Greenhouse experiment data: Soil microbial legacies influence plant survival and growth in mine reclamation
Bibliographic record
Abstract
Plants alter soil biological communities, generating ecosystem legacies that affect the performance of successive plants, influencing plant community assembly and successional trajectories. Yet, our understanding of how microbe‐mediated soil legacies influence plant establishment is limited for primary successional systems and forest ecosystems, particularly for ectomycorrhizal plants. In a two‐phase greenhouse experiment using primary successional mine reclamation materials with or without forest soil additions, we conditioned soil with an early successional shrub with low mycorrhizal dependence (willow, Salix scouleriana) and a later‐successional ectomycorrhizal conifer (spruce, Picea engelmannii × glauca). The same plant species and later‐successional plants (spruce and/or redcedar, Thuja plicata, a mid‐ to late-successional arbuscular mycorrhizal conifer) were grown as legacy‐phase seedlings in conditioned soils and unconditioned control soils. Legacy effects were evaluated based on seedling survival and biomass, and the abundance and diversity of root fungal symbionts and pathogens. We found negative intraspecific (same‐species) soil legacies for willow associated with pathogen accumulation, but neutral to positive intraspecific legacies in spruce associated with increased mycorrhizal fungal colonization and diversity. Our findings support research showing that soil legacy effects vary with plant nutrient acquisition strategy, with plants with low mycorrhizal dependence experiencing negative feedbacks and ectomycorrhizal plants experiencing positive feedbacks. Soil legacy effects of willow on next‐stage successional species (spruce and redcedar) were negative, potentially due to allelopathy, while ectomycorrhizal spruce had neutral to negative legacy effects on arbuscular mycorrhizal redcedar, likely due to the trees not associating with compatible mycorrhizae. Thus, positive biological legacies may be limited to scenarios where mycorrhizal‐dependent plants grow in soil containing legacies of compatible mycorrhizae. We found that soil legacies influenced plant performance in mine reclamation materials with and without forest soil additions, indicating that initial restoration actions may potentially exert long‐term effects on plant community composition, even in primary successional soils with low microbial activity.
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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 | 0.001 | 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".