Spatial ecology and resource selection of a high-elevation American marten (<i>Martes</i> <i>americana</i>) population in the northeastern United States
Bibliographic record
Abstract
High-elevation forests that contain mature, closed canopy stands are considered important habitat for American martens (Martes americana (Turton, 1806)) in the northeastern United States. To investigate this hypothesis, we monitored 15 radio-collared martens over a 2-year period and measured spatial use, as well as second- and third-order resource selection, from 33 seasonal home ranges and 889 telemetry locations. The population was composed primarily of adults that had small home-range size with average seasonal fidelity. During leaf-off seasons, martens selected against regenerating forest at both scales and selected for mixedwood and softwood forests and areas with rugged terrain within home ranges. Second-order selection was less pronounced during leaf-on seasons, yet martens exhibited greater selection for hardwood forest and areas with rugged terrain within home ranges. Home-range size was correlated positively with the amount of regenerating forest and body-condition index scores were lower during winter, indicating that these spatial and temporal attributes were influential. Although martens utilized low-elevation forest with extensive timber harvesting, contiguous, mature, and rugged high-elevation forest was used preferentially during winter. Land managers should minimize disturbance of montane ecosystems to ensure population viability for martens and other boreal forest species along distributional edges.
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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 | 0.000 |
| 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 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".