Chronic bioaccumulation and toxicity of cadmium from a periphyton diet to Hyalella azteca
Bibliographic record
Abstract
Dietary cadmium (Cd) can contribute significantly to chronic bioaccumulation and toxicity in aquatic organisms. This contribution needs to be quantified so that the relative importance of waterborne and dietary cadmium exposure pathways can be incorporated into protective water quality guidelines and ecological risk assessments. \n \nIn this research, the contribution of dietary Cd from a natural periphyton diet to chronic (28 d) bioaccumulation and toxicity in the freshwater amphipod Hyalella azteca was quantified using a mechanistically-based saturation bioaccumulation model. Factors that influence dietary Cd bioavailability such as food type, food form, dietary Cd speciation and concentration were investigated. Assimilation efficiency, ingestion rate and the excretion rate constant of dietary Cd were determined for each of these factors. Food nutrition was also considered. Lastly, model predictions of Cd bioaccumulation and toxicity were compared to measurements of tissue concentration and survival when H. azteca were exposed to metal contaminated water and periphyton collected from lakes in the metal mining region of Rouyn-Noranda, Quebec, Canada. \n \nIn 28 d laboratory experiments where H. azteca bioaccumulated Cd from water and food, dietary Cd was estimated to contribute markedly (21 – 94 %) to bioaccumulated Cd in H. azteca. Effects on chronic survival were best predicted from body concentration rather than water or food exposure concentration. Assimilation efficiency of dietary Cd differed with food type likely as a result of Cd speciation, but did not differ with Cd concentration or food form. Ingestion rate differed with food form while excretion rate constants were unaffected by dietary Cd bioavailability. Predictions of chronic Cd bioaccumulation in H. azteca exposed to field contaminated samples were robust, however the model did not account for effects of water chemistry on Cd bioaccumulation and is thus constrained in its application. Predictions of chronic survival were over-estimated likely due to the additional toxicity caused by the low nutritional quality of the field contaminated periphyton. This research demonstrated that both waterborne and dietary Cd need to be considered in models that assess chronic risk of exposure and effects to H. azteca.
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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 | 0.000 | 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".