Impact of Land Use on Arbuscular Mycorrhizal Fungal Communities in Rural Canada
Bibliographic record
Abstract
The influence of land use on soil bio-resources is largely unknown. We examined the communities of arbuscular mycorrhizal (AM) fungi in wheat-growing cropland, natural areas, and seminatural areas along roads. We sampled the Canadian prairie extensively (317 sites) and sampled 20 sites in the Atlantic maritime ecozone for comparison. The proportions of the different AM fungal taxa in the communities found at these sites varied with land use type and ecozones, based on pyrosequencing of 18S rRNA gene (rDNA) amplicons, but the lists of AM fungal taxa obtained from the different land use types and ecozones were very similar. In the prairie, the Glomeraceae family was the most abundant and diverse family of Glomeromycota, followed by the Claroideoglomeraceae, but in the Atlantic maritime ecozone, the Claroideoglomeraceae family was most abundant. In the prairie, species richness and Shannon's diversity index were highest in roadsides, whereas cropland had a higher degree of species richness than roadsides in the Atlantic maritime ecozone. The frequencies of occurrence of the different AM fungal taxa in croplands in the prairie and Atlantic maritime ecozones were highly correlated, but the AM fungal communities in these ecozones had different structures. We conclude that the AM fungal resources of soils are resilient to disturbance and that the richness of AM fungi under cropland management has been maintained, despite evidence of a structural shift imposed by this type of land use. Roadsides in the Canadian prairie are a good repository for the conservation of AM fungal diversity.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".