Distribution and abundance of herbivorous reef fishes on a barrier reef system in the Florida Keys and Dry Tortugas, Florida
Bibliographic record
Abstract
Herbivorous reef fishes control algal growth and are critical for maintaining reef health. Grazing effects vary due to community composition, so a diverse herbivore community is important for preventing phase shifts from coral to algal-dominated reefs. However, herbivore communities and grazing effects vary spatially, resulting in non-uniform distribution of algal mitigation across the seascape. Therefore, understanding how habitat influences herbivore communities is essential for predicting the spatial distribution of these species' ecological services. This study used underwater visual surveys (n = 5455) to examine how habitat influences spatial patterns of herbivorous fish densities and species richness in the Florida Keys and Dry Tortugas, Florida. Herbivorous fishes were ubiquitous, and communities were dominated by small herbivores such as damselfishes (Pomacentridae), gobies (Gobiidae), surgeonfishes (Acanthuridae), and small- to medium-bodied parrotfishes (subfamily Scarinae). A suite of factors influenced herbivorous fish communities but boosted regression tree results showed that habitat relief, depth, and spatial location within the Florida Keys and Dry Tortugas were the most important factors. In general, herbivore occurrence, density, and species richness increased as percent of low relief hardbottom habitat (<0.2 m high) decreased. In addition, density and occurrence of herbivores generally increased at shallower depths. Spatial location influenced the density of herbivores with potential hotspots predominantly located in the Upper Keys and the Dry Tortugas Bank. These data provide a valuable understanding of the spatial distribution of herbivorous reef fishes, and aid management decisions regarding the protection and sustainability of herbivore resources and the ecosystems that rely on them.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".