Passive and active behavioural contributions to patchiness and spatial pattern during the early life history of marine fishes
Bibliographic record
Abstract
Multiple ichthyoplankton surveys of Placentia Bay, Newfoundland during the spring and summers of 1997 and 1998 indicated that both passive and active processes contribute to spatial pattern in pelagic eggs and larval fish. Distribution patterns of pelagic eggs and early larvae in coastal Newfoundland waters were consistent with passive drift during development, but older larvae were associated with areas of high production. Recently hatched larvae from pelagic spawners decreased in size throughout the spawning season, reflecting seasonal decreases in egg diameter. Larvae from demersal eggs increased in size over the same time period, possibly reflecting retention and growth. Lloyd's index of patchiness calculated for pelagic eggs generally increased during development, suggesting passive retention. Patchiness decreased after hatch, then increased at approximately 10 mm. We hypothesize that the observed spatial patterns in older larvae, seasonal size increases in larvae from demersal eggs, and ontogenetic changes in patchiness reflect active processes. Predator patchiness, ontogenetic changes in spatial patterns, and published larval consumption rates support the hypothesis that mortality did not generate this pattern. Furthermore, mean crowding of capelin larvae by potential prey increased with development. Increases in patchiness during late larval development coincided with the size at which swimming ability was predicted to exceed ambient flow. This pattern suggests that larger larvae may actively contribute to their spatial distribution. We conclude that swimming ability and behaviour become increasingly important in determining spatial distribution patterns as pelagic larvae develop.
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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 | 0.001 | 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".