Early colonization of Populus wood by saproxylic beetles (Coleoptera)
Bibliographic record
Abstract
The early colonization of newly created coarse woody material (CWM) by beetles was studied in aspen mixedwood forests at two locations in north-central Alberta. Healthy trembling aspen (Populus tremuloides Michx.) trees, in old (>100 years) and mature (40–80 years) stands, were cut to provide three types of CWM: stumps, bolts on the ground (logs), and bolts suspended above the ground to simulate snags. Over 2 years, 1049 Coleoptera, represent- ing 49 taxa, were collected. Faunal structure differed little between the two locations. Species diversity was higher in old than in mature stands, and higher in stumps and logs than in suspended bolts; however, these “snags” tended to have higher abundance when compared with stumps and logs. Overall beetle abundance and the catch of wood-boring beetles was significantly higher in the first year post-treatment, mainly because of the ambrosia beetle (Trypodendron retusum (LeConte)) and one of its predators, Rhizophagus remotus LeConte; however, beetle diversity was higher in the second year, suggesting that early wood-boring species may “precondition” the wood for a number of succeeding spe- cies. The high turnover rate of taxa and spatial or temporal variation in faunal structure suggests that effort focused on habitat classification of CWM will facilitate management to conserve saproxylic faunal diversity.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".