YOUNG SCIENTIST AWARD (DONATH MEDAL): PEERING THROUGH THE WEB OF COMPLEXITY WITHOUT GETTING CAUGHT: HOW TOOLS FROM COMPLEX-SYSTEMS THEORY HELP IDENTIFY DOMINANT DRIVERS AND FEEDBACKS OF CURIOUSLY BEHAVING AQUATIC LANDSCAPES

Aquatic landscapes exhibit many types of surprising behaviors: low-gradient wetlands that develop regular and remarkably stable ridges and channels oriented parallel to flow despite the theoretical instability of such a configuration; restored streams that exhibit only limited biogeochemical function compared to unrestored streams with a much less stable channel morphology; morphologies that change rapidly and dramatically with just small changes in flow velocity or frequency. Often, these behaviors arise from feedback between biotic and abiotic drivers. However, it can be challenging to disentangle effects of interacting climatic, hydrologic, biogeochemical, and biological processes and identify the responsible dominant processes. One tenet of complexity theory is that complex behaviors commonly arise from just a few interacting state variables. These variables may be identified through hypothesis testing with highly simplified models, multivariate statistics, or mapping trajectories of the behavior in state space. With the emergence of “big data” in earth surface process research and new tools for interpretation, it is now also possible to directly delineate and quantify the strengths of feedback from sensor time series or remote sensing. Here I provide examples of how each of these methods of “reducing complexity” has elucidated drivers of the aforementioned case studies.