Seagrass ecosystems are inherently dynamic, responding to environmental change across a range of scales. Habitat requirements of seagrass are well defined, but less is known about their ability to resist disturbance. Specific means of recovery after loss are particularly difficult to quantify. Here we assess the resistance and recovery capacity of 12 seagrass genera.

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Humans strongly impact the dynamics of coastal systems, yet surprisingly few studies mechanistically link management of anthropogenic stressors and successful restoration of nearshore habitats over large spatial and temporal scales. Such examples are sorely needed to ensure the success of ecosystem restoration efforts worldwide.

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Chronic seasonal low oxygen condition (hypoxia) occurs in the deep waters of Chesapeake Bay as a result of eutrophication-induced phytoplankton blooms and their subsequent decomposition. Summertime hypoxia has been observed in Chesapeake Bay for over 80 years, with scientific attention and understanding increasing substantially during the past several decades after rigorous and routine monitoring programs were put in place.

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Chesapeake Bay has undergone profound changes since European settlement. Increases in human and livestock populations, associated changes in land use, increases in nutrient loadings, shoreline armoring, and depletion of fish stocks have altered the important habitats within the Bay. Submersed aquatic vegetation (SAV) is a critical foundational habitat and provides numerous benefits and services to society.

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Regression-based approaches are often employed to estimate riverine constituent concentrations and fluxes based on typically sparse concentration observations. One such approach is the recently developed WRTDS (“Weighted Regressions on Time, Discharge, and Season”) method, which has been shown to provide more accurate estimates than prior approaches in a wide range of applications.

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Two statistical approaches, weighted regression on time, discharge, and season and generalized addi- tive models, have recently been used to evaluate water quality trends in estuaries. Both models have been used in similar contexts despite differences in statistical foundations and products. This study provided an empirical and qualitative comparison of both models using 29 years of data for two discrete time series of chlorophyll-a (chl-a) in the Patuxent River estuary.

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The influence of sea level rise and warming on circulation and water quality of the Chesapeake Bay under projected climate conditions in 2050 were estimated by computer simulation. Four estuarine circulation scenarios in the estuary were run using the same watershed load in 1991-2000 period. They are, 1) the Base Scenario, which represents the current climate condition, 2) a Sea Level Rise Scenario, 3) a Warming Scenario, and 4) a combined Sea Level Rise and Warming Scenario.

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Interactions among global change stressors and their effects at large scales are often proposed, but seldom evaluated. This situation is primarily due to lack of comprehensive, sufficiently long-term, and spatially extensive datasets. Seagrasses, which provide nursery habitat, improve water quality, and constitute a globally important carbon sink, are among the most vulnerable habitats on the planet.

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Antimicrobial resistance is a global health issue. The discharge, maintenance and transfer of antimicrobial resistance to the aquatic environment and the risk this presents is relatively unknown. This work describes the presence and distribution of antimicrobial resistant Escherichia coli in surface waters of seven rivers in south east Queensland, Australia.

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Derived from river monitoring data, concentration-discharge (C-Q) relationships are powerful indicators of export dynamics. Proper interpretation of such relationships can be made complex, however, if the ln(C)-ln(Q) relationships are nonlinear or if the relationships change over time, season, or discharge. Methods of addressing these issues by “binning” data can introduce artifacts that obscure underlying interactions among time, discharge, and season.

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