Predatory hymenopteran assemblages in boreal Alaska: associations with forest composition and post-fire succession
Bibliographic record
Abstract
Changes to the fire regime in boreal Alaska are shifting the ratio of coniferous to deciduous dominance on the landscape. The increase in aspen and birch may have important effects on predatory hymenopteran assemblages by providing a source of extrafloral nectar and increasing prey availability. Furthermore, fire-induced changes in successional age alter habitat structure and microclimate in ways that may favor ants. This study is the first to characterize the influence of fire-related vegetation changes on boreal predatory hymenopteran assemblages. We compare the abundance, species richness, and composition of predatory hymenopteran assemblages among forests at different stages of succession and of varying post-fire tree species compositions. Ant assemblages were weakly related to forest composition, but ants were significantly more abundant and speciose in early-successional forests than in mid-late successional forests. In contrast, macropterous wasp morphospecies richness and abundance, and micropterous wasp abundance, were positively related to the basal area of aspen, but were not related to successional stage. The results suggest that shifts in boreal vegetation related to climate warming will result in changes to the predaceous insect community, with ants responding positively to disturbance and wasps responding positively to an increase in the representation of aspen on the landscape.
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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 | 0.001 | 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".