Above- and belowground plant-associated microbiota interact to shape plant diversity-productivity relationships
Bibliographic record
Abstract
Plant-associated microbes play a key role in mediating the relationship between plant diversity and productivity. However, previous studies have generally focused on a sole microbial guild (i.e. plant-beneficial microbes or pathogens), and on either aboveground or belowground microbes. As a result, the interplay among different microbial guilds and the overall impact of above- and belowground microbes on plant diversity-productivity relationships have rarely been investigated. Here we carried out an experiment where we applied microbial inocula collected from leaves and soils in the field onto plant leaves and soil in a greenhouse experiment with a herbaceous plant community. We showed that microbial inoculation of leaves reduced plant productivity and this negative effect was weaker at higher plant diversity, which promoted positive diversity-productivity relationships through complementarity effects. In contrast, microbial inoculation of soil alone had no impact on plant diversity-productivity relationships, but it counteracted the negative effects of leaf inoculum on plant productivity and weakened the leaf microbe-induced positive diversity-productivity relationships. We found that the abundance of arbuscular mycorrhizal fungi and Streptomyces bacteria increased when soil microbes were inoculated, and such increase was more significant at lower plant diversity, potentially explaining the effects of soil inoculation on plant productivity. These results suggest that the belowground plant beneficial microbes can counteract the effect of aboveground plant pathogens in mediating positive plant diversity-productivity relationships. Simultaneous study of plant-pathogenic and -beneficial microbes both above- and belowground is required to better understand the contributions of plant-associated microbes to biodiversity-ecosystem function relationships.
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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 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".