Site occupancy and spatial co-occurrence of boreal small mammals are favoured by late-decay woody debris
Bibliographic record
Abstract
Dwindling stocks of decaying coarse woody debris (CWD), as a result of forest management and growing interest for biofuels, may jeopardize the persistence of a broad spectrum of organisms such as small mammals. In this study, we quantified the effects of CWD in late-decay stages on the occupancy dynamics of small mammals in managed and unmanaged boreal forests. Probabilities of initial site occupancy, colonization, local extinction, and co-occurrence were modelled for five boreal small mammal species. Southern red-backed voles (Myodes gapperi Vigor) and southern bog lemmings (Synaptomys cooperi Baird) were more likely to occupy sites with high volumes of late-decay CWD early in the summer. The probability of local extinction for deer mice (Peromyscus maniculatus Wagner) slightly decreased with an increasing volume of late-decay CWD in harvested sites. Southern red-backed voles and meadow voles (Microtus pennsylvanicus Ord) co-occurred more often in old, uncut forests, as well as harvested sites with high volumes of late-decay CWD. These results suggest that cover provided by late-decay CWD benefited two small rodent species during early reproduction and increased persistence of deer mice later in the summer. Finally, we found that in addition to high live-tree basal areas, high late-decay CWD volume also favours local diversity of small mammals.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".