Impacts of postfire salvage logging on understory plant communities of the boreal mixedwood forest 2 and 34 years after disturbance
Bibliographic record
Abstract
We compared understory vegetation composition and richness in aspen-dominated boreal mixedwood forest stands in Alberta, Canada, that had been burned by wildfire with those that burned and were subsequently salvage logged. Stands were examined at early and midsuccessional (2 and 34 years after disturbance(s), respectively) developmental stages. In comparison with wildfire stands, understory communities of early successional salvage-logged stands were characterized by greater species richness, weedy species presence, higher shrub abundance, and lower abundances of fire-specialist seed bank species. In constrained ordination, the understory community of early successional wildfire stands was related to greater canopy cover, sapling density, and moss depth, whereas that of salvage-logged stands was related to greater light, volume of downed deadwood, and litter and organic matter. Longer term effects of salvage logging on the understory community were minimal and, instead, reflected the influence of forest canopy redevelopment. In midsuccessional stands, understory composition was related to conifer density, litter cover, soil moisture, organic layer depth, tall shrub density, and bryophyte-covered microsite cover. Postfire salvage logging can have substantial short-term effects on the postfire understory plant community; in the longer term, effects will depend to a large extent on the influence of harvesting and subsequent management on canopy redevelopment.
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 | 0.000 | 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) | 0.001 | 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".