Site fidelity and movement of a small‐bodied fish species, the rainbow darter (<scp><i>Etheostoma caeruleum</i></scp>): Implications for environmental effects assessment
Bibliographic record
Abstract
Abstract Small‐bodied fish species are commonly used for the assessment of environmental effects because they are short lived, abundant, and they mature early. Although they are generally considered to be less mobile than larger bodied species, relatively little is known about their movement patterns. In this study, we tagged 3,001 rainbow darters (Etheostoma caeruleum) (≤76 mm) in the upper Grand River of southern Ontario with visible implant alpha tags and elastomers in 3 riffles. Five hundred sixty‐five fish were recaptured over 4 recapture events (including spawning and nonspawning periods) over a spatial extent of 1900 m. The rainbow darter demonstrated high site fidelity having a median movement of 5 m and with 85% staying within the riffle in which they were originally tagged. Most movements occurred during the spawning period, where males moved at a greater frequency and had a tendency to move longer distances (up to 975 m). There was also a bias in the direction of movement, which was dependent on the recapture season. Overall, the high site fidelity of the rainbow darter makes it a candidate, sentinel species for the assessment of environmental effects.
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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 | 0.000 | 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".