Genetic structure in Elk persists after translocation
Bibliographic record
Abstract
ABSTRACT Elk (Cervus canadensis) translocation success is thought to be facilitated by high post‐release herd cohesion and limited movements; both should ensure genetic mixing following release. Such mixing is important to reduce potential effects of inbreeding or genetic drift, which can be especially important in small founding populations. We had a natural experiment where we could evaluate genetic mixing of 2 distinct lineages of elk after translocation to the same area. Founding elk ultimately came from north and south of a road barrier at Elk Island National Park (EINPN or EINPS, respectively), Alberta, Canada and the 2 groups were genetically distinct. During 2000 to 2003, elk originating from Elk Island National Park were translocated to Cumberland Mountains, Tennessee (TNCM) and Great Smoky Mountains National Park, North Carolina (GSMNP), USA (some elk spent time at Land Between the Lakes Recreation Area, Kentucky, USA, before their final translocation). At TNCM, translocated elk were hard released, whereas at GSMNP elk were held in pens up to 60 days before release (i.e., soft release). We hypothesized that associations formed in the source population would affect genetic structure in the future population. We predicted that matrilineal groups would stay closer together and have similar movements after translocation. We used 16 microsatellite markers to analyze genetic composition and structure of translocated elk and their offspring in the years after release. Most source elk used for translocation strongly assigned to either EINPN or EINPS (93.2%, n = 204). Evaluating the genetic structure of offspring after translocation, we found the 2 genetic groups mostly persisted ≥11 years following release. We measured the Euclidean distance between all possible pairs of telemetered female elk during each season and year and calculated the maximum distance moved from the release sites for females surviving >1 year. Mean Euclidean distances between pairwise locations of female elk were similar for each genetic cluster for each area. The mean distances for all paired locations (genetic clusters combined) in TNCM were 14.67 km (n = 4,576 ± 13.23 [SD]) and in GSMNP were 9.30 km (n = 1,468 ± 9.75). However, when looking at only simultaneous locations <50 m apart, the frequency of occurrence was higher (P < 0.001) for elk with the same genetic structure (71.1%) compared with those with different structure (28.9%). The maximum distance travelled from the release site was not different for the 2 genetic groups, but EINPN females tended to travel farther. Pairwise female distances were lower in GSMNP where we used a soft release. Release methodology and social structure appear to affect movements and possibly genetic mixing after translocation. Given that restoration success can depend on maintaining genetic diversity and number of founders, our analyses suggest that within‐cluster breeding bias can result in lower genetic variability and a smaller effective population size than previously assumed. © 2018 The Wildlife Society.
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 | 0.000 | 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".