Habitat associations of the Threatened pugnose minnow (<i>Opsopoeodus emiliae</i>) at the northern edge of the species range
Bibliographic record
Abstract
Abstract Pugnose minnow (Opsopoeodus emiliae) is a small, reclusive species that is widespread in North America, but is one of the rarest fishes in Canada, found in less than 12 known localities in southwestern Ontario. In contrast to most pugnose minnow populations across the global range, Canadian populations are primarily found in turbid systems, potentially indicating persistence in suboptimal conditions. We used data from a multi‐gear species and habitat survey in the Canard River, Ontario, a system dominated by agricultural inputs and the best‐known capture site of the species in Canada, to parameterise multi‐gear occupancy models for understanding the relationship between pugnose minnow occupancy and microhabitat features, including the role of turbidity. Almost 300 pugnose minnow were captured, representing the largest single collection of the species in Canadian history. The best occupancy model indicated that the probability of pugnose minnow occupancy was highest in the deepest sites with the lowest water clarity (i.e. high turbidity); however, competing models suggested that occupancy was highest at sites with wild celery (Vallisneria americana) and higher water clarity, signifying that habitats with low turbidity may be utilised if sufficient physical cover exists. Together, our results suggest that Canadian pugnose minnow populations occupy and potentially favour turbid conditions, possibly to avoid visual predators in clearer habitats. It remains uncertain whether this abiotic association represents a long‐term, viable, local adaptation or whether persistence of pugnose minnow in the Canard River is at risk unless significant water quality improvements can be made.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".