Larval Fish Assemblage Structure at Coastal Fronts and the Influence of Environmental Variability
Bibliographic record
Abstract
Within the coastal zone, oceanographic features, such as fronts, can have major effects on the abundance and distribution of larval fish. We investigated the effects of fronts on larval fish assemblages by jointly collecting physical (ADCP and CTD) and biological (larvae) data in the nearshore waters of the south coast of South Africa, on four separate neap-tide occasions. Accumulation of fish larvae at predominantly internal wave-associated fronts was observed, with higher larval densities inshore of and within the front than farther offshore. On each occasion, larvae of coastal species with pelagic eggs (Mugillidae and Sparidae) were numerically dominant at the front itself, while inshore of the front, larvae of coastal species with benthic eggs (Gobiesocidae and Gobiidae) were more abundant. Offshore catches mainly comprised Engraulidae (pelagic species with pelagic eggs) larvae, which were generally restricted to the bottom, where current velocities were onshore on each occasion. On the occasion when fast (>100 cm/s) currents prevailed, however, accumulation of the larvae of coastal species occurred offshore of the front, and larvae were mixed throughout the water column. Thus, larval occurrence at these coastal frontal systems was strongly affected by the degree of mixing by currents, which on most occasions resulted in onshore retention. The results underline the importance of frontal systems in determining the nearshore distributions of fish larvae, particularly by retaining coastal fish species in the inshore region. The environmental variability observed at these frontal systems has potential implications for larval connectivity of fish populations.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".