Early colonization of white spruce deadwood by saproxylic beetles in aggregated and dispersed retention
Bibliographic record
Abstract
Retention harvests may leave retention in aggregations evenly dispersed or in various combinations. Although the relative efficacy of aggregated and dispersed retention for biodiversity conservation is widely debated, there has been little study of combinations. We studied this question relative to saproxylic beetles that initially colonize horizontal and upright coarse woody material (CWM) of white spruce (Picea glauca (Moench) Voss) in boreal mixedwood stands at the Ecosystem Management Emulating Natural Disturbance (EMEND) in northern Alberta 12–13 years after retention prescription. Neither species richness nor emergence of beetles differed among freshly cut bolts exposed as “horizontal” or “upright” in retention patches of two sizes (0.20 ha and 0.46 ha) that were surrounded by different levels of dispersed retention (2%, 20%, and 50%). However, species composition in retention patches differed significantly from those in unharvested controls, except in the larger patches surrounded by 50% dispersed retention, although patterns differed among feeding guilds. Both mycetophage and predator assemblages in patches were similar to those in unharvested controls, suggesting that even relatively small patches retain these guilds regardless of the surrounding matrix quality. Because species composition differed between horizontal and upright bolts, an appropriate mix of horizontal and upright CWM may contribute to conservation of saproxylic beetle faunas.
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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 | 0.000 |
| 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) | 0.001 | 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".