Saprotrophs and nitrifiers, not pathogens, drive plant-soil feedbacks in a semi-arid grassland
Bibliographic record
Abstract
By influencing soil biota and nutrient cycling, plants can alter their fitness and that of their neighbours through plant-soil feedbacks. However, we need more detailed understanding of the biological causes of such feedbacks. This includes identifying the soil microbial guilds causing them. As most plant-soil feedbacks have been reported to be negative, the dominant paradigm is focused on the accumulation of soil pathogens. This neglects the full range of soil microorganisms likely to influence plant performance. Here, we studied plant growth responses to field-collected soil inocula in a large-scale greenhouse study coupled with next-generation sequencing. Although we found a high prevalence of negative plant-soil feedbacks, the microorganisms driving the responses were largely saprotrophs and N-cycling prokaryotes, not pathogens. These results show that negative plant-soil feedbacks need not be caused by trophic interactions, highlighting the need to bring back nutrient cycling as a central component of plant-soil feedbacks.
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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 | 0.000 | 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 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".