Optimality and game theory

Question 1

Tinbergan’s four questions

Answer 1

He came up with 4 questions which are key for understanding the evolution of behaviour.

Proximate ‘evolutionary’ (Why) questions:
- Adaptive significane
- Phylogeny (evolutionary history)

Ultimate ‘causal’ (How) questions:
- Mechanisms (what physical signals drive one behavior over another)
- Development (how does behaviour develop)

Question 2

Phenotypic gambit

Answer 2

The assumption that phenotypic data (observable characteristics or traits) can provide insights into the underlying genetic and evolutionary processes, even when detailed genetic data is lacking or challenging to obtain.

Assumptions
* phenotypic data are an adequate predictor of the underlying genetics
* Simple haploid genetics (A, a) are used
* Simplified model with only two alleles

Question 3

The problem with the phenotypic gambit

Answer 3

The phenotypic gambit only works if genetics is simple and we can use phenotypes as a surrogates for fitness? Is this valid?

What happens if a behaviour is determined by heterozygous advantage?

Question 4

Optimality theory

Answer 4

Optimality theory refers to the idea that certain traits or behaviours observed in living organisms have evolved because they represent optimal solutions

Optimal solution optimise benefits and minimise costs

Question 5

Optimality models

Answer 5

Optimality models predict the extent of a specific behaviour under defined circumstances by looking at the costs and benefits.

Question 6

Optimal foraging on a patchy environment (MacArthur)

Answer 6

MacArthur studied birds’ foraging in patchy environments to understand how they devide their time between searching, eating and handling prey.

Optimal utilisation of time or energy budgets follows that behaviour (which has fitness consequences) should increase as long as the resulting gain in unit of food per time spent exceeds the loss

This model is applied to searching time vs handling costs of prey.
- Larger prey is easier to find but has a greater hand cost and vise versa.
- This can be used to predict the optimal size of prey.

Question 7

Marginal gain theorem and optimal foraging

Answer 7

An optimality approach used to predict how much time an animal will spend foraging in a patch dependent on time spend travelling to the patch and the resources in the patch.

Question 8

Example of MVT

Answer 8

Study looking at root growth of plants through different qualities of soil in chambers.

Conclusion: GUT is larger when the quality of the soil is higher. Plants travel further for higher-quality soil.

Question 9

Marginal gain theory and male mate investment

Answer 9

An optimality approach used to predict how much time an animal will spend copulating depending on how long they have spent searching for the mate.

Question 10

Ideal free distribution

Answer 10

An ideal free distribution (IFD) is a theoretical way in which a population’s individuals distribute themselves among several patches of resources within their environment, in order to minimize resource competition and maximize fitness.

Assumptions:
- Any individual settles in a habitat most suitable for it
- All individuals have identical expected success rates.

Example: 33 mallard fed at 2 stations on a pond

Question 11

Depostic ducks

Answer 11

Depostic ducks are an example of why ideal free distribution is not possible

Question 12

Game theory vs optimality theory

Answer 12

Game theory and optimality theory are both frameworks used in different fields to study strategic decision-making and optimization, but they are applied in distinct contexts.

Question 13

Game theory

Answer 13

Game theory is a mathematical and conceptual framework used to study and analyze strategic interactions between rational decision-makers.

Question 14

Game theory example: Prisoner’s dilemma

Answer 14

Cooperate or deflect?

It seems that deflect has the lowest payoff so how do altruistic behaviors evolve?

When the game is repeated it is revealed that the best option is to start by cooperating and then make future decisions based on the decisions of the other individual.

Question 15

Hawks and dove

Answer 15

Hawks and doves describe two contrasting strategies.

Looking at hawks and doves in game theory explains why you get mixed strategies.

There is no pure strategy as each strategy can be invaded by the other player. Hawk vs hawk is invaded by doves and dove vs dove is invaded by hawks.

This can lead to Evolutionary stable strategies which is a combination of hawks and doves.

Question 16

Economically stable strategy

Answer 16

Strategies that cannot be invaded by other strategies.

e.g. a specific combination of hawks and doves.

Question 17

Applications of ESS

Answer 17

ESS approaches are now widely used in behaviour and evolutionary ecology studies

For example, to understand the evolution of parental care (which sex should care), the evolution of the sexes (isogamy vs anisogamy), altruism and cooperative behaviours.