Paradigm Shifts in Habitat Ecology of Threatened Newfoundland Martens
Bibliographic record
Abstract
Abstract: We evaluated multiscale habitat selection by threatened Newfoundland (Canada) martens ( Martes americana atrata ) across landscapes composed of a range of habitat types to test the hypothesis that martens preferred mature (61–80‐yr‐old) and overmature (>80 yr) conifer stands. At both the landscape and stand scales, adult (≥1 yr) resident martens ( n = 58, 92 yr‐specific home ranges) selected for, or used in proportion to availability, a broad range of habitat types, including recent cuts ≤ 5 yr old, regenerating forest <6.5 m, precommercially thinned stands, and mature and overmature forest. Marten home ranges were not dominated by mature and overmature forest; median availability of mature and overmature forest within individual home ranges was only 30% (range = 11–76%). Age distributions were not different among martens with high, intermediate, and low quantity of mature and overmature forest in their home range; our data do not indicate that martens inhabiting ranges with little mature and overmature forest were compromising fitness. Habitat selection by martens in Newfoundland was more generalized than has traditionally been inferred, and we suggest that inherent landscape fragmentation, in combination with absence of many predators and competitors (i.e., ecological release), caused the Newfoundland marten to evolve to use a more generalized habitat niche than many mainland populations of American martens. We recommend that landscapes suitable for marten not exceed >29% younger aged forest. Maintaining resident martens in landscapes where forest harvesting is occurring requires prescriptions that recognize the highly fragmented nature of the natural landscape, the prevalence of mature and overmature forest, younger forests, avoided landcover types, and human access.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".