Species-specific effects of turbidity on the physiology of imperiled blackline shiners Notropis spp. in the Laurentian Great Lakes
Bibliographic record
Abstract
Increased sedimentary turbidity associated with human activities is often cited as a key stressor contributing to the decline of fishes globally. The mechanisms underlying negative effects of turbidity on fish populations have been well documented, including effects on behavior (e.g. visual impairment) and/or respiratory function (e.g. clogging of the gills); however, the long-term physiological consequences are less well understood. The decline or disappearance of several blackline shiners Notropis spp. in the Laurentian Great Lakes has been associated with increased turbidity. Here, we used non-lethal physiological methods to assess the responses of 3 blackline shiners under varying degrees of threat in Canada (Species at Risk Act; pugnose shiner N. anogenus: endangered; bridle shiner N. bifrenatus: special concern; blacknose shiner N. heterolepis: common) to increased turbidity. Fish were exposed for 3 to 6 mo to continuous low levels of turbidity (~7 nephelometric turbidity units, NTU). To test for effects on respiratory function, we measured both resting metabolic rate (RMR) and critical oxygen tension (the oxygen partial pressure at which the RMR of fish declines). No change in RMR was detected across species or in clear versus turbid treatments. However, critical oxygen tensions were negatively affected by long-term exposure to low levels of sedimentary turbidity in the 2 imperiled species, viz. pugnose and bridle shiner, but not in the more common blacknose shiner. Variation in effects of turbidity on respiratory performance suggests differential sensitivity to turbidity, which may contribute to the current conservation status of the 3 species.
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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 | 0.000 |
| 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".