Whole-genome sequencing across space and time reveals impact of population decline and reduced gene flow in Florida Scrub-Jays
Bibliographic record
Abstract
Summary Whole-genome sequence data is proving to be highly informative about the past demography of free-living populations, and in the context of endangered species, it can provide a quantification of the genetic risk posed by reduced genetic diversity and inbreeding. Prior to 1920, the Florida scrub-jay ( Aphelocoma coerulescens ) had been widespread across Florida, but with the expansion of agriculture and human habitation, its population has declined by 95%, resulting in fragmentation into semi-isolated subpopulations. By sequencing 241 individuals sampled from five different regions and across two time points, this study quantifies a greater magnitude of loss of genetic diversity and greater levels of inbreeding in smaller and more isolated subpopulations. Consistent with population genetics theory, reduction in population size results in a dramatic loss of rare alleles, skewing the site frequency spectrum far from the expected equilibrium. Increased inbreeding in the smaller, more remote subpopulations is especially evident in the increased size and number of runs of homozygosity. The Florida scrub-jay displays limited dispersal, and habitat fragmentation has greatly reduced the magnitude of gene flow in the past 30 years, resulting in further decline of genetic diversity, especially in the peripheral populations. Analysis of these data is informative in guiding conservation efforts to retain genetic diversity and minimize the consequences of inbreeding in the Florida scrub-jay. Highlights Five regional populations show distinct degrees of population isolation and decline. There has been commensurate loss of genetic diversity, skewed site frequency spectra, reduced migration, and increased inbreeding ( F ROH ). As many state-wide populations decline, the smaller, more remote populations provide a glimpse into the future and a testbed for remediation approaches.
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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 | 0.000 |
| 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) | 0.001 | 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".