Coastal Sciences, Gulf Coast Research Laboratory
Many of the world's coastal ecosystems are impacted by multiple stressors each of which may be subject to different management strategies that may have overlapping or even conflicting objectives. Consequently, management results may be indirect and difficult to predict or observe. We developed a network simulation model intended specifically to examine ecosystem-level responses to management and applied this model to a comparison of nutrient load reduction and restoration of highly reduced stocks of bivalve suspension feeders (eastern oyster, Crassostrea virginica) in an estuarine ecosystem (Chesapeake Bay, USA). Model results suggest that a 50% reduction in nutrient inputs from the watershed will result in lower phytoplankton production in the spring and reduced delivery of organic material to the benthos that will limit spring and summer pelagic secondary production. The model predicts that low levels of oyster restoration will have no effect in the spring but does result in a reduction in phytoplankton standing stocks in the summer. Both actions have a negative effect on pelagic secondary production, but the predicted effect of oyster restoration is larger. The lower effect of oysters on phytoplankton is due to size-based differences infiltration efficiency and seasonality that result in maximum top-down grazer control of oysters at a time when the phytoplankton is already subject to heavy grazing. These results suggest that oyster restoration must be achieved at levels as much as 25-fold present biomass to have a meaningful effect on phytoplankton biomass and as much as 50-fold to achieve effects similar to a 50% nutrient load reduction. The unintended effect of oyster restoration at these levels on other consumers represents a trade-off to the desired effect of reversing eutrophication.
Fulford, R. S.,
Breitburg, D. L.,
Newell, R. I.
(2010). Evaluating Ecosystem Response to Oyster Restoration and Nutrient Load Reduction With a Multispecies Bioenergetics Model. Ecological Applications, 20(4), 915-934.
Available at: https://aquila.usm.edu/fac_pubs/704