Rare earth elements accumulation and patterns in abiotic and biotic compartments of a large river system influenced by natural and anthropogenic sources in Eastern Canada
Bibliographic record
Abstract
The mobilization of rare earth elements (REEs) in aquatic ecosystems is expected to rise significantly due to intensified exploitation, erosion, and climate change . As a result, more attention has been brought to study their environmental fate . However, our ability to assess contamination risks in freshwater organisms remains limited due to scarce data on the composition and accumulation of REEs. Understanding how organisms bioaccumulate REEs requires knowledge of their environmental conditions, exposure pathways, and ecological characteristics—areas few studies have explored. In this study, we examined the fate of REEs across abiotic (water, suspended sediments , and sediments) and biotic (invertebrates and fishes) compartments in the St. Lawrence River (Canada), identifying the main drivers of their accumulation and relative composition. The results were consistent with REE biodilution along the food chain, with concentrations greater in suspended (REEs = 76.1–241.4 μg g −1 ) and bulk sediments (REEs = 4.2–204.2 μg g −1 ). Higher concentrations were found in fine-grained sediments, with a relative enrichment in middle REEs, likely due to REE adsorption onto Fe- or Mn-bearing minerals. Nonpredatory invertebrates ingesting suspended sediments , such as Ephemeroptera and Diptera larvae, exhibited higher concentrations of REEs than both filter-feeding species (i.e., mussels, polychaetes) and fish. Additionally, some amphipods displayed anomalous concentrations of gadolinium (Gd/Gd∗ = 5.7, 2.6, and 2.0), possibly originating from anthropogenic activities near Montreal Island. While fish bioaccumulated only light REEs in their liver, multiple regression models revealed how their length and the concentration of REEs in surrounding water—in dissolved form or as free ions—influenced their concentrations. Finally, benthivorous species like Moxostoma spp. and Ictalurus punctatus accumulated more REEs compared to piscivorous Sander spp., reflecting differences in feeding behavior and trophic level . Overall, these findings provide insights into how REE concentrations and compositions varied among organisms, likely due to differences in environmental conditions and ecological characteristics.
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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 | 0.000 | 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 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".