Effect of microsites on the survival, density, and ectomycorrhizal status of shade-tolerant<i>Abies alba</i>regeneration attacked by fungal pathogens
Bibliographic record
Abstract
An increased incidence of fungal pathogens has been recognized as one of the most important causes for insufficient natural regeneration in pure Abies alba Mill. forests in the Western Carpathians (central Europe). We investigated the spatial distribution of A. alba seedlings in seven stands in which severe symptoms of fungal pathogen infections were observable and compared microsite variables and ectomycorrhizal status of seedlings in locations with abundant or poor regeneration. We also tested the effect of local stand density, seedbed, and vegetation control on seed germination and the survival of 1-year seedlings. The study provided evidence that gap environment may increase the mortality of 1-year seedlings caused by fungal pathogens. That pattern was consistent with the spatial distribution of older seedlings: locations with abundant older regeneration were characterized by a greater local stand density, lower canopy openness, and lower mineral topsoil moisture than poorly regenerated locations. Yet, despite considerable spatial differentiation in ectomycorrhizal types, the mycorrhizal status of 2-year seedlings in abundantly regenerated areas did not differ from that in poorly regenerated areas.
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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 | 0.000 | 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".