Butterfly assemblages along a human disturbance gradient in Ontario, Canada
Bibliographic record
Abstract
This study relates patterns of butterfly abundance and species richness to position along an urban disturbance gradient in southeastern Ontario, Canada. Observed assemblages along the gradient (N = 15) included butterflies from the Papilionidae, Pieridae, Lycaenidae, Nymphalidae, and Hesperiidae families. Of the total 26 observed species, 15 were noticeably absent from the disturbed sites. Butterfly assemblages had equal or higher number of individuals and species richness at moderately disturbed sites compared with the least disturbed sites. In relation to distribution patterns along the gradient, 28% of butterfly species were classified as disturbance adaptable and 58% as disturbance avoiders. These classifications were correlated with host-plant use and voltinism. Canonical correspondence analysis of local-scale data strongly associated disturbance avoiders with a specific environmental variable (e.g., Everes comyntas (Godart, 1824) with grasslands), whereas disturbance-adaptable species were weakly associated with any variable. One-time disturbances (i.e., mowing) during the survey resulted in pronounced changes in butterfly abundance and species composition at two sites, reducing species richness and total abundance by up to 80%. Species were patchily distributed along the gradient, suggesting that they respond differentially to disturbance in the landscape.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Science and technology studies | 0.002 | 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".