Comparative patterns of dung beetle (Coleoptera: Scarabaeidae) diversity in native fescue grassland and wooded habitats in the Cypress Hills, Alberta, Canada
Bibliographic record
Abstract
Abstract Dung beetles (Coleoptera: Scarabaeidae (Aphodiinae, Scarabaeinae) and some Geotrupidae) provide important ecosystem services on pastures by disrupting and burying deposits of cattle dung. The extent of these services is influenced by the number of individuals and species present, which may differ with habitat type. In the present study, we compared dung beetle assemblages in a mosaic of open grassland and wooded habitats on native fescue pastures in the Cypress Hills of southern Alberta, Canada. Using pitfall traps baited with cattle dung and operated from spring through autumn for two years at each of the two sites, we collected 4944 individuals representing 14 dung beetle species. More individuals and species were recovered in grassland habitat, which was dominated by nonnative species associated with cattle dung. Wooded habitat was dominated by a native species associated with deer dung. Dwellers (species that develop within the dung deposit) comprised 93% of the beetles recovered during the study. Significant variation in annual beetle counts in the two habitats highlights the value of studies conducted over multiple years. These results emphasise the importance of habitat diversity and interspecific habitat preference in structuring dung beetle assemblages on fescue grasslands, which are among the most threatened ecosystems in Canada.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 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".