Conservation genetics of the endangered Spotted Turtle (<i>Clemmys guttata</i>) illustrate the risks of “bottleneck tests”
Bibliographic record
Abstract
Studies of population genetics in turtles have suggested that turtles do not experience genetic impacts of bottlenecks as strongly as expected. However, recent studies cast doubt on two commonly used tests implemented in the program BOTTLENECK, suggesting that these findings should be re-evaluated. The Spotted Turtle (Clemmys guttata (Schneider, 1792)) is endangered both globally and within Canada, but genetic data required to develop effective recovery strategies are unavailable. Here, we conducted the first study of population genetic structure in C. guttata. We then used multiple small populations of C. guttata as replicates to test whether the commonly used program BOTTLENECK could detect the genetic signature of bottlenecks in our study populations, which are all thought to have experienced significant declines in the past 2–3 generations (75 years). Turtles (n = 256) were genotyped at 11 microsatellite loci. A suite of Bayesian population genetics analyses and a principal coordinates analysis identified a minimum of 6 distinct genetic populations and a maximum of 10 differentiated subpopulations across the sampled Canadian range of C. guttata, which corresponded to demographically independent units. BOTTLENECK failed to detect population declines. A literature review found that bottleneck tests in 17 of 18 previous genetic studies of tortoises and freshwater turtles were based on suboptimal sampling, potentially confounding their results. High retention of genetic diversity (allelic richness and heterozygosity) in isolated populations of C. guttata and other turtle species is encouraging for species recovery, but conclusions about the prevalence of genetic bottlenecks in such populations should be re-examined.
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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 | 0.001 |
| 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".