Responses of ground beetle (Coleoptera: carabidae_ species and assemblages to forest practices in the interior Douglas-fir forests of British Columbia
Bibliographic record
Abstract
The Opax Mountain Silvicultural Systems Project was initiated in 1993 to address concerns over the widespread use of uniform stand-level partial cutting in the dry Douglas-fir forests of BC's Southern Interior. Various alternative harvesting methods were tested, and responses of several wildlife indicator groups were measured. The following study examined responses of ground beetle (Coleoptera: Carabidae) species and assemblages using a variety of diversity indices. The alternative harvesting practices were: 1) 20% and 2) 50% removal using individual-tree selection (I.T.S.); 3) 20% and 4) 50% removal using patch-cuts of 0.1, 0.4, and 1.6 ha; 5) 35% removal using 50% I.T.S. on 70% of the treatment area, leaving 30% in reserves; and 6) uncut controls. Results showed that species richness, evenness, and heterogeneity were greater in logged treatments. However, only in the heterogeneity values of Mud Lake assemblages (1996/1997) was there a general increase in diversity that accompanied either an increase in percent forest removal, or a change from control to I.T.S. to patch-cut methods of harvest. Other than taxonomic distinctness, no other distinctness index decreased in logged treatments, and none of the distinctness indices displayed any trend in decreasing with an increasing percentage of forest removal, or to a change from control to I.T.S. to patch-cut methods of harvest. In multivariate analysis, carabid assemblages within each site (Mud Lake and Opax Mountain.) showed patch-cut treatments to cluster/map together and I.T.S. treatments to cluster/map together. Dominance structure tables generally showed that carabid assemblages from lower percent removal treatments, as well as from I.T.S. methods, to most resemble dominance structure found in control blocks. Species analysis showed that carabid species respond to logging in a variety of ways. Because every method of harvest evidently benefited some species at the expense of others, no one treatment appears sufficient for the whole carabid community. Instead, a mix of harvesting methods that maintained the greatest number of all native forest species, including sensitive species, and over an indefinite period of time, would be the best strategy for the preservation of carabid 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 | 0.001 |
| 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 | 0.000 | 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".