Optimal phenology of life history events in <i>Calanus finmarchicus</i>: exit from diapause in relation to interannual variation in spring bloom timing and predation
Bibliographic record
Abstract
Abstract Respiration of lipids by copepods during diapause (overwintering dormancy) contributes to ocean carbon sequestration via the seasonal lipid pump (SLP). Parameterizing this flux in predictive models requires a mechanistic understanding of how life history adaptation in copepods shapes their timing of exit from diapause. We investigate the optimal phenology of Calanus finmarchicus in the Norwegian Sea using an individual-based model in which diapause exit is represented as a trait characterized by phenotypic mean and variance. Without interannual variability, optimal exit correlated with the onset of the spring phytoplankton bloom and phenotypic variance was of no benefit. In contrast, copepods endured reduced fitness and adopted bet-hedging strategies when exposed to interannual variability in bloom timing and predation: later exit from diapause and phenotypic variance maintained adult numbers in anomalous late-bloom years. Exit nevertheless remained well before the peak of the bloom which is a favorable strategy when low predation early in the year enhances survival of eggs and early developmental stages. Our work highlights the complex interactions between C. finmarchicus and its environment and the need for improved understanding of bet-hedging strategies and the cues of diapause exit to progress the representation of the SLP in global biogeochemical models.
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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) | 0.001 | 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".