Fish Assemblages of Shoal‐ and Shoreline‐Associated Seagrass Beds in Eastern Gulf of Mexico Estuaries
Bibliographic record
Abstract
Abstract Assemblage structure of fishes associated with seagrasses (order Alismatales) is affected by factors such as depth, seagrass coverage, location of seagrass beds, and proximity of seagrass beds to adjacent habitats. Although these relationships have been well explored for small‐bodied fishes, few studies have examined seagrass habitat use by large‐bodied fishes (>100 mm SL). To examine the effects of habitat characteristics on assemblages of large‐bodied fishes, two seagrass habitat types were sampled in three eastern Gulf of Mexico estuaries (2008–2010) with a 183‐m haul seine: (1) seagrasses immediately adjacent to shorelines and (2) seagrasses associated with shoals (seagrass beds >100 m from shoreline). Within each estuary, fish density was greater (as much as two times greater) in shoal seagrass beds than in those along shorelines. Fish assemblage structure also differed significantly between the two habitat types. Species that distinguished the seagrass shoreline (e.g., Spot Leiostomus xanthurus, Redfin Needlefish Strongylura notata) had affinities for habitats that were relatively shallow, gently sloped, less saline, and muddy with less seagrass coverage. Species that distinguished seagrass shoals (e.g., Pigfish Orthopristis chrysoptera, Silver Perch Bairdiella chrysoura) had affinities for habitats that were deeper, steeply sloped, sandy, and more saline, with greater seagrass coverage. Among economically important fishes, some were more abundant along shorelines (e.g., Common Snook Centropomus undecimalis, Sheepshead Archosargus probatocephalus, and Striped Mullet Mugil cephalus), while others were more abundant on shoals (e.g., Gag Mycteroperca microlepis, Spotted Seatrout Cynoscion nebulosus, and Scaled Sardine Harengula jaguana). This study demonstrates that seagrass shoals, which are being lost in some estuaries, provide different environmental conditions than those along shorelines, support unique fish assemblages, and host greater densities of several economically important species. Received November 12, 2013; accepted March 18, 2014
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".