Phylogeography, genetic stocks, and conservation implications for an Australian endemic marine turtle
Bibliographic record
Abstract
Abstract Identification of the geographic extent of population boundaries, the distribution of genetic lineages, and the amount of genetic exchange among breeding groups is needed for effective conservation of vulnerable marine migratory species. This is particularly true of the flatback turtle ( Natator depressus ), which only breeds in Australia but has extensive migrations that can include international waters. This study investigated the phylogeography and genetic structure among 17 flatback turtle rookeries across their range by sequencing an 810 bp portion of the mitochondrial DNA in 889 samples and genotyping 10 microsatellite loci in 598 samples. There was low phylogenetic divergence among haplotypes and evidence of recent population expansion, likely in the late Pleistocene. A predominant haplotype was found across all rookeries, but other haplotype groups were regionally specific. In general, there was agreement in patterns of genetic differentiation in the mitochondrial DNA and microsatellite data, and in some pairwise comparisons a higher mutation rate of microsatellites provided stronger evidence of differentiation. These results suggest natal philopatry operates in the choice of breeding locations for males as well as females. Evidence of genetic connectivity among neighbouring rookeries led to the identification of seven genetic stocks. Geographic boundaries of rookeries used by genetic stocks varied widely (160–1,300 km), highlighting a need for field studies to better understand movement patterns. Hierarchical analysis of molecular variance identified significant genetic differentiation based upon genetic stock, nesting phenology (summer vs. winter nesters), and a west–east discontinuity across Torres Strait. A pattern of isolation by distance was identified, which was most strongly observed in the microsatellite data. In combination with tagging and telemetry studies, these results will allow better quantification of stock‐specific threats along migratory routes and in foraging habitats. Implications of climate change will be stock specific and may depend upon the extent of genetic connectivity between neighbouring stocks.
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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 | 0.000 |
| 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".