The role of temperature and flow on the migration of Chinook salmon (Oncorhynchus tshawytscha) smolts.
Bibliographic record
Abstract
For salmonids, the smolting process includes substantial morphological, physiological and behavioral changes all of which must coincide to ensure the greatest chance of survival in the marine environment. Therefore, understanding how environmental parameters influence the onset, duration, and termination of smolting can have substantial management implications. I used historical data and a controlled laboratory experiment to investigate the role of both temperature and flow on the timing of migration in Chinook salmon (Oncorhynchus tshawytscha) smolts. An Information Theoretic Model Comparison (ITMC) technique was used to correlate 13 years of historical smolt migration data from the Nechako River in central British Columbia, Canada with data on temperature and discharge from the same period. A combination of temperature experience (accumulated thermal units ATU) and flow discharge were best able to describe the observed migration patterns. In addition, ATU consistently performed better than daily mean temperature suggesting that temperature experience plays a larger role in the migration process than a temperature threshold. In a laboratory experiment, temperature manipulation affected growth and development of physiological smolt characteristics. In addition, fish in tanks with increasing temperature showed earlier movement than those in constant temperature tanks. Flow velocity was not found to have an effect on physiological development of smolt characteristics and did not appear to affect timing of migration in the absence of increasing temperature. However, velocity did influence the pattern of migration, since the presence of a strong, directional flow resulted in a well defined migration event with a clear increase, peak and decrease in movement regardless of the temperature manipulation. Alternatively, fish in experimental tanks without increased flow showed either pulses of movement or no clearly defined movement period. A model similar to the approach for the historical data was used to assess the mo
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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) | 0.000 | 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".