Genetic assessment and monitoring of wild, captive, and reintroduced northern leopard frog populations
Bibliographic record
Abstract
Abstract The northern leopard frog ( Lithobates pipiens ) has undergone dramatic declines in population size and range over recent decades in western Canada and the United States. In British Columbia, only a single population remains at the Creston Valley Wildlife Management Area. Yet, the continuing viability of this population is uncertain. In this paper, the current genetic structure of northern leopard frog populations in western Canada was assessed using microsatellite markers. Historical samples from the extinct population of Fort Steele in British Columbia were compared with the Creston Valley population to understand changes in population genetic parameters over time. Genotypic data from four populations (Creston Valley, Drain K, Prince Spring, and Cypress Hill) sampled in 2004 and 2019 were compared. To evaluate changes in the genetic diversity of the Creston Valley population over time, allelic richness and expected heterozygosity of the population were compared at three time points using genotypes from 2000, 2004, and 2019. Northern leopard frog populations in western Canada showed high genetic differentiation, with genetic diversity decreasing from east to west. Although there weren’t notable changes in genetic parameters between 2004 and 2019, there was evidence of a decline in diversity between 2000 and 2019. The extinct population of Fort Steele had private alleles, while the current Creston Valley population did not, suggesting a genetic bottleneck in the Creston Valley population. Therefore, genetic rescue, specifically for the endangered Creston Valley population, can be considered as an action to support recovery. Additionally, continued genetic monitoring will help in the effective management of the species by providing information on the success of conservation actions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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 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".