Recovery of a Wild Fish Population from Whole-Lake Additions of a Synthetic Estrogen
Bibliographic record
Abstract
Despite widespread recognition that municipal wastewaters contain natural and synthetic estrogens, which interfere with development and reproduction of fishes in freshwaters worldwide, there are limited data on the extent to which natural populations of fish can recover from exposure to these compounds. We conducted whole-lake additions of an active component of the birth control pill (17α-ethynylestradiol; EE2) that resulted in the collapse of the fathead minnow (Pimephales promelas) population. Here we quantify physiological, population, and genetic characteristics of this population over the 7 years after EE2 additions stopped to determine if complete recovery was possible. By 3 years post-treatment, whole-body vitellogenin concentrations in male fathead minnow had returned to baseline, and testicular abnormalities were absent. In the spring of the fourth year, adult size-frequency distribution and abundance had returned to pretreatment levels. Microsatellite analyses clearly showed that postrecovery fish were descendants of the original EE2-treated population. Results from this whole-lake experiment demonstrate that fish can recover from EE2 exposure at the biochemical through population levels, although the timelines to do so are long for multigenerational exposures. These results suggest that wastewater treatment facilities that reduce discharges of estrogens and their mimics can improve the health of resident fish populations in their receiving environments.
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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".