Development of a preliminary relative risk model for evaluating regional ecological conditions in the Delaware River Estuary, USA.

Effective environmental management and restoration of urbanized systems such as the Delaware River Estuary requires a holistic understanding of the relative importance of various stressor-related impacts throughout the watershed, both historical and ongoing. To that end, it is important to involve as many stakeholders as possible in the management process and to develop a system for sharing of scientific data and information, as well as effective technical tools for evaluating and disseminating the data needed to make management decisions. In this study, we describe a preliminary assessment that was undertaken to evaluate the relative risks for the variety of stressors currently operating within the Delaware Estuary using a relative risk model (RRM) framework. This model was constructed using existing data and information on the ecological conditions and stressors in the main-stem Delaware River below the head of tide at Trenton, New Jersey, USA. A large database was developed with pertinent data from a variety of library, scientific, and regulatory sources. Data were compiled, reviewed, and characterized before development of the Estuary-specific RRM. Our primary goals and objectives in developing this preliminary RRM for the Estuary were to 1) determine if the RRM framework can be adapted to a large complex estuarine system such as the Delaware River, 2) identify the issues associated with adapting the model framework to the various management issues and regional areas/habitats of the River, 3) help identify data needs and potential refinements that might be needed to more specifically quantify relative stressor risks in various areas and habitats of the Estuary to better inform future management goals/actions by Stakeholders. The key conclusions of our preliminary assessment are 1) a diverse suite of stressors is likely affecting the ecological conditions of the Delaware Estuary, 2) chemical (toxicants/contaminants) and physical (sedimentation, habitat loss) stressors were found to be on par with regards to their ranking, and 3) the RRM, in its current form, made it difficult to effectively balance the inequality in the sizes of the study subareas considered in the assessment. Management objectives and related research activities should focus on collecting the necessary data and information to further refine the RRM and assess the relative impacts of these stressors at various scales in the Estuary. By having such a framework and tool available, we believe that stakeholders within the Delaware River watershed will be able to make more informed and risk-based management decisions regarding restoration options for the Estuary.

Ecological food web analysis for chemical risk assessment.

Food web analysis can be a critical component of ecological risk assessment, yet it has received relatively little attention among risk assessors. Food web data are currently used in modeling bioaccumulation of toxic chemicals and, to a limited extent, in the determination of the ecological significance of risks. Achieving more realism in ecological risk assessments requires new analysis tools and models that incorporate accurate information on key receptors in a food web paradigm. Application of food web analysis in risk assessments demands consideration of: 1) different kinds of food webs; 2) definition of trophic guilds; 3) variation in food webs with habitat, space, and time; and 4) issues for basic sampling design and collection of dietary data. The different kinds of food webs include connectance webs, materials flow webs, and functional (or interaction) webs. These three kinds of webs play different roles throughout various phases of an ecological risk assessment, but risk assessors have failed to distinguish among web types. When modeling food webs, choices must be made regarding the level of complexity for the web, assignment of species to trophic guilds, selection of representative species for guilds, use of average diets, the characterization of variation among individuals or guild members within a web, and the spatial and temporal scales/dynamics of webs. Integrating exposure and effects data in ecological models for risk assessment of toxic chemicals relies on coupling food web analysis with bioaccumulation models (e.g., Gobas-type models for fish and their food webs), wildlife exposure models, dose-response models, and population dynamics models.