Aye-aye population genomic analyses highlight an important center of endemism in northern Madagascar
Bibliographic record
Abstract
We performed a population genomics study of the aye-aye, a highly specialized nocturnal lemur from Madagascar. Aye-ayes have low population densities and extensive range requirements that could make this flagship species particularly susceptible to extinction. Therefore, knowledge of genetic diversity and differentiation among aye-aye populations is critical for conservation planning. Such information may also advance our general understanding of Malagasy biogeography, as aye-ayes have the largest species distribution of any lemur. We generated and analyzed whole-genome sequence data for 12 aye-ayes from three regions of Madagascar (North, West, and East). We found that the North population is genetically distinct, with strong differentiation from other aye-ayes over relatively short geographic distances. For comparison, the average FST value between the North and East aye-aye populations--separated by only 248 km--is over 2.1-times greater than that observed between human Africans and Europeans. This finding is consistent with prior watershed- and climate-based hypotheses of a center of endemism in northern Madagascar. Taken together, these results suggest a strong and long-term biogeographical barrier to gene flow. Thus, the specific attention that should be directed toward preserving large, contiguous aye-aye habitats in northern Madagascar may also benefit the conservation of other distinct taxonomic units. To help facilitate future ecological- and conservation-motivated population genomic analyses by noncomputational biologists, the analytical toolkit used in this study is available on the Galaxy Web site.
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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 | 0.001 | 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) | 0.001 | 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".