Soil inoculation of lodgepole pine seedlings alters root‐associated fungal communities but does not improve seedling performance in beetle‐killed pine stands
Bibliographic record
Abstract
Extensive tree mortality in forests can change the community composition of soil fungi altering seedling establishment, a process critical to forest restoration. Disturbances that result in the loss of ectomycorrhizal fungi, in particular, may impede the establishment of tree species reliant on these symbionts for their survival. Inoculation of seedlings with soil from intact forests may improve the establishment of seedlings in such disturbances but the method has rarely been tested in the field. Here, we assess whether soil inoculation improves lodgepole pine (Pinus contorta var. latifolia) seedling performance in conspecific stands with high levels of tree mortality caused by a mountain pine beetle (Dendroctonus ponderosae) outbreak and whether underlying soil type modifies inoculation effects. We first inoculated seedlings in a growth chamber with small amounts of soils (5% volume) originating from either intact (<10%) or “beetle‐killed” (>70% pine basal area killed) conspecific stands or added no soil inoculum and, after 4 months, transplanted them into 15 beetle‐killed stands. After two growing seasons, root‐associated fungal communities of seedlings receiving inoculum from intact stands differed in composition from those receiving inoculum from beetle‐killed stands or no inoculum. However, inoculation had no effect on seedling survival, height, or biomass. Site properties, including soil texture and the resident fungal community composition, overwhelmed the effect of soil inoculation on seedling performance. Seedling survival and shoot mass was higher in sandy than loamy soils. Restoration to improve seedling performance in beetle‐killed stands should consider stand‐level treatments as soil inoculation at the level evaluated was ineffective.
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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) | 0.001 | 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 | 0.001 |
| 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".