Linking optimization and ecological models in a decision support tool for oyster restoration and management.

Restoration of ecologically important marine species and habitats is restricted by funding constraints and hindered by lack of information about trade-offs among restoration goals and the effectiveness of alternative restoration strategies. Because ecosystems provide diverse human and ecological benefits, achieving one restoration benefit may take place at the expense of other benefits. This poses challenges when attempting to allocate limited resources to optimally achieve multiple benefits, and when defining measures of restoration success. We present a restoration decision-support tool that links ecosystem prediction and human use in a flexible "optimization" framework that clarifies important restoration trade-offs, makes location-specific recommendations, predicts benefits, and quantifies the associated costs (in the form of lost opportunities). The tool is illustrated by examining restoration options related to the eastern oyster, Crassostrea virginica, which supported an historically important fishery in Chesapeake Bay and provides a range of ecosystem services such as removing seston, enhancing water clarity, and creating benthic habitat. We use an optimization approach to identify the locations where oyster restoration efforts are most likely to maximize one or more benefits such as reduction in seston, increase in light penetration, spawning stock enhancement, and harvest, subject to funding constraints and other limitations. This proof-of-concept Oyster Restoration Optimization model (ORO) incorporates predictions from three-dimensional water quality (nutrients-phytoplankton zooplankton-detritus [NPZD] with oyster filtration) and larval transport models; calculates size- and salinity-dependent growth, mortality, and fecundity of oysters; and includes economic costs of restoration efforts. Model results indicate that restoration of oysters in different regions of the Chesapeake Bay would maximize different suites of benefits due to interactions between the physical characteristics of a system and nonlinear biological processes. For example, restoration locations that maximize harvest are not the same as those that would maximize spawning stock enhancement. Although preliminary, the ORO model demonstrates that our understanding of circulation patterns, single-species population dynamics and their interactions with the ecosystem can be integrated into one quantitative framework that optimizes spending allocations and provides explicit advice along with testable predictions. The ORO model has strengths and constraints as a tool to support restoration efforts and ecosystem approaches to fisheries management.

Chesapeake Bay eutrophication: scientific understanding, ecosystem restoration, and challenges for agriculture.

Chesapeake Bay has been the subject of intensive research on cultural eutrophication and extensive efforts to reduce nutrient inputs. In 1987 a commitment was made to reduce controllable sources of nitrogen (N) and phosphorous (P) by 40% by the year 2000, although the causes and effects of eutrophication were incompletely known. Subsequent research, modeling, and monitoring have shown that: (i) the estuarine ecosystem had been substantially altered by increased loadings of N and P of approximately 7- and 18-fold, respectively; (ii) hypoxia substantially increased since the 1950s; (iii) eutrophication was the major cause of reductions in submerged vegetation; and (iv) reducing nutrient sources by 40% would improve water quality, but less than originally thought. Strong public support and political commitment have allowed the Chesapeake Bay Program to reduce nutrient inputs, particularly from point sources, by 58% for P and 28% for N. However, reductions of nonpoint sources of P and N were projected by models to reach only 19% and 15%, respectively, of controllable loadings. The lack of reductions in nutrient concentrations in some streams and tidal waters and field research suggest that soil conservation-based management strategies are less effective than assumed. In 1997, isolated outbreaks of the toxic dinoflagellate Pfiesteria piscicida brought attention to the land application of poultry manure as a contributing factor to elevated soil P and ground water N concentrations. In addition to developing more effective agricultural practices, emerging issues include linking eutrophication and living resources, reducing atmospheric sources of N, enhancing nutrient sinks, controlling sprawling suburban development, and predicting and preventing harmful algal blooms.

Measuring the health of the Chesapeake Bay: toward integration and prediction.

The health of an ecosystem is a function of its vigor (useful productivity), organization (complexity of interspecific interactions), and resilience (ability to maintain itself in the face of disturbance). The health of the Chesapeake Bay ecosystem has deteriorated largely as a result of nutrient overenrichment, concomitant reduction in light availability, and loss of habitats that provide complexity. This has resulted in an ecosystem that is a less vigorous producer of valuable fish and shellfish, less diverse and well organized, and more susceptible to and slower to recover from disturbances. It is not clear that degraded ecosystem health directly threatens human health; in fact sanitation and reductions in loadings of potentially toxic substances have reduced human health risks in recent decades. On the other hand, recently observed outbreaks of the toxin-producing dinoflagellate Pfiesteria piscicida could be a result of deteriorated ecosystem health and pose a human health risk. Monitoring of the environmental conditions, ecosystem health, and human health risks is critically important to the adaptive management of the Chesapeake Bay. Although this monitoring has produced very useful information, monitoring can be more effective if it more directly addressed the multiple uses of the resulting information, applied new technologies, and were more effectively integrated across environmental media, among resources, over space and time scales, and with modeling and research.