UC Davis

I present results from three studies addressing apparently disparate challenges: conserving biodiversity, maintaining sustainable fisheries, and controlling infectious disease. All, however, require fateful choices to be made urgently in the context of substantial uncertainty and environmental change. Uncertainty and environmental change can have complex interactive effects on the decision-making process. Uncertainty adds an element of risk that can be amplified over time by changing conditions and dynamics feedback mechanisms. Furthermore, the combination of uncertainty and time introduces the possibility of learning; policymakers may choose to delay fateful choices until more information is available, invest in improved knowledge, and take experimental actions. For my dissertation, I developed mathematical models to understand how these interactive effects shape optimal decision-making in three applied case studies: prioritizing scarce COVID-19 vaccines, mitigating unintended genetic impacts of fish hatcheries, and designing fisheries monitoring programs. Across the case studies, I found that the time scales of underlying biological processes were critical for designing effective management strategies. Furthermore, when decision-makers respond adaptively to changes in the underlying ecosystem state, they can act as a stabilizing feedback mechanism, reducing the risks introduced by stochastic environmental variability and scientific uncertainty.