Genomic‐wide sequencing reveals remarkable connection between widely disjunct populations of the internationally threatened bog buck moth
Bibliographic record
Abstract
Abstract Rare, threatened species often suffer from habitat fragmentation, which leads to smaller populations vulnerable to negative impacts including inbreeding depression and collapse of metapopulation dynamics. Therefore, understanding the population structure and relationships of each population of a threatened species is critical for prioritising habitat conservation and reintroduction efforts. The bog buck moth ( Hemileuca sp.) is a lineage previously recognised as several populations of conservation concern in New York state and the Province of Ontario. Recent genomic research discovered that bog buck moth from New York was a highly divergent, distinct entity compared to the group's diversity across North America. Nevertheless, the Canadian populations have not been evaluated and are geographically disjunct from the nearest New York population by ~170 km. As New York populations are in sharp decline, confirming that the relatively robust Ontario populations are conspecific, and understanding their relationship to New York populations, is a conservation priority. We integrated genomic data from an Ontario population into a broader dataset containing populations from across the range of the species group. Bog buck moth populations from Ontario and New York were identified as reciprocally monophyletic conspecifics, and other ecologically similar populations of Hemileuca from the western Great Lakes region are confirmed to be a different, widespread species. These results corroborate the restricted range of the bog buck moth and suggest that Ontario and New York populations have not been in recent contact. Therefore, reintroduction efforts must be developed in the context of this population structure.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".