The potential for woody understory plants to provide refuge for ectomycorrhizal inoculum at an interior Douglas-fir forest after clear-cut logging
Bibliographic record
Abstract
Clear-cut logging can decrease the amount of inoculum for some ectomycorrhizal fungi. Ectomycorrhizal plants that are not selected for harvest (refuge plants) may, therefore, be important for the maintenance of ectomycorrhizal fungal inoculum in clearcuts following logging. The purpose of this study was to identify refuge plants that could provide ectomycorrhizal fungal inoculum for outplanted seedlings. The ectomycorrhizal status of selected plants was assessed in 1.6-ha clearcuts and in adjacent forest. Over 3 years, 17 and 14 morphotypes were described for Pseudostuga menziesii (Mirb.) Franco (Douglas-fir) and Arctostaphylos uva-ursi (L.) Spreng, respectively. Ten morphotypes (six of these confirmed with restriction fragment length polymorphism patterns) were shared by both species. Anatomical and molecular analyses revealed that, for the morphotypes observed, ectomycorrhizal fungi formed ectomycorrhizal anatomy when associated with Douglas-fir and arbutoid anatomy with A. uva-ursi. Because advanced regeneration seedlings of Douglas-fir and A. uva-ursi are well distributed throughout this site, these two species have a high potential to provide ectomycorrhizal fungal inoculum for outplanted seedlings. There was no difference in mycorrhizal richness between A. uva-ursi plants sampled from the clearcut and forest in the latter 2 years of the study. Conversely, the richness of ectomycorrhizae associated with Douglas-fir sampled from the forest was significantly greater than for seedlings sampled from the clearcuts.
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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".