One of the unifying themes in ecology may be the acknowledgement that we live in a world of finite resources, and so we also live in a world of tradeoffs. A diverse range of research questions can be distilled into a question about tradeoffs. For example, how should an animal forage in the presence of predation? Which selective forces determine the life history of a flowering perennial? How should we manage a population to maximize the sustainable harvest rate?

Questions as varied as these can all be addressed using the same method of stochastic programming[1] (SDP) (see McNamara and Houston, 1986; Rees et al. 1999; and Runge and Johnson, 2002, respectively). SDP has been used extensively to study optimal tradeoffs in a wide range of applications in ecology, evolutionary biology, and management. It is a flexible and powerful modelling framework that allows for simultaneous consideration of an individual’s state, how an optimal decision might explicitly depend on time, and for a probabilistic landscape of risks and rewards.
[1] Also known as Markov Decision Processes
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