Modelling interactions of acid-base balance and respiratory status in the toxicity of metal mixtures in the American oyster Crassostrea virginica.

Heavy metals, such as copper, zinc and cadmium, represent some of the most common and serious pollutants in coastal estuaries. In the present study, we used a combination of linear and artificial neural network (ANN) modelling to detect and explore interactions among low-dose mixtures of these heavy metals and their impacts on fundamental physiological processes in tissues of the Eastern oyster, Crassostrea virginica. Animals were exposed to Cd (0.001-0.400 microM), Zn (0.001-3.059 microM) or Cu (0.002-0.787 microM), either alone or in combination for 1 to 27 days. We measured indicators of acid-base balance (hemolymph pH and total CO(2)), gas exchange (Po(2)), immunocompetence (total hemocyte counts, numbers of invasive bacteria), antioxidant status (glutathione, GSH), oxidative damage (lipid peroxidation; LPx), and metal accumulation in the gill and the hepatopancreas. Linear analysis showed that oxidative membrane damage from tissue accumulation of environmental metals was correlated with impaired acid-base balance in oysters. ANN analysis revealed interactions of metals with hemolymph acid-base chemistry in predicting oxidative damage that were not evident from linear analyses. These results highlight the usefulness of machine learning approaches, such as ANNs, for improving our ability to recognize and understand the effects of sub-acute exposure to contaminant mixtures.

Development of a data management framework in support of southeastern tidal creek research.

The NOAA Center of Excellence for Oceans and Human Health Initiative (OHHI) at the Hollings Marine Laboratory (HML) is developing a data management framework that supports an integrated research program across scientific disciplines. The primary focus of the database is to support environmental research focused on tidal creek watershed systems. Specifically, the current data holdings include physical water quality parameters, nutrients, pathogens, chemical contaminants, benthic and nekton species abundances and human dimensions data from Georgia, North Carolina and South Carolina dating to 1994. These data are not from a single long-term research project but are derived from several state and federal research programs and integrated into a common database model to support current research being conducted under the OHHI program at HML. The Tidal Creek database was developed with the intent to support a well documented and open system, thus metadata elements from common metadata standards including the Dublin Core ISO 15836:2003 and Federal Geographic Data Committee (FGDC-STD-001-1998) are components of the database model. The result is a semantic database framework with descriptive ancillary data at the record level including methods, investigator names, date, locations and other descriptive elements. The primary users of the database are project personnel to meet analytical needs. The database is also available through a number of web-based applications that are designed to give users the necessary information to evaluate and access data. In addition, data can be accessed with Open Geospatial Consortium (OGC) standards, and species records and abundances are being made available to the Ocean Biogeographic Information System (OBIS). Overall, the Tidal Creek database summarizes the response of tidal creeks and watersheds to coastal development, and serves as a repository for environmental, demographic, and socioeconomic data in the Southeast.

Initial results from a multi-institutional collaboration to monitor harmful algal blooms in South Carolina.

The rapid rate of development in the South Carolina (SC) coastal zone has heightened public concern for the condition of the state's estuaries, and alerted scientists to the potential that novel and adverse effects on estuarine ecosystems may result. Although well-developed databases from long-term monitoring programs exist for many variables valuable in predicting and following system responses, information on phytoplankton distributions in SC estuaries has lagged. Knowledge of the dynamical relationship between environmental (e.g., nutrient quantity and quality) and biological (e.g., grazing) regulation, and phytoplankton biomass and composition is critical to understanding estuarine susceptibility to eutrophication or harmful algal blooms (HABs). Recently, SC scientists from federal, state, and academic institutions established a collaborative monitoring program to assess HAB distribution and ecology statewide. The South Carolina Harmful Algal Bloom Program includes: a) intensive temporal monitoring at areas of known HAB occurrence or those exhibiting symptoms potentially related to HABs (e.g., prevalent fish lesions), b) extensive spatial monitoring in coordination with existing statewide efforts, c) a citizen volunteer monitoring network, d) nutrient response bioassays, and e) laboratory-based physiological experiments on HAB isolates. By combining "trip-wire" surveillance and rapid response systems, routine monitoring of environmental parameters and HAB distribution, and process-oriented studies examining the physiological functioning of HAB species, an enhanced understanding of the impact and environmental control of HABs in SC estuaries will be achieved. The application of this approach to studies on the distribution and physiological ecology of a new widespread SC red tide, and to the discovery of several potentially toxic blooms (including Pfiesteria) in SC holding ponds, are described.