An assessment of a biosensor system for the quantification of microcystins in freshwater cyanobacterial blooms.

Microcystin-producing cyanobacterial blooms are a global issue threatening drinking water supplies and recreation on lakes and beaches. Direct measurement of microcystins is the only way to ensure waters have concentrations below guideline concentrations; however, analyzing water for microcystins takes several hours to days to obtain data. We tested LightDeck Diagnostics' bead beater cell lysis and two versions of the quantification system designed to give microcystin concentrations within 20 min and compared it to the standard freeze-thaw cycle lysis method and ELISA quantification. The bead beater lyser was only 30 % effective at extracting microcystins compared to freeze-thaw. When considering freeze-thaw samples analyzed in 2021, there was good agreement between ELISA and LightDeck version 2 (n = 152; R2 = 0.868), but the LightDeck slightly underestimated microcystins (slope of 0.862). However, we found poor relationships between LightDeck version 2 and ELISA in 2022 (n = 49, slopes 0.60 to 1.6; R2 < 0.6) and LightDeck version 1 (slope = 1.77 but also a high number of less than quantifiable concentrations). After the quantification issues are resolved, combining the LightDeck system with an already-proven rapid lysis method (such as microwaving) will allow beach managers and water treatment operators to make quicker, well-informed decisions.

The effect of single versus dual nutrient decreases on phytoplankton growth rates, community composition, and Microcystin concentration in the western basin of Lake Erie.

The primary management strategy for minimizing harmful algal blooms (HABs) in Lake Erie has been to reduce springtime loading of phosphorus (P) to the lake. However, some studies have shown that the growth rate and toxin content for the HABs-causing cyanobacterium Microcystis also respond to the availability of dissolved inorganic nitrogen (N). This evidence is based on both observational studies that correlate bloom development with changes in N forms and concentrations in the lake, and experiments in which P and/or N are added at concentrations in excess of those present in the lake. The goal of this study was to determine whether a combined decrease in N and P concentrations from ambient levels in Lake Erie could limit the development of HABs more than a reduction in P concentration only. To directly test the impact of P-only versus dual N and P concentration decreases on phytoplankton in the western basin of Lake Erie, we evaluated changes in growth rate, community composition, and microcystin (MC) concentration through eight bioassay experiments performed from June through October 2018, which encompassed the normal Lake Erie Microcystis-dominated HAB season. Our results showed that during the first five experiments covering June 25 to August 13, the P-only and the dual N and P decrease treatments had similar effects. However, when ambient N became scarce later in the season, the N and P decrease treatments resulted in negative growth rates for cyanobacteria, whereas -P only decreases did not. During low ambient N conditions, dual nutrient decreases lowered the prevalence of cyanobacteria among the total phytoplankton community and decreased microcystin concentrations. The results presented here complement previous experimental work on Lake Erie and suggest that dual nutrient control could be an effective management strategy to decrease microcystin production during the bloom and even possibly diminish or shorten the duration of the bloom based on creating nutrient limiting conditions sooner in the HAB growing season.

Heterotrophic Bacteria Dominate Catalase Expression during Microcystis Blooms.

In the oligotrophic oceans, key autotrophs depend on "helper" bacteria to reduce oxidative stress from hydrogen peroxide (H2O2) in the extracellular environment. H2O2 is also a ubiquitous stressor in freshwaters, but the effects of H2O2 on autotrophs and their interactions with bacteria are less well understood in freshwaters. Naturally occurring H2O2 in freshwater systems is proposed to impact the proportion of microcystin-producing (toxic) and non-microcystin-producing (nontoxic) Microcystis in blooms, which influences toxin concentrations and human health impacts. However, how different strains of Microcystis respond to naturally occurring H2O2 concentrations and the microbes responsible for H2O2 decomposition in freshwater cyanobacterial blooms are unknown. To address these knowledge gaps, we used metagenomics and metatranscriptomics to track the presence and expression of genes for H2O2 decomposition by microbes during a cyanobacterial bloom in western Lake Erie in the summer of 2014. katG encodes the key enzyme for decomposing extracellular H2O2 but was absent in most Microcystis cells. katG transcript relative abundance was dominated by heterotrophic bacteria. In axenic Microcystis cultures, an H2O2 scavenger (pyruvate) significantly improved growth rates of one toxic strain while other toxic and nontoxic strains were unaffected. These results indicate that heterotrophic bacteria play a key role in H2O2 decomposition in Microcystis blooms and suggest that their activity may affect the fitness of some Microcystis strains and thus the strain composition of Microcystis blooms but not along a toxic versus nontoxic dichotomy. IMPORTANCE Cyanobacterial harmful algal blooms (CHABs) threaten freshwater ecosystems globally through the production of toxins. Toxin production by cyanobacterial species and strains during CHABs varies widely over time and space, but the ecological drivers of the succession of toxin-producing species remain unclear. Hydrogen peroxide (H2O2) is ubiquitous in natural waters, inhibits microbial growth, and may determine the relative proportions of Microcystis strains during blooms. However, the mechanisms and organismal interactions involved in H2O2 decomposition are unexplored in CHABs. This study shows that some strains of bloom-forming freshwater cyanobacteria benefit from detoxification of H2O2 by associated heterotrophic bacteria, which may impact bloom development.

Recent Patterns in Lake Erie Phosphorus and Chlorophyll a Concentrations in Response to Changing Loads.

Despite the initial success of extensive efforts to reduce phosphorus (P) loading to Lake Erie as a part of the Great Lakes Water Quality Agreement, Lake Erie appears to be undergoing a re-eutrophication and it is plagued by harmful algal blooms. To offer insights into potential lake responses under differing Maumee River loads and reveal recent changes with time, we explored patterns in phosphorus and chlorophyll a data from 2008 to 2018 collected in western Lake Erie near the mouth of the Maumee River. We found high, but relatively stable Maumee River and lake concentrations of total P (TP) and soluble reactive P (SRP) with no discernable annual or seasonal patterns. Maumee spring TP load was not strongly related to lake TP, and lake SRP concentrations were positively but weakly related to SRP loads. Lake TP was a strong predictor of chlorophyll a, but the relationship was weaker at sites closer to the Maumee. These results highlight spatial differences both in P concentration and the relationship between TP and chlorophyll a, and these indicate that spring phosphorus loads are a weak algal biomass predictor in the portion of the western basin of Lake Erie represented by these sampling stations.

Metatranscriptomic Analyses of Diel Metabolic Functions During a Microcystis Bloom in Western Lake Erie (United States).

This study examined diel shifts in metabolic functions of Microcystis spp. during a 48-h Lagrangian survey of a toxin-producing cyanobacterial bloom in western Lake Erie in the aftermath of the 2014 Toledo Water Crisis. Transcripts mapped to the genomes of recently sequenced lower Great Lakes Microcystis isolates showed distinct patterns of gene expression between samples collected across day (10:00 h, 16:00 h) and night (22:00 h, 04:00 h). Daytime transcripts were enriched in functions related to Photosystem II (e.g., psbA), nitrogen and phosphate acquisition, cell division (ftsHZ), heat shock response (dnaK, groEL), and uptake of inorganic carbon (rbc, bicA). Genes transcribed during nighttime included those involved in phycobilisome protein synthesis and Photosystem I core subunits. Hierarchical clustering and principal component analysis (PCA) showed a tightly clustered group of nighttime expressed genes, whereas daytime transcripts were separated from each other over the 48-h duration. Lack of uniform clustering within the daytime transcripts suggested that the partitioning of gene expression in Microcystis is dependent on both circadian regulation and physicochemical changes within the environment.

A space-time geostatistical model for probabilistic estimation of harmful algal bloom biomass and areal extent.

Harmful algal blooms (HABs) have been increasing in intensity worldwide, including the western basin of Lake Erie. Substantial efforts have been made to track these blooms using in situ sampling and remote sensing. However, such measurements do not fully capture HAB spatial and temporal dynamics due to the limitations of discrete shipboard sampling over large areas and the effects of clouds and winds on remote sensing estimates. To address these limitations, we develop a space-time geostatistical modeling framework for estimating HAB intensity and extent using chlorophyll a data sampled during the HAB season (June-October) from 2008 to 2017 by five independent monitoring programs. Based on the Bayesian information criterion for model selection, trend variables explain bloom northerly and easterly expansion from Maumee Bay, wind effects over depth, and variability among sampling methods. Cross validation results demonstrate that space-time kriging explains over half of the variability in daily, location-specific chlorophyll observations, on average. Conditional simulations provide, for the first time, comprehensive estimates of overall bloom biomass (based on depth-integrated concentrations) and surface areal extent with quantified uncertainties. These new estimates are contrasted with previous Lake Erie HAB monitoring studies, and deviations among estimates are explored and discussed. Overall, results highlight the importance of maintaining sufficient monitoring coverage to capture bloom dynamics, as well as the benefits of the proposed approach for synthesizing data from multiple monitoring programs to improve estimation accuracy while reducing uncertainty.

Reduced forms of nitrogen are a driver of non-nitrogen-fixing harmful cyanobacterial blooms and toxicity in Lake Erie.

Western Lake Erie (WLE) experiences anthropogenic eutrophication and annual, toxic cyanobacterial blooms of non-nitrogen (N) fixing Microcystis. Numerous studies have shown that bloom biomass is correlated with an increased proportion of soluble reactive phosphorus loading from the Maumee River. Long term monitoring shows that the proportion of the annual Maumee River N load of non-nitrate N, or total Kjeldahl nitrogen (TKN), has also increased significantly (Spearman's ρ = 0.68, p = 0.001) over the last few decades and is also significantly correlated to cyanobacterial bloom biomass (Spearman's ρ = 0.64, p = 0.003). The ratio of chemically reduced N to oxidized N (TKN:NO3) concentrations was also compared to extracted chlorophyll and phycocyanin concentrations from all weekly sampling stations within WLE from 2009 to 2015. Both chlorophyll (Spearman's ρ = 0.657, p < 0.0001) and phycocyanin (Spearman's ρ = 0.714, p < 0.0001) were significantly correlated with TKN:NO3. This correlation between the increasing fraction of chemically reduced N from the Maumee River and increasing bloom biomass demonstrates the urgent need to control N loading, in addition to current P load reductions, to WLE and similar systems impacted by non-N-fixing, toxin-producing cyanobacteria.

Establishing spatial and temporal patterns in Microcystis sediment seed stock viability and their relationship to subsequent bloom development in Western Lake Erie.

This study assessed the distribution, abundance, and viability of pre- and post-overwintering Microcystis sediment seed stocks in Western Lake Erie and how these variables are potentially related to past and subsequent bloom formation. We conducted a two-year spatiotemporal survey of vegetative seed stocks in Western Lake Erie, the region where annual algal blooms generally develop. Sediment was collected from 16 sites covering an area of 375 km2 and water column depths ranging from 3-9 meters. Sample collection occurred in November 2014, April 2015, November 2015, and April 2016. The abundance of total and potentially-toxic Microcystis cell equivalents were determined using quantitative polymerase chain reaction. A series of laboratory experiments using lake sediment were conducted to assess the viability of Microcystis vegetative seed stocks. Across all sampling periods, the abundance of total Microcystis in the sediment ranged from 6.6 x 10(4) to 1.7 x 10(9) cell equivalents g-1, and potentially-toxic Microcystis ranged from 1.4 x 10(3) to 4.7 x 10(6) cell equivalents g-1. The percent potentially-toxic Microcystis in the sediment ranged from <1% to 68% across all samples. Total Microcystis abundance diminished significantly over winter with densities in spring nearly 10 times less than the previous fall. However, despite cell loss from fall to spring, lab experiments demonstrated that remaining non-toxic and potentially-toxic cells were viable after the overwintering period. Further, lab grow-out experiments indicate that potentially-toxic strains recruited at a slightly higher rate than non-toxic strains, and may in part, contribute to the pattern of higher relative toxicity during early stages of the blooms. The abundance and distribution of overwintering cells did not correlate strongly to areas in the lake where subsequent summer blooms were most persistent. However, numerical analysis suggests that recruitment of benthic overwintering populations could help explain a portion of the initial rapid increase in bloom biomass and the spatial extent of this bloom initiation, particularly when recruitment is paired with subsequent growth in appropriate water column conditions.

Correction: Verrucomicrobia are prevalent in north-temperate freshwater lakes and display class-level preferences between lake habitats.

[This corrects the article DOI: 10.1371/journal.pone.0195112.].

Verrucomicrobia are prevalent in north-temperate freshwater lakes and display class-level preferences between lake habitats.

The bacterial phylum Verrucomicrobia was formally described two decades ago and originally believed to be a minor member of many ecosystems; however, it is now recognized as ubiquitous and abundant in both soil and aquatic systems. Nevertheless, knowledge of the drivers of its relative abundance and within-phylum habitat preferences remains sparse, especially in lake systems. Here, we documented the distribution of Verrucomicrobia in 12 inland lakes in Southeastern Michigan, a Laurentian Great Lake (Lake Michigan), and a freshwater estuary, which span a gradient in lake sizes, depths, residence times, and trophic states. A wide range of physical and geochemical parameters was covered by sampling seasonally from the surface and bottom of each lake, and by separating samples into particle-associated and free-living fractions. On average, Verrucomicrobia was the 4th most abundant phylum (range 1.7-41.7%). Fraction, season, station, and depth explained up to 70% of the variance in Verrucomicrobia community composition and preference for these habitats was phylogenetically conserved at the class-level. When relative abundance was linearly modeled against environmental data, Verrucomicrobia and non-Verrucomicrobia bacterial community composition correlated to similar quantitative environmental parameters, although there were lake system-dependent differences and > 55% of the variance remained unexplained. A majority of the phylum exhibited preference for the particle-associated fraction and two classes (Opitutae and Verrucomicrobiae) were identified to be more abundant during the spring season. This study highlights the high relative abundance of Verrucomicrobia in north temperate lake systems and expands insights into drivers of within-phylum habitat preferences of the Verrucomicrobia.

Lake Bacterial Assemblage Composition Is Sensitive to Biological Disturbance Caused by an Invasive Filter Feeder.

One approach to improve forecasts of how global change will affect ecosystem processes is to better understand how anthropogenic disturbances alter bacterial assemblages that drive biogeochemical cycles. Species invasions are important contributors to global change, but their impacts on bacterial community ecology are rarely investigated. Here, we studied direct impacts of invasive dreissenid mussels (IDMs), one of many invasive filter feeders, on freshwater lake bacterioplankton. We demonstrated that direct effects of IDMs reduced bacterial abundance and altered assemblage composition by preferentially removing larger and particle-associated bacteria. While this increased the relative abundances of many free-living bacterial taxa, some were susceptible to filter feeding, in line with efficient removal of phytoplankton cells of <2 µm. This selective removal of particle-associated and larger bacteria by IDMs altered inferred bacterial functional group representation, defined by carbon and energy source utilization. Specifically, we inferred an increased relative abundance of chemoorganoheterotrophs predicted to be capable of rhodopsin-dependent energy generation. In contrast to the few previous studies that have focused on the longer-term combined direct and indirect effects of IDMs on bacterioplankton, our study showed that IDMs act directly as a biological disturbance to which freshwater bacterial assemblages are sensitive. The negative impacts on particle-associated bacteria, which have been shown to be more active than free-living bacteria, and the inferred shifts in functional group representation raise the possibility that IDMs may directly alter bacterially mediated ecosystem functions. IMPORTANCE Freshwater bacteria play fundamental roles in global elemental cycling and are an intrinsic part of local food webs. Human activities are altering freshwater environments, and much has been learned regarding the sensitivity of bacterial assemblages to a variety of these disturbances. Yet, relatively few studies have focused on how species invasion, which is one of the most important aspects of anthropogenic global change, affects freshwater bacterial assemblages. This study focuses on the impact of invasive dreissenid mussels (IDMs), a globally distributed group of invasive species with large impacts on freshwater phyto- and zooplankton assemblages. We show that IDMs have direct effects on lake bacterioplankton abundance, taxonomic composition, and inferred bacterial functional group representation.

Ecophysiological Examination of the Lake Erie Microcystis Bloom in 2014: Linkages between Biology and the Water Supply Shutdown of Toledo, OH.

Annual cyanobacterial blooms dominated by Microcystis have occurred in western Lake Erie (U.S./Canada) during summer months since 1995. The production of toxins by bloom-forming cyanobacteria can lead to drinking water crises, such as the one experienced by the city of Toledo in August of 2014, when the city was rendered without drinking water for >2 days. It is important to understand the conditions and environmental cues that were driving this specific bloom to provide a scientific framework for management of future bloom events. To this end, samples were collected and metatranscriptomes generated coincident with the collection of environmental metrics for eight sites located in the western basin of Lake Erie, including a station proximal to the water intake for the city of Toledo. These data were used to generate a basin-wide ecophysiological fingerprint of Lake Erie Microcystis populations in August 2014 for comparison to previous bloom communities. Our observations and analyses indicate that, at the time of sample collection, Microcystis populations were under dual nitrogen (N) and phosphorus (P) stress, as genes involved in scavenging of these nutrients were being actively transcribed. Targeted analysis of urea transport and hydrolysis suggests a potentially important role for exogenous urea as a nitrogen source during the 2014 event. Finally, simulation data suggest a wind event caused microcystin-rich water from Maumee Bay to be transported east along the southern shoreline past the Toledo water intake. Coupled with a significant cyanophage infection, these results reveal that a combination of biological and environmental factors led to the disruption of the Toledo water supply. This scenario was not atypical of reoccurring Lake Erie blooms and thus may reoccur in the future.

Are Oligotypes Meaningful Ecological and Phylogenetic Units? A Case Study of Microcystis in Freshwater Lakes.

Oligotyping is a computational method used to increase the resolution of marker gene microbiome studies. Although oligotyping can distinguish highly similar sequence variants, the resulting units are not necessarily phylogenetically and ecologically informative due to limitations of the selected marker gene. In this perspective, we examine how oligotyping data is interpreted in recent literature, and we illustrate some of the method's constraints with a case study of the harmful bloom-forming cyanobacterium Microcystis. We identified three Microcystis oligotypes from a western Lake Erie bacterial community 16S rRNA gene (V4 region) survey that had previously clustered into one OTU. We found the same three oligotypes and two additional sequence variants in 46 Microcystis cultures isolated from Michigan inland lakes spanning a trophic gradient. In Lake Erie, shifts in Microcystis oligotypes corresponded to spatial nutrient gradients and temporal transitions in bloom toxicity. In the cultures, Microcystis oligotypes showed preferential distributions for different trophic states, but genomic data revealed that the oligotypes identified in Lake Erie did not correspond to toxin gene presence. Thus, oligotypes could not be used for inferring toxic ecotypes. Most strikingly, Microcystis oligotypes were not monophyletic. Our study supports the utility of oligotyping for distinguishing sequence types along certain ecological features, while it stresses that 16S rRNA gene sequence types may not reflect ecologically or phylogenetically cohesive populations. Therefore, we recommend that studies employing oligotyping or related tools consider these caveats during data interpretation.

Cyanobacterial harmful algal blooms are a biological disturbance to Western Lake Erie bacterial communities.

Human activities are causing a global proliferation of cyanobacterial harmful algal blooms (CHABs), yet we have limited understanding of how these events affect freshwater bacterial communities. Using weekly data from western Lake Erie in 2014, we investigated how the cyanobacterial community varied over space and time, and whether the bloom affected non-cyanobacterial (nc-bacterial) diversity and composition. Cyanobacterial community composition fluctuated dynamically during the bloom, but was dominated by Microcystis and Synechococcus OTUs. The bloom's progression revealed potential impacts to nc-bacterial diversity. Nc-bacterial evenness displayed linear, unimodal, or no response to algal pigment levels, depending on the taxonomic group. In addition, the bloom coincided with a large shift in nc-bacterial community composition. These shifts could be partitioned into components predicted by pH, chlorophyll a, temperature, and water mass movements. Actinobacteria OTUs showed particularly strong correlations to bloom dynamics. AcI-C OTUs became more abundant, while acI-A and acI-B OTUs declined during the bloom, providing evidence of niche partitioning at the sub-clade level. Thus, our observations in western Lake Erie support a link between CHABs and disturbances to bacterial community diversity and composition. Additionally, the short recovery of many taxa after the bloom indicates that bacterial communities may exhibit resilience to CHABs.

Tracking cyanobacteria blooms: Do different monitoring approaches tell the same story?

Cyanobacteria blooms are a major environmental issue worldwide. Our understanding of the biophysical processes driving cyanobacterial proliferation and the ability to develop predictive models that inform resource managers and policy makers rely upon the accurate characterization of bloom dynamics. Models quantifying relationships between bloom severity and environmental drivers are often calibrated to an individual set of bloom observations, and few studies have assessed whether differences among observing platforms could lead to contrasting results in terms of relevant bloom predictors and their estimated influence on bloom severity. The aim of this study was to assess the degree of coherence of different monitoring methods in (1) capturing short- and long-term cyanobacteria bloom dynamics and (2) identifying environmental drivers associated with bloom variability. Using western Lake Erie as a case study, we applied boosted regression tree (BRT) models to long-term time series of cyanobacteria bloom estimates from multiple in-situ and remote sensing approaches to quantify the relative influence of physico-chemical and meteorological drivers on bloom variability. Results of BRT models showed remarkable consistency with known ecological requirements of cyanobacteria (e.g., nutrient loading, water temperature, and tributary discharge). However, discrepancies in inter-annual and intra-seasonal bloom dynamics across monitoring approaches led to some inconsistencies in the relative importance, shape, and sign of the modeled relationships between select environmental drivers and bloom severity. This was especially true for variables characterized by high short-term variability, such as wind forcing. These discrepancies might have implications for our understanding of the role of different environmental drivers in regulating bloom dynamics, and subsequently for the development of models capable of informing management and decision making. Our results highlight the need to develop methods to integrate multiple data sources to better characterize bloom spatio-temporal variability and improve our ability to understand and predict cyanobacteria blooms.

Challenges for mapping cyanotoxin patterns from remote sensing of cyanobacteria.

Using satellite imagery to quantify the spatial patterns of cyanobacterial toxins has several challenges. These challenges include the need for surrogate pigments - since cyanotoxins cannot be directly detected by remote sensing, the variability in the relationship between the pigments and cyanotoxins - especially microcystins (MC), and the lack of standardization of the various measurement methods. A dual-model strategy can provide an approach to address these challenges. One model uses either chlorophyll-a (Chl-a) or phycocyanin (PC) collected in situ as a surrogate to estimate the MC concentration. The other uses a remote sensing algorithm to estimate the concentration of the surrogate pigment. Where blooms are mixtures of cyanobacteria and eukaryotic algae, PC should be the preferred surrogate to Chl-a. Where cyanobacteria dominate, Chl-a is a better surrogate than PC for remote sensing. Phycocyanin is less sensitive to detection by optical remote sensing, it is less frequently measured, PC laboratory methods are still not standardized, and PC has greater intracellular variability. Either pigment should not be presumed to have a fixed relationship with MC for any water body. The MC-pigment relationship can be valid over weeks, but have considerable intra- and inter-annual variability due to changes in the amount of MC produced relative to cyanobacterial biomass. To detect pigments by satellite, three classes of algorithms (analytic, semi-analytic, and derivative) have been used. Analytical and semi-analytical algorithms are more sensitive but less robust than derivatives because they depend on accurate atmospheric correction; as a result derivatives are more commonly used. Derivatives can estimate Chl-a concentration, and research suggests they can detect and possibly quantify PC. Derivative algorithms, however, need to be standardized in order to evaluate the reproducibility of parameterizations between lakes. A strategy for producing useful estimates of microcystins from cyanobacterial biomass is described, provided cyanotoxin variability is addressed.

How many organisms are in ballast water discharge? A framework for validating and selecting compliance monitoring tools.

As regulations governing the discharge of living organisms in ships' ballast water enter into force, tools to rapidly and easily measure compliance with the discharge standards will be essential. To assess, validate, and select compliance tools, a framework-consisting of three parts-is presented: proof-of-concept, validation and verification, and final selection stages. Next, a case study describing the proof-of-concept stage is discussed. Specifically, variable fluorescence was evaluated as an approach for determining compliance with the discharge standard for living organisms ⩾10 µm and <50 µm (typically protists). Preliminary laboratory experiments were conducted, which were followed by an expert workshop to gauge the feasibility of this approach and propose hypothetical thresholds indicating when the discharge standard is undoubtedly exceeded. Subsequently, field trials were conducted to assess this approach and recommended thresholds. All results were favorable, indicating the validation and verification stages are merited to further evaluate fluorometers as compliance monitoring tools.

Record-setting algal bloom in Lake Erie caused by agricultural and meteorological trends consistent with expected future conditions.

In 2011, Lake Erie experienced the largest harmful algal bloom in its recorded history, with a peak intensity over three times greater than any previously observed bloom. Here we show that long-term trends in agricultural practices are consistent with increasing phosphorus loading to the western basin of the lake, and that these trends, coupled with meteorological conditions in spring 2011, produced record-breaking nutrient loads. An extended period of weak lake circulation then led to abnormally long residence times that incubated the bloom, and warm and quiescent conditions after bloom onset allowed algae to remain near the top of the water column and prevented flushing of nutrients from the system. We further find that all of these factors are consistent with expected future conditions. If a scientifically guided management plan to mitigate these impacts is not implemented, we can therefore expect this bloom to be a harbinger of future blooms in Lake Erie.

Spatial and temporal trends in Lake Erie hypoxia, 1987-2007.

Hypoxic conditions, defined as dissolved oxygen (DO) concentrations below 2 mg/L, are a regular summertime occurrence in Lake Erie, but the spatial extent has been poorly understood due to sparse sampling. We use geostatistical kriging and conditional realizations to provide quantitative estimates of the extent of hypoxia in the central basin of Lake Erie for August and September of 1987 to 2007, along with their associated uncertainties. The applied geostatistical approach combines the limited in situ DO measurements with auxiliary data selected using the Bayesian Information Criterion. Bathymetry and longitude are found to be highly significant in explaining the spatial distribution of DO, while satellite observations of sea surface temperature and satellite chlorophyll are not. The hypoxic extent was generally lowest in the mid-1990s, with the late 1980s (1987, 1988) and the 2000s (2003, 2005) experiencing the largest hypoxic zones. A simple exponential relationship based on the squared average measured bottom DO explains 97% of the estimated variability in the hypoxic extent. The change in the observed maximum extent between August and September is found to be sensitive to the corresponding variability in the hypolimnion thickness.

Phosphorus load estimation in the Saginaw River, MI using a Bayesian hierarchical/multilevel model.

We propose the use of Bayesian hierarchical/multilevel ratio approach to estimate the annual riverine phosphorus loads in the Saginaw River, Michigan, from 1968 to 2008. The ratio estimator is known to be an unbiased, precise approach for differing flow-concentration relationships and sampling schemes. A Bayesian model can explicitly address the uncertainty in prediction by using a posterior predictive distribution, while in comparison, a Bayesian hierarchical technique can overcome the limitation of interpreting the estimated annual loads inferred from small sample sizes by borrowing strength from the underlying population shared by the years of interest. Thus, by combining the ratio estimator with the Bayesian hierarchical modeling framework, long-term loads estimation can be addressed with explicit quantification of uncertainty. Our study results indicate a slight decrease in total phosphorus load early in the series. The estimated ratio parameter, which can be interpreted as flow-weighted concentration, shows a clearer decrease, damping the noise that yearly flow variation adds to the load. Despite the reductions, it is not likely that Saginaw Bay meets with its target phosphorus load, 440 tonnes/yr. Throughout the decades, the probabilities of the Saginaw Bay not complying with the target load are estimated as 1.00, 0.50, 0.57 and 0.36 in 1977, 1987, 1997, and 2007, respectively. We show that the Bayesian hierarchical model results in reasonable goodness-of-fits to the observations whether or not individual loads are aggregated. Also, this modeling approach can substantially reduce uncertainties associated with small sample sizes both in the estimated parameters and loads.