A coupled three-dimensional hydrodynamic-biogeochemical model is used to simulate plankton dynamics in Chesapeake Bay and examine its sensitivity to variations in biological parameters and physical forcing. The coupled biophysical model captures observed seasonal cycle and regional distributions of plankton in Chesapeake Bay and predicts the "phase lag" between the spring chlorophyll maximum and the summer primary productivity maximum. This lag traces to the delivery of dissolved inorganic nutrients in the winter-spring freshet from the Susquehanna River that fuels the spring bloom, whereas regenerated nutrients support high primary productivity in summer. The model shows that episodic wind events commonly associated with frontal passages in summer inject nutrients into the euphotic layer, leading to short periods of elevated primary productivity. Quantitative comparisons between the predicted and observed annual time series of euphotic-layer chlorophyll and primary productivity show that the model possesses reasonable skill. Sensitivity analyses of model simulations for different biological parameter values and alternative formulations of biogeochemical processes suggest that model predictions are robust. To understand the impacts of climate variability and change on Chesapeake Bay, we examine how the plankton system responds to variations in river runoff, wind forcing, temperature and light level. Annual mean chlorophyll (AMC) and annual integrated production (AIP) increase by about 70% for a doubling of river runoff, but only reduce by 30% and 13% for 50% reduction of river runoff, suggesting a nonlinear response of plankton system to changes in river runoff and nutrient loading. Doubling of wind stress results in a small increase in AMC but 28% increase in AIP. For 2°C warming AMC increases from 25.4 to 30 mg m−2 and AIP increases from 180 to 246 g C m−2 yr−1.
Li, Ming, Liejun Zhong, and Lawrence W. Harding. 2009. "Sensitivity of plankton biomass and productivity to variations in physical forcing and biological parameters in Chesapeake Bay." Journal of Marine Research 67, (5). https://elischolar.library.yale.edu/journal_of_marine_research/247