Genomic assessment of an endemic Hawaiian surgeonfish, Acanthurus triostegus sandvicensis, reveals high levels of connectivity and fine-scale population structure
Bibliographic record
Abstract
Abstract The Hawaiian Archipelago has served as a natural laboratory to assess genetic connectivity patterns across a broad spectrum of taxonomic and ecological diversity. Almost all these studies were based on a few targeted loci, but technologies now allow us to assess population structure with genomic coverage and greater resolution. Here, we provide a SNP-based analysis for an endemic surgeonfish, Acanthurus triostegus sandvicensis (manini) across the Hawaiian Archipelago and adjacent Johnston Atoll (N = 461). Based on 3649 SNPs, manini showed population structure in the main Hawaiian Islands, but genetic homogeneity across most of the northwestern extent of the archipelago (overall FST = 0.033, P < 0.001). Net migration occurred from Johnston Atoll into Hawai‘i, providing further support for Johnston Atoll being a pathway for dispersal (or colonization) into Hawai′i. These results highlight the higher efficacy of genomic sequencing to characterize fine-scale patterns of connectivity relative to a targeted loci approach and, moving forward, may invoke a reassessment of past connectivity studies in a genomics framework.
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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".