The response of mammals to forest fire and timber harvest in the North American boreal forest
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT 1. This paper reviews and compares the effects of forest fire and timber harvest on mammalian abundance and diversity, throughout successional time in the boreal forest of North America. 2. Temporal trends in mammal abundance and diversity are generally similar for both harvested and burned stands, with some differences occurring in the initiation stage (0–10 years post disturbance). 3. Small mammals and ungulates are most abundant immediately post disturbance, and decrease as stands age. Lynxes and hares utilize mid‐successional stands, but are rare in young and old stands. Bats, arboreal sciurids and mustelids increase in abundance with stand age, and are most abundant in old growth. 4. Substantial gaps in the data exist for carnivores; the response of these species to fire and harvest requires research, as predator–prey interactions can affect mammal community structure in both early and late successional stages. 5. The lack of explicit treatment of in‐stand forest structure post disturbance, in the reviewed literature made comparisons difficult. Where forest structure was considered, the presence of downed woody material, live residual trees and standing dead wood were shown to facilitate convergence of mammal communities to a pre‐disturbance state for both disturbance types. 6. Mammalian assemblages differed considerably between successional stages, emphasizing the importance of maintaining stands of each successional stage on the landscape when implementing forest management strategies.
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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 it