Stand composition and structure of the boreal mixedwood and epigaeic arthropods of the Ecosystem Management Emulating Natural Disturbance (EMEND) landbase in northwestern Alberta
Bibliographic record
Abstract
Conservation of biological diversity under the natural disturbance model of boreal forest management relies on the assumption that natural mosaics of stand composition and structure can be adequately recreated through forest management activities. Maintaining compositional and structural features that provide adequate habitat for species within managed stands is the basis of coarse-filter conservation strategies. Here we test the effect of stand composition and stand structure on the epigaeic arthropod fauna from four boreal mixedwood cover types in western Canada. We observed differences in epigaeic community composition and species-specific associations among each of the four cover types. Differences in the carabid fauna between cover types were defined by relative abundance of carabid species associated specifically with moss cover, forb cover, and of coarse woody material, rather than unique, stand-specific species compositions of the overstory. Cover-type differences were less apparent among the comparatively species-rich spider assemblages largely because of their low abundance in undisturbed stands. For the effective conservation of all species, our results suggest that coarse-filter management of mixedwood boreal forests must incorporate structural features beyond overstory canopy composition. Our analyses also suggest that activities directed at managing the amount of coarse woody material on the ground and understory plant composition, perhaps through variable retention harvesting, is a logical first step.
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) | 0.001 | 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".