A Bayesian assessment of the mercury and PCB temporal trends in lake trout (Salvelinus namaycush) and walleye (Sander vitreus) from lake Ontario, Ontario, Canada

Visha, Ariola; Gandhi, Nilima; Bhavsar, Satyendra P.; Arhonditsis, George B.

doi:10.1016/j.ecoenv.2015.03.022

Cited by 27 publications

(11 citation statements)

References 64 publications

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“…deviance

= - 2 log [likelihood] false)

with uncertainty of the year‐specific estimates of the stochastic nodes (such as regression coefficients, rates of change, fish biomass corrected for the TP variability) as well as the error terms. Specifically, we selected the discount factor that resulted in the highest model performance, while ensuring the highest degree of identification, as expressed by the coefficient‐of‐variation values of the dynamic model parameters (Visha, Gandhi, Bhavsar, & Arhonditsis, ). A discount factor of 0.95 stipulates that the precision of each stochastic node within a given year is reduced by 5% relative to the precision assigned to the same parameter for the previous time step.…”

Section: Methodsmentioning

confidence: 99%

Nutrient management and structural shifts in fish assemblages: Lessons learned from an Area of Concern in Lake Ontario

et al. 2019

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While total phosphorus (TP) is a critical determinant of freshwater ecosystem productivity, multiple stressors can induce shifts in energy pathways, with profound implications for ecosystem and fishery restoration. The Bay of Quinte (Lake Ontario, Canada) is a Great Lakes nearshore ecosystem that has been historically subjected to a variety of environmental perturbations: cultural eutrophication, low dissolved oxygen, reduced fisheries, climatic extremes, phosphorus (P) abatement, and aquatic invasive species. We used the Bay of Quinte to study how trophic state alterations affect fish assemblages in Great Lakes nearshore environments by examining the response of fish biomass to TP concentration variability in the presence of multiple stressors. Our analysis is based on a 42‐year (1972–2013) dataset from the Bay of Quinte for water quality through the food web to fishes. We employed a series of statistical tools that can offer insights into the structural changes induced by the events examined. We first used dynamic linear modelling to detect temporal trends in fish biomass, while accounting for year‐to‐year TP variability over three spatial segments of the bay. We then developed piecewise regression models to assess the extent to which specific ecological events induced distinct shifts in the fish assemblage. Multiple regression modelling was used to quantify the relative importance of TP, zooplankton, and surface water temperature on fish biomass. Based on gillnets, there were consistent fish biomass changes across the bay with increased biomass before P control (1972–1977), declines after P control followed by the establishment of a steady state or modest increase (1978–1994), and a declining trajectory during the recent period (1995–2013). Even when accounting for the role of water temperature and zooplankton, TP still had a significant effect on fish biomass. However, the strength and nature of the relationship varied among fish groups, and overall, the effect of TP on fish biomass has weakened in recent years. Our models show that fish biomass in the Bay of Quinte is shaped by the year‐to‐year TP variability. However, the relationship between P and fish abundance has been modulated by various ecological events with the consequence that the Bay of Quinte fish assemblage has changed and the food web now produces less fish biomass per unit of TP. A projected reduction of mean ambient TP levels from 30 to 25 μg/L, is expected to induce a 24% decline in total fish biomass, and further shift the fish assemblage with the biomass of planktivores and walleye declining by >60% and 30%, respectively. Recreational fishing provides important economic benefits in the Bay of Quinte, through tourism and other local business operations. Recognising the economic importance of fishing, our analysis provides critical insights regarding the on‐going management efforts to reduce external nutrient loadings (point and non‐point sources, urban storm water) and further lower ambient TP levels and primary productivity. The...

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“…deviance

= - 2 log [likelihood] false)

Section: Methodsmentioning

confidence: 99%

Nutrient management and structural shifts in fish assemblages: Lessons learned from an Area of Concern in Lake Ontario

et al. 2019

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“…Although lipid concentration tends to show a positive correlation with PCB concentration, lipid concentration does not control PCB accumulation in fish [35–39]. Rather, food consumption controls PCB accumulation in fish.…”

Section: Sex Difference In Pcb Concentrationsmentioning

confidence: 99%

Sex differences in contaminant concentrations of fish: a synthesis

et al. 2016

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A comparison of whole-fish polychlorinated biphenyl (PCB) and total mercury (Hg) concentrations in mature males with those in mature females may provide insights into sex differences in behavior, metabolism, and other physiological processes. In eight species of fish, we observed that males exceeded females in whole-fish PCB concentration by 17 to 43 %. Based on results from hypothesis testing, we concluded that these sex differences were most likely primarily driven by a higher rate of energy expenditure, stemming from higher resting metabolic rate (or standard metabolic rate (SMR)) and higher swimming activity, in males compared with females. A higher rate of energy expenditure led to a higher rate of food consumption, which, in turn, resulted in a higher rate of PCB accumulation. For two fish species, the growth dilution effect also made a substantial contribution to the sex difference in PCB concentrations, although the higher energy expenditure rate for males was still the primary driver. Hg concentration data were available for five of the eight species. For four of these five species, the ratio of PCB concentration in males to PCB concentration in females was substantially greater than the ratio of Hg concentration in males to Hg concentration in females. In sea lamprey (Petromyzon marinus), a very primitive fish, the two ratios were nearly identical. The most plausible explanation for this pattern was that certain androgens, such as testosterone and 11-ketotestosterone, enhanced Hg-elimination rate in males. In contrast, long-term elimination of PCBs is negligible for both sexes. According to this explanation, males not only ingest Hg at a higher rate than females but also eliminate Hg at a higher rate than females, in fish species other than sea lamprey. Male sea lamprey do not possess either of the above-specified androgens. These apparent sex differences in SMRs, activities, and Hg-elimination rates in teleost fishes may also apply, to some degree, to higher vertebrates including humans. Our synthesis findings will be useful in (1) developing sex-specific bioenergetics models for fish, (2) developing sex-specific risk assessment models for exposure of humans and wildlife to contaminants, and (3) refining Hg mass balance models for fish and higher vertebrates.

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“…According to this guidance (European Commission ), the comparability of data across member states within the European Union would be achieved by adjusting the biota‐monitoring results to a standard TL, that is, TL 4 for continental water bodies, and to a standard lipid content (5% or 0.05) or a standard dry weight (dw) content (26% or 0.26), by use of the following equations:

true[C_{a d j - T L, n o r m} true] = true[C_{m e a s} true] \times T M F^{(4 - normalT normalL (x))} \times 0.05 / l i p i d

true[C_{a d j - T L, n o r m} true] = true[C_{m e a s} true] \times T M F^{(4 - normalT normalL (x))} \times 0.26 / d w

where C adj−TL,norm is the contaminant concentration adjusted to TL and lipid content (Equation ) (μg/kg‐lipid) or dry weight (Equation ) (μg/kg‐dw) basis, C meas is the measured, nonnormalized contaminant concentration (μg/kg‐ww), and TL , lipid , and dw are the TL (based on expert knowledge, available databases, or stable isotope data [see below]), lipid content, and dry mass of the monitored species, respectively. The Equation variant is proposed for contaminants for which accumulation is not influenced by the organism's lipid content, such as PFOS (Jones et al ) or Hg (Visha et al ).…”

Section: Introductionmentioning

confidence: 99%

Practical advice for selecting or determining trophic magnification factors for application under the European Union Water Framework Directive

Kidd

Burkhard

Babut

et al. 2018

Integr Envir Assess & Manag

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European Union Directive 2013/39/EU, which amended and updated the Water Framework Directive (WFD; 2000/60/EC) and its daughter directive (2008/105/EC), sets Environmental Quality Standards for biota (EQS biota ) for a number of bioaccumulative chemicals. These chemicals pose a threat to both aquatic wildlife and human health via the consumption of contaminated prey or the intake of contaminated food originating from the aquatic environment. EU member states will need to establish programs to monitor the concentration of 11 priority substances in biota and assess compliance against these new standards for the classification of surface water bodies. An EU-wide guidance effectively addresses the implementation of EQS biota . Flexibility is allowed in the choice of target species used for monitoring to account for both diversity of habitats and aquatic community composition across Europe. According to that guidance, the consistency and comparability of monitoring data across member states should be enhanced by adjusting the data on biota contaminant concentrations to a standard trophic level by use of the appropriate trophic magnification factor (TMF), a metric of contaminant biomagnification through the food web. In this context, the selection of a TMF value for a given substance is a critical issue, because this field-derived measure of trophic magnification can show variability related to the characteristics of ecosystems, the biology and ecology of organisms, the experimental design, and the statistical methods used for TMF calculation. This paper provides general practical advice and guidance for the selection or determination of TMFs for reliable application within the context of the WFD (i.e., adjustment of monitoring data and EQS derivation). Based on a series of quality attributes for TMFs, a decision tree is presented to help end users select a reasonable and relevant TMF. Integr Environ Assess Manag 2019;15:266-277. C

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A Bayesian assessment of the mercury and PCB temporal trends in lake trout (Salvelinus namaycush) and walleye (Sander vitreus) from lake Ontario, Ontario, Canada

Cited by 27 publications

References 64 publications

Nutrient management and structural shifts in fish assemblages: Lessons learned from an Area of Concern in Lake Ontario

Nutrient management and structural shifts in fish assemblages: Lessons learned from an Area of Concern in Lake Ontario

Sex differences in contaminant concentrations of fish: a synthesis

Practical advice for selecting or determining trophic magnification factors for application under the European Union Water Framework Directive

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