Ancient DNA suggests a historical demographic decline and genetic erosion in the Atlantic bluefin tuna
Bibliographic record
Abstract
Overexploitation has depleted fish stocks during the past century; nonetheless, its genomic consequences remain poorly understood for most species. Characterizing the spatiotemporal patterns of these consequences may provide baseline estimates of past diversity and productivity to aid management targets, help predict future dynamics, and facilitate the identification of evolutionary factors limiting fish population recovery. Here, we evaluate human impacts on the evolution of the iconic Atlantic bluefin tuna ( Thunnus thynnus ), one of the longest and most intensely exploited marine fishes, with a tremendous cultural and economic importance. We sequenced whole genomes from modern (n = 49) and ancient (n = 41) specimens dating up to 5,000 y ago, uncovering several findings. First, we identify temporally stable patterns of population admixture, as bluefin tuna caught off Norway and in the eastern Mediterranean share a greater degree of ancestry with Gulf of Mexico bluefin tuna than western and central Mediterranean bluefin tuna. This suggests that Atlantic spawning areas are important mixing grounds for the genetic diversity of Mediterranean bluefin tuna. We model effective population size to show that Mediterranean bluefin tuna began to undergo a demographic decline by the year 1900 to an extent not observed across the previous millennia. Coinciding with this, we found that heterozygosity and nucleotide diversity were significantly lower in modern (2013 to 2020) than ancient (pre-1941) Mediterranean bluefin tuna, suggesting that bluefin tuna underwent a genetic bottleneck. With this work, we show how ancient DNA provides unique perspectives on ecological complexity with the potential to inform the management and conservation of fishes.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".