a higher RHP will be more likely to win a contest.
  • Uncorrelated Asymmetry – This is any asymmetry which is not correlated to the value of the resource.

Resource Holding Power (RHP):

  • RHP is the fighting ability of an animal, therefore the animal with the greatest RHP is going to keep the resource and the animal with the lower RHP will retreat.
  • Animals must therefore find a way to assess the RHP of others.
  • If RHPs are of similar value, this is when a fight will escalate.
  • For example:
    • The roar contest in red deer helps to determine the RHP. The deer with the lower roaring rate retreats as it is very likely to have a lower RHP. This type of contest is a true signal of RHP (unlike size for example).
    • Croaking in toads when trying to find/compete for a female allows the toads to determine RHP and thus whether or not to attack. Larger males produce deeper croaks and are determined to have a higher RHP.

Bourgeois Strategy

The Bourgeois strategy is a method used to determine the payoff values for competing for resources. It is substituted into the Hawk/Dove model. The Bourgeois strategy is:

  • If it is the owner of a resource, it plays hawk
  • If it is the intruder, it plays dove
  • The assumption is 50% of the time; the Bourgeois is the owner of the resource.

When we put this into a payoff matrix we get the results:

  • If V>C – The hawk strategy is an ESS
  • If V<C – The Bourgeois strategy is an ESS

e.g. The speckled wood butterfly protect areas of sunlight as they are looking for a mate. When an intruder approaches a short spiral fight occurs. The owner of the path of sunlight always wins the spiral fight. If there is confusion over the ownership of the sunlight patch then the spiral fight lasts much longer.

There also exists an Anti-Bourgeois strategy where the intruder always wins the resource for example:

  • In certain spider species, intruders always displace the owner of a web funnel.
  • Seagulls on a flag post always give up the space immediately to invaders.

Introduction to Kin Selection


Some organisms tend to exhibit strategies that favour the reproductive success of their relatives, even at a cost to their own survival and/or reproduction. The classic example is a eusocial (highly social) insect colony, with sterile females acting as workers to assist their mother in the production of additional offspring. Many evolutionary biologists explain this by the theory of kin selection. Natural selection should eliminate such behaviours; however, there are many cases, such as alarm calling in squirrels, helpers at the nest in scrub jays, and sterile worker castes in honey bees, in which these animals cooperate despite an obvious disadvantage to the donor.

This sacrifice of individual success for the aid of other individuals is known as altruism.

There are thought to be four possible ‘routes’ to altruism – why it might arise, these are:

  • Kin selection – Keeping altruism in the family, possibly shared in the genes. Altruism within a family helps it to proliferate well.
  • Reciprocal altruism – ‘One good turn, deserves another.’ Altruism expressed by an individual is at some point returned. E.g. social grooming in primates, the individual doing the grooming is eventually groomed back.
  • Selfish mutualism – ‘What’s in it for me?’ Altruism which is expressed only because an individual also gains from it. E.g. feeding in house sparrows, they will call for help to break up large pieces of food which they are unable to carry alone thus losing some of the resource but gained more than they would have alone.
  • Group selection – ‘For the good of the group.’ Groups within a population – not necessarily family – which benefit by co-operation.

Kin Selection

John Maynard Smith described Kin Selection in 1964 as “…The evolution of characteristics which favour the survival of close relatives of the affected individual, by processes which do not require any discontinuities in the population breeding structure.”

It goes on the idea that because similar genes are more prevalent within a family (either by kind [species] or by descent [ancestral]), any altruistic genes expressed within the family are more likely to become more prevalent within the entire species.

Kin selection refers to changes in gene frequency across generations that are driven at least in part by interactions between related individuals. Under natural selection, a gene encoding a trait that enhances the fitness of each individual carrying it should increase in frequency within the population; and conversely, a gene that lowers the individual fitness of its carriers should be eliminated. However, a gene that prompts behaviour which enhances the fitness of relatives but lowers that of the individual displaying the behaviour (altruistic genes), may nonetheless increase in frequency, because relatives often carry the same gene; this is the fundamental principle behind the theory of kin selection. According to the theory, the enhanced fitness of relatives can at times more than compensate for the fitness loss incurred by the individuals displaying the behaviour.

Hamilton’s Rule

Whether or not altruism is favoured within a family or species depends on whether or not Hamilton’s rule is met:

Hamilton’s Rule: rB-C>0 or rearranged rB>C

Altruism is favoured when rB>C

  • C – The cost of displaying altruism, any disadvantages to the individuals.
  • B – Benefit to the individual(s) who receive aid.
  • r – The coefficient of relatedness. The probability that 2 individuals contain a gene identical by descent at the same locus. It has a value of 0-1.

Possible r values:

Relationship Coefficient of Relatedness
Identical Twins 1.0
Parent to an offspring 0.5
Siblings 0.5
Half Siblings 0.25
Unrelated individuals 0.0

Hamilton’s rule therefore predicts that we expect closer related individuals to express greater amounts of altruism. For example:

Would a mother warn her child of a predator, thus exposing herself as a target? If doing so has an arbitrary value of 2, but the benefit of saving the child of 5 then using Hamilton’s Rule the following must be true:

r(0.5) x B(5) – C(2) > 0

0.5 x 5 – 2 = 0.5

Thus as the value is greater than zero, altruism in this situation is favoured, would the same be true between half siblings? (r=0.25)

r(0.25) x B(5) – C(2) > 0

0.25 x 5 – 2 = -0.75

Because the result of Hamilton’s rule is less than 0, altruism in the same situation but a half-sibling attempting to warn a half-sibling, is not favoured.

Introduction to optimal foraging theory


Darwinian fitness – The rate of increase of a gene in the population, this is difficult to measure. It describes the capability of an individual of certain genotype to reproduce, and usually is equal to the proportion of the individual’s genes in all the genes of the next generation. If differences in individual genotypes affect fitness, then the frequencies of the genotypes will change over generations; the genotypes with higher fitness become more common. This process is called natural selection.

Survival value – Survival value is how a form of behaviour contributes to survival.  For example the removal of an eggshell to prevent predation, how will this affect the survival of the organism within the egg shell?  Early removal of the egg shell removes the stimulus of the egg shell which is a sign to predators that there is food available (the egg) for them to eat, however the early removal of the egg shell means that the young will be underdeveloped and are less likely to survive. Also in certain species of gulls this leaves the newly hatched gulls prone to cannibalism of each other, in this species of gull the parents remove the shell after 30 minutes the chicks hatch. This is also an example of a trade-off.

Trade-off – A trade-off is a situation that involves losing one quality or aspect of something in return for gaining another quality or aspect. It implies a decision to be made with full comprehension of both the upside and downside of a particular choice.  In terms of animal behaviour, these aspects are different behaviours.  See the above example.

Optimal foraging theory

Optimal foraging theory or the optimal patch model is the exploitation of resource patchiness.  Food tends to be clumped which gives rise patches of food/resources.  If we think of Tt as the travel time between patches and Tp as the time spent in the patch we can begin to develop optimal patch model.  More time spent per patch means more energy used for foraging, as prey numbers in the patch decrease, less time spent in the patch means relatively large amounts of time will be spent on travelling.  This is the basis of the optimal patch model.

This graph shows the period of travelling Tt, in relation to the period in the patch Tp. The grey line shows the prey consumed whilst the red line (gradient) is the energy gain:

The gradient (energy gain) is equal to:

E/Tp+Tt   (E = energy gain, Tp = Time in patch, Tt = Travel Time)

The optimal patch time (the optimal amount of time spent in the patch) is when the gradient (energy gain) is at a tangent. At this point any further time spent in the patch will not produce sufficient energy gain from prey as the prey resource has decreased. It is now more efficient to move onto the next patch.

When the distance between patches increases, the time spent in the patch for efficient energy gain also increases.  We can see this by using the graph, as the travel time increases the gradient becomes less meaning it reaches a tangent at a later point.  This later point is the optimal patch time.  This is a benefit to the organism because of the increased travel time between patches which require more energy; due to the increase in energy requirements it is more beneficial to remain in the patch for a longer period of time to extract more energy from the resource i.e.  Consume more prey.

This model does make some assumptions however:

  • That the patches are equidistance apart
  • That the patches are equally stocked with prey

An Introduction to Animal Behaviour and Sociobiology

Tinbergen’s four Questions of Ethology

Explanations to Tinbergen’s questions can be split into two groups; evolutionary (ultimate) and proximate. Ultimate explanations pertain to the evolution of a species and include:

Function (adaptation) – This type of explanation for animal behaviour usually concerns a trait that is functional to the reproductive success of the organism which is a result of natural selection. Why an organism is the way it is

Evolution (phylogeny) – This type of explanation for animal behaviour encapsulates all evolutionary explanations other than function/adaptation, it include the history of the species reconstructed from as far back as possible. Sequential changes in a species through time

Proximate explanations pertain to individuals within the species and include:

Mechanism (causation) – This type of explanation describes an organism’s structure and how biological mechanisms of the organism are able to work. What organism’s structures are like and how they work

Development (ontogeny) – This type of explanation describes how an organism has developed, from changes in its DNA code to the different forms of life stages. Sequential changes in individuals across their lifespan

Examples of Explaining Tinbergen’s four Questions of Ethology

Example 1: Why do birds sing in spring?

• Mechanism – Alterations in day length affect hormone secretions within birds

• Function – Singing helps to defend the bird’s territory as well as attract females

• Evolution – Here you would need to compare the songs of a species of bird throughout the species’ evolution

• Development – This concerns the learning of an individual bird’s song, which would be easier to observe than the evolution aspect above

Example 2: Why do we see?

• Mechanism – The lens of the eye focuses light on the retina visual system

• Function – We see so we can find food easier and avoid danger

• Evolution – The vertebrate eye initially developed with a blind spot, the lack of adaptive intermediate forms prevented the loss of this blind spot

• Development – Neurons connect the eye to the brain and require photo-stimulation to transmit information

Example 3: Why do we not find siblings attractive? (Westermarck effect)

• Mechanism – Little is known about this neuromechanism

• Function – To discourage inbreeding which would otherwise decrease the number of viable offspring

• Evolution – This mechanism is found in a number of mammalian species which suggests it may have evolved tens of millions of years ago

• Development – Results from familiarity with another individual early in life, especially in the first 30 months for humans. The effect is also manifested in nonrelatives raised together

The Comparative Method

In ethology, comparative is used in specific sense, meaning to indicate systematic comparisons between different species (including humans). The comparative method has been used by Lorenz to make inferences about the evolution of behaviour and by Gittleman to study evolutionary function.

One way of using the comparative method to make comparisons about species is to gather information on two variables which are believed to be related. Collect data from each species and plot this on a graph. If the variables are related, there will be a positive linear relationship and the differences between species can be compared. For example, body weight against testes weight gives a positive linear relationship.

The outcome of the method becomes useful when groups are made within the data, using the testes example, by forming groups of species which are either monogamous, have one dominant male or have multiple males we can compare relative testes weights. We can see that on average multi-male species have larger testes, whilst monogamous species have smaller.