Forest management and maintenance of ectomycorrhizae: A case study of green tree retention in south-coastal British Columbia
Bibliographic record
Abstract
Assessment of ectomycorrhizal (EM) colonization was carried out in a variable green tree retention experimental block near Powell River, British Columbia. We hypothesized that increasing retention level enhances colonization of EM fungi onto seedlings in harvested areas. We also investigated the role of isolated trees in EM maintenance. Transects were established in treatments where 0% (a clearcut), 5%, 10%, and 30% of trees were retained. Douglas-fir seedlings (Pseudotsuga menziesii) were planted at 5, 15, 25 and 45 m from the remaining forest edge and excavated 18 months later for analysis of EM colonization. Within the forest, soil cores and sporocarp surveys provided information on EM species potentially available for colonization of seedlings. We observed a total of 85 EM morphotypes. The edge effects—declines with distance from the forest, observed in the 0% retention treatment—were diminished in the higher-retention treatments. EM richness and root colonization increased insignificantly with increasing tree retention when the influence of ubiquitous early-stage EM fungi and inherent microsite differences were accounted for. EM diversity next to isolated trees was greater than at 10 m from the trees, but lower than at 5 m from the forest edge. We discuss the implications of these relationships and the role of isolated trees in the context of these exploratory findings. While these results suggest certain trends, they are for a single installation and their applicability to forests elsewhere in the region needs further study.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".