Woodland mouse and vole response to increased structural diversity following midrotation commercial thinning in spruce plantations
Bibliographic record
Abstract
We assessed whether commercially thinning (CT) spruce (Picea spp.) plantations (40% basal area removal) can cause structural changes in fine woody debris (FWD) and understory vegetation to improve habitat quality for small rodents in northwestern New Brunswick, Canada. We created three contrasting environments (FWD rich – understory vegetation rich, FWD poor – understory vegetation rich, and FWD poor – understory vegetation poor) by establishing CT with debris retention (merchantable trunk removal), CT with all debris removed (full tree removal), and non-CT (plantation without CT) in six midrotation white spruce (Picea glauca (Moench) Voss) plantations. We live-trapped small mammals in each plantation during spring and summer of 2011 and 2012 and estimated animal density and survival with capture–recapture models. Southern red-backed vole (Myodes gapperi (Vigors, 1830)) density was two to three times greater in CT with debris retention than in either non-CT or CT with debris removal, and their survival rate was twice that in CT with debris removal. Woodland jumping mouse (Napaeozapus insignis (Miller, 1891)) density was two to five times greater in non-CT than in either CT treatment. Deer mice (Peromyscus maniculatus (Wagner, 1845)) did not show any treatment effect. Productivity and demographics were not affected by CT treatment for any species. We found evidence that midrotation spruce plantations are used differently by small mammal species based on stand condition and recommend that managers maintain plantations in CT and non-CT states.
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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 | 0.002 | 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 | 0.000 |
| 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".