Rare earth elements (REE) in freshwater, marine, and terrestrial ecosystems in the eastern Canadian Arctic
Bibliographic record
Abstract
ABSTRACT Few ecotoxicological studies exist for rare earth elements (REEs), particularly field-based studies on their bioaccumulation and food web dynamics. REE mining has led to significant environment impacts in several countries (China, Brazil, U.S.), yet little is known about the fate and transport of these contaminants of emerging concern. To understand how REEs behave in pristine northern food webs, we measured REE concentrations and carbon and nitrogen stable isotope ratios (∂ 15 N, ∂ 13 C) in biota from marine, freshwater, and terrestrial ecosystems of the eastern Canadian Arctic (N=339). Northern ecosystems are potentially vulnerable to REE enrichment from prospective mining projects at high latitudes. Wildlife harvesting and tissue sampling was partly conducted by local hunters through a community-based monitoring project. Results show that REE generally follow a coherent bioaccumulation pattern for sample tissues, with some anomalies for redox-sensitive elements (Ce, Eu). Highest REE concentrations were found at low trophic levels, especially in vegetation and aquatic invertebrates. Terrestrial herbivores, ringed seal, and fish had low REE levels in muscle tissue (<0.1 nmolg -1 ), yet accumulation was an order of magnitude higher in all liver tissues. Age- and length-dependent REE accumulation also suggest that REE uptake is faster than elimination for some species. Overall, REE bioaccumulation patterns appear to be species- and tissue-species, with limited potential for biomagnification. This study provides novel ecotoxicological data on the behaviour of REE in ecosystems and will be useful for environmental impact assessment of REE enrichment in northern regions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".