Bioaccumulation of Persistent Organic Pollutants in Lichen−Caribou−Wolf Food Chains of Canada's Central and Western Arctic
Bibliographic record
Abstract
While biomagnification of persistent organic pollutants (POPs) in aquatic food chains is well documented, there have been few investigations of the trophodynamics of POPs in Arctic terrestrial food chains. This study presents field-collected concentration data and corresponding fugacities of various hydrophobic organic chemicals (ranging in octanol-water partition coefficients or K(OW) from approximately 10(3.8) to 10(9)) in two lichen species (Cladina rangiferina and Cetraria nivalis), willow leaves (Salix glauca), barren-ground caribou (Rangifer tarandus), and wolves (Canis lupus) from Canada's Central and Western Arctic region. The results show that, in contrast to aquatic food chains, persistent substances including beta-hexachlorocyclohexane and 1,2,4,5-tetrachlorobenzene with a K(OW) <10(5) can substantially biomagnify in lichen-caribou-wolf food chains in Canada's Central and Western Arctic. Strong positive correlations between the biomagnification factor and the octanol-air partition coefficients (K(OA)) of nonmetabolizable compounds were observed in wolves. In caribou, the biomagnification factors dropped slightly with increasing K(OA). K(OA) proved to be a better indicator of biomagnification than K(OW). Current management policies that consider only chemicals with K(OW) values >10(5) as bioaccumulative substances fail to identify substances that have the potential to biomagnify in Arctic terrestrial food chains despite a low K(OW) because of a high K(OA).
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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 | 0.001 | 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".