Limited resilience of the soil microbiome to mechanical compaction within four growing seasons of agricultural management
Bibliographic record
Abstract
Soil compaction affects many soil functions, but we have little information on the resistance and resilience of soil microorganisms to this disturbance. Here, we present data on the response of soil microbial diversity to a single compaction event and its temporal evolution under different agricultural management systems during four growing seasons. Crop yield was reduced (up to -90%) in the first two seasons after compaction, but mostly recovered in subsequent seasons. Soil compaction increased soil bulk density (+15%), and decreased air permeability (-94%) and gas diffusion (-59%), and those properties did not fully recover within four growing seasons. Soil compaction induced cropping system-dependent shifts in microbial community structures with little resilience over the four growing seasons. Microbial taxa sensitive to soil compaction were detected in all major phyla. Overall, anaerobic prokaryotes and saprotrophic fungi increased in compacted soils, whereas aerobic prokaryotes and plant-associated fungi were mostly negatively affected. Most measured properties showed large spatial variability across the replicated blocks, demonstrating the dependence of compaction effects on initial conditions. This study demonstrates that soil compaction is a disturbance that can have long-lasting effects on soil properties and soil microorganisms, but those effects are not necessarily aligned with changes in crop yield.
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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 | 0.001 |
| 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".