Trophic niche differentiation and foraging plasticity of long-finned pilot whales (Globicephala melas edwardii) in Tasmanian waters: insights from isotopic analysis
Bibliographic record
Abstract
Understanding the foraging preference of cetaceans is crucial for assessing their role as apex predators and indicators of marine ecosystem health. Using stable isotope analysis, we investigated trophic niche differentiation and foraging plasticity in 141 long-finned pilot whales ( Globicephala melas edwardii ) that stranded along the Tasmanian coast at three locations (Marion Bay, King Island, and Maria Island). Stranding location accounted for most of the variability in skin isotopic values ( δ 13 C: - 17.9 ± 0.2 ‰ to –16.9 ± 0.2 ‰, Principal Coordinate 1 = 89%), likely reflecting differences in foraging habitats. In addition, isotopic niche overlap ranged from minimal (0-10% between Marion Bay and Maria Island) to moderate (between Marion Bay and King Island, and King Island and Maria Island). While sex related differences in isotopic niche space were minimal overall, there was some variability in the core niche space between males and females at Maria Island. Dietary proportions from our mixing model support a predominantly cephalopod diet for pilot whales in Tasmanian waters (91%, CI: 63-90%), with greater contributions from offshore dietary sources (68%, CI: 25-95%). The dietary variability across the three strandings highlights the foraging plasticity of pilot whales, which despite their preferences for a wide range of oceanic cephalopods, can adopt a more generalist feeding strategy when necessary. These findings provide valuable insights into the ecological role and adaptability of pilot whales in Tasmanian waters, highlighting the importance of monitoring apex predators to inform conservation and ecosystem management strategies in dynamic marine ecosystems.
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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".