Movement ecology of a mobile predatory fish reveals limited habitat linkages within a temperate estuarine seascape
Bibliographic record
Abstract
Large predatory fishes, capable of traveling great distances, can facilitate energy flow linkages among spatially separated habitat patches via extended foraging behaviors over expansive areas. Here, we tested this concept by tracking the movement of a large mobile estuarine fish, red drum (Sciaenops ocellatus). Specifically, we addressed the following two questions: (i) What are the spatial and temporal patterns of red drum movement (rates of dispersal) and activity space? (ii) Does red drum movement facilitate linkages among estuarine marsh complexes? Dispersal from the release location was greatest during the first 2 weeks at liberty before declining to less than 0.5 km·week–1 for the remainder of the study. Activity space initially increased rapidly before reaching an asymptote at 2.5 km2 2 weeks postrelease. Connectivity indices calculated among marsh complexes corroborated these observations, suggesting high residency and limited seascape-scale linkages via red drum movement behaviors. These data highlight potential within-estuary spatial structure for mobile fishes and could inform subsequent efforts to track energy flows in coastal food webs, predict the footprint of local habitat restoration benefits, and enhance the design of survey regimes to quantify overall population demography.
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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".