Symbiotic soil fungi enhance resistance and resilience of an experimental grassland to drought and nitrogen deposition
Bibliographic record
Abstract
Abstract Ecosystem stability is threatened by multiple global change factors such as drought and elevated nitrogen deposition. Yet, it is still poorly understood whether soil organisms can buffer against such perturbations. Here we focus on arbuscular mycorrhizal fungi (AMF), a common and widespread group of soil fungi. AMF form symbiotic associations with the majority of terrestrial land plants and promote a range of ecosystem services including plant production, diversity and nutrient cycling. We tested whether AMF have the ability to enhance the resistance and resilience of plant communities under soil moisture deficit (hereby drought) and nitrogen deposition. Grassland microcosms with 11 different plant species were established with and without AMF and exposed to elevated nitrogen levels and to an intermittent period of drought. Drought strongly reduced plant productivity and nitrogen cycling, but had limited effects on plant diversity. Nitrogen enrichment reduced plant diversity and increased nitrogen leaching and N 2 O emissions. The presence of AMF enhanced plant productivity, plant diversity and reduced nitrogen losses. AMF facilitated the resistance of plant productivity and nitrogen cycling to drought and the recovery of the plant community structure back to its pre drought state. Furthermore, AMF also mitigated the adverse effects of nitrogen enrichment on the resistance of multiple ecosystem functions to drought. Synthesis . Our work highlights the integral role of AMF for the stability of ecosystem functioning; AMF are not only able to promote resistance to harsh conditions of global change but also improve resilience by enabling plant communities to recover. These findings underline AMF's insurance capacity to buffer ecosystems against global change.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".