Conservation genetics of Roosevelt elk: population isolation and reduced diversity
Bibliographic record
Abstract
Species reintroductions have the potential to cause genetic bottleneck events resulting in increased genetic drift, increased inbreeding, and reduced genetic diversity creating negative fitness consequences for populations. Roosevelt elk ( Cervus canadensis roosevelti Erxleben, 1777) are “at risk” in British Columbia (BC), Canada. Once widespread along the west coast, Roosevelt elk were likely extirpated from the mainland by 1900 and experienced a substantial population bottleneck on Vancouver Island at that time, and again in the 1950s. Reintroduced to the mainland from Vancouver Island in the 1980s, this re-established population became the source for subsequent mainland translocations. To understand the effects of reintroduction strategy on genetic diversity, we analyzed genetic variation in 355 Roosevelt elk from Vancouver Island and mainland BC. Using mitochondrial DNA and 10 microsatellite loci, molecular analyses showed overall reduced genetic diversity relative to other extant elk populations, genetic isolation of the southern Vancouver Island population, and increased genetic drift among reintroduced herds. Four reintroduced populations were found to have increased levels of inbreeding. Results of this study contribute to our knowledge of reintroduction biology and can be used to guide continued conservation and management of at-risk species.
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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 | 0.000 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 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".