Influences of spawning timing, water temperature, and climatic warming on early life history phenology in western Alaska sockeye salmon
Bibliographic record
Abstract
We applied an empirical model to predict hatching and emergence timing for 25 western Alaska sockeye salmon (Oncorhynchus nerka) populations in four lake-nursery systems to explore current patterns and potential responses of early life history phenology to warming water temperatures. Given the temperature regimes sockeye salmon experienced during development, we predicted hatching to occur in as few as 58 days to as many as 260 days depending on spawning timing and temperature. For a focal lake spawning population, our climate–lake temperature model predicted a water temperature increase of 0.7 to 1.4 °C from 2015 to 2099 during the incubation period, which translated to a hatching timing that was 16 to 30 days earlier. The most extreme warming scenarios shifted development to approximately 1 week earlier than historical minima and thus climatic warming may lead to only modest shifts in phenology during the early life history stage of this population. The marked variation in the predicted timing of hatching and emergence among populations in close proximity on the landscape may serve to buffer this metapopulation from climate change.
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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 | 0.001 | 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 | 0.001 | 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".