Species traits modify the species-area relationship in ground-beetle (Coleoptera: Carabidae) assemblages on islands in a boreal lake
Bibliographic record
Abstract
Life-history traits influence colonization, persistence, and extinction of species on islands and are important aspects of theories predicting the geographical distribution and evolution of species. We used data collected from a large freshwater lake (1,413 km2) in central Canada to test the effects of island area and isolation on species richness and abundance of carabid beetles as a function of body size, wing length, and breeding season. A total of 10,018 individual beetles from 37 species were collected during the frost-free period of 2013 using transects of pitfall traps on 30 forested islands ranging in area from 0.2 to 980.7 ha. Life-history traits improved the predictive ability and significantly modified the shape of species-area and abundance-area curves. Abundance and richness of small-bodied (< 13.9 mm), macropterous (winged), and spring-breeding species decreased with island area and increased with isolation. In contrast, richness and abundance of larger-bodied (> 14.0 mm) and flightless species increased with area, but not isolation. Body size of female Carabus taedatus Fabricius, the largest-bodied species, was positively related to island area, while body size on the adjacent mainland was most similar to that on smaller islands. Overall, species with large body size and low dispersal ability, as indicated by flightlessness, were most sensitive to reductions in area. We suggest that large-bodied, flightless species are rare on small islands because habitat is less suitable for them and immigration rates are lower because they depend on freshwater drift for dispersal to 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 | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".