Rise and fall of island butterfly diversity: Understanding genetic differentiation and extinction in a highly diverse archipelago
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Aim We describe fine‐scale diversity patterns of the entire butterfly fauna occurring on the Tuscan Archipelago. By assessing the traits associated with population diversification, haplotype uniqueness and extinction, we aim to identify the factors determining the origin and maintenance of genetic diversity, and population vulnerability to environmental changes. Location Tuscan Archipelago, Sardinia, Tuscany (Italy) and Corsica (France). Methods We built a mt DNA dataset (1,303 COI sequences) for the 52 butterfly species reported in the Archipelago, also including specimens from neighbouring areas, and compiled data on 12 species traits and on the apparent extinction of species from the main islands. We calculated indices that measure genetic differentiation, and using phylogenetic regressions we evaluated the relationships between these indices and species traits. Finally, we inferred which traits are associated with disappearance of species on individual islands using phylogenetic regression. Results The overall spatial pattern of genetic diversity corresponded with the proximity of the areas, but strong contrasts were also identified between geographically close areas. Together with the island endemics, several common and widespread species had a high genetic diversification among islands and mainland. Phylogenetic regressions revealed that smaller‐sized, more specialized species, with a preference for drier regions, displayed greater genetic structure and/or haplotype uniqueness. Species that disappeared from islands had a higher population diversification. Capraia has experienced a notable loss of diversity, which significantly affected species with shorter flight periods. Main conclusions Tuscan island butterflies are characterized by strong genetic contrasts and species differ in their contribution to the overall genetic diversity. By ranking the species for their contribution to genetic diversity and identifying the traits linked to the emergence and maintenance of diversity, we have developed a valuable tool for prioritizing populations as targets for monitoring and conservation action. The dataset constructed also represents a valuable resource for testing biogeographical hypotheses.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 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) | 0.000 | 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 it