Persistence of plant-mediated microbial soil legacy effects in soil and inside roots
Bibliographic record
Abstract
Abstract Plant-soil feedbacks are shaped by microbial legacies previous plants leave in the soil. We tested the persistence of such soil legacies after subsequent colonization by the same or other plant species, and whether the microbiome created by the previous plant explains current plant growth. Legacies of previous plants were detectable in soil fungal communities several months after their removal while concomitantly the effect of the current plant amplified in time. Remarkably, bacterial legacies faded away rapidly in the soil and bacterial communities were selected strongly by plant currently growing in the soil. Both fungal and bacterial legacies wrought by the previous plant were conserved inside the root endophytic compartment of the current plant and these endophytes affected significantly the plant growth. Hence, microbial soil legacies present at the time of plant establishment play a vital role in shaping plant growth even as the composition gradually changes in the soil after subsequent plant colonization, as they are taken up as endophytes in the plant. This suggests that plant-soil feedbacks may be partly mediated by a relatively stable endophytic community acquired in early ontogeny while the effects of previous plants detected on soil microbiomes vary between organisms studied. We further show that plants growing in their own soils harbor different endophytic microbiomes than plants growing in soils with legacy of other plants and that especially grasses are sensitive to species specific fungal pathogens while all plant species have less endophytic Streptomycetes when growing in their own soil. In conclusion, we show that soil legacies wrought by previous plants can remain present in the soils and inside the roots for months, even when subsequent plants colonize the soil and that these legacies also substantially modulate the plant growth.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".