Effects of Reforestation Practices on Staphylinid Beetles (Coleoptera: Staphylinidae) in Southwestern China Forests
Bibliographic record
Abstract
In 2004, Staphylinid beetle (Coleoptera) assemblages were studied via pitfall trapping to examine the effects of reforestation in southwestern China forests. Sites included two 100-yr-old mature forest types (hemlock-spruce forest and birch forest), and three 40-yr-old forest types established after harvesting (spruce plantation, larch plantation, and natural broad-leaved forest). Staphylinid species richness was greater in natural broad-leaved forests than those in hemlock-spruce forests and spruce plantations, but no significant difference was found in abundance among the five forest types. Beetle assemblages from young forest stands were significantly different from those in older forest stands, and some environmental characteristics, i.e., elevation, proportion of broad-leaved trees, and coarse woody debris, significantly affected species abundances. Moreover, some staphylinid species predominantly found only in older forest stands indicate that mature forest specialists might be threatened by loss of habitat. So it is necessary to retain adequate patches of older successional stages for conserving these beetle assemblages.
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 | 0.001 | 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 | 0.000 | 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) | 0.000 | 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".