Effect of small-scale forest management on fungivorous Coleoptera in old-growth forest fragments in southeastern Ontario, Canada
Bibliographic record
Abstract
Abstract Fungivorous Coleoptera were sampled from old-growth and managed (selectively logged in 1999) hemlock–hardwood forests in southeastern Ontario to examine the effect of small-scale forest management on fungivore diversity in forest fragments. Sampling using flight-intercept traps and trunk-window traps for 22 weeks in 2003 yielded 11 888 beetles representing 73 species in 11 target families (Anthribidae, Cerylonidae, Endomychidae, Erotylidae, Leiodidae, Mycetophagidae, Scaphidiidae, Sphindidae, Tenebrionidae, Trogossitidae, and Zopheridae). The leiodid subfamily Leiodinae was the dominant taxon (10 386 individuals, 38 species). While old-growth stands had no recent logging and had higher volumes of coarse woody debris, species diversity and composition of fungivorous Coleoptera were similar between forest types, suggesting that the stand differences measured (recent logging history, volume of coarse woody debris) did not have a significant effect on beetle diversity in this study. Indicator species analysis showed that Triplax macra LeConte (Erotylidae) was strongly associated with old-growth stands, while Anisotoma blanchardi (Horn), Anogdus obsoletus (Melsheimer), Agathidium sp. 1 (Leiodidae), and Mycetina perpulchra (Newman) (Endomychidae) were associated with managed stands. The lack of difference observed between stand types may be related to the small size of the forest fragments or the relatively small scale of the disturbance.
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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 | 0.000 | 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".