Multiple environmental stressors interactively affect soil phosphorus cycling microbiomes
Bibliographic record
Abstract
Abstract Soil phosphorus (P) cycling microorganisms (PCMs) facilitate organic P mineralization (represented by the phoD gene) and inorganic P dissolution ( pqqC ), driving terrestrial P cycling and enhancing P availability to plants. However, the interactive effects (i.e., additive, synergistic, and antagonistic interactions) of multiple environmental stressors (i.e., acidification, salinization, drought, metal pollution and human disturbance) on PCMs remain unclear. Combining a large-scale survey and controlled experiments, we found that the interactive effects of stressors with significance on PCM abundance and diversity were more ubiquitous than the effects of individual stressors. Specifically, acidification and drought had antagonistic and synergistic effects on the abundances of organic P mineralization microorganisms and inorganic P dissolution microorganisms, respectively, while antagonistic effects between drought and metal pollution were observed on the diversity of these microorganisms. The PCM changes were associated with soil P-related stoichiometric parameters under interactive effects, indicating that interactive stressors strongly influenced microbial-regulated P cycling and P availability in soil. These findings underscore the need to incorporate interactive stressor effects into strategies for sustainable soil P management and ecosystem resilience.
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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 | 0.001 | 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 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".