Assessing the chronic effect of the bioavailable fractions of radionuclides and heavy metals on stream microbial communities: A case study at the Rophin mining site
Bibliographic record
Abstract
This study aimed to assess the potential impact of long-term chronic exposure (69 years) to naturally-occurring radionuclides (RNs) and heavy metals on microbial communities in sediment from a stream flowing through a watershed impacted by an ancient mining site (Rophin, France). Four sediment samples were collected along a radioactivity gradient (for 238U368 to 1710 Bq.Kg−1) characterized for the presence of the bioavailable fractions of radionuclides (226Ra, 210Po), and trace metal elements (Th, U, As, Pb, Cu, Zn, Fe). Results revealed that the available fraction of contaminants was significant although it varied considerably from one element to another (0 % for As and Th, 5–59 % for U). Nonetheless, microbial communities appeared significantly affected by such chronic exposure to (radio)toxicities. Several microbial functions carried by bacteria and related with carbon and nitrogen cycling have been impaired. The high values of fungal diversity and richness observed with increasing downstream contamination (H′ = 4.4 and Chao1 = 863) suggest that the community had likely shifted toward a more adapted/tolerant one as evidenced, for example, by the presence of the species Thelephora sp. and Tomentella sp. The bacterial composition was also affected by the contaminants with enrichment in Myxococcales, Acidovorax or Nostocales at the most contaminated points. Changes in microbial composition and functional structure were directly related to radionuclide and heavy metal contaminations, but also to organic matter which also significantly affected, directly or indirectly, bacterial and fungal compositions. Although it was not possible to distinguish the specific effects of RNs from heavy metals on microbial communities, it is essential to continue studies considering the available fraction of elements, which is the only one able to interact with microorganisms.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".