Bioaccumulation and differential partitioning of polychlorinated biphenyls in freshwater, planktonic food webs
Bibliographic record
Abstract
The planktonic food chain phytoplankton - zooplankton - young-of-the-year roach (Rutilus rutilus) was studied in 19 lakes in southern Sweden to investigate the bioaccumulation of polychlorinated biphenyls (PCBs). The ΣPCB concentrations did not steadily increase with increasing trophic level. The ΣPCB concentrations in zooplankton (400 ng·g lipid-1) were lower than in both phytoplankton (660 ng·g lipid-1) and fish (890 ng·g lipid-1), which did not differ significantly. Lipid content explained 40% of the total variation in dry weight normalised ΣPCB concentrations in the samples. The PCBs were differentially partitioned between the trophic levels. The logBMFs (biomagnification factors, concentration in predator/concentration in prey) were a function of the logKowof the PCB congeners. The logBMFzoo/phytovalues were < 0 for all PCB congeners on a lipid weight basis, and the logBMFfish/zoovalues were < 0 for PCB congeners with logKow> 6. We conclude that no PCBs had higher lipid-normalised concentrations in zooplankton than in phytoplankton and the most lipophilic PCBs had moderately higher concentrations in roach than in zooplankton. PCBs with logKow> 6 decreased in concentration from phytoplankton to zooplankton to roach. We suggest that the concept of biomagnification did not apply to the planktonic food chain investigated in these lakes.
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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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".