Effect of oceanic straits on gene flow in the recently endangered little brown bat (<i>Myotis lucifugus</i>) in maritime Canada: implications for the spread of white-nose syndrome
Bibliographic record
Abstract
White-nose syndrome is rapidly spreading in eastern North America, causing mass mortality of hibernating bats. We characterized levels of genetic diversity and population structure of the little brown bat (Myotis lucifugus (Le Conte, 1831)) in eastern Canada to infer the extent to which oceanic straits may be barriers to movement. To quantify metrics of gene flow and infer movement dynamics, we genotyped 679 M. lucifugus at nine nuclear microsatellites (nDNA) and sequenced a portion of the mitochondrial DNA (mtDNA). We found high levels of genetic diversity and little population structure, with ≈13-fold higher differentiation of mtDNA than nDNA markers, suggesting that structuring patterns largely result from female philopatry. Discriminant analysis of principle components suggested that the subtle underlying structure was not concordant with sampling site. Regional differentiation (FST, Dest, Mantel test residuals) is mostly consistent with genetic isolation by distance. However, samples from Newfoundland showed genetic differentiation over and above the effects of distance, lower levels of genetic diversity, and less genetic connectivity with other sampled regions. Despite this, oceanic straits in the Gulf of Saint Lawrence do not appear to create an impenetrable barrier to movement, therefore it may be possible for white-nose syndrome to spread to Newfoundland.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".