Ontogenetic and seasonal shifts in diets of sharptail mola Masturus lanceolatus in waters off Taiwan
Bibliographic record
Abstract
Sharptail mola Masturus lanceolatus share a circumglobal distribution with ocean sunfish Mola mola and are typically regarded as gelatinous plankton feeders. Both species are frequently captured as bycatch in the same areas, but sharptail mola are often targeted and heavily harvested in certain regions. However, the diet of sharptail mola remains poorly described. We examined the foraging habits and trophic dynamics of sharptail mola from waters off eastern Taiwan using stomach content analysis (SCA; n = 162), bulk tissue stable isotope analysis (SIA; n = 213), and compound-specific isotope analysis of amino acids (CSIA-AA; n = 10). Results demonstrated that sharptail mola mainly consumed tunicates, with lower dietary proportions of diverse prey from epi- and mesopelagic, coastal, and benthic habitats. The diet of sharptail mola changed significantly with size; small mola (<80 cm) had lower δ15N and δ13C values and fed on more pteropods and Salpidae, while large mola (>80 cm) fed on more Pyrosoma spp., cephalopods, and benthic organisms living on sandy substrates, with larger individuals having correspondingly higher isotope values and trophic positions. Diet compositions and δ13C values also showed seasonal variations across body size, suggesting that sharptail mola might undergo seasonal migrations with changing availability of food resources. The results provide insights into the trophic dynamics of sharptail mola and suggest that their foraging behavior varies across life-history stages and seasons.
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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".