Effective population size and genetic structure of a Piute ground squirrel (<i>Spermophilus mollis</i>) population
Bibliographic record
Abstract
Piute ground squirrels (Spermophilus mollis) are distributed continuously in habitat dominated by native shrubs and perennial grasses in the Snake River Birds of Prey National Conservation Area in Idaho, U.S.A. This habitat is being fragmented and replaced by exotic annual plants, changing it to a wildfire-dominated system that provides poor habitat for ground squirrels. To assess potential effects of this fragmentation on ground squirrel populations, we combined an estimate of effective population size (Ne) based upon a demographic study with a population genetic analysis. The study area included three subpopulations separated from each other by 813 km. The ratio of effective population size to census number (Ne/N) was 0.57. Combining Ne/N with dispersal distances from a radio-tracking study, we calculated that neighborhood size was 62.2 ha, which included between 204 and 480 individuals. Our population genetic analysis (based on randomly amplified polymorphic DNA (RAPD) and microsatellite markers) showed relatively low levels of genetic differentiation (Qpopulations[Formula: see text] 0.070.10) between subpopulations and no inbreeding within subpopulations (f = 0.0003). These estimates of population subdivision translate into an effective migration rate (Nem) of 2.33.3 per year, which represents a high level of gene flow. Invasion by exotics will reduce the overall productivity of the habitat, and will lead to isolation among subpopulations if favorable habitat patches become isolated.
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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 | 0.000 |
| 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) | 0.001 | 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".