Investigating hotspots of Parelaphostrongylus spp. transmission to moose (Alces alces) in Western Manitoba
Bibliographic record
Abstract
Moose (Alces alces) are a conservation concern for managers in areas of Manitoba due to slower than anticipated recovery from population declines. One factor potentially affecting their recovery is infection with pathogenic protostrongylid parasites. Meningeal worm (Parelaphostrongylus tenuis) and muscle worm (Parelaphostrongylus andersoni) infect moose, but only meningeal worm is known to cause severe pathology. These parasites also infect white-tailed deer (WTD, Odocoileus virginianus), which are thought to be the primary hosts spreading larval parasites in the environment. In Chapter 1, we investigated the spatial and temporal variation of protostrongylid infections in WTD to determine transmission hotspots. In four game-hunting areas in Western Manitoba, we found that prevalence of Parelaphostrongylus spp. in WTD feces was higher in two areas where managers are concerned for moose populations. Genetic analyses of the partial cytochrome c oxidase I gene revealed that parasite species co-occurred in three areas, which extended the southern range of muscle worm in Manitoba. In Chapter 2, we measured host density and habitat type to predict where and when transmission risk was highest. We assessed the spatial and temporal variation of host density (WTD fecal pellets and gastropods) and gastropod species richness. In addition, we determined whether larval parasite prevalence in WTD feces was associated with host density or habitat type. Only gastropod species richness was associated with areas where moose populations are of conservation concern. In addition, gastropod densities were higher in late summer, particularly in grasslands and forests. Although parasites tended to be found in mixed-wood and coniferous forests, there was no association with habitat. Our results suggest that moose have higher risk of protostrongylid transmission in areas with conservation concern due to higher Parelaphostrongylus spp. larval prevalence in WTD and higher gastropod host species richness. Moose have a higher risk of infection in late summer due to higher gastropod host densities and species richness. Further, WTD are transmitting not one, but two parasites suggesting the importance of determining the pathology of muscle worm to moose. Conservation efforts aimed at preventing moose declines should incorporate these higher risk areas into their management plans.
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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".