Once upon a larva: revisiting the relationship between feeding success and growth in fish larvae
Bibliographic record
Abstract
Abstract Variations in larval fish growth rates are largely the result of variability in biotic and abiotic characteristics of the feeding environment experienced by each individual. An assessment of an individual's overall feeding success (i.e. accumulation of utilizable organic matter) can best be achieved at the time of capture when the relationships among environment, short-term feeding success as defined by gut content and long-term feeding success as defined by accumulated growth can be contrasted. Here, we investigated the relationships between average growth, feeding success, and variability in individual growth and feeding rates across a range of taxa based on a synthesis of studies in which stomach content and otolith growth were measured in the same individuals. Instantaneous measures of feeding success were highly variable and demonstrated a positive yet somewhat limited association with growth rates across all taxa. The strength of the feeding-growth relationships among taxa, and cohorts within taxa, was reflected in the autocorrelation of individual growth rates, suggesting that stable growth was achieved through consistent feeding success. However, when viewed at the individual level, faster growth was achieved in individuals with more variable growth rates, and by inference more variable past feeding success. The dichotomy in these underlying relationships may point to the importance of stochastic events in the development of exceptional individuals in a population, and may be linked to how surplus energy is allocated to individual growth rates. The positive correlation found between feeding success and growth in all taxa is consistent with the growth-survival paradigm for the larval stage of fish. However, both the correlation between feeding success and growth and the serial correlation of growth time-series was greatest in fast-growing species, suggesting that the potential for an early “critical period” regulating survival varies among species, reaching a maximum in fast-growing fish.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".