Phylogenetic and functional clustering illustrate the roles of adaptive radiation and dispersal filtering in jointly shaping late‐Quaternary mammal assemblages on oceanic islands
Bibliographic record
Abstract
Islands frequently harbour unique assemblages of species, yet their ecological roles and differences are largely ignored in island biogeography studies. Here, we examine eco-evolutionary processes structuring mammal assemblages on oceanic islands worldwide, including all extant and extinct late-Quaternary mammal species. We find island mammal assemblages tend to be phylogenetically clustered (share more recent evolutionary histories), with clustering increasing with island area and isolation. We also observe that mammal assemblages often tend to be functionally clustered (share similar traits), but the strength of clustering is weak and generally independent from island area or isolation. These findings indicate the important roles of in situ speciation and dispersal filtering in shaping island mammal assemblages under pre-anthropogenic conditions, notably through adaptive radiation of a few clades (e.g. bats, with generally high dispersal abilities). Our study demonstrates that considering the functional and phylogenetic axes of diversity can better reveal the eco-evolutionary processes of island community assembly.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".