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Aaron J. Bever

Publications and source records attributed to Aaron J. Bever.

4 recordsLinked to original sources

Nitrogen reductions have decreased hypoxia in the Chesapeake Bay: Evidence from empirical and numerical modeling

Seasonal hypoxia is a characteristic feature of the Chesapeake Bay due to anthropogenic nutrient input from agriculture and urbanization throughout the watershed. Although coordinated management efforts since 1985 have reduced nutrient inputs to the Bay, oxygen concentrations at depth in the summer still frequently fail to meet water quality standards that have been set to protect critical estuarine living resources. To quantify the impact of watershed nitrogen reductions on Bay hypoxia during a recent period including both average discharge and extremely wet years (2016–2019), this study employed both statistical and three-dimensional (3-D) numerical modeling analyses. Numerical model results suggest that if the nitrogen reductions since 1985 had not occurred, annual hypoxic volumes (O 2 < 3 mg L −1 ) would have been ~50–120% greater during the average discharge years of 2016–2017 and ~20–50% greater during the wet years of 2018–2019. The effect was even greater for O 2 < 1 mg L −1 , where annual volumes would have been ~80–280% greater in 2016–2017 and ~30–100% greater in 2018–2019. These results were supported by statistical analysis of empirical data, though the magnitude of improvement due to nitrogen reductions was greater in the numerical modeling results than in the statistical analysis. This discrepancy is largely accounted for by warming in the Bay that has exacerbated hypoxia and offset roughly 6–34% of the improvement from nitrogen reductions. Although these results may reassure policymakers and stakeholders that their efforts to reduce hypoxia have improved ecosystem health in the Bay, they also indicate that greater reductions are needed to counteract the ever-increasing impacts of climate change.

Chesapeake Bay

Advancing estuarine ecological forecasts: Seasonal hypoxia in Chesapeake Bay

Ecological forecasts are quantitative tools that can guide ecosystem management. The coemergence of extensive environmental monitoring and quantitative frameworks allows for widespread development and continued improvement of ecological forecasting systems. We use a relatively simple estuarine hypoxia model to demonstrate advances in addressing some of the most critical challenges and opportunities of contemporary ecological forecasting, including predictive accuracy, uncertainty characterization, and management relevance. We explore the impacts of different combinations of forecast metrics, drivers, and driver time windows on predictive performance. We also incorporate multiple sets of state-variable observations from different sources and separately quantify model prediction error and measurement uncertainty through a flexible Bayesian hierarchical framework. Results illustrate the benefits of (1) adopting forecast metrics and drivers that strike an optimal balance between predictability and relevance to management, (2) incorporating multiple data sources in the calibration data set to separate and propagate different sources of uncertainty, and (3) using the model in scenario mode to probabilistically evaluate the effects of alternative management decisions on future ecosystem state. In the Chesapeake Bay, the subject of this case study, we find that average summer or total annual hypoxia metrics are more predictable than monthly metrics and that measurement error represents an important source of uncertainty. Application of the model in scenario mode suggests that absent watershed management actions over the past decades, long-term average hypoxia would have increased by 7% compared to 1985. Conversely, the model projects that if management goals currently in place to restore the Bay are met, long-term average hypoxia would eventually decrease by 32% with respect to the mid-1980s.

Chesapeake Bay

Synthesis of data and studies relating to Delta Smelt biology in the San Francisco Estuary, emphasizing water year 2017

In the San Francisco Estuary (SFE), the effects of freshwater flow on the aquatic ecosystem have been studied extensively over the years and remains a contentious management issue. It is especially contentious with regards to the Delta Smelt (Hypomesus transpacificus), a species endemic to the SFE that has been listed as threatened under the Federal Endangered Species Act and endangered by the State of California. Early studies of Delta Smelt distribution within the SFE suggested that Delta Smelt habitat is determined largely by freshwater flow; however, the exact mechanisms and processes producing such benefits remained unclear. In the summer of 2017, the Flow Alteration Management, Analysis, and Synthesis Team (FLOAT-MAST) was established to analyze, synthesize, and summarize the data collected from the various flow-related monitoring and special studies occurring in 2017(see Table Intro 4). This report will focus on the 2017 summer-fall status of Delta Smelt and its habitat following a record wet year. There has been a long-term decline in the abundance of Delta Smelt associated with a decline in other pelagic fishes. Investigators concluded that the decline has likely been caused by the interactive effects of several causes, including changes in both physical and biotic habitats, many of which are tied to amount and timing of freshwater flow. For this report, we formulated a number of basic predictions about the likely effects of high flows in 2017 on Delta Smelt and their habitat (Table 3). We use a qualitative weight of evidence approach to evaluate whether these predictions were supported by available data. Data sources included a variety of long-term monitoring surveys conducted by Interagency Ecological Program (IEP) agencies, as well as model outputs. Delta Smelt population, health, and life history metrics rarely responded as predicted. Water temperature appears to have a stronger effect on Delta Smelt growth rate and some metrics of life history diversity than outflow or X2 position. Other life history diversity attributes varied but did not appear to be driven by outflow or temperature. Health status was difficult to interpret. Low prevalence of lesions and improved nutritional condition during the drought was contradicted by declining overall population levels. Because of the sparse catches of Delta Smelt in the post-POD years, we consider the data insufficient to reach firm conclusions about the predictions concerning range and distribution of Delta Smelt, especially in the fall. The prediction of high survival was not supported. The 2017 Delta Smelt year class began with poor recruitment in spring of 2017 and below average survival for spring to summer and summer to fall. Thus, low production and low survival led to low abundance of all life stages. During the fall to winter period survival improved, yet the resulting adults were low in number. Foraging success of the fish captured, as measured by stomach fullness, was high for juveniles and adults in 2017 relative to recent years associated with the higher densities of common zooplankton prey that occurred in 2017.

California

Linking hydrodynamic complexity to delta smelt (Hypomesus transpacificus) distribution in the San Francisco Estuary, USA

Long-term fish sampling data from the San Francisco Estuary were combined with detailed three dimensional hydrodynamic modeling to investigate the relationship between historical fish catch and hydrodynamic complexity. Delta Smelt catch data at 45 stations from the Fall Midwater Trawl (FMWT) survey in the vicinity of Suisun Bay were used to develop a quantitative catch-based station index. This index was used to rank stations based on historical Delta Smelt catch. The correlations between historical Delta Smelt catch and 35 quantitative metrics of environmental complexity were evaluated at each station. Eight metrics of environmental conditions were derived from FMWT data and 27 metrics were derived from model predictions at each FMWT station. To relate the station index to conceptual models of Delta Smelt habitat, the metrics were used to predict the station ranking based on the quantified environmental conditions. Salinity, current speed, and turbidity metrics were used to predict the relative ranking of each station for Delta Smelt catch. Including a measure of the current speed at each station improved predictions of the historical ranking for Delta Smelt catch relative to similar predictions made using only salinity and turbidity. Current speed was also found to be a better predictor of historical Delta Smelt catch than water depth. The quantitative approach developed using the FMWT data was validated using the Delta Smelt catch data from the San Francisco Bay Study. Complexity metrics in Suisun Bay were-evaluated during 2010 and 2011. This analysis indicated that a key to historical Delta Smelt catch is the overlap of low salinity, low maximum velocity, and low Secchi depth regions. This overlap occurred in Suisun Bay during 2011, and may have contributed to higher Delta Smelt abundance in 2011 than in 2010 when the favorable ranges of the metrics did not overlap in Suisun Bay.

California