The influence of ecological traits and environmental factors on the co‐occurrence patterns of birds on islands worldwide
Bibliographic record
Abstract
Abstract To understand the mechanisms shaping global species diversity patterns, we focused on species assembly of bird communities on islands, which are ideal for detecting ecological and historical processes. We tested the hypotheses that species traits and island environments interactively shape the phylogenetic structure of island bird assemblages through a variety of ecological processes: habitat filtering, in‐situ speciation, extinction, dispersal limitation and competitive exclusion. We assessed the effects of species ecological traits and environment factors on the phylogenetic fields, which defined as phylogenetic distance between individual bird species and co‐occurred species within each island, using phylogenetic generalized linear mixed models. Climate and isolation were the most important factors driving the co‐occurrence patterns of island bird species: the species' phylogenetic fields were significantly clustered on tropical and/or isolated islands. We also found that the phylogenetic fields strongly correlated with the ecological traits especially for the diet and habitat preferences: the phylogenetic fields tended to over‐disperse for granivores and species inhabiting in wetlands or coasts, while frugivores showed clustered phylogenetic fields. Moreover, mobility and body size had substantial effects on species assemblages: long‐distance dispersers had clustered phylogenetic fields and small‐bodied species showed overdispersed phylogenetic fields.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 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".