Multiple stressor effects on benthic biodiversity of Chesapeake Bay: implications for ecological risk assessment.
In natural aquatic systems, there is frequently overlap in the spatial distribution of both natural and anthropogenic stressors, particularly at regional geographic scales. Yet the proportional risk associated with individual stressors, their cumulative effects and the manner in which they interact to affect aquatic ecology is frequently unknown, limiting the robustness of multiple-stressor ecological risk assessments (ERA). The current study used historical environmental monitoring data (1984-1999) to identify a combination of natural and anthropogenic stressors that best accounted for observed patterns of benthic biodiversity in Chesapeake Bay. Geographic information systems (GIS) were used to geographically link spatially heterogeneous databases for benthic biodiversity, water quality and sediment toxicant concentrations. Single and multiple variable regression techniques were subsequently used to develop a statistical model to explain observed patterns of benthic biodiversity. Combinations of natural stressors alone accounted for as much as 34% of the variation in benthic biodiversity, and combinations of anthropogenic toxicants accounted for as much as 48% of the variation. The consideration of both natural and anthropogenic stressors resulted in a statistical model that accounted for approximately 73% of the observed variation in benthic biodiversity of Chesapeake Bay. These results suggest that benthic biodiversity in Chesapeake Bay is a function of complex interactions among water quality characteristics and anthropogenic toxicants. Therefore, new risk assessment methodologies are required to assess the risk of multiple stressors at regional scales.
Preston
Benjamin L
BL
Carolina Environmental Program, UNC-Chapel Hill, NC 27599-1105, USA. prestonb@pewclimate.org
Shackelford
Jeremiah
J
D000818:Animals; D003627:Data Interpretation, Statistical; D016208:Databases, Factual; D017753:Ecosystem; D004784:Environmental Monitoring; D019015:Geologic Sediments / Q000737:chemistry; D007448:Invertebrates; D008396:Maryland; D015233:Models, Statistical; D012044:Regression Analysis; D018570:Risk Assessment; D012623:Seawater / Q000032:analysis*; D014768:Virginia; D014874:Water Pollutants, Chemical / Q000032:analysis
D014874:Water Pollutants, Chemical