Does soil history decline in influencing the structure of bacterial communities of <i>Brassica napus</i> host plants across different growth stages?
Bibliographic record
Abstract
Abstract Soil history has been shown to condition future plant-soil microbial communities up to a year after being established. However, previous experiments have also illustrated that mature, adult plants can “re-write”, or mask, different soil histories through host plant-soil microbial community feedbacks. This leaves a knowledge gap concerning how soil history influences bacterial community structure across different growth stages. Therefore, in this experiment we tested the hypothesis that previously established soil histories will decrease in influencing the structure of Brassica napus bacterial communities over the growing season. We used an on-going agricultural field experiment to establish three different soil histories, plots of monocrop canola ( B . napus ), or rotations of wheat-canola, or pea-barley-canola. During the following season, we repeatedly sampled the surrounding bulk soil, rhizosphere and roots of B . napus at different growth stages— the initial seeding conditions, seedling, rosette, bolting, and flower— from all three soil history plots. We compared the taxonomic composition and diversity of bacterial communities, as estimated using 16S rRNA metabarcoding, to identify any changes associated with soil history and growth stages on the different B. napus soil bacterial communities. We found that soil history remained significant across each growth stage in structuring the bulk soil and rhizosphere communities, but not the roots. This suggests that the host plant’s capacity to “re-write” different soil histories may be quite limited as key components that constitute the soil history’s identity remain present and continue to impact bacterial communities. For agriculture, this highlights how previously established soil histories persist and may have important long-term consequences on future plant-microbe communities, including bacteria.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".