Copepod production drives recruitment in a marine fish
Bibliographic record
Abstract
Predicting fluctuations in recruitment of commercial marine fish remains the Holy Grail of fisheries science. In previous studies, we identified statistical relationships linking Atlantic mackerel ( Scomber scombrus ) recruitment to regional climate, zooplankton biomass, and the production of copepod nauplii over a decade (1982–1991) that included the exceptionally strong year class of 1982. Here we tested the validity of these relationships by adding a second decade (1992–2003) of observations that includes another exceptional year class in 1999. We provide the first field-based evidence linking availability of plankton prey in the sea to early growth of larval fish and to year-class strength in a commercially exploited marine fish. Recruitment is shown to strongly depend on production of the copepod nauplii species that contribute to the diet of mackerel larvae. Both strong year classes were characterized by exceptionally high availability of these specific prey. We suggest that mackerel recruitment can be anticipated 3 years in advance based on prey availability during the first weeks of planktonic life and predict a strong year class for fish hatched in 2006.
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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 | 0.002 |
| 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".