Site occupancy by American martens and fishers in temperate deciduous forests of Québec
Bibliographic record
Abstract
are two sympatric mesocarnivores in eastern North American forests. Due to their larger size, fishers have a competitive advantage over martens. We investigated site occupancy of martens and fishers in temperate deciduous forests of Québec, an environment modified by forest management and climate change. We formulated hypotheses on the spatial distribution of the studied species based on the knowledge of local trappers and on the scientific literature regarding forest cover composition, habitat fragmentation, and competitive relationships. We used a network of 49 camera traps monitored over two fall seasons to document site occupancy by both species. We used two-species site occupancy models to assess habitat use and the influence of fishers on martens at spatial grains of different sizes. None of the habitat variables that we considered explained site occupancy by fishers. Availability of dense old coniferous stands explained the spatial distribution of martens both at the home range grain size and at the landscape grain size. We identified the characteristics of habitat hotspots based on the knowledge of trappers, which highlighted the importance of stand composition, height, age, and canopy closure. The characteristics of habitat hotspots for martens in temperate deciduous forests refine the habitat suitability model for American martens that was originally developed for boreal forests of Québec.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".