Climate and intraspecific competition control the growth and life history of juvenile sockeye salmon (Oncorhynchus nerka) in Iliamna Lake, Alaska
Bibliographic record
Abstract
Recent climate changes have had marked effects on the ice-free season and thermal conditions in many high-latitude lakes, but their ecological effects combine with density-dependent processes to affect fish growth and life history. To better understand the relative roles of climate and intraspecific density, we applied Gaussian state–space models to long-term data (1962–2006) on growth of juvenile sockeye salmon ( Oncorhynchus nerka ) in Iliamna Lake, Alaska, USA. Both temperature and density influenced fry size at the end of their first growing season, but the positive effect of temperature exceeded the negative effects of density. Fry growth was affected by the magnitude of their own cohort more strongly than by the previous brood (i.e., yearlings). In contrast, density was more important than temperature in Lake Aleknagik, also in Bristol Bay, over the same period of record, probably because Iliamna Lake is cooler and has generally lower densities of juvenile sockeye salmon than Lake Aleknagik. In both lakes, the size of the fish at the end of the first growing season affects smolt size and age at seaward migration, hence survival at sea and age at maturity, so the relative effects of climate and density depend on the ecological context.
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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".