Influence of habitat and microhabitat on carabid (Coleoptera: Carabidae) assemblages in four stand types
Bibliographic record
Abstract
Abstract Studies based on presence/absence of a species may provide insight into habitat associations, allowing the distribution of species to be predicted across the landscape. Our objective was to characterize the carabid fauna in three mature boreal forest types (conifer, mixedwood, and deciduous) and a disturbed habitat (clearcut) to provide baseline data on the carabid species inhabiting the major forest types of boreal northwestern Ontario. Only spring-active carabids were considered for logistical reasons. We further identified the coarse woody debris structure and microhabitat characteristics within these stand types to try to refine our ability to predict the within-stand occurrence of carabids. We found the carabid composition of deciduous stands (mixedwood and aspen) similar and typical of the carabid fauna found in mixedwood forest in other nearby studies. The important feature of these forest types may be the presence of a deciduous leaf litter layer. In contrast, spruce stands contained fewer species and individuals and a distinct carabid fauna. As predicted, the clearcut habitats were dominated by open habitat species, although the fauna was dissimilar to what was recorded in clearcut habitats in other studies within northwestern Ontario. Coarse woody debris appeared to be an important habitat attribute for several carabid species in clearcut habitats.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| 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".