The direct and habitat-mediated influence of climate on the biogeography of boreal caribou in Canada
Bibliographic record
Abstract
Effective species conservation efforts require insight into whether a species’ extent of occurrence may shift due to changing climate, habitat loss, or both. The extent of occurrence of the threatened boreal population of woodland caribou (Rangifer tarandus caribou; caribou) has contracted due to environmental and anthropogenic disruption, with further contractions predicted as boreal habitat shifts with the changing climate. However, the direct and indirect climate drivers of caribou extent of occurrence have not been explicitly investigated. We estimated and compared the influence of climate and habitat drivers on the occurrence of caribou ranges across the Canadian boreal forest. We fit path models that estimated the direct effects of climate on caribou range occurrence and its indirect effect through climate's influence on caribou habitat (i.e., forest cover, presence of peatland, human disturbance and wildfire). Our analysis suggests that the distribution of caribou ranges is less sensitive to the direct effects of climate than to those of habitat and human disturbance. However, through its relationship to caribou habitat, climate exerts indirect influence over the distribution of caribou. As the climate changes, future distributions of caribou may be more heavily relegated to refuge habitats, particularly peatlands in the western boreal forest. Our biogeographical approach enables more informed decisions for large-scale caribou conservation efforts (e.g. establishment of protected areas, habitat restoration) that account for potential shifts in the distribution of caribou under changing environmental and climatic conditions.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".