What factors shape genetic diversity in cetaceans?
Bibliographic record
Abstract
Understanding what factors drive patterns of genetic diversity is a central aspect of many biological questions, ranging from the inference of historical demography to assessing the evolutionary potential of a species. However, as a larger number of datasets have become available, it is becoming clear that the relationship between the characteristics of a species and its genetic diversity is more complex than previously assumed. This may be particularly true for cetaceans, due to their relatively long lifespans, long generation times, complex social structures, and extensive ranges. In this study, we used microsatellite and mitochondrial DNA data from a systematic literature review to produce estimates of diversity for both markers across 42 cetacean species. Factors relating to demography, distribution, classification, biology, and behavior were then tested using phylogenetic methods and linear models to assess their relative influence on the genetic diversity of both marker types. The results show that while relative nuclear diversity is correlated with population size, mitochondrial diversity is not. This is particularly relevant given the widespread use of mitochondrial DNA to infer historical demography. Instead, mitochondrial diversity was mostly influenced by the range and social structure of the species. In addition to population size, habitat type (neritic vs. oceanic) had a significant correlation with relative nuclear diversity. Combined, these results show that many often-unconsidered factors are likely influencing patterns of genetic diversity in cetaceans, with implications regarding how to interpret, and what can be inferred from, existing patterns of diversity.
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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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".