Widespread wetland loss and degradation has resulted in a subsequent loss of the ecosystem services they provide, including the removal of human-produced nitrogen. Human-made stormwater control systems such as roadside ditches are possible hotspots for nitrogen removal in coastal watersheds, yet few studies have quantified their biogeochemical potential. We measured soil nitrogen removal potential and microbial 16S rRNA structure in 96 roadside ditches draining predominately forested, urban, and agricultural catchments surrounding Mobile Bay, AL (USA). Nitrogen removal by denitrification and anammox dominated over nitrogen retention by dissimilatory nitrate reduction to ammonium (DNRA), accounting for upwards of 89% of nitrate reduction on average. There were no differences in soil chemistry, annamox, DNRA, or microbial diversity across land use types. However, denitrification was more than twice as high in urban and agricultural ditches compared to forested ditches, and microbial indicator species analysis selected putative ammonia oxidizers (Nitrososphaeraceae and Nitrosomonadaceae), nitrate reducers (Gaiellales), nitrous oxide reducers (Myxococcales) as significant groups in Urban and Agricultural ditches. Additionally, denitrification and DNRA were positively correlated with plant biomass, which was selected as a key driver of microbial community structure. These results suggest that while land development may influence nitrogen removal in these systems, ditch management practices, such as mowing, may outweigh the effects of land use. Further, our findings show that constructed drainage networks represent areas of considerable nutrient removal potential in the landscape, with denitrification and anammox rates equal to or greater than those measured in “natural” ecosystems, and can potentially compensate for a loss of nitrogen removal capacity associated with stream and wetland degradation in the region.

The Watershed Game is a decade-old proven interactive tool for educating audiences about relationships between land use and water quality in streams, lakes, and large rivers. Existing in both local leader (policymakers, community leaders) and classroom (student) versions, the game allows players to understand how land use impacts water quality, increases their knowledge of tools (Best Management Practices, BMPs) that can be used to reduce or prevent adverse impacts, and realize how their collective actions can help achieve a clean water goal. The gaming approach serves to break down group barriers, encourage dialogue, civility and mutual respect; and build a sense of community among participants. Over the years, users have requested expansion of the game to include a focus on the unique needs and issues of coastal and estuarine environments. For the past 2 years, a team of individuals including Sea Grant personnel from Minnesota and Mississippi-Alabama, the Alabama Water Institute, the Dauphin Island Sea Lab, NOAA’s Office for Coastal Management and Gulf partners have worked to create a Coast model of the Watershed Game. The Coast model focuses on water quality but additionally integrates resilience into game play. Through literature reviews, surveys, and focus groups, the project team identified priority issues and existing BMPs. The Coast model’s gameboard depicts land uses appropriate for coastal environments, and the tool cards present plans, practices and policies that reduce nitrogen, phosphorus, and sediment in coastal waters or enhance a community’s resilience to flooding. Two pilot workshops were held in Louisiana and Alabama (prior to cessation of travel due to the pandemic) and helped to refine gameboard graphics, select the most relevant tool cards, and clarify guidelines for game facilitation. Join us to tour the gameboard, view a round of play and offer input for the game’s remaining elements under development.

Many metal ions are known to have severe health and environmental impacts, particularly in aqueous environments. Therefore, we have investigated the detection of divalent metal cations in water using array sensing techniques. Array sensing, also known as chemical fingerprinting or pattern recognition, can offer rapid detection of metal cations using simpler instrumentation that can be conducted on-site immediately following sample collection. Through our research group’s recent involvement in a MS-AL EPSCoR consortium, we intend to apply these results to metal cation detection and water quality monitoring along the Gulf Coast. A multivariate data set obtained by exposing an array containing two water soluble commercially available dyes (xylenol orange and methylthymol blue) to multiple metal ions was interpreted using pattern recognition algorithms such as linear discriminant analysis (LDA). The array was shown to discriminate nine divalent metal cations qualitatively with excellent resolution. We optimized our array further by taking advantage of responses from a variety of metal-dye stoichiometries to map metal ion concentrations of four environmentally relevant divalent metal ions (Hg(II), Pb(II), Cd(II), and Cu(II)) quantitatively at concentrations as low as 1 µM in neutral water. Based on each metal cation’s strong binding affinity to both dyes, near stoichiometric binding, and the system's overall linear response over a wide range of metal ion concentrations, our array was used to successfully discriminate binary and ternary metal cation mixtures, a particularly valuable accomplishment for chemical fingerprinting systems, which otherwise typically struggle with the “problem of mixtures”. To validate our array’s utility as a calibration plot, we projected a series of unknown metal cation mixtures on our original scores plot with exceptional predictive ability.

Human impacts on coastal marshes are considerable, with 1-2% of coastal marshes lost per year leading to subsequent losses in ecosystem services like nutrient filtering and carbon sequestration. Currently, marsh construction is being used to mitigate losses of marsh cover and services resulting from human impacts in coastal areas. Though marsh structure can be recovered shortly after construction, there are often long-term temporal lags in the recovery of ecosystem functions in constructed marshes. We conducted a year-long field study comparing productivity, denitrification and dissimilatory nitrate reduction to ammonium (DNRA) between two 30-year old constructed marshes (CON-1, CON-2) and a nearby natural reference marsh (NAT). Additionally, we compared porewater nutrient stocks and above- and belowground biomass stocks in each marsh to identify potential drivers of functional differences between marshes. We found that CON-1 and CON-2 were structurally similar to NAT (i.e., plant biomass was similar). Likewise, gross ecosystem productivity (GEP), ecosystem respiration (ER) and net ecosystem exchange (NEE) were similar across all marshes. Further, DNRA and denitrification were fully recovered in the constructed marshes; in fact, denitrification was greater in CON-2 when compared to NAT. While ammonium porewater concentrations were similar across all marshes, phosphate, nitrate + nitrite, and hydrogen sulfide concentrations were greater in NAT than CON-1 and CON-2. This work suggest that current marsh construction practices could be a suitable tool for replacing lost marsh function and cover. However, the lag in recovery of porewater nutrient stocks may also suggests that there are other biogeochemical functions not observed in this study that may lost or not fully restored in constructed marshes.

Oysters and other bivalve shellfish assimilate elements from the environment into their shell and soft tissues, making them potentially useful bioindicators of pollution to local waters. Unlike soft tissues, shell material is not readily metabolized and may provide a temporally explicit record of past pollution exposure. To determine if shell can be used as a bioindicator of pollution similarly to soft tissues (as a proxy for tissues) and how relationships between shell and tissue might vary with pollution sources or environmental conditions, we used solution-based Inductively Coupled Plasma Mass Spectrometry to measure trace metal concentrations in shell and soft tissues of native and lab-reared oysters. Native oysters were obtained from restored reef sites in LA, MS, and AL, with different expected pollution from nearby anthropogenic sources, and Lab-reared oysters were exposed to different types of contaminated water at two salinities (25, 14) to test a common local environmental variable. Overall, trace metal concentrations in shell increased with concentrations in tissue, with the values in tissue explaining 50% (native), 43% (lab-25), and 33% (lab-14) of variation in shell values. Mg and V were conserved (assimilated near 1:1) between shell and tissues in all treatments. Variation between shell and tissue was higher at lower salinity. These data indicate that shell can be a direct proxy for tissue for some elements and at least predictive for others but may be affected by environmental conditions such as salinity. Salinity may be particularly important to interpreting bioindicator data because it affects both oyster physiology and bioavailability of trace metals in the environment. This method, therefore, has high potential for use to reconstruct historical pollution events, such as the Deepwater oil spill, and may be most informative when other conditions that affect oyster physiology and trace metal bioavailability are also considered.

In the United States and around the world, the security of critical water resources is at risk. Too much water, too little water, or water of poor quality endangers life, property, economies, and ecosystems. These threats to water security arise from several factors, including increased water demand from population growth and weather and water-related impacts of climate variability and change. As these complex threats have intensified, so has the Nation’s demand for advanced water prediction capabilities to better inform decisions. The National Weather Service’s Office of Water Prediction and partners are developing the National Water Model as a tool to help serve this need. The National Water Model is a high resolution hydrologic model that provides estimates of existing conditions and forecasts of key components of the water cycle across the continental United States and Hawaii. The model utilizes meteorological inputs, environmental data, and observations from United States Geological Survey stream gages to simulate observed and forecast streamflow for nearly 5 million miles of rivers and streams. The hydrologic guidance provided by the National Water Model significantly expands geographic coverage while offering greater spatial and temporal resolution than other tools. These features make the model a unique and complementary tool to existing services. Information and visuals from the National Water Model, show how impacts of weather cascade across regions and basins in the continental United States. The guidance provided about how much water can be expected, when, and how it will likely flow improves the integrated understanding of U.S. water resources. Further, it enables communities to make more informed decisions about what actions to take, and when, to prepare for and protect their citizens and infrastructure. This session will describe the publicly available aspects of the National Water Model, how to access the information, and the value of the resources.