Genetic Load and Adaptive Potential of a Recovered Avian Species that Narrowly Avoided Extinction
Bibliographic record
Abstract
High genetic diversity is a good predictor of long-term population viability, yet some species persevere despite having low genetic diversity. Here we study the genomic erosion of the Seychelles paradise flycatcher (Terpsiphone corvina), a species that narrowly avoided extinction after having declined to 28 individuals in the 1960s. The species recovered unassisted to over 250 individuals in the 1990s and was downlisted from Critically Endangered to Vulnerable in the International Union for the Conservation of Nature Red List in 2020. By comparing historical, prebottleneck (130+ years old) and modern genomes, we uncovered a 10-fold loss of genetic diversity. Highly deleterious mutations were partly purged during the bottleneck, but mildly deleterious mutations accumulated. The genome shows signs of historical inbreeding during the bottleneck in the 1960s, but low levels of recent inbreeding after demographic recovery. Computer simulations suggest that the species long-term small Ne reduced the masked genetic load and made the species more resilient to inbreeding and extinction. However, the reduction in genetic diversity due to the chronically small Ne and the severe bottleneck is likely to have reduced the species adaptive potential to face environmental change, which together with a higher load, compromises its long-term population viability. Thus, small ancestral Ne offers short-term bottleneck resilience but hampers long-term adaptability to environmental shifts. In light of rapid global rates of population decline, our work shows that species can continue to suffer the effect of their decline even after recovery, highlighting the importance of considering genomic erosion and computer modeling in conservation assessments.
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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".