Selenium Distribution and Trophic Transfer in the Periphyton–Benthic Macroinvertebrate Food Chain in Boreal Lakes Downstream from a Milling Operation
Bibliographic record
Abstract
Selenium (Se) is an essential micronutrient with a narrow essentiality-toxicity range known to bioaccumulate in aquatic food webs. Selenium uptake and trophic transfer at the base of aquatic food chains represent a great source of uncertainty for Se risk assessment. The goal of the present study was to investigate Se distribution in water and sediment and its subsequent transfer into the periphyton-benthic macroinvertebrate (BMI) food chain in boreal lakes downstream from a Saskatchewan uranium mill. In particular, the present study aimed to assess potential differences in Se bioaccumulation patterns by BMI taxa to contribute to the current knowledge gap. During summer 2018 and 2019, water, sediment, periphyton, and BMI were sampled at two sites in Vulture Lake, seven sites in McClean Lake east basin, and one reference site in McClean Lake west basin. Periphyton and BMI taxa were sampled with artificial substrates (Hester-Dendy) deployed for 5 weeks in 2018 and 7 weeks in 2019; BMI were sorted into the lowest practical achievable taxonomic level and analyzed for total Se concentrations. At the diluted effluent exposure sites, Se concentrations in BMI ranged from 1.3 to 18.0 µg/g dry weight and from 0.3 to 49.3 µg/g dry weight in 2018 and 2019, respectively, whereas concentrations ranged from 0.01 to 3.5 µg/g dry weight at the reference site. Selenium concentrations in periphyton and some BMI taxa sampled near the effluent diffuser (Se < 1 µg/L) reached levels comparable to higher effluent exposure sites (Se > 2 µg/L). Despite differences in Se bioaccumulation among BMI taxa, an approximately one-to-one trophic transfer ratio was observed for benthic primary consumers and benthic predatory taxa. Environ Toxicol Chem 2022;41:2181-2192. © 2022 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 | 0.001 | 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".