Impact of Zirconium on Freshwater Periphytic Microorganisms
Bibliographic record
Abstract
The majority of studies on biofilms have focused on autotrophic and bacterial taxa, without considering the potential effects on biofilm grazers. In this work, we investigated the effects of realistic environmental concentrations of zirconium (Zr) on periphyton algal growth and micromeiofauna biodiversity. Glass slides were submerged in a pond for four weeks to colonize biofilms and exposed for four weeks in aquaria to targeted Zr concentrations of 0, 1, and 10 nM, which were monitored over time (average measured concentrations were 0.2 ± 0.1, 0.5 ± 0.3, and 2.9 ± 0.3 nM Zr). The four-week exposure to the highest concentration (3 nM) affected the micromeiofauna structure of biofilms and modified the autotrophic biofilm structure by increasing the proportion of green algae and decreasing the abundance of cyanobacteria and brown algae. Rotifers and the ciliate Aspidisca cicada appeared to be the most sensitive organisms among the observed micromeiofauna. A toxic effect of Zr on rotifers could explain such results. Indirect effects, such as reduced food availability given the reduced algal growth in the presence of Zr, could also play a role in the changes of micromeiofauna community structure. These results are among the few published data on the effects of Zr.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 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".