Influence of Feeding Ecology on Legacy Organochlorine Contaminants in Freshwater Fishes of Lake Erie
Bibliographic record
Abstract
Abstract Persistent organic pollutants (POPs) in biota are influenced by ecological, physiological, and physicochemical properties; however, there is a need for a better understanding about the interplay of these parameters on POP dynamics and fate. To address this, POPs in three Lake Erie freshwater fishes (freshwater drum, Aplodinotus grunniens; walleye, Sander vitreus; and white perch, Morone americana) with different feeding ecologies were assessed using life history characteristics and three stable isotopes (δ13C, δ15N, and δ34S). Lipid normalized POP concentrations were in the range of past studies and were generally similar among the three species when all ages were combined. Principal component analysis (PCA) found the two significant PCs (explaining 59% and 10% of the variation), with all POPs loading significantly onto PC1, which indicated a common source of contamination, likely legacy sediment loads. Loadings on both PCs were correlated with POP log KOW. Age, habitat use (δ13C and δ34S), trophic position (δ15N) and interactions between age and δ15N, age and species, and δ15N and δ34S were significant predictors of POP concentration based on PC1 scores, whereas δ13C and species were significant predictors of PC2 scores. The similar concentrations among the species, yet variation related to the ecology (age and trophic position) across individuals demonstrates the complexity of contaminant dynamics in freshwater fish in a large lake system and the need to consider variation across individuals within species. Environ Toxicol Chem 2021;40:3421–3433. © 2021 SETAC
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".