Presence of Cavities in Snags Retained in Forest Cutblocks: Do Management Policies Promote Species Retention?
Bibliographic record
Abstract
Tree cavities, which are frequently excavated by primary cavity nesters, are typically used by a number of avian and non-avian species and are thus important components in maintaining biodiversity in forest ecosystems. One way to provide these habitat opportunities in harvested areas is through the retention of snags. In this study, we assessed the habitat and snag characteristics that promote cavity excavation, using the presence of cavities to infer activity of primary cavity excavators. Snags retained closer to the forest/cutblock edge contained a greater density of cavities than trees further from edge. However, the proportion of cavities found within cutblocks declined at a more rapid rate with distance from edge than did those in adjacent forested stands. There was also a tendency for cavities to occur more frequently in trees that were at the advanced stages of decay. The results of our study suggest management for snags in harvest areas should include the retention of snags closer to the forest edge combined with incorporating trees showing signs of advanced decay.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".