Saproxylic beetle (Coleoptera) communities and forest management practices in coniferous stands in southwest Nova Scotia, Canada
Bibliographic record
Abstract
Old-growth forest in Nova Scotia typically exhibits an uneven-aged, multi-layered stand structure and contains significant amounts of coarse woody debris. Many forest species, including invertebrates, depend in various ways on deadwood substrates. The objective of this study was to investigate relationships between forest stand age, silvicultural treatment, dead wood, and invertebrate biodiversity, using saproxylic beetles as an indicator group. Saproxylic beetle communities were also compared in the context of other studies in Nova Scotia. Beetles were gathered using four collection techniques: pitfall traps, funnel traps, sweep-netting, and manual searching. Results show that both stand age and harvest treatment had an effect on species richness and species composition. Younger stands had lower species richness and hosted a significantly different suite of species than medium-aged or older ones. Similarly, harvested stands had lower species richness and were host to a significantly different suite of species than unharvested stands. The results from the investigation of stand age are of particular interest. Forest management that disregards the dependence of different suites of beetles on forest stands of various ages and compositions, emphasizing even-aged single-species stands, may be harmful to the species diversity of Nova Scotia's forest ecosystems.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".