Evolutionary drivers of morphological differentiation among three bottlenose dolphin lineages,<i>Tursiops</i>spp. (Delphinidae), in the northwest Indian Ocean utilizing linear and geometric morphometric techniques
Bibliographic record
Abstract
Abstract Local adaptation and adaptive radiations are typically associated with phenotypic variation suited to alternative environments. In the marine environment, the nature of relevant ecological or environmental transitions is poorly understood, especially for highly mobile species. Here we compare three genetic lineages in the genus Tursiops (bottlenose dolphins), using linear measurements and geometric morphometric techniques, in the context of environmental variation in the northwest Indian Ocean. Cranial morphology was clearly differentiated comparing Tursiops truncatus and Tursiops aduncus, while a recently discovered genetic lineage, found in the Arabian Sea, was morphologically most similar to T. aduncus from the same region, but distinct for various measures, particularly metrics associated with the lateral dimension of the skull. The extent of divergence between T. truncatus and T. aduncus compared to differences between the T. aduncus lineages is consistent with the recent phylogeny for these species. Therefore, with the corroboration of genetic and morphological inference, we propose two conservation units of T. aduncus be recognized in the region at a sub-specific level so that their conservation can be managed effectively. We consider possible evolutionary mechanisms associated with regional habitat characteristics and the exploitation of distinct prey resources.
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 | 0.000 |
| 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 | 0.001 | 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".