Genetic structuring of Fishers in British Columbia, Canada: implications for population conservation and management
Bibliographic record
Abstract
Abstract In the westernmost Canadian province of British Columbia, fishers (Pekania pennanti) occur in low-elevation forested ecosystems in the central and northern portions of the province, with several substantial mountain ranges and rivers bisecting this distribution. The effect of these geographic features on gene flow and population structuring is unknown and may contribute to fishers differentiating into 2 or more populations within the province. To better understand population structuring within the range of fishers in British Columbia, we collected tissue samples from 491 fishers from throughout the province and evaluated variation of neutral genetic markers using a 385-base pair section of the mitochondrial DNA control region and 13 microsatellite loci. Fishers appeared to be genetically structured as hierarchical stepping-stone populations where an upper hierarchical level of genetic partitioning resulted in 2 populations at the provincial scale, with 3 subpopulations occurring in the central interior region. We observed gene flow of 2 to 5 migrants per generation between the 2 upper populations, which was substantially less than the 90 migrants per generation estimated as needed to maintain genetic homogeneity. This resulted in differentiated upper populations (haplotype FST = 0.272, microsatellite FST = 0.049) characterized by relatively low Ne (Columbian population = 252, 95% CI = 185 to 332; Boreal population [British Columbia only] = 136, 95% CI = 92 to 234). The consequence of low gene flow and resultant population structuring is that the Columbian population likely receives relatively little genetic and demographic support from other populations and, combined with precipitous recent declines in its numbers, puts this population at heightened conservation risk. As a result, swift and effective actions are needed to conserve this vulnerable population of fishers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".