The Effects of Forest Harvesting on Small Mammals in Western Newfoundland and its Significance to Marten
Bibliographic record
Abstract
The depauperate fauna of Newfoundland provides a limited prey base for marten. Only two small mammal prey species, Microtus pennsylvanicus and Sorex cinereus, were found in any abundance in the old-growth forests of the study area. Of these two, Microtus displayed population fluctuations typical of most microtines. Analysis of marten scats indicated that Microtus is a very important prey item to the marten with other food. items being of lesser importance particularly when Microtus are abundant. Trapping in various habitats indicated that Sorex densities were three to five times higher in logged areas compared to uncut areas. Unfortunately, the effects of logging on Microtus could not be determined directly from this study. Microtus numbers declined drastically in the spring of 1987, apparently independently of logging operations. Microtus numbers dropped from a density of 25.0 per hectare in the spring of 1986 to virtually zero in the spring of 1987. This reduction may be linked to an outbreak of viral encephalitus in the marten population in the fall of 1986. Marten (Martes arnericana) prefer mature coniferous and mixed forests and utilize regenerating cutovers minimally. The reasons for this are unclear, although prey abundance and availability may be involved. In this study, Sorex were more abundance in regenerating cutovers and the literature suggests that Microtus are also more abundant in these areas. This would seem to suggest that prey abundance above certain threshold densities is not critical to marten habitat selection. However, prey availability may play a more important role. Although prey species may be more abundance in logged areas, prey availability may be reduced.
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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 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".