The National Oceanic and Atmospheric Administration (NOAA) collects, manages, and disseminates a wide range of climate, weather, ecosystem and other environmental data that are used by scientists, engineers, resource managers, policy makers, and others in the United States and around the world. The increasing volume and diversity of NOAA's data holdings - which include everything from satellite images of clouds to the stomach contents of fish - and a large number of users present NOAA with substantial data management challenges. NOAA asked the National Research Council to help identify the observations, model output, and other environmental information that must be preserved in perpetuity and made readily accessible, as opposed to data with more limited storage lifetime and accessibility requirements. This report offers nine general principles for effective environmental data management, along with a number of more specific guidelines and examples that explain and illustrate how these principles could be applied at NOAA.

The proliferation of harmful phytoplankton in marine ecosystems can cause massive fish kills, contaminate seafood with toxins, impact local and regional economies and dramatically affect ecological balance. Real-time observations are essential for effective short-term operational forecasting, but observation and modelling systems are still being developed. This volume provides guidance for developing real-time and near real-time sensing systems for observing and predicting plankton dynamics, including harmful algal blooms, in coastal waters. The underlying theory is explained and current trends in research and monitoring are discussed.Topics covered include: coastal ecosystems and dynamics of harmful algal blooms; theory and practical applications of in situ and remotely sensed optical detection of microalgal distributions and composition; theory and practical applications of in situ biological and chemical sensors for targeted species and toxin detection; integrated observing systems and platforms for detection; diagnostic and predictive modelling of ecosystems and harmful algal blooms, including data assimilation techniques; observational needs for the public and government; and future directions for research and operations.