Differences Between Forest Type and Vertical Strata in the Diversity and Composition of Hymenpteran Families and Mymarid Genera in Northeastern Temperate Forests
Bibliographic record
Abstract
Most insects' assemblages differ with forest type and show vertical stratification. We tested for differences in richness, abundance and composition of hymenopteran families and mymarid genera between sugar maple (Acer saccharum) and white pine (Pinus strobus) stands and between canopy and understory in northeastern temperate forests in Canada. We used flight interception traps (modified malaise traps) suspended in the canopy and the understory in a split-split block design, with forest type as the main factor, forest stratum as the first split factor, and collection bottle location as the second split factor. Hymenopteran families and mymarid genera differed in their diversity depending on forest type and stratum. Both family and genera richness were higher in maple than in pine forests, whereas family richness was higher in the canopy and top bottles and generic richness was higher in the understory and bottom bottles. Multivariate analysis separated samples by forest type, vegetation stratum, and bottle location. Family composition showed 77% similarity between forest types and 73% between the canopy and understory. At the lower taxa level, mymarid genera showed only 47% similarity between forest types and 40% between forest strata, indicating vertical stratification and relatively high beta-diversity. Our study suggests that hymenopteran diversity and composition is strongly dependent on forest type and structure, making flying members of this order particularly vulnerable to forest management practices. It also shows that insect assemblage composition (especially at low-taxon levels), rather than relative abundance and richness, is the community attribute most sensitive to forest type and vertical stratification.
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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 | 0.000 |
| 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".