Stable Isotope Analysis of Specimens of Opportunity Reveals Ocean-Scale Site Fidelity in an Elusive Whale Species
Bibliographic record
Abstract
Elusive wildlife are challenging to study, manage, or conserve, as the difficulty of obtaining specimens or conducting direct observations leads to major data deficiencies. Specimens of opportunity, such as salvaged carcasses or museum specimens, are a valuable source of fundamental biological and ecological information on data-deficient, elusive species, increasing knowledge of biodiversity, habitat and range, and population structure. Stable isotope analysis is a powerful indirect tool that can be used to infer foraging behavior and habitat use retrospectively from archived specimens. Beaked whales are a speciose group of cetaceans that are challenging to studyin situ, and although Sowerby's beaked whale (Mesoplodon bidens) was discovered >200 years ago, little is known about its biology. We measured δ13C and δ15N stable isotope composition in bone, muscle, and skin tissue from 102 Sowerby's beaked whale specimens of opportunity collected throughout the North Atlantic Ocean to infer movement ecology and spatial population structure. Median δ13C and δ15N values in Sowerby's beaked whale bone, muscle, and skin tissues significantly differed between whales sampled from the east and west North Atlantic Ocean. Quadratic discriminant analysis that simultaneously considered δ13C and δ15N values correctly assigned >85% of the specimens to their collection region for all tissue types. These findings demonstrate Sowerby's beaked whale exhibits both short- and long-term site fidelity to the region from which the specimens were collected, suggest that this species is composed of two or more populations or exhibits a metapopulation structure, and have implications for conservation and management policy. Stable isotope analysis of specimens of opportunity proved a highly successful means of generating new spatial ecology data for this elusive species and is a method that can be effectively applied to other elusive species.
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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 | 0.001 |
| 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".