Rapid loss of genetic variation and increased inbreeding in small and isolated populations of Norwegian wild reindeer
Bibliographic record
Abstract
Abstract Wildlife responses to habitat loss and fragmentation are a central concern in the management and conservation of biodiversity. Small and isolated populations are vulnerable, both due to demographic and genetic mechanisms, which are often linked. Thus, understanding how (changes in) genetic diversity, effective population sizes, and levels of inbreeding relate to population size and degree of isolation is key for developing effective conservation strategies. High-density Single Nucleotide Polymorphism (SNP) arrays represent an increasingly cost-efficient tool to achieve the data needed for such analysis. Here, we present the development of a novel 625k SNP array for reindeer Rangifer tarandus and apply this array to assess conservation genetic issues across thirteen Norwegian wild reindeer populations of varying size, isolation, and genetic origin (i.e., semi-domesticated reindeer origin or a mix of wild reindeer and semi-domesticated reindeer origins). Many of these populations are currently completely isolated, with no gene flow from other populations. We genotyped n = 510 individuals sampled by hunters and found that variation in population size across the populations largely predicted their (recent loss of) genetic variation (observed heterozygosity, H o ), as well as effective population size (N e ) and (change in) level of recent inbreeding. For the smallest and most isolated populations, with total population sizes of <50-100 individuals and a high and increasing level of recent inbreeding, estimated loss of genetic variation was as high as 3-10% over the time span of a generation or less, and estimated N e was as low as six individuals. With the current level of isolation and associated lack of gene flow, and considering their already low genetic diversity, these populations are hardly viable – neither demographically nor genetically – in the long term. These results have direct relevance for the management of Norwegian wild reindeer, recently red-listed as ‘Near Threatened’. Yet, these genetic challenges, characterizing many of the small ‘wild reindeer’ populations in Norway, have been largely ignored by management thus far. Mitigation efforts such as reducing barriers would introduce substantial conservation dilemma due to the aim of avoiding further spread of chronic wasting disease (CWD), as well as potential further domestic introgression into populations with genetically wild reindeer (or mixed) origin. Nevertheless, our cost-efficient and high-density SNP array especially designed for reindeer and caribou offers a powerful genetic tool to include in future monitoring, providing important contributions to management and conservation decisions.
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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 | 0.001 | 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".