Wave and tide‐driven flow act on multiple scales to shape the distribution of a juvenile fish (<i>Albula vulpes</i>) in shallow nearshore habitats
Bibliographic record
Abstract
Abstract Environmental stress associated with incident flow is among the most fundamental physical factors structuring fish distributions. In shallow marine habitats, flow‐related stress arises through several distinct processes, yet their combined ramifications for habitat utilization by fishes are rarely evaluated concurrently. We used hydrodynamic models to resolve spatial and temporal variability in wave‐ and tide‐driven water velocities across the littoral zone of a subtropical island, and related these, along with other environmental predictors, to patterns in the abundance of a juvenile fish (Albula vulpes) as determined by 785 beach‐seine samples. Exerting universally negative effects on abundance, flow‐related predictors were among the most influential drivers of habitat use, particularly at landscape scales where contrasts were most apparent. Spatial gradients in the strength of wave‐induced and tide‐driven flow were pronounced and varied inversely across the study area, applying contradictory constraints on A. vulpes distributions and limiting juveniles to the small subset of habitats where near‐maximal wave and tide‐driven water velocities were mutually depressed over the long term. Meanwhile, within the few embayments where A. vulpes occurred with regularity, abundance was inversely related to short‐term fluctuations in wave‐driven water velocity, evidencing fine‐scale movements as fish presumably sought reduced rates of flow. Juveniles were consistently absent from the remaining majority of stations regardless of temporal variability, indicating that they were unable to exploit these areas even during periods of calm. Collectively, these observations are consistent with the hypothesis that spatial and temporal variability in incident flow act simultaneously at distinct scales to structure motile fish distributions.
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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 | 0.000 |
| 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".