Arbuscular mycorrhizal diversity sustains plant performance under multiple global changes with varying impacts on soil functions
Bibliographic record
Abstract
High biodiversity can mitigate the negative impacts of global change factors (GCFs) on differing ecosystem functions captured in multifunctionality. However, multiple GCFs occurring simultaneously may diminish the positive effects of high biodiversity on multifunctionality. Arbuscular mycorrhizal fungi (AMF) play a crucial role in determining ecosystem functionality, yet it remains unclear whether AMF alleviate the negative impact of multiple GCFs on ecosystem multifunctionality. In this study, we conducted a microcosm experiment to explore the role of AMF in maintaining ecosystem multifunctionality under multiple GCFs. We found that ecosystem multifunctionality under high AMF diversity was greater than under low AMF diversity under multiple GCFs. Notably, AMF diversity significantly improved plant growth simultaneously. While AMF inoculation significantly influenced soil functions, the diversity of AMF showed limited effect on soil functions. Our findings emphasize the importance of conserving AMF diversity to maintain ecosystem functionality.
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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 | 0.001 |
| 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".