Investigating the Relationship Between Body Shape and Life History Traits in Toothed Whales: Can Body Shape Predict Fast-Slow Life Histories?
Bibliographic record
Abstract
Abstract A widespread pattern in vertebrate life-history evolution is for species to evolve towards either fast or slow life histories; however, the possible causes of this pattern are multiple. Toothed whales (Odontoceti) are a particularly speciose group that includes a substantial range of body sizes and life histories and thus represent a model group to test the possible cause of this dichotomy. Using ancestral reconstruction, we find that some groups of odontocetes evolved sleek, presumably fast, body shapes around the same time that killer whales (Orcinus orca) evolved to be a predator of other whales approximately 1 Mya during the Pleistocene. A sleek body shape may have evolved as an adaptation to escape killer whale predation and resulted in a longer life-history events. A cluster analysis of odontocete whales confirmed the dual pattern of life-history traits with one group called ‘reproducers’ characterized by early age of maturity, short gestation, short interbirth interval, and short life, and the other group called ‘bet-hedgers’ with the opposite pattern. However, we found life history grouping relatively unrelated to whale shape (sleek or chunky). Results of mixed effects models incorporating principle components, indicated support for body shape as being positively related to neonate length (investment in progeny) but not significantly related to the temporal life-history traits. Thus, whale body shape is not an adequate explanation for the evolution of fast-slow life histories in odontocete whales.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".