State-Dependent Decision Analysis for Conservation Biology

Summary

If applied conservation biology is to be effective, it is essential we develop conservation theory within an explicit decision-making framework. Most conservation theory enables us to identify management options that are beneficial, but it fails to help us to choose between those options given limited resources. Although the tools for making decisions in a stochastic world are not simple, economists and management scientists already have an array of methods for making decisions in risky and uncertain circumstances. This chapter explores a specific example of the application of a decision theory tool to nature conservation. I use Markov decision theory to choose between management options for a threatened metapopulation. A presence-absence stochastic metapopulation model is coupled to Markov decision theory machinery to determine the optimal management strategy for a threatened metapopulation. An important attribute of this decision-making tool is that the best management strategy depends on the current state of the system being modeled. I explore other possibilities for the application of state-dependent decision theory in conservation biology.