Partial Retention of Legacy Trees Protect Mycorrhizal Inoculum Potential, Biodiversity, and Soil Resources While Promoting Natural Regeneration of Interior Douglas-Fir
Bibliographic record
Abstract
Clearcutting reduces proximity to seed sources and mycorrhizal inoculum potential for regenerating seedlings. Partial retention of legacy trees and protection of refuge plants, as well as preservation of the forest floor, can maintain mycorrhizal networks that colonize germinants and improve nutrient supply. However, little is known of overstory retention levels that best protect mycorrhizal inoculum while also providing sufficient light and soil resources for seedling establishment. To quantify the effect of tree retention on seedling regeneration, refuge plants, and resource availability, we compared five harvesting methods with increasing retention of overstory trees (clearcutting (0% retention), seed tree (10% retention), 30% patch retention, 60% patch retention, and 100% retention in uncut controls) in an interior Douglas-fir-dominated forest in British Columbia. Regeneration increased with proximity to legacy trees in partially cut forests, with increasing densities of interior Douglas-fir, western redcedar, grand fir, and western hemlock seedlings with overstory tree retention. Clearcutting reduced cover of ectomycorrhizal refuge plants (from 80 to 5%) while promoting arbuscular mycorrhizal plants the year after harvest. Richness of shrubs, herbs, and mosses declined with increasing harvesting intensity, but tree richness remained at control levels. The presence of legacy trees in all partially cut treatments mitigated these losses. Light availability declined with increasing overstory cover and proximity to leave trees, but it still exceeded 1,000 W m −2 in the clearcut, seed tree and 30% retention treatments. Increasing harvesting intensity reduced aboveground and belowground C stocks, particularly in live trees and the forest floor, although forest floor losses were also substantial where thinning took place in the 60% retention treatment. The loss of forest floor carbon, along with understory plant richness with intense harvesting was likely associated with a loss of ectomycorrhizal inoculum potential. This study suggests that dispersed retention of overstory trees where seed trees are spaced ~10–20 m apart, and aggregated retention where openings are <60 m (2 tree-lengths) in width, will result in an optimal balance of seed source proximity, inoculum potential, and resource availability where seedling regeneration, plant biodiversity, and carbon stocks are protected.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".