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Record W2800095792 · doi:10.1002/jwmg.21482

Genetic structure in Elk persists after translocation

2018· article· en· W2800095792 on OpenAlexaboutno aff
Lisa I. Muller, Jennifer L. Murrow, Jason L. Lupardus, Joseph D. Clark, Joseph Yarkovich, William H. Stiver, E. Kim Delozier, Brittany L. Slabach, John J. Cox, Bradley F. Miller

Bibliographic record

VenueJournal of Wildlife Management · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsnot available
FundersUniversity of TennesseeTennessee Wildlife Resources Agency
KeywordsNational parkPopulationChromosomal translocationInbreedingGenetic driftEcologyBiologyGeographyZoologyGenetic diversityDemographyGeneticsGene

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.005
GPT teacher head0.202
Teacher spread0.197 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations20
Published2018
Admission routes1
Has abstractyes

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