Ground Beetle Assemblages (Coleoptera: Carabidae) and Their Seasonal Abundance in Cool Season Turfgrass Lawns of Quebec
Bibliographic record
Abstract
Turfgrass lawns support a diverse fauna of arthropods including ground beetles, a major predator and seed feeding group. Despite their ubiquity and ecological roles, few studies have looked at ground beetle diversity and composition within lawns. We studied assemblages of Carabidae and their seasonal abundance in a newly established and a 10-yr-old lawn located in Quebec City, Canada. Carabids were sampled from May to November in 2003, 2004, and 2005 using pitfall traps. A total of 17 species in 10 genera and 7 tribes were identified. In the new lawn, three ground beetle species represented 72% of total Carabidae: Harpalus rufipes (30%), Clivina fossor (30%), and Amara aenea (12%). In the older lawn, the most abundant species were Amara aenea (31%), Bembidion mimus (21%), and Dyschirius brevispinus (19%), representing 71% of total Carabidae. Ground beetles were six times more abundant at the older site, and there were minor differences in species diversity between sites and years. For the most abundant Carabidae collected, seasonal abundance patterns were similar for A. aenea and B. mimus with peak abundance in July and/or August. For Harpalus rufipes, seasonal abundance was higher in 2003 and 2005 than in 2004, suggesting a biennial life cycle.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".