Effects of silver nanoparticles on bacterioplankton in a boreal lake
Bibliographic record
Abstract
Summary Silver nanoparticles (Ag NP s) are widely used antimicrobial agents and a growing body of evidence suggests that their release into aquatic environments threatens natural bacterial communities and whole ecosystems. However, a knowledge gap exists between the toxic effects of Ag NP s found in laboratory studies and their potential impacts in natural environments. In an enclosure experiment conducted in a boreal lake, we exposed natural bacterial communities to Ag NP s with two common types of coatings (polyvinylpyrrolidone ( PVP ) and citrate) under two different exposure regimes, a one‐time (pulse) and a continuous (chronic) addition. Ag NP additions increased Ag concentrations to nearly 50 μg L −1 in the highest treatments. We examined bacterial responses (abundance, biomass, production, chlorophyll‐ a content and nutrient stoichiometry) over the course of 6 weeks in the summer of 2012. Bacterioplankton exposed to Ag NP s initially accumulated Ag over the experimental period regardless of Ag NP concentration or coating. After the initial period of increase, Ag in the bacterial size fraction changed largely in concert with bacterial biomass. We found no toxic effects of Ag NP s on bacterioplankton abundance, biomass, production or chlorophyll‐ a content throughout the experiment. Bacterial production was greater after the pulse addition of PVP ‐coated Ag NP s and in the chronic addition of PVP ‐coated Ag NP s at the highest concentrations. Furthermore, Ag NP s produced no significant changes in nutrient stoichiometry of the bacterioplankton size fraction. This lack of effects of Ag NPs on lake bacterioplankton observed under the natural conditions studied here differs from results of short‐term and laboratory studies of single‐species bacterial cultures. Our results thus indicate Ag NP effects in lakes may be less than expected based on standard laboratory experiments, and that additional studies are needed to understand Ag NP toxicity under realistic natural conditions in lakes and other ecosystems.
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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".