Mycorrhizal Fungal Inoculum Potential in Crop Rotation Soil With Different Levels of Irrigation
Bibliographic record
Abstract
Research indicates arbuscular mycorrhizal fungi (AMF) inoculum potential and AMF biomass production in agricultural soil are strongly influenced by both soil moisture availability and crop rotation (CR) strategies. We hypothesized that AMF biomass production in and inoculum potential of Wyoming semiarid agricultural soil would increase when managed using CR and irrigation. To test this hypothesis, we examined AMF activity (AMF biomarker fatty acid, and AMF infection of roots) in two differently managed soils (no-CR soil and two-year CR soil) in a field experiment. Furthermore, in a greenhouse experiment, we examined AMF activity in the same two CR treatment soils under different irrigation regimes (wet, irrigated to 60% field capacity, and dry, irrigated to 15% field capacity). Notably, the two-year CR soil had greater amounts of AMF biomarker fatty acid and greater inoculum potential, and higher percentage of AMF root colonization compared to no-CR soil. Despite the fact that the CR soil had more AMF propagules, it was less than the undisturbed non-agricultural native sage-grassland soils previously reported. Overall, the findings suggest that high levels of irrigation can inhibit the activity of AMF adapted to semiarid soil conditions and CR can increase activity of AMF in soils from semiarid regions.
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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 | 0.000 |
| 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 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".