Optimal management of complex ecological systems

Grant number: DP0346165

Abstract

Natural systems are inherently complex and difficult to predict. This complexity means that efficient management strategies are often uncertain, and resource managers have few theories or rules on which to base their decisions. We will integrate the existing theories and principles of conservation biology with decision-making tools and theory used in statistics, economics, control theory, engineering and mathematics. We will use novel methods to investigate the reliability of different management decisions that are made in the face of uncertainty and involve learning. Our aim is to discover a general theory for a new branch of conservation biology: applied theoretical conservation ecology.