Historical and contemporary factors generate unique butterfly communities on islands
Bibliographic record
Abstract
The mechanisms shaping island biotas are not yet well understood mostly because of a lack of studies comparing eco-evolutionary fingerprints over entire taxonomic groups. Here, we linked community structure (richness, frequency and nestedness) and genetic differentiation (based on mitochondrial DNA) in order to compare insular butterfly communities occurring over a key intercontinental area in the Mediterranean (Italy-Sicily-Maghreb). We found that community characteristics and genetic structure were influenced by a combination of contemporary and historical factors, and among the latter, connection during the Pleistocene had an important impact. We showed that species can be divided into two groups with radically different properties: widespread taxa had high dispersal capacity, a nested pattern of occurrence, and displayed little genetic structure, while rare species were mainly characterized by low dispersal, high turnover and genetically differentiated populations. These results offer an unprecedented view of the distinctive butterfly communities and of the main processes determining them on each studied island and highlight the importance of assessing the phylogeographic value of populations for conservation.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".