Biologists now appreciate the interconnected nature of genetic, neural, and ecological systems,< but with this complexity can often come limitations to interpretation, prediction, and application. To make these tangled webs tractable, we simplify them, focusing on a single node or a simplified motif, or we attempt to characterize them fully1. These approaches have all demonstrated their merits, yet we rarely objectively evaluate the value of embracing or ignoring complexity. Objectively valuing information can be incredibly beneficial as the collection of high quality data about biological systems can be costly2. Therefore, the future of embracing biological complexity requires an optimized approach that values complexity explicitly. In particular, we can borrow the principles of valuing information from economics to quantify the value of information as it is incorporated into decision-making (or conversely, the value foregone when there is uncertainty3). Here, I propose to apply this value of information framework to study the dynamics and management of interconnected species within marine food webs.

Specifically, I will ask:

• What is the value of adding complexity to species interaction networks?
• How can management of a human-natural coupled system benefit from placing value on complexity?

Marine ecosystems are highly complex, multilayered networks that are highly connected to human activities through global climate processes, resource extraction, and cultural value. My current research addresses how biological complexity within a single species scales up to ecosystems and human communities. I have used field experiments and mathematical models to characterize intraspecific complexity, and a simulation approach to determine how uncertainty around that complexity affects the outcomes of management decisions. I want to take this research further by developing tools that can effectively incorporate complexity in decision-making. To achieve this career goal, I require a vertical leap into more complex quantitative methods. The McDonnell fellowship will offer three specific new analytical skills: (i) The ability to construct and analyze multi-species models, (ii) The integration of bioeconomic theory with natural resource management by learning and applying the value of information theoretical framework from the economics literature, and (iii) The integration of risk management and network analysis to link network science directly to management decision-making through the value of information. These skills will complement my current training in population modeling and enhance my ability to address pressing questions in complex social-ecological systems.