When can we declare a success? A Bayesian framework to assess the recovery rate of impaired freshwater ecosystems.

Evaluating the degree of improvement of an impaired freshwater ecosystem resembles the statistical null-hypothesis testing through which the prevailing conditions are compared against a reference state. The pillars of this process involve the robust delineation of what constitutes an achievable reference state; the establishment of threshold values for key environmental variables that act as proxies of the degree of system impairment; and the development of an iterative decision-making process that takes advantage of monitoring data to assess the system-restoration progress and revisit management actions accordingly. Drawing the dichotomy between impaired and non-impaired conditions is a challenging exercise that is surrounded by considerable uncertainty stemming from the variability that natural systems display over time and space, the presence of ecosystem feedback loops (e.g., internal loading) that actively influence the degree of recovery, and our knowledge gaps about biogeochemical processes directly connected to the environmental problem at hand. In this context, we reappraise the idea of probabilistic water quality criteria, whereby the compliance rule stipulates that no more than a stated number of pre-specified water quality extremes should occur within a given number of samples collected over a compliance assessment domain. Our case study is the Bay of Quinte, Ontario, Canada; an embayment lying on the northeastern end of Lake Ontario with a long history of eutrophication problems. Our study explicitly accounts for the covariance among multiple water quality variables and illustrates how we can assess the degree of improvement for a given number of violations of environmental goals and samples collected from the system. The present framework offers a robust way to impartially characterize the degree of restoration success and minimize the influence of the conflicting perspectives among decision makers/stakeholders and conscious (or unconscious) biases pertaining to water quality management.

A Bayesian risk assessment framework for microcystin violations of drinking water and recreational standards in the Bay of Quinte, Lake Ontario, Canada.

Freshwater ecosystems can experience harmful algal blooms, which negatively impact recreational uses, aesthetics, taste, and odor in drinking water. Cyanobacterial toxins can have dire repercussions on aquatic wildlife and human health, and the most ubiquitous worldwide are the hepatotoxic compounds known as microcystins. The factors that influence the occurrence and magnitude of cyanobacteria blooms and toxin production vary in space and time and remain poorly understood. It is within this context that we present a suite of statistical models, parameterized with Bayesian inference techniques, to link the retrospective analysis of important environmental factors with the probability of exceedance of threshold microcystin levels. Our modelling framework is applied to the Bay of Quinte, Lake Ontario, Canada; a system with a long history of eutrophication problems. Collectively, 16.1% of the samples of the system collected during the study period (2003-2016) exceeded the drinking water guideline of 1.5 µgL-1, while approximately 3% of recorded values exceeded the recommended recreational threshold of 20 µgL-1. Using a segmented regression model with a stochastic breakpoint of microcystin concentrations estimated at 0.54 µg L-1, we demonstrate that the environmental conditions associated with increased probability of exceedance of the drinking water standard are chlorophyll a concentration ≥7 µg L-1, water temperature ≥20 °C, ammonium concentration ≤40 µgL-1, total phosphorus concentration ≥25 µg L-1, and wind speed ≤37 km h-1. Considering the multitude of factors that can influence the ambient levels of toxins, our study argues that the adoption of probabilistic water quality criteria offers a pragmatic approach to accommodate the associated uncertainty by permitting a realistic frequency of violations. In this context, we present a framework to evaluate the confidence of compliance with probabilistic standards that stipulate less than 10% violations of microcystin threshold ambient levels.

Delineation of the role of nutrient variability and dreissenids (Mollusca, Bivalvia) on phytoplankton dynamics in the Bay of Quinte, Ontario, Canada.

The Bay of Quinte, a Z-shaped embayment at the northeastern end of Lake Ontario, has a long history of eutrophication problems primarily manifested as spatially extensive algal blooms and predominance of toxic cyanobacteria. The purpose of this study was to identify the structural changes of the phytoplankton community induced by two environmental alterations: point-source phosphorus (P) loading reduction in the late 1970s and establishment of dreissenid mussels in the mid-1990s. A combination of statistical techniques was used to draw inference about compositional shifts of the phytoplankton assemblage, the consistency of the seasonal succession patterns along with the mechanisms underlying the algal biovolume variability in the Bay of Quinte over the past three decades. Based on a number of diversity and similarity indices, the algal assemblages in the upper and middle segments of the Bay are distinctly different from those typically residing in the outer segments. Our analysis also identified significant differences among the phytoplankton communities, representing the pre- and post-P control as well as the pre- and post-dreissenid invasion periods. Recent shifts in phytoplankton community composition were mainly associated with increased frequency of occurrence of toxin-producing Microcystis outbreaks and reduced biovolume of N2 fixers, such as Aphanizomenon and Anabaena. Bayesian hierarchical models were developed to elucidate the importance of different abiotic factors (light attenuation, water temperature, phosphorus, and ammonium) on total cyanobacteria, Microcystis, Aphanizomenon, and Anabaena relative biovolume. Our modelling exercise suggests that there is significant spatial heterogeneity with respect to the role of the factors examined, and thus total phosphorus alone cannot always explain the year-to-year variability of cyanobacteria succession patterns in the system. The lessons learned from the present analysis will be helpful to the water quality criteria setting process and could influence the management decisions in order to delist the system as an Area of Concern.

Critical role of H2O2 generated by NOX4 during cellular response under glucose deprivation.

Glucose is the most efficient energy source, and various cancer cells depend on glycolysis for energy production. For maintenance of survival and proliferation, glucose sensing and adaptation to poor nutritional circumstances must be well organized in cancer cells. While the glucose sensing machinery has been well studied in yeasts, the molecular mechanism of glucose sensing in mammalian cells remains to be elucidated. We have reported glucose deprivation rapidly induces AKT phosphorylation through PI3K activation. We assumed that regulation of AKT is relevant to glucose sensing and further investigated the underlying mechanisms. In this study, AKT phosphorylation under glucose deprivation was inhibited by galactose and fructose, but induced by 2-deoxyglucose (2-DG). Both 2-DG treatment and glucose deprivation were found to induce AKT phosphorylation in HepG2 cells. These findings suggested that glucose transporter may not be involved in the sensing of glucose and induction of AKT phosphorylation, and that downstream metabolic events may have important roles. A variety of metabolic stresses reportedly induce the production of reactive oxygen species (ROS). In the present study, glucose deprivation was found to induce intracellular hydrogen peroxide (H2O2) production in HepG2 cells. N-acetylcysteine (NAC), an antioxidant reagent, reduced both the increase in cellular H2O2 levels and AKT phosphorylation induced by glucose deprivation. These results strongly suggest that the glucose deprivation-induced increase of H2O2 in the cells mediated the AKT phosphorylation. RNA interference of NOX4, but not of NOX5, completely suppressed the glucose deprivation-induced AKT phosphorylation as well as increase of the intracellular levels of ROS, whereas exogenous H2O2 could still induce AKT phosphorylation in the NOX4-knockdown cells. In this study, we demonstrated that the ROS generated by NOX4 are involved in the intracellular adaptive responses by recognizing metabolic flux.

Temporal PCB and mercury trends in Lake Erie fish communities: a dynamic linear modeling analysis.

We performed dynamic linear modeling analysis on fish contaminant data collected from the Ontario Ministry of the Environment and Environment Canada to examine long-term trends of total mercury (THg) and polychlorinated biphenyls (PCBs) in Lake Erie. Several sport fish species (walleye, smallmouth bass, rainbow trout) with differences in their diet habits, food competition strategies and foraging patterns are characterized by weakly increasing trends of their THg levels in Lake Erie after the mid- or late 1990s. Similarly, our analysis shows that the decline rates of the PCB body burdens in white bass, smallmouth bass, freshwater drum and whitefish have slowed down or have switched to weakly increasing rates over the last decade. Our analysis also provides evidence that the rainbow trout and coho salmon PCB concentrations have been decreasing steadily but the associated rates were fairly weak. The systematic shifts in energy trophodynamics along with the food web alterations induced from the introduction of non-native species, the new role of the sediments as a net contaminant source, and the potentially significant fluxes from the atmosphere stand out as some of the hypotheses proposed to explain the limited Lake Erie response in recent years to the various contamination mitigation strategies.

Detection of temporal trends of α- and γ-chlordane in Lake Erie fish communities using dynamic linear modeling.

Dynamic linear modeling (DLM) analysis was performed to identify the long-term temporal trends of two toxic components of the technical chlordane pesticide, α- and γ-chlordane, in skinless-boneless muscle tissues of a number of sport fish species in Lake Erie. Our analysis considers the fish length as a covariate of the chlordane concentrations. The α-chlordane models for the coho salmon, channel catfish, rainbow trout, and common carp showed continuously decreasing trends during the entire 30+ year survey period (1976-2007). The γ-chlordane models demonstrated similar trends for the coho salmon, channel catfish, and common carp. These fish species had higher levels of α- and γ-chlordane in their muscle tissues. The α- and γ-chlordane levels in freshwater drum, smallmouth bass, walleye, white bass, whitefish, and yellow perch decreased until the mid-1980s and hovered at levels around the detection limits for the remaining period. The pesticide biotransformation process, the reduction of contaminant emissions to the environment, the feeding habits of the different fish species, and the food-web alterations induced by the introduction of aquatic invasive species are some of the hypotheses proposed to explain the observed temporal trends in different fish species in Lake Erie.