Mycorrhizal fungi maintain plant community stability by mitigating the negative effects of nitrogen deposition on subordinate species in Central Asia
Bibliographic record
Abstract
Abstract Questions Plant community stability is threatened by increasing numbers of simultaneously changing factors such as increased precipitation and nitrogen (N) deposition. Despite the pivotal roles of arbuscular mycorrhizal fungi (AMF) for plant community dynamics, only few studies have paid attention to their roles in maintaining plant community stability under global change. We therefore assessed the interactive effects of a realistic N deposition and AMF on plant community temporal stability under future increased precipitation scenarios. Location Gurbantunggut desert, China. Methods We conducted a four‐year field experiment simulating a realistic N deposition and with/without AMF treatments in one typical ephemeral plant community, dynamically monitoring the changes in plant community biomass and composition. Results We found that suppression of AMF significantly reduced Shannon–Wiener diversity and evenness while the realistic N deposition only marginally reduced the Shannon–Wiener diversity. Suppression of AMF and increased N deposition highly increased the species turnover. Particularly, the stability of subordinate plant species significantly correlated to the community‐level stability. AMF were able to buffer the negative effects of increased N deposition on plant community diversity, to maintain community‐level stability. Conclusions Our study supports the subordinate insurance hypothesis, highlighting the considerable roles of subordinate plant species in maintaining community stability. Furthermore, our results indicate the joint roles of AMF and N deposition in regulating plant community stability, and point to the importance of taking AMF and the realistic N deposition into account for understanding the responses of community stability to multiple global change scenarios.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".