Long-term effects of timber management on marten (Martes americana) habitat potential in an Ontario boreal forest
Bibliographic record
Abstract
To evaluate the hypothesis that current forest management practices in the \nboreal forest are decreasing the quantity and quality of long-term marten \nhabitat, and alternative, more suitable strategies exist, a Geographic \nInformation System (GlS)-based simulation study was initiated to determine \nthe habitat suitability for marten of a boreal forest under various timber management \nstrategies. Two simulation models were used in this study. The \nfirst was the Harvest Schedule Generator (HSG), a wood-supply model created \nat the Petawawa National Forestry Institute (Forestry Canada). The second \nwas a marten Habitat Suitability Index (HSI) model developed for this study. \nEach of the timber harvest strategies decreased the amount of long-term \nmarten habitat. However, slight decreases in the level of spruce harvest \nprovide significant future increases in suitable habitat. In the short term, \ndelayed harvest of mature black spruce stands provides an improvement in \nmarten habitat suitability. The procedures developed in this study provide \nvaluable quantitative information which can be used to aid in forest \nmanagement decision making.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".