Introgression of exotic <i>Cervus</i> (<i>nippon</i> and <i>canadensis</i>) into red deer (<i>Cervus elaphus</i>) populations in Scotland and the English Lake District
Bibliographic record
Abstract
Abstract Since the mid‐19th century, multiple introductions of Japanese sika deer ( Cervus nippon nippon ) and North American wapiti ( C. canadensis ) have taken place in the British Isles. While wapiti have generally been unsuccessful, sika have been very successful, especially in Scotland where they now overlap at least 40% of the range of native red deer ( C. elaphus ). Hybridization between these two species and red deer has been demonstrated in captivity and in the wild. Using a panel of 22 microsatellite loci that are highly diagnostic between red deer and sika, and moderately diagnostic between red deer and wapiti, we investigated the extent of introgression between these species in 2,943 deer sampled from around Scotland and from the English Lake District using the Bayesian clustering software STRUCTURE . We also used a diagnostic mitochondrial marker for red deer and sika. Our survey extends previous studies indicating little introgression of wapiti nuclear alleles into red deer, in particular in Northern Scotland, Kintyre, and the Lake District. We found a new area of extensive sika introgression in South Kintyre. In the North Highlands, we show for the first time geographically scattered evidence of past hybridization followed by extensive backcrossing, including one red‐like individual with sika introgression, two sika‐like individuals with red deer introgression, and six individuals that were apparently pure sika at the nuclear markers assessed but which carried red deer mitochondria. However, there has not been a collapse of assortative mating in this region. Similarly, in the English Lake District red deer, we found only traces of past sika introgression. No sika alleles were detected in the Central Highlands or the Hebridean red deer refugia. We make suggestions for management to prevent further spread of sika alleles into red deer and vice versa .
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".