Environmental drivers of diurnal visits by transient predatory fishes to Caribbean patch reefs
Bibliographic record
Abstract
Video cameras recorded the diurnal visitation rates of transient (large home range) piscivorous fishes to coral patch reefs in The Bahamas and identified 11 species. Visits by bar jack Caranx ruber, mutton snapper Lutjanus analis, yellowtail snapper Ocyurus chrysurus, barracuda Sphyraena barracuda and cero Scomberomorus regalis were sufficiently frequent to correlate with a range of biophysical factors. Patch-reef visitation rates and fish abundances varied with distance from shore and all species except S. regalis were seen more frequently inshore. This pattern is likely to be caused by factors including close proximity to additional foraging areas in mangroves and on fore-reefs and higher abundances close to inshore nursery habitats. Visitation rates and abundances of C. ruber, L. analis, O. chrysurus and S. regalis also varied seasonally (spring v. winter), possibly as fishes responded to temperature changes or undertook spawning migrations. The abundance of each transient predator species on the patch reefs generally exhibited limited diurnal variability, but L. analis was seen more frequently towards dusk. This study demonstrates that the distribution of transient predators is correlated spatially and temporally with a range of factors, even within a single lagoon, and these drivers are species specific. Transient predators are considered an important source of mortality shaping reef-fish assemblages and their abundance, in combination with the biomass of resident predators, was negatively correlated with the density of prey fishes. Furthermore, transient predators are often targeted by fishers and understanding how they utilize seascapes is critical for protecting them within reserves.
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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 | 0.000 | 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".