Although many studies measure the abundance of benthic microalgae (BMA), at the meters squared scale, comparing these studies is difficult due to the variety of sampling, extraction, and analysis techniques. This difficulty is exacerbated by the fact that BMA abundance has high spatial and temporal variability, at all spatial scales.

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This paper proposes a neural network (NN)-embedded genetic algorithm (GA) approach for solving inverse water quality modeling problems to overcome the computational bottleneck of inverse modeling by replacing a water quality model with an efficient NN functional evaluator. An existing one-step, NN-embedded GA approach is found incapable of solving an inverse water quality modeling problem because it tends to fail in guiding the global search process to converge toward the near optima.

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Communication among managers, the public, and scientists is the key to successful ecosystem management; however, the varied perspectives and interests of these groups can make such communication difficult. One way to achieve effective communication is to develop a common knowledge base by combining syntheses of key scientific results with information-rich visual elements.

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The Barnegat Bay–Little Egg Harbor Estuary is classified here as a highly eutrophic estuary based on application of the National Oceanic and Atmospheric Administration’s National Estuarine Eutrophication Assessment model. Because it is shallow, poorly flushed, and bordered by highly developed watershed areas, the estuary is particularly susceptible to the effects of nutrient loading.

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Environmentally distributed ecological networks (EDENs) are growing increasingly important in ecology, coordinating research in more disciplines and over larger areas than ever before, while supplanting post hoc syntheses of uncoordinated research. With the rise of multiple broadly focused, continental-scale EDENs, these networks will be directing an increasingly large proportion of resources in ecology, which warrants a review of their use.

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The proportional cover of forest and grassland vegetation, known as landscape openness, has been particularly difficult to reconstruct because of differences in pollen productivity and transport between the two vegetation types. To begin to calibrate landscape openness in eastern North America, we collected 2 1 samples of surface sediments front small ponds (less than 60 ha) in the Upper Connecticut River Valley of New England, USA.

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Seagrasses, marine flowering plants, are widely distributed along temperate and tropical coastlines of the world. Seagrasses have key ecological roles in coastal ecosystems and can form extensive meadows supporting high biodiversity. The global species diversity of seagrasses is low (b60 species), but species can have ranges that extend for thousands of kilometers of coastline.

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DEET (N,N-diethyl-m-toluamide) is the active ingredient of most commercial insect repellents. This compound has commonly been detected in aquatic water samples from around the world indicating that DEET is both mobile and persistent, despite earlier assumptions that DEET was unlikely to enter aquatic ecosystems. DEET's registration category does not require an ecological risk assessment, thus information on the ecological toxicity of DEET is sparse.

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The mid-Atlantic coastal bays are shallow coastal lagoons, separated from the Atlantic Ocean by barrier sand islands with oceanic exchanges restricted to narrow inlets. The relatively poor flushing of these lagoon systems makes them susceptible to eutrophication resulting from anthropogenic nutrient loadings. An intensive water quality and seagrass monitoring program was initiated to track ecological changes in the Maryland and Virginia coastal bays.

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We validated a novel method for screening Escherichia coli resistance to antibiotics in environmental samples using modified Difco MI agar (Becton Dickinson) impregnated with selected antibiotics (tetracycline, ampicillin, cephalexin, and sulfamethoxazole), termed MI-R. This method combines an existing rapid assessment technique for E.

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