Measured and modeled effects of benthic algae on eutrophication in Indian River-Rehoboth Bay, Delaware

A combination of field studies and mathematical modeling was used to examine the role of subtidal benthic algae in the eutrophication processes in two shallow estuarine systems. Field measurements indicated uptake by benthic algae retained ammonium and phosphate in the sediments when light at the sediment surface exceeded ≈150 μE m² s^?1. The measurements were used to calibrate a newly developed model of benthic algal activity. The benthic algal model was coupled with a hydrodynamic model, a eutrophication model, and a sediment diagenesis model. In the simulated ecosystem, benthic algae had a major influence in the intra-annual cycling of nitrogen and phosphorus. When nutrients were abundant in the water column (late winter and spring) they were transferred to the sediments through algal activity. Diagenesis released these nutrients to the water column in summer when nutrients were scarce. As a result of the nutrient transfer, annual primary production in the water column, in the presence of benthic algae, exceeded production in the absence of the algae.     

System-wide submerged aquatic vegetation model for Chesapeake Bay

A predictive model of submerged aquatic vegetation (SAV) biomass is coupled to a eutrophication model of Chesapeake Bay. Domain of the model includes the mainstem of the bay as well as tidal portions of major embayments and tributaries. Three SAV communities are modeled: ZOSTERA, RUPPIA, and FRESHWATER. The model successfully computes the spatial distribution and abundance of SAV for the period 1985–1994. Spatial distribution is primarily determined by computed light attenuation. Sensivitity analysis to reductions in nutrient and solids loads indicates nutrient controls will enhance abundance primarily in areas that presently support SAV. Restoration of SAV to areas in which it does not presently exist requires solids controls, alone or in combination with nutrient controls. For regions in which SAV populations exist at the refuge level or greater, improvements in SAV abundance are expected within 2 to 10 years of load reductions. For regions in which no refuge population exists, recovery time is unpredictable and will depend on propagule supply.     

A spatially-explicit approach for estimating carrying capacity: An application for the Atlantic menhaden (Brevoortia tyrannus) in Chesapeake Bay

A spatially-explicit methodology was developed for estimating system carrying capacities of fish stocks, and used to estimate the seasonal and spatial patterns of carrying capacity of Chesapeake Bay for Atlantic menhaden (Brevoortia tyrannus). We used a spatially-explicit three-dimensional (3-D) model that divided the heterogeneous habitat of Chesapeake Bay into over 4,000 cubes. Each cube represented a volume of water that was characterized by a specific set of environmental variables (phytoplankton biomass, temperature, and dissolved oxygen) driven by the 3-D water quality model. Foraging and bioenergetics models transformed the environmental variables into measures of potential growth rates of menhaden. Potential carrying capacity of menhaden was estimated as a function of phytoplankton production, menhaden consumption rate, and potential growth rate, combining phytoplankton production, thermal habitat, and menhaden physiology into one ecological value that is a measure of habitat quality from the perspective of the fish. Seasonal analysis of the Chesapeake Bay carrying capacity for Atlantic menhaden suggested two bottleneck periods: one in early June and a second during the fall. The bottleneck in carrying capacity was at about 10 billion age-0 fish. Annual recruitment of age-0 menhaden for the entire Atlantic coast of the U.S. ranged from 1.2–18.6 billion fish between 1955 and 1986. It appears that carrying capacity of, Chesapeake Bay does not limit the coastwide production of young menhaden. Any conditions such as nutrient reduction strategies, further eutrophication, or global climatic warming, that may influence the carrying capacity during the fall or early June periods, may ultimately alter coastwide abundance of menhaden through changes in Chesapeake Bay carrying capacity.     

Can oyster restoration reverse cultural eutrophication in Chesapeake Bay?

We investigated the hypothesis that effects of cultural eutrophication can be reversed through natural resource restoration via addition of an oyster module to a predictive eutrophication model. We explored the potential effects of native oyster restoration on dissolved oxygen (DO), chlorophyll, light attenuation, and submerged aquatic vegetation (SAV) in eutrophic Chesapeake Bay. A tenfold increase in existing oyster biomass is projected to reduce system-wide summer surface chlorophyll by approximately 1 mg m⁻³, increase summer-average deep-water DO by 0.25 g m⁻³, add 2100 kg C (20%) to summer SAV biomass, and remove 30,000 kg d⁻¹ nitrogen through enhanced denitrification. The influence of osyter restoration on deep extensive pelagic waters is limited. Oyster restoration is recommended as a supplement to nutrient load reduction, not as a substitute.     

Phytoplankton Kinetics in the Chesapeake Bay Eutrophication Model

The CE-Qual-ICM model computes phytoplankton biomass and production as a function of temperature, light, and nutrients. Biomass is computed as carbon while inorganic nitrogen, phosphorus, and silica are considered as nutrients. Model formulations for production, metabolism, predation, nutrient limitation, and light limitation are detailed. Methods of parameter determination and parameter values are presented. Results of model application to a ten-year period in Chesapeake Bay indicate the model provides reasonable representations of observed biomass, nutrient concentrations, and limiting factors. Computed primary production agrees with observed under light-limited conditions. Under strongly nutrient-limited conditions, computed product is less than observed. The production characteristics of the model are similar to behavior reported for several similar models. Process omitted from the model that may account for production shortfalls include variable algal stoichiometry, use of urea as nutrient, and vertical migration by phytoplankton.