Effects of <i>Bacillus thuringiensis</i> subsp. <i>kurstaki</i> application on non-target nocturnal macromoth biodiversity in the eastern boreal forest, Canada
Bibliographic record
Abstract
Abstract Insect biodiversity is crucial for resilient ecosystems, supporting essential services. Moths play significant roles as herbivores, pollinators, decomposers, and as prey for birds, bats, and predatory invertebrates, emphasizing their conservation importance. However, large-scale studies on the non-target effects of Bacillus thuringiensis subs. kurstaki (Btk) on moth communities are limited, particularly in northern forests where diversity is lower. Btk is commonly used to control pest insect populations, with forest managers in eastern Canada applying it to manage eastern spruce budworm. We established a replicated two-year study in the North American Boreal Forest of western Newfoundland, Canada, using paired Btk-treated and control (untreated) sites. No significant differences in total abundance or richness were found between treated and control sites. In 2021, Hill numbers only differed between our northern treatment and control sites, which may reflect those stands having already received multiple years of treatment compared to just one year in the southern sites. In 2022, control sites showed higher diversity (Shannon and Simpson diversity metrics) compared to treated sites, extending to all locations. Multiple years of Btk treatment led to shifts in community composition and the relative abundance of some common species, without affecting total richness or abundance. Species responses varied, likely due to Btk sensitivity, application timing, and differences in phenology and voltinism, making it difficult to generalize the effects of Btk on moth communities.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".