Mandible allometry in extant and fossil Balaenopteridae (Cetacea: Mammalia): the largest vertebrate skeletal element and its role in rorqual lunge feeding
Bibliographic record
Abstract
Rorqual whales (crown Balaenopteridae) are unique among aquatic vertebrates in their ability to lunge feed. During a single lunge, rorquals rapidly engulf a large volume of prey-laden water at high speed, which they then filter to capture suspended prey. Engulfment biomechanics are mostly governed by the coordinated opening and closing of the mandibles at large gape angles, which differentially exposes the floor of the oral cavity to oncoming flow. The mouth area in rorquals is delimited by unfused bony mandibles that form kinetic linkages to each other and with the skull. The relative scale and morphology of these skeletal elements have profound consequences for the energetic efficiency of foraging in these gigantic predators. Here, we performed a morphometric study of rorqual mandibles using a data set derived from a survey of museum specimens. Across adult specimens of extant balaenopterids, mandibles range in size from ∼1–6 m in length, and at their upper limit they represent the single largest osteological element of any vertebrate, living or extinct. Our analyses determined that rorqual mandibles exhibit positive allometry, whereby the relative size of these mandibles becomes greater with increasing body size. These robust scaling relationships allowed us to predict mandible length for fragmentary remains (e.g. incomplete and/or fossil specimens), as we demonstrated for two partial mandibles from the latest Miocene of California, USA, and for mandibles from previously described fossil balaenopterids. Furthermore, we showed the allometry of mandible length to body size in extant mysticetes, which hints at fundamental developmental constraints in mysticetes despite their ecomorphological differences in feeding styles. Lastly, we outlined how our findings can be used to test hypotheses about the antiquity and evolution of lunge feeding.
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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 | 0.001 |
| 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".