Assessing the utility of shellfish sanitation monitoring data for long-term estuarine water quality analysis.

Regular testing of coastal waters for fecal coliform bacteria by shellfish sanitation programs could provide data to fill large gaps in existing coastal water quality monitoring, but research is needed to understand the opportunities and limitations of using these data for inference of long-term trends. In this study, we analyzed spatiotemporal trends from multidecadal fecal coliform concentration observations collected by a shellfish sanitation program, and assessed the feasibility of using these monitoring data to infer long-term water quality dynamics. We evaluated trends in fecal coliform concentrations for a 20-year period (1999-2021) using data collected from spatially fixed sampling sites (n = 466) in North Carolina (USA). Findings indicated that shellfish sanitation data can be used for long-term water quality inference under relatively stationary management conditions, and that salinity trends can be used to investigate management-driven bias in fecal coliform observations collected in a particular area.

Short-term forecasting of fecal coliforms in shellfish growing waters.

This study sought to develop models for predicting near-term (1-3 day) fecal contamination events in coastal shellfish growing waters. Using Random Forest regression, we (1) developed fecal coliform (FC) concentration models for shellfish growing areas using watershed characteristics and antecedent hydrologic and meteorologic observations as predictors, (2) tested the change in model performance associated when forecasted, as opposed to measured, rainfall variables were used as predictors, and (3) evaluated model predictor importance in relation to shellfish sanitation management criteria. Models were trained to 10 years of coastal FC measurements (n = 1285) for 5 major shellfish management areas along the Florida (USA) coast. Model performance varied between the 5 management areas with R2 ranging from 0.36 to 0.72. Antecedent precipitation variables were among the most important predictors in the day-of forecast models in all management areas. When forecasted rainfall was included in the models, wind components became increasingly important.

Satellite and in situ cyanobacteria monitoring: Understanding the impact of monitoring frequency on management decisions.

Cyanobacterial harmful algal blooms (cyanoHABs) in reservoirs can be transported to downstream waters via scheduled discharges. Transport dynamics are difficult to capture in traditional cyanoHAB monitoring, which can be spatially disparate and temporally discontinuous. The introduction of satellite remote sensing for cyanoHAB monitoring provides opportunities to detect where cyanoHABs occur in relation to reservoir release locations, like canal inlets. The study objectives were to assess (1) differences in reservoir cyanoHAB frequencies as determined by in situ and remotely sensed data and (2) the feasibility of using satellite imagery to identify conditions associated with release-driven cyanoHAB export. As a representative case, Lake Okeechobee and the St. Lucie Estuary (Florida, USA), which receives controlled releases from Lake Okeechobee, were examined. Both systems are impacted by cyanoHABs, and the St. Lucie Estuary experienced states of emergency for extreme cyanoHABs in 2016 and 2018. Using the European Space Agency's Sentinel-3 OLCI imagery processed with the Cyanobacteria Index (CIcyano), cyanoHAB frequencies across Lake Okeechobee from May 2016-April 2021 were compared to frequencies from in situ data. Strong agreement was observed in frequency rankings between the in situ and remotely sensed data in capturing intra-annual variability in bloom frequencies across Lake Okeechobee (Kendall's tau = 0.85, p-value = 0.0002), whereas no alignment was observed when evaluating inter-annual variation (Kendall's tau = 0, p-value = 1). Further, remotely sensed observations revealed that cyanoHABs were highly frequent near the inlet to the canal connecting Lake Okeechobee to the St. Lucie Estuary in state-of-emergency years, a pattern not evident from in situ data alone. This study demonstrates how remote sensing can complement traditional cyanoHAB monitoring to inform reservoir release decision making.

Reconstructing the historical expansion of industrial swine production from Landsat imagery.

In the USA, historical data on the period over which industrial swine farms have operated are usually only available at the county scale and released every 5 years via the USDA Census of Agriculture, leaving the history of the swine industry and its potential legacy effects on the environment poorly understood. We developed a changepoint-based workflow that recreates the construction timelines of swine farms, specifically by identifying the construction years of swine manure lagoons from historical Landsat 5 imagery for the period of 1984 to 2012. The study focused on the Coastal Plain of North Carolina, a major pork-producing state in the USA. The algorithm successfully predicted the year of swine waste lagoon construction (+ /- 1 year) with an accuracy of approximately 94% when applied to the study area. By estimating the year of construction of 3405 swine waste lagoons in NC, we increased the resolution of available information on the expansion of swine production from the county scale to spatially-explicit locations. We further analyzed how the locations of swine waste lagoons changed in proximity to water resources over time, and found a significant increase in swine waste lagoon distances to the nearest water feature across the period of record.

Hurricanes, El Niño and harmful algal blooms in two sub-tropical Florida estuaries: Direct and indirect impacts.

Future increases in the intensity of hurricanes and El Niño periods predicted by climate change models have focused attention on their role in stimulating harmful algal blooms (HABs). A series of hurricanes that recently impacted Florida (USA) provided a unique opportunity to explore the relationships between hurricanes, El Niño and HABs in two Florida estuaries subject to repeated intense ecosystem disruptive HABs, the Indian River Lagoon and the St. Lucie Estuary. The roles that hurricanes and El Niño play in contributing to HAB events are examined in the context of key structural and functional features of each estuary and their watersheds, including morphology, water residence time and hydrology, such as the influence of Lake Okeechobee discharges into the St. Lucie Estuary. The most direct impact was the increase in rainfall associated with hurricanes and El Niño, resulting in enhanced nutrient loads which drive HABs in the Indian River Lagoon and Lake Okeechobee. Major HABs in Lake Okeechobee also present an indirect threat of freshwater HAB blooms in the St. Lucie Estuary via mandated discharges from the lake into the estuary during high rainfall periods. Conversely, during the absence of HABs in Lake Okeechobee, short water residence times produced by discharges into the St. Lucie Estuary can result in lower bloom intensities.

Revealing Biotic and Abiotic Controls of Harmful Algal Blooms in a Shallow Subtropical Lake through Statistical Machine Learning.

Harmful algal blooms are a growing human and environmental health hazard globally. Eco-physiological diversity of the cyanobacteria genera that make up these blooms creates challenges for water managers tasked with controlling the intensity and frequency of blooms, particularly of harmful taxa (e.g., toxin producers, N2 fixers). Compounding these challenges is the ongoing debate over the efficacy of nutrient management strategies (phosphorus-only versus nitrogen and phosphorus), which increases decision-making uncertainty. To improve our understanding of how different cyanobacteria respond to nutrient levels and other biophysical factors, we analyzed a unique 17 year data set comprising monthly observations of cyanobacteria genera and zooplankton abundances, water quality, and flow in a bloom-impacted, subtropical, flow-through lake in Florida (United States). Using the Random Forests machine learning algorithm, an ensemble modeling approach, we characterized and quantified relationships among environmental conditions and five dominant cyanobacteria genera. Results highlighted nonlinear relationships and critical thresholds between cyanobacteria genera and environmental covariates, the potential for hydrology and temperature to limit the efficacy of cyanobacteria bloom management actions, and the importance of a dual nutrient management strategy for reducing bloom risk in the long term.

Apoptotic susceptibility to DNA damage of pluripotent stem cells facilitates pharmacologic purging of teratoma risk.

Pluripotent stem cells have been the focus of bioengineering efforts designed to generate regenerative products, yet harnessing therapeutic capacity while minimizing risk of dysregulated growth remains a challenge. The risk of residual undifferentiated stem cells within a differentiated progenitor population requires a targeted approach to eliminate contaminating cells prior to delivery. In this study we aimed to validate a toxicity strategy that could selectively purge pluripotent stem cells in response to DNA damage and avoid risk of uncontrolled cell growth upon transplantation. Compared with somatic cell types, embryonic stem cells and induced pluripotent stem cells displayed hypersensitivity to apoptotic induction by genotoxic agents. Notably, hypersensitivity in pluripotent stem cells was stage-specific and consistently lost upon in vitro differentiation, with the mean half-maximal inhibitory concentration increasing nearly 2 orders of magnitude with tissue specification. Quantitative polymerase chain reaction and Western blotting demonstrated that the innate response was mediated through upregulation of the BH3-only protein Puma in both natural and induced pluripotent stem cells. Pretreatment with genotoxic etoposide purged hypersensitive pluripotent stem cells to yield a progenitor population refractory to teratoma formation upon transplantation. Collectively, this study exploits a hypersensitive apoptotic response to DNA damage within pluripotent stem cells to decrease risk of dysregulated growth and augment the safety profile of transplant-ready, bioengineered progenitor cells.