Ancient DNA reveals historical demographic decline and genetic erosion in the Atlantic bluefin tuna
Bibliographic record
Abstract
Abstract Overexploitation has depleted fish stocks during the past century, nonetheless its genomic consequences remain poorly understood. Characterising 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 5000 years ago, uncovering several novel 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 was significantly lower in modern (2013-2020), than ancient (pre-1941) Mediterranean bluefin tuna, suggesting bluefin tuna underwent a genetic bottleneck. With this work we show how ancient DNA provides novel perspectives on ecological complexity with the potential to inform the management and conservation of fishes. Significance Achieving the aim of the current UN Ocean Decade to “protect and restore ecosystems and biodiversity” is stymied by a lack of historical knowledge on how human exploitation has impacted and therefore what should be restored. Here, we sequence DNA in ancient fish bones to evaluate the historical diversity of the Atlantic bluefin tuna; which has been of great commercial importance for centuries. We find that bluefin tuna began to undergo demographic decline by 1900, 70 years earlier than currently recognised. Correspondingly, we find modern bluefin tuna had lower levels of genetic diversity than historical ones. This suggests that human impacts on the diversity of marine fishes are likely to have begun earlier and be more complex than previously thought.
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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 | 0.000 | 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".