Flippers versus feet: comparative trends in aquatic and non‐aquatic carnivores
Bibliographic record
Abstract
Summary It is commonly accepted that many adaptations characterize carnivores that live in water. However, no comparative tests have ever shown systematic differences between aquatic and terrestrial carnivore species as a whole. We examine numerous hypotheses that purport to distinguish aquatic and terrestrial carnivores using 20 morphological, life history, physiological and ecological traits. Using the method of independent contrasts with a complete species‐level phylogeny of extant carnivores, we found few differences between aquatic and terrestrial species. Compared to terrestrial sister taxa, aquatic carnivores are streamlined (increased head and body length for a given body weight), have larger brains, smaller litter sizes, shorter interbirth intervals, and shorter lifespans. Some of these differences are important functionally. Larger brain size may be related to increased cognitive and sensory needs required for an amphibious lifestyle; smaller litters are likely associated with increased neonatal survival amidst competition for suitable breeding sites and advantages accruing to increased precociality. We conclude that broad differentiation of carnivores into aquatic and terrestrial ecotypes is not useful given that adaptive differences between these groups are limited and seemingly no more numerous than those that occur within each ecological group.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.003 | 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".