Characterizing polychlorinated biphenyl exposure pathways from sediment and water in aquatic life using a food web bioaccumulation model
Bibliographic record
Abstract
Contaminant remediation decisions often focus on sediment-organism relationships, omitting the partitioning between sediment and water that exists across a given site. The present study highlights the importance of incorporating nonsedimentary routes of exposure into a nonequilibrium, steady-state food web bioaccumulation model for predicting polychlorinated biphenyl (PCB) concentrations in benthic invertebrates. Specifically, we examined the proportion of overlying water relative to the sediment porewater respired by benthic invertebrates, which has been used in previous studies to examine contaminant bioaccumulation. We evaluated the model accuracy using paired benthos-sediment samples and an extensive fish contamination database to ensure realistic predictions at the base of the Detroit River (Ontario, Canada, and Michigan, USA) food web. The results demonstrate that, compared with empirical regression analyses, the food web bioaccumulation model provided satisfactory estimates of PCB bioaccumulation for benthos simulations and better estimates for fish simulations. Our results showed that PCB bioaccumulation measurements are significantly affected by variations in pollutant uptake and elimination routes via the overlying water, which in turn are affected by the degree of disequilibrium of PCBs between sediments and water. Interestingly, we obtained contrasting results regarding the effectiveness of remediation strategies for reducing the contaminant burden of the aquatic biota based on different proportions of overlying water relative to porewater. These differences could consequently impact decisions about the approaches for source control and strategic sediment remediation. This study suggests that bioaccumulation assessments could be improved through better identification of chemical uptake-elimination routes in benthos and by accounting for chemical bioavailability in sediment and water components in areas with disequilibrium.Integr Environ Assess Manag 2019;00:000-000. © 2019 SETAC.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".