Quantifying behavioural impairment as a proxy for physiological stress to improve welfare of imperilled white sturgeon (Acipenser transmontanus) during routine sampling efforts
Bibliographic record
Abstract
The white sturgeon ( Acipenser transmontanus ) is a large bodied imperilled fish species of significant conservation interest in western North America. Since 2002, hatchery-origin fish have been released in the Upper Columbia River’s Transboundary Reach to support population recovery, and captured with baited setlines as part of routine monitoring of fish health and reproductive status. Here, we investigated whether the use of increasingly long and intensive sampling protocols was associated with differences in short-term post-release behaviour derived from biologger data. In addition to basic sampling (e.g., body measurements, fin clipping), we exposed hatchery-origin juveniles to blood sampling; blood sampling and ultrasonography for sex determination; and blood sampling, ultrasonography, and gonadal biopsy surgeries. We also quantified the stress of setline-captured fish prior to processing using whole-blood glucose and lactate and compared these values (mean ± SD glucose = 4.2 ± 1.4 mmol/l; lactate = 5.9 ± 3.0 mmol/l) to those from an angled baseline group (glucose 1.5 ± 0.2 mmol/l; most lactate < 0.3 mmol/l). Overall, sampling regime did not affect tri-axial accelerometer-derived post-release locomotor activity (overall and vectorized dynamic body acceleration) or depth preferences over the course of 10 min trials, and the stress induced by setline capture and retrieval appears to be a major contribution to the total stress experienced by these fish. We offer some recommendations to improve the routine sampling protocols used in management efforts in this system and elsewhere.
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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) | 0.001 | 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".