Spatial and temporal structuring of arbuscular mycorrhizal communities is differentially influenced by abiotic factors and host crop in a semi-arid prairie agroecosystem
Bibliographic record
Abstract
Agroecosystems are dynamic systems that experience frequent chemical inputs and changes in plant cover. The objective of this study was to test whether abiotic (soil chemical properties and climate) and biotic (plant host identity) factors influence the spatial and temporal structuring of arbuscular mycorrhizal fungal (AMF) communities in a semi-arid prairie agroecosystem. 454 GS FLX+ high-throughput sequencing technology was successfully utilized to characterize the AMF communities based on long reads (mean length: 751.7 bp) and generated high-resolution data with excellent taxonomic coverage. The composition of the AMF community colonizing roots of the three crops (pea, lentil, and wheat) significantly differed, but plant host identity had a minimal effect on the composition of the AMF community in the soil. We observed a temporal shift in the composition of AMF communities in the roots and surrounding soil of the crops during the growing season. This temporal shift was particularly evident in the root-associated AMF community and was correlated with soil phosphate flux and climatic variables. In contrast, the spatial structuring of the AMF community in the site was correlated with soil pH and electrical conductivity. Individual AMF taxa were significantly correlated with pH, electrical conductivity, and phosphate flux, and these relationships were phylogenetically conserved at the genus level within the Glomeromycota.
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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".