Yuko Shimoda

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.

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.

Integration of best management practices in the Bay of Quinte watershed with the phosphorus dynamics in the receiving waterbody: What do the models predict?

We present a modelling analysis of the management practices that could lead to significant reduction of phosphorus export from the Bay of Quinte watershed and an evaluation of the overall uncertainty associated with the assessment of the Beneficial Use Impairment Eutrophication and Undesirable Algae. Our work highlights the internal recycling as one of the key drivers of phosphorus dynamics in the Bay. The flow from the Trent River is the predominant driver of the upper Bay dynamics until the main stem of the middle area however, the sediments in the same segment release a significant amount of phosphorus and the corresponding fluxes are likely amplified by the macrophyte and dreissenid activity. From a management standpoint, the presence of a significant positive feedback loop in the upper Bay suggests that the anticipated benefits of additional reductions of the exogenous point and non-point loading may not be realized within a reasonable time frame (i.e. 5—10 years). Our analysis of nutrient loading scenarios shows that the restoration pace of the Bay could be slow, even if the riverine total phosphorus concentrations reach levels significantly lower than their contemporary values, <25 µg TP l−1. We believe that the on-going management decisions, monitoring, and modelling should also explicitly consider the role and broader ramifications of internal phosphorus loading into the system. The anticipated lessons from such a multi-faceted exercise are a unique aspect of the Bay of Quinte ecosystem because of the long history of research and monitoring data. This study can produce transferable knowledge to other systems worldwide, experiencing similar hysteresis patterns associated with internal nutrient loading.

Integrating hierarchical Bayes with phosphorus loading modelling

Abstract The causal linkage between lake productivity and phosphorus loading has provided the basis for a family of models that predict lake total phosphorus concentrations as a function of lake morphometric/hydraulic characteristics, such as the areal phosphorus loading rate, mean lake depth, fractional phosphorus retention and areal hydraulic loading. Most of these empirical models have been derived from “cross-sectional” datasets, comprising multiple point measurements or single averages from a number of lakes, and are typically used to predict changes within a single system at different points in time. This practice implicitly postulates that the large scale (cross-sectional) patterns described in the model are also representative of the dynamics of individual systems. In this study, we relax this assumption using a Bayesian hierarchical strategy that aims to accommodate the role of significant sources of variability (morphology, hydraulic regime). We first examine several hierarchical structures representing different characterizations of model error, parameter covariance, and prior distribution followed by the hyperparameters. Our analysis primarily highlights the robustness of the posterior group-level patterns to the hierarchical formulation developed. We also show that the delineation of homogeneous subsets of lakes with respect to their morphological/hydraulic characteristics and the subsequent integration with hierarchical frameworks may give empirical phosphorus retention/loading models with better predictive ability. We then present a complementary exercise that aims to accommodate the spatial and seasonal total phosphorus variability within individual systems, using a spatially-explicit simple mass-balance model forced with idealized sinusoidal loading. Our study concludes by advocating that the hierarchical Bayes provides a conceptually appealing framework to gradually accommodate different sources of variability and more prudently increase the complexity of simple empirical models.

Optimizing the complexity of phytoplankton functional group modeling: An allometric approach

Abstract Elucidating patterns and mechanisms that shape phytoplankton assemblages is a popular area of research for empirical and theoretical ecologists. Despite the daunting complexity of phytoplankton dynamics, much of our current understanding has been based on simple models describing food-web interactions with few differential equations. Skeptical views in the literature raise concerns about the increasing model complexity and advice to seek parsimony rather than simplicity. To address this controversy (simple versus complex models), we propose the introduction of an extra layer of causality into plankton models by connecting algal processes (maximum growth rates, nutrient kinetics, settling velocities, metabolic rates) with species-specific morphological features (cell volume, surface-to-volume ratio, shape). In this study, we demonstrate the capacity of a size-based plankton model to reproduce observed water quality patterns (phosphate, total phosphorus, nitrate, total ammonia, total nitrogen, chlorophyll a, and total zooplankton biomass) in the Hamilton Harbour, Ontario. Consistent with empirical evidence, our modeling analysis showed that small algal species have a distinct competitive advantage in summer epilimnetic environments across the range of cell volume and nutrient loading conditions examined; especially, when they are characterized by higher optimal temperature for growth. Strong top-down pressure mediated by high zooplankton abundance effectively controls the standing biomass of phytoplankton species that can otherwise realize high growth rates under the conditions typically prevailing in the end-of-summer epilimnetic environments (e.g., higher temperature optima, higher tolerance in low water clarity). Under high zooplankton control, the secondary variations of phytoplankton are modulated by the ambient phosphorus levels and the size-based strategies for resources procurement, such as the regulation of nutrient transport kinetics. By contrast, when the summer algal assemblage is released by the zooplankton grazing, the exceedance of critical phytoplankton biomass levels and the likelihood of harmful algal blooms are determined by the multitude of factors that shape inter-specific competition patterns (e.g., relative abundance of competing species, nutrient uptake kinetics). Our study evaluates the strengths and weaknesses of this approach and identifies future directions that would provide operational models founded upon concepts of allometry.