Rapid recovery of boreal rove beetle (Staphylinidae) assemblages 16 years after variable retention harvest
Bibliographic record
Abstract
Post‐harvest recovery of biodiversity is one of important goals in modern forestry. A variable retention (VR) approach has been of particular interest in North America because it promotes rapid faunal recovery, while minimizing negative lasting impacts of logging on the natural fauna. We studied responses of rove beetles (Coleoptera: Staphylinidae) to a broad range of retention harvests (2, 10, 20, 50 and 75% retention) in comparison to uncut controls as part of the Ecosystem Management Emulating Natural Disturbance (EMEND) experiment in the boreal mixedwood forest of western Canada. We sampled beetles using pitfall traps 1, 2, 11 and 16 years post‐harvest in replicated (n = 3) stands representing four cover types (deciduous‐dominated, deciduous with spruce understory, mixed and coniferous‐dominated). We collected 74 263 individuals distributed across 99 species (excluding Aleocharinae). Estimated species richness was highest in clear‐cuts until year 11, but by year 16 species richness was similar among treatments. Species composition initially varied strongly in relation to intensity of harvest treatments, but overall variation decreased with time, and by year 16, species composition overlapped among most treatment combinations. Assemblages recovered more quickly in early successional (deciduous‐dominated) than in late successional (mixed and conifer‐dominated) stands. Overall, our results show that rove beetle assemblages in stands harvested to all VR prescriptions converged more rapidly toward those in fire‐origin mature stands than did assemblages in clear‐cuts over the first 16 years post‐harvest. Thus, it demonstrates that even modest levels of forest retention can facilitate the recovery of staphylinid assemblages in managed landscapes.
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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 | 0.001 |
| 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) | 0.002 | 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 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".