Genetic Diversity and Divergence among Bighorn Sheep from Reintroduced Herds in Washington and Idaho
Bibliographic record
Abstract
ABSTRACT Bighorn sheep (Ovis canadensis) populations in the western United States have undergone widespread declines and extirpations since the late nineteenth century as a consequence of introduced diseases, competition with livestock, and unregulated hunting. Washington, Idaho, USA, and British Columbia, Canada were historically thought to be occupied by 2 bighorn lineages or subspecies: Rocky Mountain (O. c. canadensis) and California (O. c. californiana). The putative California lineage was completely extirpated in the United States, and reintroductions to reestablish populations were sourced directly or indirectly from a single region in southern British Columbia. Restoration efforts have attempted to maintain the diversity and divergence of these 2 lineages, sometimes referred to as subspecies although taxonomic classifications have changed over time. In this study we describe genetic variation in a subset of native and reintroduced herds of California and Rocky Mountain bighorn sheep. We examined genetic diversity and divergence between bighorn sheep herds using 15 microsatellite loci, including 4 loci linked to genes involved in immune function. We analyzed 504 samples from reintroduced herds in Washington (n = 10 California herds, n = 4 Rocky Mountain herds) and Idaho (n = 5 California), and source herds in Oregon (n = 1 Rocky Mountain) and British Columbia (n = 5 California, 1 Rocky Mountain). Genetic structure reflected known reintroduction history, and geographic proximity also was associated with decreased genetic divergence. Herds in Washington and Idaho sourced from California bighorn sheep were less genetically diverse than those sourced from Rocky Mountain herds. Also, levels of relatedness within and across California herds were higher than in Rocky Mountain herds and similar to what would be expected for full and half siblings. Lower diversity and higher relatedness among California herds is a concern for long‐term fitness and likely related to past population bottlenecks, fewer source populations, and management history, such as entirely sourcing California herds from British Columbia. Genetic divergence of neutral loci between California and Rocky Mountain herds was greater than that of adaptive loci, potentially indicating that balancing selection has maintained similar genetic diversity across lineages in loci associated with immune and other adaptive functions. Thus, we recommend future reintroductions and augmentations should continue to use source populations from the appropriate California or Rocky Mountain lineage to avoid potential outbreeding depression and maintain possible adaptive differences. This could be accomplished by obtaining sheep from ≥1 source within the genetic lineage, while avoiding sourcing from admixed herds. Future work encompassing a broader geographic sampling of populations and a greater portion of the genome is necessary to better evaluate the degree to which contemporary divergence between lineages is associated with recent founder effects and genetic isolation or evolutionary adaptation. © 2021 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 | 0.000 |
| 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 | 0.000 |
| 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".