Effects of Whole-Lake Additions of Ethynylestradiol on Leech Populations
Bibliographic record
Abstract
Leeches are widespread, found in many freshwater habitats, and have diverse dietary habits. Despite their close phylogenetic relationships to Mollusca, a phylum with species affected by exogenous estrogens, it is unclear whether Hirudinea may also be impacted. A whole-lake experiment was done at the Experimental Lakes Area in Ontario, Canada, to assess whether 17α-ethynylestradiol (EE2) affected fishes and other species. Herein, we examined whether EE2 impacted leech community composition, species abundance, growth rates, gonad size, and cocoon production, when compared with reference lakes using a before-after-control-impact design. Each month baited leech traps were set overnight in the littoral zone at 10 sites around experimental Lake 260 and 2 reference lakes, and individuals were identified, weighed, and measured. Male and female organs of common species Haemopis marmorata were measured. Across all lakes, 9 species representing 3 families were collected. There were no apparent effects of EE2 on numbers, species richness, or community composition; however, condition in 1 of 5 species increased significantly after EE2 exposures. Total gonadosomatic index (GSI) and the GSI for all male or all female organs combined for H. marmorata were not affected by EE2 additions. However, some individual reproductive organs including relative sperm sac length (+), relative epididymis weight (-), relative vaginal bulb length (+), and relative ovisac + albumen gland length (+) changed after EE2 additions. Finally, whereas overall cocoon production was similar, it occurred earlier in the EE2-amended lake. In summary, few individual through community measures of leeches responded to low ng/L concentrations of EE2, suggesting that Hirudinea are less sensitive to this endocrine disruptor than other invertebrates and vertebrates. Environ Toxicol Chem 2020;39:1608-1619. © 2020 SETAC.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".