Marten Habitat Selection in a Clearcut Boreal Landscape
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Bibliographic record
Abstract
Abstract: To describe the forest mosaic suitable for marten ( Martes americana ) in a clearcut boreal landscape, we studied habitat selection in an area (123 km 2 ) located in western Québec, in which black spruce ( Picea mariana ) was the predominant forest type. This block had been recently clearcut with the protection of regeneration cutting technique, a logging method that employs equally spaced harvesting trails. The resulting landscape had a center dominated by a cutover matrix (60% of the block) and surrounded by contiguous uncut forest. Over 2 years, 20 marten equipped with radio collars provided enough locations to delineate their winter home range. Habitat composition and spatial configuration were measured at both stand and landscape scales by means of a geographic information system database that included telemetry locations and home ranges, forest maps, and limits of clearcut areas. Inside their winter home ranges, animals avoided open regenerating stands composed mostly of recent clearcuts with sparse regeneration. They did not select coniferous stands, even those that were mature or overmature, but preferred deciduous and mixed stands, a large proportion of which had a dense coniferous shrub layer as a result of a spruce budworm ( Choristoneura fumiferana ) epidemic 15–20 years ago. At the landscape scale, winter home ranges differed from random mosaics because they had a larger proportion of uncut forest (>30 years), a smaller proportion of open regenerating stands, larger core area in forest habitat, and less edge between open regenerating stands and forest. Winter home ranges usually contained <30–35% open or closed regenerating stands and> 40–50% uncut forest. We conclude that marten and clearcutting may be compatible, provided that forest logging is adapted to that species at the landscape level. Where the objective is to maintain marten at a local scale in black spruce forest, we suggest that ≥50% uncut forest be preserved inside 10‐km 2 units and that <30% of the area be clearcut over a 30‐year period.
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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) | 0.008 | 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