Experimental testing of two urban stressors on freshwater biofilms
Bibliographic record
Abstract
Abstract Aquatic ecosystems and their communities are exposed to numerous stressors of various natures (chemical and physical), which impacts are often poorly documented. In urban areas, the use of biocides such as dodecyldimethylbenzylammonium chloride (DDBAC) and their subsequent release in wastewater result in their transfer to urban aquatic ecosystems. DDBAC is known to be toxic to most aquatic organisms. Artificial light at night (ALAN) is another stressor that is increasing globally, especially in urban areas. ALAN may have a negative impact on photosynthetic cycles of periphytic biofilms, which in turn may result in changes in their metabolic functioning. Moreover, studies suggest that exposure to artificial light could increase the biocidal effect of DDBAC on biofilms. The present study investigates the individual and combined effects of DDBAC and/or ALAN on the functioning and structure of photosynthetic biofilms. We exposed biofilms in artificial channels to a nominal concentration of 30 mg.L -1 of DDBAC and/or ALAN for 10 days. ALAN modified DDBAC exposure, decreasing concentrations in the water but not accumulation in biofilms. DDBAC had negative impacts on biofilm functioning and structure. Photosynthetic activity was inhibited by > 90% after 2 days of exposure, compared to the controls, and did not recover over the duration of the experiment. Biofilm composition was also impacted, with a marked decrease in green algae and the disappearance of microfauna under DDBAC exposure. The integrity of algal cells was compromised where DDBAC exposure altered the chloroplasts and chlorophyll content. Impacts on autotrophs were also observed through a shift in lipid profiles, in particular a strong decrease in glycolipid content was noted. We found no significant interactive effect of ALAN and DDBAC on the studied endpoints. Graphical abstract
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".