High temperature events shape the broadscale distribution of juvenile Atlantic salmon (<i>Salmo salar</i>)
Bibliographic record
Abstract
Abstract Summer water temperatures within many temperate rivers regularly surpass the incipient lethal temperature for juvenile Atlantic salmon ( c. 27°C), causing widescale abandonment of territory in favour of areas of cooler water (thermal refuges). This study aims to highlight the influence of thermal refuges on river‐scale abundance patterns. That is, do salmon parr adjust their distribution over time according to proximity to thermal refuges? Twelve reaches (seven reference: five refuge) were chosen along a 17‐km section of the Little Southwest Miramichi River in Canada. Reaches were sampled throughout the 2011 and 2012 summer periods; high temperature events were recorded during summer 2012 but not summer 2011. Multivariate principal component analyses indicated no discernible difference in habitat characteristics between the reach‐types under normal thermal conditions. However, reaches containing a thermal refuge had a significant increase in relative abundance of parr immediately after a series of high temperature events (water temperature >26°C) in 2012 ( p = 0.034). This increase in relative abundance in refuge reaches was not present during the summer of 2011 when no temperature events occurred ( p = 0.088), prior to the event of 2012 ( p = 0.999), or at the late autumn survey following the 2012 event ( p = 0.999). Difference in temperature between refuge and mainstem reaches significantly influenced the suitability of a tributary as a thermal refuge habitat ( R 2 = 0.84), with preference shown for cooler refuges. River‐wide thermal heterogeneity therefore plays a critical role in survival of juvenile salmon throughout summer months and is likely to become necessary under future climate change scenarios.
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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 | 0.000 | 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) | 0.002 | 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".