Optimality Models in Behavioral Biology

Abstract

The action of natural selection results in organisms that are good at surviving and reproducing. We show how this intuitive idea can be given a formal definition in terms of fitness and reproductive value. An optimal strategy maximizes fitness, and reproductive value provides a common currency for comparing different actions. We provide a broad review of models and methods that have been used in this area, stressing the conceptual issues and exposing the logic of evolutionary explanations.

Size‐selective fishing and the potential for fisheries‐induced evolution in lake whitefish

“…In effect, a phenotypic approach to optimization let us determine what energy allocation strategies might be beneficial under different selection regimes, without any consideration of genetic inheritance mechanisms (for a comparison of different modeling approaches, see Kokko, 2007). Dynamic optimization models have been used widely to study behavioral or physiological decisions that depend on current state and time (e.g., time of day, day of year, or year of life) given their consequences on cumulative survival and/or reproduction at a future time (McNamara, Houston, & Collins, 2001). The model we developed closely parallels Jørgensen and Fiksen's (2006) model of energy allocation in Atlantic cod.…”

Cooperation theory of cooperative breeding

“…In a series of interactions, cost/benefit relations as well as the availability of alternative options may change with time and, more importantly, with individual state. In state variable models of behaviour (for review see McNamara et al, 2001) current optimal decisions are determined in relation to future fitness expectations and single decision points may have an impact on the path of a trajectory. Specific cooperation mechanisms may be important at different times in a decision process and their combination may change with state and time.…”

“…In timedelayed interactions the value of the return act cannot be directly compared to the value of the current act. To determine the effects of cooperative behaviour on fitness and decide about the evolutionary mechanism we have to take account of the different times when young are produced (McNamara et al, 2001;Skubic et al, 2004). Decision processes that depend on individual state and time provide realistic projections but complexity of cooperative breeding systems and methodology so far limited the number of studies using this state-variable approach in cooperative breeders.…”

“…Many important dynamic asymmetries in individual characteristics that can be easily covered by state dependent models, and asymmetries in the currencies exchanged in behavioural acts can be translated to the common currency of individual fitness (McNamara and Houston, 1986;McNamara et al, 2001). Theoreticians should be encouraged to investigate specific cooperative breeding systems, as well as less complex scenarios, involving different types of cooperation mechanisms by thinking in terms of state variable dynamics.…”

sOAR: a tool for modelling optimal animal life‐history strategies in cyclic environments

“…Such grand-scale behavioural patterns can only be fully understood and protected from global change if the complete behavioural cycle, as embedded into the periodic environment, is considered from an evolutionary and mechanistic perspective (Wilcove and Wikelski 2008, Visser et al 2010, Helm et al 2013. Life history theory (Stearns 2004) predicts that natural selection and other evolutionary forces led to the evolution of optimal behaviours that ensure highest fitness in terms of long-term reproductive success (McNamara et al 2001) under the given ecological constraints.…”