Anthropogenic disturbance promotes the abundance of a newly introduced butterfly, the European common blue (<i>Polyommatus icarus</i>; Lepidoptera: Lycaenidae), in Canada
Bibliographic record
Abstract
The frequency of introductions of non-native species is increasing worldwide, but only a few introduced species undergo rapid population growth and range expansion, and even fewer become invasive, leading to negative impacts on native communities. Predicting which non-native species are likely to become widespread and abundant can be difficult when there is a lack of species’ information in the early stages of colonization. Here, we investigate the ecology of a newly introduced butterfly in Canada, the European common blue (Polyommatus icarus (Rottemberg, 1775)), by modelling its local- and landscape-scale habitat suitability in Montréal, Quebec, Canada, and the surrounding region, and by assessing its dispersal ability using a mark–release–recapture study. At a local scale, we found that P. icarus abundance was highest at sites with moderate levels of habitat disturbance (e.g., mowed every 2–3 years), the presence of their preferred larval host plant and low proportional cover of grasses. At a landscape scale, P. icarus abundance increased with an increasing proportion of urban area and decreasing proportion of forests. We also found that P. icarus is a low to moderate disperser relative to other butterflies. Our results suggest that P. icarus may become widespread in disturbed and urban areas across Canada, but that further investigation into additional potential range-constraining factors (e.g., microclimate), especially larval preferences, and modelling of the trajectory of P. icarus range expansion is needed.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".