Increasing fire frequency and severity will increase habitat loss for a boreal forest indicator species
Bibliographic record
Abstract
Abstract Climate change will lead to more frequent and more severe fires in some areas of boreal forests, affecting the distribution and availability of late‐successional forest communities. These forest communities help to protect globally significant carbon reserves beneath permafrost layers and provide habitat for many animal species, including forest‐dwelling caribou. Many caribou populations are declining, yet the mechanisms by which changing fire regimes could affect caribou declines are poorly understood. We analyzed resource selection of 686 GPS‐collared female caribou from three ecotypes and 15 populations in a ~600,000 km2 region of northwest Canada and eastern Alaska. These populations span a wide gradient of fire frequency but experience low levels of human‐caused habitat disturbance. We used a mixed‐effects modeling framework to characterize caribou resource selection in response to burns at different seasons and spatiotemporal scales, and to test for functional responses in resource selection to burn availability. We also tested mechanisms driving observed selection patterns using burn severity and lichen cover data. Caribou avoided burns more strongly during winter relative to summer and at larger spatiotemporal scales relative to smaller scales. During the winter, caribou consistently avoided burns at both spatiotemporal scales as burn availability increased, indicating little evidence of a functional response. However, they decreased their avoidance of burns during summer as burn availability increased. Burn availability explained more variation in caribou selection for burns than ecotype. Within burns, caribou strongly avoided severely burned areas in winter, and this avoidance lasted nearly 30 years after a fire. Caribou within burns also selected higher cover of terrestrial lichen (an important caribou food source). We found a negative relationship between burn severity and lichen cover, confirming that caribou avoidance of burns was consistent with lower lichen abundance. Consistent winter avoidance of burns and severely burned areas suggests that caribou will experience increasing winter habitat loss as fire frequency and severity increase. Our results highlight the potential for climate‐induced alteration of natural disturbance regimes to affect boreal biodiversity through habitat loss. We suggest that management strategies prioritizing protection of core winter range habitat with lower burn probabilities would provide important climate‐change refugia for caribou.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".