Smaller and more numerous harvesting gaps emulate natural forest disturbances: a biodiversity test case using rove beetles (Coleoptera, Staphylinidae)
Bibliographic record
Abstract
ABSTRACT Aim To evaluate changes in the abundance, species richness and community composition of rove beetles (Coleoptera, Staphylinidae) in response to three configurations of experimental gap cuts and to the effects of ground scarification in early succession yellow birch‐dominated boreal forest. In each experimental treatment, total forest removed was held constant (35% removal by partial cutting with a concomitant decrease in gap size) but the total number of gaps was increased (two, four and eight gaps, respectively), resulting in an experimental increase in the total amount of ‘edge’ within each stand. Location Early succession yellow birch‐dominated forests, Quebec, Canada. Methods Pitfall traps, ANOVA, MIXED procedure in sas ®, post hoc Tukey's adjustment, rarefaction estimates, sum‐of‐squares and distance‐based multivariate regression trees (ssMRT, dbMRT). Results Estimates of species richness using rarefaction were highest in clearcut and two‐gap treatments, decreased in smaller and more numerous gaps and were significantly higher in scarified areas than in unscarified areas. ANOVA indicated a significant impact of harvesting on the overall standardized catch. Post hoc Tukey's tests indicated that the total catch of all rove beetles was significantly higher in uncut forests than in the treated areas. Both sum‐of‐squares and distance‐based multivariate regression trees indicated that community structure of rove beetles differed among treatments. Assemblages were grouped into (a) control plots, (b) four‐ and eight‐gap treatments and (c) two‐gap and clearcut treatments. Main conclusions Rove beetle composition responded significantly to increasing gap size. Composition among intermediate and small‐sized gap treatments (four‐ and eight‐gap treatments) was more similar to uncut control forests than were larger gap treatments (two‐gap) and clearcuts. Effects of scarification were nested within the harvested treatments. When the total area of forest removed is held constant, smaller, more numerous gaps are more similar to uncut control stands than to larger gaps and falls more closely within the natural forest heterogeneity.
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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 | 0.008 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".