Investigating potential for competition between migratory caribou and introduced muskoxen
Bibliographic record
Abstract
Abstract Several caribou ( Rangifer tarandus ) populations co‐occur with endemic or introduced populations of muskoxen ( Ovibos moschatus ), which has led to concerns about the potential competition between the species, especially in regions where the growth of muskoxen populations coincides with caribou declines. We evaluated the potential for competition between migratory caribou and an introduced muskoxen population in northern Québec, Canada, at multiple spatial scales, from 2017 to 2019. We investigated space use and habitat selection patterns of satellite‐collared caribou and muskoxen, and analyzed fecal samples using DNA metabarcoding to assess diet overlap. Annual overlap between ranges was low and occurred primarily during caribou spring migrations on the coast of Hudson Bay, and during summer on the coast of Ungava Bay. During spring, muskoxen selected shrub‐dominated areas close to the coast, whereas caribou selected rock‐substrate tundra and low elevations within their overlapping ranges. Thus, co‐occurrence was low and remained limited to the vicinity of the Hudson Bay. In summer, muskoxen selected productive coastal areas and caribou selected erect‐shrub tundra; both species selected prostrate‐shrub tundra. This led to a higher co‐occurrence in the Ungava Bay study area relative to the Hudson Bay study area. We found similarities in the diets of the 2 species at the plant family level, with shrubs being commonly consumed by both species across seasons. We conclude that, at a broad spatial scale, there was limited potential for seasonal space use and diet overlap between caribou and muskoxen in our study area. Still, multiple sources of uncertainty remain such as local impacts of herbivory by muskoxen, demographic and distribution patterns of both species, trophic interactions with predators, shared diseases and parasites, and climate change. These sources of uncertainty could be mitigated through the elaboration of local management plans and community‐based monitoring.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".