Boreal ground-beetle (Coleoptera: Carabidae) assemblages of the mainland and islands in Lac la Ronge, Saskatchewan, Canada
Bibliographic record
Abstract
Abstract We tested the applicability of the “passive sampling” hypothesis and theory of island biogeography (TIB) for explaining the diversity of forest-dwelling carabid assemblages (Carabidae: Coleoptera) on 30 forested islands (0.2–980.7 ha) in Lac la Ronge and the adjacent mainland in Saskatchewan, Canada. Species richness per unit area increased with distance to mainland with diversity being highest on the most isolated islands. We detected neither a positive species-area relationship, nor significant differences in species richness among island size classes, or between islands and the mainland. Nonetheless, carabid assemblages distinctly differed on islands <1 ha in area and gradually approached the structure of mainland assemblages as island area increased. Small islands were characterised by abundant populations of small-bodied, winged species and few if any large-bodied, flightless species likeCarabus taedatusFabricius. Our findings suggest that neither the “passive sampling” hypothesis nor the theory of island biogeography adequately explain carabid beetle diversity patterns observed among islands in Lac la Ronge. Instead, we hypothesise that population processes such as higher extinction rates of large-bodied, flightless species and the associated release of smaller-bodied, flying species from intra-guild predation on small islands contribute to observed differences in the structure of carabid assemblages between islands.
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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 | 0.001 |
| 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".