Meiofauna, animals which are < 1mm and live between sand grains, are essential for ecosystem functions as they are near the base of the food web and facilitate benthic-pelagic coupling. They have been shown to be reliable bioindicators in both single- and multiple-stressor scenarios; their utility for assessing environmental impacts was demonstrated following the 2010 Deepwater Horizon oil spill. The overarching goal of this project is to develop a framework to use meiofaunal communities as indicators of short-term disturbances and long-term changing environmental conditions along the Northern Gulf of Mexico. We will use high-throughput DNA metabarcoding to assess meiofaunal diversity, and community structure in the northern Gulf of Mexico. Whereas metabarcoding often yields a long list of taxa that can only be identified to higher levels, we will use traditional morphological approaches and individual DNA barcoding and mitogenomics in conjunction with metabarcoding to enable specific identification of taxa recovered in our metabarcoding. Metabarcoding results will be correlated to environmental parameters, including granulometry and carbon and nitrogen content, to understand larger ecological patterns and inform future monitoring work. In support of these objectives, a meiofauna taxonomy workshop will be held at the Dauphin Island Sea Lab where guest taxonomic experts will identify Alabama's diverse meiofauna and help train the next generation of meiofaunal taxonomists. Meeting these objectives will allow us to ground truth high-throughput DNA sequencing techniques for use in environmental assessments of meiofauna, ameliorating the labor intensive and specialized training required in traditional taxonomic approaches.

In spring and summer of 2019, the two openings of the Bonnet Carré Spillway represented an unprecedented influence on natural modes of variability in a coastal system. The abundance of river discharge diverted by this event has an unknown potential for impacts on water quality and coastal dynamics in this region. Using a combination of data from shelf hydrographic surveys and a mooring site during the event, the dissolved oxygen dynamics on the shelf are investigated. Extensive of areas of hypoxia on the shelf were observed throughout the summer study period with high variability in both space and time. Patterns in the along and across-shelf bottom dissolved oxygen spatial structure were apparent in the data. In the along-shelf direction, dissolved oxygen tended to decrease from east to west. The across-shelf pattern was more complex with mid-shelf minimum between ~12-25 m. Furthermore, time series data of bottom dissolved oxygen from June through September were correlated with changes in bottom temperature, revealing a significant connection to upwelling/downwelling events and the presence or absence of hypoxia on the inner to mid-shelf. The results of this study are expected to facilitate the development of more effective mitigation and adaptation strategies in response to current and predicted changes in coastal oceans.

The coastal region is facing heightened risks posed by climate change. Mobile Bay, part of the Alabama coastal area, is prone to storm surge given its physical configuration and is likely to experience high surges under climate change. It is thus imperative to prepare the coastal community in Mobile Bay area for future climate change risks. The first necessary step would be to understand the spatiotemporal patterns of community vulnerability in recent history so that the information can guide future resilience plans. Using data from the American Community Surveys, we construct social vulnerability indexes at the block group level for Mobile county and Baldwin county for 2000, 2010, and 2020. To further investigate the spatiotemporal patterns of changing social vulnerabilities over the past 20 years, we conduct hotspot analysis and cluster analysis. Results suggest that the area with heightened social vulnerability has clearly expanded in Mobile county. Some consistent hotspots in Mobile city are detected. In addition to social vulnerability analyses, we depict the spatiotemporal patterns of changing land use land cover (LULC) from 2001 - 2019 by using the National Land Cover Database. Examining the changing spatial patterns of both social vulnerability and LULC highlights areas that need allocation of resources to build resilience to future climate change.

Access to clean drinking water is a cornerstone of community resilience and sustainability. Private well users are at a disproportionate risk for poor drinking water quality because the water is often under- or untreated compared to public water supplies. The objectives of this study are to measure and predict relationships between groundwater geochemistry, land use, and climatic stressors on groundwater quality, particularly for private well users. First, we've launched a citizen-science campaign to collect well water quality data across coastal Alabama, and we are working with private well users to calibrate the citizen-science data to laboratory analysis. The result of this effort will be a groundwater quality dataset that captures spatial and temporal variability of priority contaminants like nutrients, pesticides, heavy metals (e.g., As, Cr, Pb), pathogens (coliforms, E. coli), and volatile organic compounds (e.g., benzene, chlorinated solvents). We have developed a web-based portal to aggregate and analyze the data as a function of variables like hydrogeology, land cover and groundwater recharge potential to understand sources of contaminants in the water. The dataset will also be leveraged to determine the effect of precipitation extremes on the probability of adverse groundwater quality events that also consider the effect of sea level rise and changes in the depth to groundwater. Throughout the project, we are working closely with the Extension led Alabama Private Well Owner Program (APWP) at Auburn and other Extension professionals throughout the state to create resources for well users and increase stakeholder awareness of groundwater Alabama.

Alabama's coastal aquifers provide freshwater for the Gulf Coast Region, but because groundwater is hidden, this valuable resource has not received enough attention. Large data gaps and incomplete quantifications at almost all spatiotemporal levels challenge the sustainability of Alabama groundwater. Long-term coastal societies, economies, and/or ecosystems may not be expected to remain sustainable without properly managing the valuable groundwater resources by which they all depend upon. This project applies process-based models, machine learning approaches, and statistical analyses to systematically quantify sustainability and vulnerability of Southern Alabama groundwater under a changing climate. First, a three-dimensional (3D) steady-state groundwater flow model is built using MODFLOW and incorporating geologic/hydrologic information to define/calibrate main hydrostratigraphic units in southern Alabama. Backward particle tracking schemes are then applied to calculate groundwater ages, whose mean values are checked against isotope age data and wavelet analysis, providing a 3D index map for assessing vulnerability of Alabama aquifers. A stochastic model is also built using fractional calculus to calculate water flow through unsaturated soil, to quantify the impact of heterogeneous vadose zone on groundwater susceptibility. Second, long short-term memory networks (LSTMs) are applied to explore the spatiotemporal evolution characteristics of surface/subsurface water resources in Alabama under a changing climate. Results show that LSTMs capture the general trend of daily discharge at 17 gauged basins and the corresponding groundwater depth fluctuations in Alabama. Third, statistical analyses reveal the nonstationary, temporal evolution of groundwater resources at Alabama's coastal aquifers under a changing climate since 1981.