Microbial resistance and persistence increase during estuarine succession and promote nutrient accumulation
Bibliographic record
Abstract
Understanding how belowground ecosystems maintain stability in the face of environmental change remains a fundamental challenge in ecology. In this study, we examined both the topological resistance and temporal persistence of microbial communities, including bacteria, fungi, and protists, across tidal and non-tidal zones in the Yellow River Delta (YRD), sampled across four seasons. Using amplicon sequencing, combined with molecular ecological networks and the iDIRECT framework, we found that succession from tidal wetland to non-tidal land significantly enhanced microbial diversity (average increase: 44.0 %) and temporal persistence (373.0 %), while simplifying network complexity (a 36.3 % reduction in intra- and inter-domain associations). Non-tidal land exhibited higher topological resistance and temporal persistence, indicating stronger ecological memory and reduced turnover. Multivariate analyses, including the Mantel test and structural equation modeling (SEM), confirmed that these changes were primarily driven by decreases in environmental stress (e.g., lower salinity and pH) and increases in soil nutrient accumulation ( i.e. , soil organic matter and soil nitrogen). These results suggest that microbial relationships played critical roles in the succession of the estuary landscape. Our findings provide a practical basis for using microbial network stability as an indicator for ecological monitoring and management in various ecosystems.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 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 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".