Nemabiome sequencing reveals seasonal and age associated patterns of strongyle infection and high prevalence of Strongylus vulgaris in Alberta feral horses
Bibliographic record
Abstract
Unmanaged feral horses, naïve to dewormers, offer a unique opportunity to study natural communities of equine parasites. These communities may include parasites that are rare in managed populations, and these may be transmitted to domestic horses in areas where there is contact between feral and domestic equine populations. There have been only a few studies of gastrointestinal parasite populations in horses, and very few from North American equine populations. This study aimed to gain insights into parasite biology through identification of the strongyle parasite species infecting feral horses in Alberta, Canada, and to test for species-specific infection patterns across season and horse age. Fecal samples (N = 149) were collected from unique individuals in the Sundre Equine Management Zone (EMZ), Alberta, across two years: 2021 (N = 62) and 2022 (N = 87). In 2021, samples were collected in summer (N = 31; 8 foals, 5 subadults, 18 adults) and fall (N = 31; 5 foals, 1 subadult, 25 adults). In 2022, samples were collected in spring (N = 36; 4 subadults, 32 adults), summer (N = 41; 4 foals, 8 subadults, 29 adults), and fall (N = 20; 1 foal, 2 subadults, 17 adults). Fecal egg counts showed that these horses shed high numbers of strongyle eggs relative to domestic horse populations (mean = 1337.01 ± 961.81 epg), and nemabiome analyses identified a total of 34 strongyle species. Species richness and aggregate strongyle FECs were highest in subadults and during the summer, while lowest in foals and during the fall. There was a high prevalence of large strongyle species, especially Strongylus vulgaris (85.91%), with strongyle species-specific prevalence and FECs strongly associated with age and season. Understanding the factors driving species-specific parasite infection provides important information on strongyle parasite ecology and may aid the development of targeted parasite control strategies.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".