Skull morphology of bottlenose dolphins worldwide and patterns of adaptation between coastal and offshore environments
Bibliographic record
Abstract
Abstract The morphological differentiation between coastal and offshore ecotypes of bottlenose dolphins (genus Tursiops) has been researched since the 1960s, particularly in T. truncatus (Montagu, 1821), although most morphological studies have focused on localized populations. Therefore, it is unclear how patterns observed in these individual populations integrate within the global morphological variation. Here we carry out a meta‐analysis of global morphological variation between coastal and offshore ecotypes from 532 museum specimens, using both linear measurements (LM; 282 specimens), and shape data using geometric morphometrics (GM; 290 specimens). Together these analyses show consistent differentiation in skull morphology between coastal and offshore ecotypes, and provide a detailed description of variation patterns within each ecotype. These patterns show high individual morphological variation in the coastal ecotype between locations, while the offshore ecotype appears morphologically more uniform across the areas sampled. Overall, most skull shape variation can be described by features noticeable dorsally in the structures of the rostrum, whereas more limited change was found in ventral traits. Our results suggest that individual coastal populations may vary according to local environmental conditions, while those corresponding to the offshore ecotype appear to share similar morphological characteristics that might increase fitness in offshore habitats.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".