Effects of urbanization on ground beetle assemblages (Coleoptera, Carabidae) of grassland habitats in western Canada
Bibliographic record
Abstract
We pitfall‐trapped carabid beetles across an urban‐rural gradient in central Alberta, Canada to assess the relative contributions of landscape structure and habitat quality in explaining variation in composition of assemblages. The gradient ranged from the “urban” zone in the city of Edmonton, through a “suburban” zone just outside the city, into a “rural” zone 25–60 km east of the city. We trapped beetles at three replicated sites for each of two habitats (unmanaged grasslands and highly managed graveyards) in each of the three zones. Most of the 24 species (3162 individuals) captured were commonly associated with open habitats. Pterostichus melanarius , an introduced species, made up 80% of the total catch. Carabid assemblages of grasslands and graveyards were distinct, with lower species richness and lower catch rates of native, introduced and brachypterous carabids in graveyards. Graveyard assemblages also had proportionally fewer brachypterous carabid individuals (32 vs 52%) and species (20 vs 36%), suggesting that populations recruit locally from elsewhere after disturbances. Native carabids were least abundant in the urban areas. Brachypterous carabids were similarly abundant across the gradient, but more occurred in the urban zone than elsewhere (32 vs 5–10%). Samples from graveyards were characterized by lower beta diversity (variation among samples) than those from grasslands, but beta diversity was more‐or‐less equally variable across the gradient within habitats. The amount of unmanaged grassland habitat and the degree of urbanization significantly influence carabid assemblages, and therefore are relevant to management and conservation of urban grassland areas.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".