Relationships among total recoverable and reactive metals and metalloid in St. Lawrence River sediment: Bioaccumulation by chironomids and implications for ecological risk assessment
Bibliographic record
Abstract
The availability and bioaccumulation of metals and metalloids, and the geochemical interactions among them, are essential to developing an ecological risk assessment (ERA) framework and determining threshold concentrations for these elements. The purpose of this study was to explore the relationships among total recoverable and reactivemetals andmetalloid in sediment and their bioaccumulation by chironomids. In the fall of 2004 and 2005, 58 stations located in the\nthree fluvial lakes of the St. Lawrence River and its largest harbour area in Montreal,Canada, were sampled. Nine total recoverable and reactivemetals (Al, Cd, Cr, Cu, Fe, Mn,Ni, Pb and Zn) and one metalloid (As) were measured in whole sediment using two extraction methods: HCl/HNO3 and HCl 1N, respectively. The bioaccumulation of six metals (Cd, Cr, Cu, Ni, Pb and Zn) and As by chironomidswas evaluated ina subset of 22 stations. Strong collinearitieswere observed between some total recoverable or reactive metal concentrations in sediment; two principal clusters, including collinear metals, were obtained. The first one included metals of mainly geological origin (Al, Cr, Fe, Mn,Ni),while the second one included As, Cd, Cu, Pb and Zn,which likely derive mainly from point sources of anthropogenic contamination. Each element also showed strong collinearity between their total recoverable and reactive forms (0.65≤r≤0.97). We can conclude that both chemical forms are equivalent for use in statistical models needed to explain biological responses and also in screening risk assessment. However, these relationships are not always proportional. Lower availability percentages were observed for Cd,Cu and Zn in the highly mixed contaminated area of the Montreal Harbour, even though concentrations in sediment were higher. We observed a significant correlation (0.50≤r≤0.56) between concentrations in chironomids and concentrations of both total recoverable and reactive Cr and Pb in sediment. Arsenic was an exception, with accumulation by chironomids being highly related to reactive sediment concentrations. Finally, we observed variable influences of explanatory factors (e.g. sediment grain size, Al, Fe, Mn, S, TOC), depending on which metal or metalloid was being predicted in chironomids. In this context, it is difficult to choose a universal predictivemethod to explain the bioaccumulation of specific metals, and more research is still needed into normalization procedures that consider a combination of explanatory factors.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 source (direct Gemma or distilled Codex), 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".