Quantifying thermal effects on contemporary growth variability to predict responses to climate change in northern rock sole (Lepidopsetta polyxystra)
Bibliographic record
Abstract
Understanding the causes of contemporary variation in growth rates can offer insights into the likely consequences of climate change for growth and recruitment of coastal marine fishes. We examined the growth dynamics of age-0 northern rock sole ( Lepidopsetta polyxystra ) over four years in three nurseries at Kodiak Island, Alaska, USA. Following the settlement period, fish were sampled monthly (July–October) with a 3 m beam trawl at fixed-position transects. Postsettlement sizes were positively related to temperatures during the spawning and larval periods, suggesting environmental control of spawning or settlement timing. Summer growth on the nursery grounds varied significantly among sites and years (mean size 32.8–63.1 mm in mid-September), with the Holiday Beach site consistently supporting the fastest growth rates. Contrary to expectations of density dependence and thermal regulation, nursery ground growth rates were not significantly correlated with fish density or water temperatures. The minor contribution of thermal variation to growth rates appears related to the conservative growth strategy and low thermal sensitivity of northern rock sole. These results suggest that climate changes influencing spawning time and larval growth may have larger impacts on first-year growth and recruitment of this species than temperature effects on the growth of nursery-resident juveniles.
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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".