Structural and Functional Responses of Plankton to a Mixture of Four Tetracyclines in Aquatic Microcosms
Bibliographic record
Abstract
Pharmaceuticals are routinely detected at low concentrations in surface waters, but effects on non-target organisms are not well understood. Microcosms were used to assess ecological responses in freshwater ecosystems to a mixture offourtetracyclines commonly used in veterinary and human medicine. Triplicate microcosms were treated with tetracycline, oxytetracycline, doxycycline, and chlortetracycline, resulting in measured time-weighted average total mixture concentrations of 0, 0.080, 0.218, 0.662, and 2.29 microM, respectively. Responses were assessed in terms of structure and function based on measurements of zooplankton and phytoplankton communities, ecosystem productivity, and water quality. Effects were observed for some endpoints > or = the 0.218 microM treatment. The largest responses were concentration-dependent reductions in total phytoplankton abundance and species richness. Phytoplankton abundance recovered to control levels in all microcosms after treatment was terminated, and resilience (time to return to normal operating range during stress) was observed with respectto phytoplankton species richness. Zooplankton were generally unaffected by the tetracyclines. Responses also included decreased water clarity, lower oxygen concentration, and water temperature. Functional endpoints showed varying sensitivity. On the basis of dissolved oxygen concentrations, community respiration (R) increased while primary productivity (P) was unchanged with increased treatment concentration. The effects observed occurred at considerably greater concentrations than are currently measured in the environment, indicating minimal risk to aquatic organisms.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".