Spatial and temporal variation of epigaeic beetle assemblages (Coleoptera, Carabidae, Staphylinidae) in aspen-dominated mixedwood forests across north-central Alberta
Bibliographic record
Abstract
Epigaeic beetle assemblages were surveyed using continuous pitfall trapping during the summers of 1992 and 1993 in six widely geographically distributed locations in Alberta's aspen-mixedwood forests prior to initial forest harvest. Species composition and turnover (β-diversity) were evaluated on several spatial scales ranging from Natural Regions (distance between samples 120-420 km) to pitfall traps (40-60 m). A total of 19,885 ground beetles (Carabidae) representing 40 species and 12,669 rove beetles (non-AleocharinaeStaphylinidae) representing 78 species was collected. Beetle catch, species richness, and diversity differed significantly among the six locations, as did the identity of dominant species. Beetle species composition differed significantly between the Boreal Forest and Foothills Natural Regions for both taxa. Staphylinidae β-diversity differed significantly between Natural Regions, whereas Carabidae β-diversity differed among locations. Climate variables such as number of frost-free days, dry periods, and mean summer temperatures were identified as significant factors influencing beetle assemblages at coarse spatial scales, whereas over- and understory vegetation cover, litter depth, shade, slope, and stand age influenced beetle assemblages at finer spatial scales. Significant interannual variation in assemblage structure was noted for both taxa. Because composition of epigaeic beetle assemblages differed across spatial scales, forest management strategies based only on generalized understanding of a single location will be ineffective as conservation measures. In addition, site history and geographic variation significantly affect species distributions of these two beetle families across the landscape. Thus, we underscore Terry Erwin's suggestion that biodiversity assessments focused on species assemblages at different spatial scales provide a sound approach for understanding biodiversity change and enhancing conservation of arthropod biodiversity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| 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) | 0.000 | 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".