Use of genetic, climatic, and microbiological data to inform reintroduction of a regionally extinct butterfly
Bibliographic record
Abstract
Species reintroductions are increasingly used as means of mitigating biodiversity loss. Besides habitat quality at the site targeted for reintroduction, the choice of source population can be critical for success. The butterfly Melanargia russiae (Esper´s marbled white) was extirpated from Hungary over 100 years ago, and a reintroduction program has recently been approved. We used museum specimens of this butterfly, mitochondrial DNA data (mtDNA), endosymbiont screening, and climatic-similarity analyses to determine which extant populations should be used for its reintroduction. The species displayed 2 main mtDNA lineages across its range: 1 restricted to Iberia and southern France (Iberian lineage) and another found throughout the rest of its range (Eurasian lineage). These 2 lineages possessed highly divergent wsp alleles of the bacterial endosymbiont Wolbachia. The century-old Hungarian specimens represented an endemic haplotype belonging to the Eurasian lineage, differing by one mutation from the Balkan and eastern European populations. The Hungarian populations of M. russiae occurred in areas with a colder and drier climate relative to most sites with extant known populations. Our results suggest the populations used for reintroduction to Hungary should belong to the Eurasian lineage, preferably from eastern Ukraine (genetically close and living in areas with the highest climatic similarity). Materials stored in museum collections can provide unique opportunities to document historical genetic diversity and help direct conservation.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".