Patterns of Contemporary Genetic Variation and Effective Population Size in Blanding's Turtle Populations
Bibliographic record
Abstract
Adequate genetic variation in a population is fundamental to reducing the risk of inbreeding depression in the short term and maintaining its ability to respond to evolutionary forces over the long term. There are now several studies that use microsatellite loci to assess genetic variation within populations across the geographic range of Emydoidea blandingii (Blanding's Turtle), but direct comparisons among studies have not been conducted. We present estimates of allelic richness (A) and expected heterozygosity (HE) from 59 localities across much of the species'geographic range and compare them using a resampling method that calibrates values relative to a reference population to account for different sample sizes and microsatellite panels. We further compared these measures between 2 datasets, from the midwestern US and from the northeastern US, that were made compatible using a sample of re-genotyped individuals. In both cases, we found lower A and HE in the northeastern localities. We also developed a sensitivity analysis of effective population size (Ne) estimation with the linkage disequilibrium method (NeLD) that used a well-sampled population modelled in the program ‘NeOGen’ to explore the effects of adult population size (Nc), sample size, and locus number while accounting for overlapping generations, life history, and demography. We find that it is possible to estimate Ne with accuracy and precision in populations with Nc < 400 when sample size is ∼25% of adult population size and ≥11 microsatellite loci are used. With this benchmark, we then estimated NeLD in 7 localities using single-sample linkage disequilibrium in NeEstimator, a method that does not account for overlapping generations, demography, and life history but is more accessible for users. This approach overestimated NeLD by ∼37%. Collectively, our analyses of genetic variation within populations facilitate assessment of population status and resiliency in Blanding's Turtles by demonstrating the range of genetic variation across a large number of populations and developing a baseline for the estimation of effective population size in natural populations.
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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 | 0.001 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".