Relatedness of<i>Macrophomina phaseolina</i>isolates from tallgrass prairie, maize, soybean and sorghum
Bibliographic record
Abstract
Agricultural and wild ecosystems may interact through shared pathogens such as Macrophomina phaseolina, a generalist clonal fungus with more than 284 plant hosts that is likely to become more important under climate change scenarios of increased heat and drought stress. To evaluate the degree of subdivision in populations of M. phaseolina in Kansas agriculture and wildlands, we compared 143 isolates from maize fields adjacent to tallgrass prairie, nearby sorghum fields, widely dispersed soybean fields and isolates from eight plant species in tallgrass prairie. Isolate growth phenotypes were evaluated on a medium containing chlorate. Genetic characteristics were analysed based on amplified fragment length polymorphisms and the sequence of the rDNA-internal transcribed spacer (ITS) region. The average genetic similarity was 58% among isolates in the tallgrass prairie, 71% in the maize fields, 75% in the sorghum fields and 80% in the dispersed soybean fields. The isolates were divided into four clusters: one containing most of the isolates from maize and soybean, two others containing isolates from wild plants and sorghum, and a fourth containing a single isolate recovered from Solidago canadensis in the tallgrass prairie. Most of the sorghum isolates had the dense phenotype on media containing chlorate, while those from other hosts had either feathery or restricted phenotypes. These results suggest that the tallgrass prairie supports a more diverse population of M. phaseolina per area than do any of the crop species. Subpopulations show incomplete specialization by host. These results also suggest that inoculum produced in agriculture may influence tallgrass prairie communities, and conversely that different pathogen subpopulations in tallgrass prairie can interact there to generate 'hybrids' with novel genetic profiles and pathogenic capabilities.
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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".