Fish living near two wastewater treatment plants have unaltered thermal tolerance but show changes in organ and tissue traits
Bibliographic record
Abstract
Municipal wastewater treatment plants (WWTPs) are a significant source of anthropogenic pollutants and are a serious environmental stressor in Laurentian Great Lakes ecosystems. In this study, we examined whether three freshwater fish species (bluegill sunfish Lepomis macrochirus, green sunfish Lepomis cyanellus, and round goby Neogobius melanostomus) collected near two wastewater effluent outflows in Lake Ontario showed altered measures of somatic investment and thermal tolerance. Fish of all three species collected near the WWTPs were larger with 50–60% heavier body masses compared to those collected at reference sites. Green sunfish had higher body condition and increased haematocrit at wastewater-contaminated sites, and both round goby and bluegill sunfish had larger livers (controlling for body mass) at wastewater-contaminated sites. Thermal tolerance (critical thermal maximum, CTmax) differed between species (green sunfish > bluegill sunfish > round goby), but was similar in fish collected at wastewater-contaminated sites compared to cleaner reference sites. Wastewater-contaminated sites had poorer water quality, higher nutrient loadings, and higher concentrations of anthropogenic contaminants (measured via polar organic chemical integrative samplers, POCIS) than reference sites. Our results suggest that fish in the wild may have some capacity to cope with WWTP effluent and avoid any potential impairments in thermal tolerance. Our findings also suggest that treated wastewater is changing water quality locally in Great Lakes watersheds, and that many fish species may be able to access extra nutrients provided by such effluent outflows. However, if outflow areas become preferred foraging areas this will inadvertently increase exposure to anthropogenic stressors and pollutants.
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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".