Can retention harvests help conserve wildlife? Evidence for vertebrates in the 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 Retention harvesting, or the approach of leaving live mature trees behind during forest harvest, is used in natural disturbance‐based management to mitigate the effects of logging on biodiversity. However, responses of many boreal vertebrates to variable retention harvesting are unknown. We investigated the influence of different retention levels in forest harvests on stand use by wildlife 15–18 yr post‐harvest using a combination of surveys of wildlife signs (scats, middens) and camera trapping. Site‐level measures of forest structure, including canopy cover, horizontal cover, tree height, tree diameter, basal area, cover of downed coarse woody material, and understory plant cover, were used to describe post‐harvest differences in habitats used by common wildlife species in northwest Alberta's boreal forest. Stand use of six species (black bear, coyote, fisher, red squirrel, wolverine, woodland caribou) increased with level of retention, while stand use of two species (grouse, snowshoe hare) declined with retention level. Retention level did not significantly affect stand use of five species (American marten, Canada lynx, deer, gray wolf, moose). Higher levels of retention characterized by greater canopy cover, basal area, and abundance of deadwood were associated with use of forest habitats by late‐seral species. Woodland caribou, a species of conservation concern, was detected only in harvested stands with at least 20% retention. Greater understory and horizontal cover characterized lower levels of retention being attractive for early‐seral species. These findings demonstrate the value of retention harvesting for conservation of wildlife species in boreal forest, while highlighting the challenge of managing forests for multiple species with different habitat preferences.
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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 | 0.000 | 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) | 0.001 | 0.001 |
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