CAUSES AND CONSEQUENCES OF VARIATION IN GENOMIC DIVERSITY IN SABLE ISLAND FERAL HORSES
Bibliographic record
Abstract
Understanding how likely a population is to persist in a changing environment helps inform conservation priorities and strategies. It requires a multi-pronged approach to assess the genetic health of a population, which can be difficult to achieve in endangered species. Feral populations of domestic species act as useful models for this purpose, owing to the large knowledge base and advanced genetic tools associated with those species. The feral horses (Equus caballus) of Sable Island, Canada are one such population and are of conservation interest themselves. In order to approach a holistic understanding of the horses' genetic health to assess their likelihood to persist long-term, I employed a variety of genomics approaches using ~40 000 Single Nucleotide Polymorphisms (SNPs) from 239 horses. Firstly, I investigated the genomic-level consequences of inbreeding by looking at runs of homozygosity (ROH) in Sable Island horses and 33 domestic horse breeds, and identified signatures of selection unique to the population compared to their domestic counterparts. Next, I investigated the fitness consequences of inbreeding (inbreeding depression; ID) and the intrinsic and extrinsic drivers thereof. Finally, I assessed fine-scale population genetic structure, barriers to gene flow and local adaptation using landscape genomics techniques. I discovered that Sable Island horses' homozygosity is on par with the most inbred domestic breeds, with ROH length indicating more recent inbreeding. Nine ROH islands were identified in Sable Island horses, suggesting signatures of selection related to immune function and metabolism. Inbreeding depression was seen for body condition (BC), fecal egg count (FEC) and age at first reproduction (AFR), but varied depending on horse age, reproductive status and island location. Population structure revealed two genetic groups with significant admixture between them. Access to freshwater via ponds versus wells appeared to act as a barrier to gene flow, and signatures of selection were associated with differences in water source and location. Taken together, this suggests adaptive genetic variation exists within the population and has the potential to persist into the future. However, the population is vulnerable to the negative effects of small population size and low genetic diversity; as the population remains isolated, the severity of inbreeding depression is likely to increase. If the landscape becomes more or less heterogeneous over time, population structure may become more distinct or gene flow across the island may increase, respectively. Overall, this research indicates the necessity that management strategies address all geographic locations and life history stages of the population of interest, whether it be livestock or wildlife.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".