FOREST GROUND BEETLES (COLEOPTERA: CARABIDAE) ON A BOREAL ISLAND: HABITAT PREFERENCES AND THE EFFECT OF EXPERIMENTAL REMOVALS
Bibliographic record
Abstract
Abstract We used pitfall trapping to measure the species richness and relative abundance of ground beetles (Coleoptera: Carabidae) in four forest habitats on Kent Island, a 80-ha island in the Bay of Fundy, New Brunswick, Canada. Sixteen species of ground beetles representing 11 genera were identified in the forested habitats on Kent Island; the relative paucity of ground beetle species may be a result of the island’s harsh climate, dense colonies of breeding seabirds, and isolation from the mainland. Estimates of ground beetle population densities on Kent Island ranged from 50 000 to 250 000/ha. Most ground beetle species were trapped in all habitats and appeared to be habitat generalists. In a series of experiments in which we removed all ground beetles trapped daily over a 3-week period in two experimental plots, ground beetle densities remained as high as in a control plot; other ground beetles quickly moved into the experimental plots to replace beetles that had been removed. The density of ground beetles was highest in intact forest and large forest patches; in contrast, the density of invertebrates other than ground beetles (i.e., possible prey or competitors of ground beetles) was highest in open habitats and isolated forest patches, where ground beetles were less common. Removing ground beetles from experimental plots did not result in an increase in the density of other invertebrates.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".