Synopses & Reviews
As the coastal human population increases in the United States, there will likely be increasing environmental and socioeconomic pressures on our coastal and estuarine environments. Monitoring the condition of all our nation's coastal and estuarine ecosystems over the long term is more than any one program can accomplish on its own. Therefore, it is crucial that monitoring programs at all levels (local, state, and federal) cooperate in the collection, sharing, and use of environmental data. This volume is the proceedings of the Coastal Monitoring Through Partnerships symposium that was held in Pensacola, Florida in April of 2001, and was organized by the U.S. Environmental Protection Agency's (EPA's) Environmental Monitoring and Assessment Program (EMAP), and the Council of State Governments (CSG). It contains papers that describe various multi-disciplinary coastal and estuarine environmental monitoring programs, designed and implemented by using regional and national partnerships with federal and state agencies, academia, Native American tribes, and nongovernmental organizations. In addition, it includes papers on modeling and data management; monitoring and assessment of benthic communities; development of biological indicators and interlaboratory sediment comparisons; microbiological modeling and indicators; and monitoring and assessment of phytoplankton and submerged aquatic vegetation. There are many components involved in determining the overall impacts of anthropogenic stressors on coastal and estuarine waters. It will take strong partnerships like those described in this volume to ensure that we have healthy and sustainable coastal and estuarine environments, now and in the future.
Table of Contents
Preface; M.E. McDonald. B: Regional and National Coastal Monitoring Partnership Programs.
Southern California's Marine Monitoring System Ten Years After the National Research Council Evaluation; B.B. Bernstein, et al.
Effective Application of Monitoring Information: The Case of San Francisco Bay; R. Hoenicke, et al.
Bi-National Assessment of the Great Lakes: SOLEC Partnerships; P. Bertram, et al.
The MYSound Project: Building an Estuary-Wide Monitoring Network for Long Island Sound, U.S.A.; M. Tedesco, et al.
Conservation and Management Applications of the REEF Volunteer Fish Monitoring Program; C.V. Pattengill-Semmens, B.X. Semmens.
The Coastal Component of the U.S. Integrated Ocean Observing System; T.C. Malone. C: Monitoring Approaches, Modeling, and Data Management.
Great Lakes Monitoring Results Comparison of Probability Based and Deterministic Sampling Grids; G.J. Warren, P.J. Horvatin.
A Hydrologic Network Supporting spatially referenced Regression Modeling in the Chesapeake Bay Watershed; J.W. Brakebill, S.J. Preston.
The Importance of Considering Spatial Attributes in Evaluating Estuarine Habitat Condition: The South Carolina Experience; R.F.van Dolah, et al.
Living with a Large Reduction in Permitted Loading by Using a Hydrograph-Controlled Release Scheme; P.A. Conrads, et al.
A Proposed Coast-Wide Reference Monitoring System for Evaluating Wetland Restoration Trajectories in Louisiana; G.D. Steyer, et al.
Stormwater Toxicity in Chollas Creek and San Diego Bay, California; K. Schiff, et al.
Managing Troubled Data: Coastal Data Partnerships Smooth Data Integration; S.H. Hale, et al. D: Benthic Communities Monitoring and Assessment.
Incidence of Stress in Benthic Communities Along the U.S. Atlantic and Gulf of Mexico Coasts Within Different Ranges of Sediment Contamination From Chemical Mixtures; J.H. Hyland, et al.
Application of the Benthic Index of Biotic Integrity to Environmental Monitoring in Chesapeake Bay; R.J. Llansó, et al.
Spatial Scales and Probability Based Sampling in Determining Levels of Benthic Community Degradation in the Chesapeake Bay; D.M. Dauer, R.J. Llans<>
An Approach to Identifying the causes of Benthic Degradation in Chesapeake Bay; C.S. Christman, D.M. Dauer.
Variability in the Identification and Enumeration of Marine Benthic Community Samples and its Effect on Benthic Assessment Measures; J.A. Ranasinghe, et al. E: Biological Indicators & Interlaboratory Sediment Comparisons.
Production, Respiration and Net Ecosystem Metabolism in U.S. Estuaries; J.M. Caffrey.
Foraminifera as Bioindicators in Coral Reef Assessment and Monitoring: The FORAM Index; P. Hallock, et al.
Monitoring Nekton as a Bioindicator in Shallow Estuarine Habitats; K.B. Raposa, et al.
Interlaboratory Variability of Amphipod Sediment Toxicity Tests in a Cooperative Regional Monitoring Program; S.M. Bay, et al.
Making Performance-Based Chemistry Work: How We Created Comparable Data Among Laboratories as Part of a Southern California Marine Regional Assessment; R. Gossett, et al. F: Microbiological Modeling, Indicators, and Monitoring.
Characterization and Statistical Modeling of Bacterial (Escherichia coli
) Outflows from Watersheds that Discharge into Southern Lake Michigan; G.A. Olyphant, et al.
Comparison of Beach Bacterial Water Quality Indicator Measurement Methods; R.T. Noble, et al.
Molecular Approaches to Microbiological Monitoring: Fecal Source Detection; K.G. Field, et al.
Characterization of Microbial Communities from Coastal Waters Using Microarrays; O.C. Stine, et al.
Using Multiple Antibiotic Resistance and Land Use Characteristics to Determine Sources of Fecal Coliform Bacterial Pollution; R.H. Kelsey, et al. G: Monitoring and Assessment of Phytoplankton and Submerged Aquatic Vegetation Communities.
Long-Term Phytoplankton Trends and Related Water Quality Trends in the Lower Chesapeake Bay, Virginia, U.S.A.; H.G. Marshall, et al.
Initial Results from a Multi-Institutional Collaboration to Monitor Harmful Algal Blooms in South Carolina; A.J. Lewitus, A.F. Holland.
A Pilot Project to Detect and Forecast Harmful Algal Blooms in the Northern Gulf of Mexico; W.S. Fisher, et al.
Preliminary Investigation of Submerged Aquatic Vegetation Mapping Using Hyperspectral Remote Sensing; D.J. Williams, et al.
Effect of El Niño on Demographic, Morphological, and Chemical Parameters in Turtlegrass, Thalassia testudinum
: an Unexpected Test of Indicators; P.R. Carlson Jr., et al.