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Dr Rebecca Pike

Theoretical Behavioural Biology

Pike et al. (2016). A general expression for the reproductive value of behaviour

Information transfer and utilization is ubiquitous in nature. Animals can increase their reproductive value by changing their behavior in light of new information. Previous work has shown that the reproductive value of information can never be negative given an animal behaves optimally. Statistical decision theory uses Bayes’ theorem as a mathematical tool to model how animals process information gained from their environment. We use this technique with an optimality model to establish a new expression for the value of information when behavior is chosen from a continuous range of possibilities. Our expression highlights that the value of information is proportional to the rate of change of behavior with information. We illustrate our approach using the cooperative behavior between a male and a female raising their common young. We show that the value of knowing about one’s partner can be quantified and establish the value of information to a member of the pair when the continuous trait is how long to spend caring for their young. However, the applications of this expression are wider reaching than parental care decisions and can be used to analyze the behavior of individuals across a variety of species and contexts.

 

Energy-Predation Trade-off for a parent feeding its young

Parents feeding their young during the breeding season face a trade-off between provisioning their young with food for growth and mortality risk. When mortality to both parent and young is considered, can describing mortality risk as a single effect sufficiently predict parental behaviour? We consider mortality functions for both parent and young which comprise of the sum of a background mortality risk and a mortality risk attributed to parental behaviour. Mortality functions of this nature generate novel predictions of parental behaviour. We find that a parent should invest a greater proportion of time in being vigilant for predators with an increase in the mortality parameter determining the proportion of parental effort that contributes to mortality of the young. An increase in other mortality parameters prompt an opposite effect. Our new expression shows that mortality should be described by multiple parameters to fully predict how a parent should behave.

Research keywords

  • Parental care
  • Pair bond
  • Value of Information
  • Cooperation
  • Optimisation models

Research equipment

  • Matlab
  • C
  • R
  • Maple
  • Python
  • Netlogo

Research findings

Pike R.K., McNamara, J.M. and Houston, A.I. (2016). A general expression for the reproductive value of behaviour, Behavioural Ecology.

Information transfer and utilization is ubiquitous in nature. Animals can increase their reproductive value by changing their behavior in light of new information. Previous work has shown that the reproductive value of information can never be negative given an animal behaves optimally. Statistical decision theory uses Bayes’ theorem as a mathematical tool to model how animals process information gained from their environment. We use this technique with an optimality model to establish a new expression for the value of information when behavior is chosen from a continuous range of possibilities. Our expression highlights that the value of information is proportional to the rate of change of behavior with information. We illustrate our approach using the cooperative behavior between a male and a female raising their common young. We show that the value of knowing about one’s partner can be quantified and establish the value of information to a member of the pair when the continuous trait is how long to spend caring for their young. However, the applications of this expression are wider reaching than parental care decisions and can be used to analyze the behavior of individuals across a variety of species and contexts.

 

Pike, R.K., McNamara, J.M. and Houston, A.I. (2018). The role of mortality risk in parental behaviour, Evolutionary Ecology Research

Background: A parent feeding its young during the breeding season faces a tradeoff between mortality risk and provisioning young with food for growth.

Question: How should the parent behave to maximise reproductive success when mortality to both parent and young are considered?

Mathematical method: Using an optimality model, we establish new formulae to describe parental behaviour when there is a trade-off between growth rate of the young and mortality risk to both parent and young.

Key assumptions: We consider mortality functions for both parent and young. These comprise the sum of a background mortality risk and a mortality risk attributed to parental behaviour.

Conclusions: Mortality is an important parameter in the determination of parental behaviour. As the dependence of the mortality of the young on parental effort grows, a parent should invest a greater proportion of time in being vigilant for predators. An increase in other mortality parameters prompts the opposite effect. Mortality should be described by multiple parameters to predict fully how a parent should behave.