Microbial diversity, genomics, and phage-host interactions of cyanobacterial harmful algal blooms.

The occurrence of cyanobacterial harmful algal blooms (cyanoHABs) is related to their physical and chemical environment. However, less is known about their associated microbial interactions and processes. In this study, cyanoHABs were analyzed as a microbial ecosystem, using 1 year of 16S rRNA sequencing and 70 metagenomes collected during the bloom season from Lake Okeechobee (Florida, USA). Biogeographical patterns observed in microbial community composition and function reflected ecological zones distinct in their physical and chemical parameters that resulted in bloom "hotspots" near major lake inflows. Changes in relative abundances of taxa within multiple phyla followed increasing bloom severity. Functional pathways that correlated with increasing bloom severity encoded organic nitrogen and phosphorus utilization, storage of nutrients, exchange of genetic material, phage defense, and protection against oxidative stress, suggesting that microbial interactions may promote cyanoHAB resilience. Cyanobacterial communities were highly diverse, with picocyanobacteria ubiquitous and oftentimes most abundant, especially in the absence of blooms. The identification of novel bloom-forming cyanobacteria and genomic comparisons indicated a functionally diverse cyanobacterial community with differences in its capability to store nitrogen using cyanophycin and to defend against phage using CRISPR and restriction-modification systems. Considering blooms in the context of a microbial ecosystem and their interactions in nature, physiologies and interactions supporting the proliferation and stability of cyanoHABs are proposed, including a role for phage infection of picocyanobacteria. This study displayed the power of "-omics" to reveal important biological processes that could support the effective management and prediction of cyanoHABs. IMPORTANCE: Cyanobacterial harmful algal blooms pose a significant threat to aquatic ecosystems and human health. Although physical and chemical conditions in aquatic systems that facilitate bloom development are well studied, there are fundamental gaps in the biological understanding of the microbial ecosystem that makes a cyanobacterial bloom. High-throughput sequencing was used to determine the drivers of cyanobacteria blooms in nature. Multiple functions and interactions important to consider in cyanobacterial bloom ecology were identified. The microbial biodiversity of blooms revealed microbial functions, genomic characteristics, and interactions between cyanobacterial populations that could be involved in bloom stability and more coherently define cyanobacteria blooms. Our results highlight the importance of considering cyanobacterial blooms as a microbial ecosystem to predict, prevent, and mitigate them.

Quantifying the contribution of external loadings and internal hydrodynamic processes to the water quality of Lake Okeechobee.

The water quality of a waterbody is determined by internal hydrodynamic processes as well as external loadings. Understanding the interaction between the external loading and internal process of a waterbody is essential for efficient water management and water quality improvement. Studies and efforts have focused on water and nutrient loading from drainage watersheds, but the contribution of the waterbody's internal process to water quality is often ignored and not well documented. This study investigated how the water quality of Lake Okeechobee is controlled by external and internal factors using statistical and numerical modeling approaches. Water quantity and quality observed at the outlets of the Lake Okeechobee drainage basins and 19 monitoring sites located within the lake were statistically analyzed using multilinear regression. A three-dimensional numerical model, namely Environmental Fluid Dynamics Code (EFDC), was calibrated to the observations to mathematically represent the lake's internal hydrodynamic process. The multilinear regression found that the water quality was the most sensitive to air temperature, the total phosphorus (TP) concentration of inflow entering the lake from the Kissimmee River basins, and the amount of outflow discharged from the lake among external factors. However, the regression models and their explanatory power were substantially varied by the monitoring stations. The model parameter sensitivity analysis of the calibrated EFDC model showed that model parameters related to the lake's internal algal processes including algal growth, predation, and basal metabolism rates had greater impacts on algal biomass than other model parameters controlling nutrient-related processes such as nutrient half-saturation and hydrolysis rates. The EFDC input data sensitivity analysis found that wind (speed) is the major driving force for the internal hydrodynamic processes; its impact on algal biomass was greater than those of the external loadings. In addition, the algal biomass was found to have an inverse relationship with wind-induced horizontal currents. The results demonstrate the dynamic contribution of the internal and external drivers to the water quality of Lake Okeechobee, suggesting the need to consider both internal hydrodynamic and external loading processes for efficient water quality improvement of the lake.

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.

Efficient anaerobic sediment processing via a novel sediment core extruder.

Collection, extrusion and sampling of sediment cores are common methods used to explore the biogeochemistry of marine and lake deposits. We present a novel design for a sediment-core extruder that has greatly improved our core processing efficiency and reduced costs, while ensuring reliable results from solid phase and porewater analyses. The free-standing, aluminum structure is lightweight, enabling easy transport and quick setup/breakdown when processing cores in the field, and the height of the apparatus can be adjusted to fit any lab space and create a comfortable sampling experience for the user. Set up and processing time are reduced by eliminating the need for clamps or collars that secure the core barrel. A unique feature is the novel means to attach a portable glove bag for anaerobic sample processing. Dissolved iron speciation data from sediment cores collected in hypereutrophic Lake Okeechobee, Florida, USA, are presented to demonstrate the utility of the device in maintaining redox conditions throughout the process of core extrusion and sectioning.•A sediment extrusion device is described to allow efficient sediment core processing (separation) for subsequent biogeochemical analyses•The extruder is portable and can be adapted to cores of any diameter.•The extruder can be outfitted with an optional novel mechanism for attaching a glove bag to allow for anaerobic processing, and testing demonstrates that reduced iron is maintained in the dissolved state.

Nitrogen-enriched discharges from a highly managed watershed intensify red tide (Karenia brevis) blooms in southwest Florida.

Karenia brevis blooms on Florida's Gulf Coast severely affect regional ecosystems, coastal economies, and public health, and formulating effective management and policy strategies to address these blooms requires an advanced understanding of the processes driving them. Recent research suggests that natural processes explain offshore bloom initiation and shoreward transport, while anthropogenic nutrient inputs may intensify blooms upon arrival along the coast. However, past correlation studies have failed to detect compelling evidence linking coastal blooms to watershed covariates indicative of anthropogenic inputs. We explain why correlation is neither necessary nor sufficient to demonstrate a causal relationship-i.e., a persistent pattern of interaction governed by deterministic rules-and pursue an empirical investigation leveraging the fact that systematic temporal patterns may reveal systematic cause-and-effect relationships. Using time series derived from in-situ sample data, we applied singular spectrum analysis-a non-parametric spectral decomposition method-to recover deterministic signals in the dynamics of K. brevis blooms and upstream water quality and discharge covariates in the Charlotte Harbor region between 2012 and 2021. Next, we applied causal analysis methods based on chaos theory-i.e., convergent cross-mapping and S-mapping-to detect and quantify persistent, state-dependent interaction regimes between coastal blooms and watershed covariates. We discovered that nitrogen-enriched Caloosahatchee River discharges have consistently intensified K. brevis blooms to varying degrees over time. River discharge was typically most influential at the earliest stages of blooms, while total nitrogen concentrations exerted the strongest influence during blooms' growth/maintenance stages. These results indicate that discharges and nitrogen inputs influence blooms through distinct yet synergistic causal mechanisms. Additionally, we traced this anthropogenic influence upstream to Lake Okeechobee (which discharges to the Caloosahatchee River) and the Kissimmee River basin (which drains into Lake Okeechobee), suggesting that watershed-scale nutrient management and modifications to Lake Okeechobee discharge protocols will likely be necessary to mitigate coastal blooms.

Growth limitation status and its role in interpreting chlorophyll a response in large and shallow lakes: A case study in Lake Okeechobee.

Understanding the response of Chlorophyll a concentration (Chl-a, an indicator of phytoplankton biomass) to environmental factors is critical for eutrophication management. Light and nutrients often act as two main limiting environmental factors in large and shallow lakes. However, the limitation status is usually not considered explicitly when building empirical relationships even though the growth limitation is the possible mechanism controlling the behaviors of these relationships. Here we chose a typical large and shallow eutrophic lake (Lake Okeechobee) to study the response of Chl-a concentration under different growth limitation conditions. Using an existed decision tree model followed by Carlson's trophic state index, monitoring data from 1994 to 2020 were classified into light-limitation, nitrogen-limitation, or phosphorus-limitation. The spatio-temporal patterns of limitation status were revealed. By subdivision of observations according to these growth limitation classes, our results demonstrated three main findings. First, algae responded differently between light limitation and nutrient limitation. Chl-a concentrations were lower with smaller variability when light was limiting than those when nutrient was limiting. In addition, the evolution of Chl-a in enduring nutrient limitation events were more dynamic. Second, limitation-specific regressions provided a more straightforward interpretation compared with those without consideration of limitation status. Chl-a ∼ nutrient relationship based on limitation classification displayed a higher R2 with a positive slope. This positive slope indicates the sensitivity of Chl-a to that specific nutrient. Moreover, response of Chl-a to phosphorus was successfully detected by identifying P-limited samples. Otherwise, the Chl-a ∼ TP response would be muted since nitrogen is the main limiting nutrient in Lake Okeechobee. Third, a spatial heterogeneity of Chl-a ∼ TN relationship was revealed by Bayesian hierarchical modelling. This indicates the necessity of focusing more on hot spots where Chl-a displays a higher sensitivity to increase of nutrient. Our findings demonstrate the advantage of developing the limitation-specific and zone-specific relationships between algal biomass and environmental factors.

Evaluation of ECOSTRESS Thermal Data over South Florida Estuaries.

Operational coarse-resolution satellite thermal sensors designed for global oceans are often insufficient for evaluating surface temperature of small water bodies. Here, the quality of the thermal data, collected by the ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS), over several South Florida estuaries, Chesapeake Bay, and Lake Okeechobee is evaluated using both in situ and Moderate Resolution Imaging Spectroradiometer (MODIS) Sea Surface Temperature (SST) data. Overall, for SST between ~6 and ~32 °C, ECOSTRESS LST (Land Surface Temperature, used as a surrogate for SST in this study) appears to be slightly underestimated, with the underestimation being more severe at night (-1.13 °C) than during the day (-0.64 °C), in spring and summer (-1.25 ± 1.39 °C) than in autumn and winter (-0.57 ± 0.98 °C), and after May 2019 when two of the five bands failed. The root-mean-square uncertainties of ECOSTRESS SST are generally within 1-2 °C. Spatial analysis further suggests that ECOSTRESS SST covers waters closer to shore and reveals more spatial features than MODIS, with comparable image noise. From these observations, after proper georeferencing and empirical correction of the negative bias, ECOSTRESS SST may be used to evaluate the thermal environments of small water bodies, thus filling gaps in the coarse-resolution satellite data.

Seasonal dynamics of terrestrially sourced nitrogen influenced Karenia brevis blooms off Florida's southern Gulf Coast.

Harmful algal blooms (HABs) threaten coastal ecological systems, public health, and local economies, but the complex physical, chemical, and biological processes that culminate in HABs vary by locale and are often poorly understood. Despite broad recognition that cultural eutrophication may exacerbate nearshore bloom events, the association is typically not linear and is often difficult to quantify. Off the Gulf Coast of Florida, Karenia brevis blooms initiate in the open waters of the Gulf of Mexico, and advection of cells supplies nearshore blooms. However, past work has struggled to describe the relationship between terrestrial nutrient runoff and bloom maintenance near the Gulf Coast. This study applied a novel nonlinear time series (NLTS) analytical framework to investigate whether nearshore bloom dynamics observed near Charlotte Harbor, FL were causally and systematically driven by terrestrially sourced inputs of nitrogen, phosphorus, and freshwater between 2012 and 2018. Singular spectrum analysis (SSA) isolated low-dimensional, deterministic signals in K. brevis log10-density dynamics and in the dynamics of nine of 10 candidate drivers. The predominantly seasonal K. brevis signal was strong, explaining 77.6% of the total variance in the observed time series. Causal tests with convergent cross-mapping provided evidence that nitrogen concentrations measured at the discharge point of the Caloosahatchee River systematically influenced K. brevis bloom dynamics. However, further causal testing failed to link these nitrogen dynamics to an upstream basin, possibly due to data limitations. The results support the hypothesis that anthropogenic nitrogen runoff facilitated the growth of K. brevis blooms near Charlotte Harbor and suggest that bloom events would be mitigated by nitrogen source and transport controls within the Caloosahatchee and/or Kissimmee River basins. More broadly, this work demonstrates that management-relevant causal inferences into the drivers of HABs may be drawn from available monitoring records.