Revisiting the role of early life growth for survival potential in three clupeoid species
Bibliographic record
Abstract
Abstract Johan Hjort's “critical period” hypothesis, which postulates that year‐class strength is determined in the short period following the onset of exogenous feeding, has rarely been supported by empirical data. Instead, the current understanding is that recruitment is determined by cumulative mortality throughout early life. Recent studies relied on the measure of growth autocorrelation derived from otolith daily increment widths to test the link between growth rate achieved during the post‐hatch period and during subsequent phases of the larval stage. Based on this approach, we revisit the role of larval growth in driving survival potential in three clupeoid species: Japanese sardine Sardinops melanostictus, Japanese anchovy Engraulis japonicus, and Pacific round herring Etrumeus micropus throughout the larval stage, using a combination of published datasets of otolith increment widths. Strong growth autocorrelation was detected for all three species throughout the larval stage, suggesting that initial growth determines to some extent growth rates achieved later in life. The extent of autocorrelation was reduced in sardine relative to anchovy and round herring at older ages. This interspecific difference could be attributed to differences in sensitivity to variability of environmental factors such as water temperature and food availability. The present findings suggest that the effect of early growth rate persists into later life stages for driving survival potential, which could reconcile the classic concept of “critical period” and the current “growth–survival” paradigm.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".