Dynamics of a large submersed plant bed in upper Chesapeake Bay

A large SAV bed in upper Chesapeake Bay has experienced several abrupt shifts over the past half-century, beginning with near-complete loss after a record-breaking flood in 1972, followed by an unexpected, rapid resurgence in the early 2000’s, then partial decline in 2011 following another major flood event. Together, these trends and events provide a unique opportunity to study a recovering SAV ecosystem from several different perspectives. First, I analyzed and synthesized existing time series datasets to make inferences about what factors prompted the recovery. Next, I analyzed existing datasets, together with field samples and a simple hydrodynamic model to investigate mechanisms of SAV bed loss and resilience to storm events. Finally, I conducted field deployments and experiments to explore how the bed affects internal physical and biogeochemical processes and what implications those effects have for the dynamics of the system. I found that modest reductions in nutrient loading, coupled with several consecutive dry years likely facilitated the SAV resurgence. Furthermore, positive feedback processes may have played a role in the sudden nature of the recovery because they could have reinforced the state of the bed before and after the abrupt shift. I also found that scour and poor water clarity associated with sediment deposition during the 2011 flood event were mechanisms of plant loss. However, interactions between the bed, water flow, and waves served as mechanisms of resilience because these processes created favorable growing conditions (i.e., clear water, low flow velocities) in the inner core of the bed. Finally, I found that that interactions between physical and biogeochemical processes led to low nutrient concentrations inside the bed relative to outside the bed, which created conditions that precluded algal growth and reinforced vascular plant dominance. This work demonstrates that positive feedbacks play a central role in SAV resilience to both chronic eutrophication as well as acute storm events. Furthermore, I show that analysis of long-term ecological monitoring data, together with field measurements and experiments, can be an effective approach for understanding the mechanisms underlying ecosystem dynamics.