Sympatric elasmobranchs and fecal samples provide insight into the trophic ecology of the smalltooth sawfish
Bibliographic record
Abstract
Growing concerns about the conservation of elasmobranchs have prompted a surge in research, because scientific studies that can support management actions are needed. Sawfishes are among the most threatened fishes worldwide and epitomize the challenge of conserving widely distributed, large-bodied marine fishes. We used a comparative approach to provide data on the trophic ecology of the smalltooth sawfish Pristis pectinata in the western Atlantic coastal waters of southwest Florida, USA. Specifically, we applied (1) stable isotope techniques to fin tissues of smalltooth sawfish and 2 sympatric elasmobranch species that have well-documented diets (i.e. bull shark Carcharhinus leucas and cownose ray Rhinoptera bonasus), and muscle tissue from a variety of known and potential prey species; and (2) an 18S rRNA gene sequencing technique to identify prey taxa in sawfish fecal samples. These analyses provided evidence that the smalltooth sawfish feeds primarily on teleost and elasmobranch fishes at all life stages even though sawfish move from estuarine to coastal habitats during their ontogeny. Although both sawfish and bull sharks occupy estuarine waters as juveniles and are piscivorous, the results also indicate that these species partition habitat. The cownose ray has been thought of as migratory throughout its range, but these data indicate that non-migratory, estuarine populations exist at lower latitudes. Collectively, these results will aid in the development of management decisions regarding these species and in improving long-term recovery planning for the smalltooth sawfish.
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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 | 0.000 |
| 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".