Persistent organic pollutants in river food webs: influence of trophic position and degree of heterotrophy
Bibliographic record
Abstract
We investigated how the degree of autotrophy/heterotrophy and organism trophic position influenced the bioaccumulation of polychlorinated biphenyls (PCBs) in 10 benthic river food webs consisting of terrestrial detritus, periphyton, invertebrates, and age-0 brown trout (Salmo trutta) in southern Sweden. Concentrations of PCBs increased with trophic position, estimated from δ15N and δ13C, on a dry weight basis (ng·g1 dry weight) but not on a lipid weight basis (ng·g1 lipid). PCB biomagnification factors between the first and second trophic levels (invertebrates/ periphyton and invertebrates/detritus) ranged between 0.3 and 2.3 and between the second and third levels (trout/invertebrates) between 0.3 and 2.0 on a lipid weight basis. The mean proportion of carbon ultimately derived from terrestrial sources, α, was 0.82 ± 0.19 for invertebrates and 0.67 ± 0.28 for trout. Contrary to our hypothesis, PCB concentrations in trout were positively related to α (r2 = 0.580.77, p < 0.05). As α and the periphyton density (g C·m2) in the rivers was positively related (r2 = 0.88, p < 0.01), we propose that this relationship was due to an increased retention and exposure of PCBs to trout in rivers with low grazing pressure and high periphyton density.
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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 | 0.001 |
| 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 | 0.001 | 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".