Vertebral microchemistry as an indicator of habitat use of the oceanic whitetip shark <i>Carcharhinus longimanus</i> in the central and eastern <scp>Pacific Ocean</scp>
Bibliographic record
Abstract
The oceanic whitetip shark, Carcharhinus longimanus, is a highly migratory, epipelagic top predator that is classified as critically endangered. Although this species is widely distributed throughout the world's tropical oceans, its assumed mobility and pelagic behavior limit studies to derive required lifetime data for management. To address this data deficiency, we assessed variation in the habitat use of C. longimanus by oceanic region and over ontogeny through time series trace element and stable isotope values conserved along the vertebral centra (within translucent annulus bands) of 13 individuals sampled from the central and eastern Pacific Ocean. Elemental ratios of Mg:Ca, Mn:Ca, Fe:Ca, Zn:Ca, and Ba:Ca varied significantly among individuals from both sampling regions while principal component analysis of combined standardized elements revealed minimal overlap between the two areas. The limited overlap was also in agreement with stable isotope niches. These findings indicate that C. longimanus exhibit a degree of fidelity to sampling regions but also connectivity in a proportion of the population. The relatively stable Sr:Ca ratio supports its occurrence in oceanic environments. The decreasing trends in Ba:Ca, Mn:Ca, and Zn:Ca ratios, as well as in carbon and nitrogen isotope values along vertebral transects, indicate that C. longimanus undergo a directional habitat shift with age. Combined elemental and stable isotope values in vertebral centra provide a promising tool for elucidating lifetime data for complex pelagic species. For C. longimanus, management will need to consider subpopulation movement behavior in the Pacific to minimize the potential for localized depletions. Further work is now required to sample individuals across the entire Pacific and to link these findings with genetic and movement data to define population structure.
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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".