Bibliographic record
Abstract
We applied a stage-specific population matrix, the Lefkovitch matrix, to the northern anchovy Engraulis mordax and the Pacific sardine Sardinops sagax to determine which vital rates in the life history have the most effect on population growth. Three vital rates considered are the daily stage-specific instantaneous mortality rate, stage duration and daily age-specific fecundity per female. The models incorporate variability in growth rates among individuals and link simpler stage-based and more complicated individual-based modeling approaches. The elasticity of population growth rate for anchovy (percentage change from a 1 % change of a vital rate) was greatest for mortality in yolk-sac larvae, fecundity of 2 yr old fish (111 to 135 mm), and stage duration in late larvae (11 to 35 mm). For sardine, elasticity was greatest for mortality in life stages of egg and yolk-sac larvae, fecundity of 5 and 6 yr old fish (211 to 250 mm), and stage duratlon in the early larvae (5 to 10 mm). When stage duration was variable, elasticity was !:;(l as large as when stage duration was constant, indicating that sensitivity of populations to changes in vital rates IS reduced by variation In growth rates. Population growth rates for both specles increased with variance in individual growth rates. Thus, a population with individuals that grow at varying rates is more likely to increase. Our models indicate that growth rates are important determinants of population growth and recruitment and it is likely that growth and mortality rates are linked. We suggest, therefore, that inexpensive estimates of larval growth rates could be used to help forecast future recruitment.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.988 | 0.990 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".