Population structure of the butternut canker fungus, <i><scp>O</scp>phiognomonia clavigignenti‐juglandacearum,</i> in <scp>N</scp>orth <scp>A</scp>merican forests
Bibliographic record
Abstract
The occurrence of multiple introduction events, or sudden emergence from a host jump, of forest pathogens may be an important factor in successful establishment in a novel environment or on a new host; however, few studies have focused on the introduction and emergence of fungal pathogens in forest ecosystems. While Ophiognomonia clavigignenti-juglandacearum (Oc-j), the butternut canker fungus, has caused range-wide mortality of butternut trees in North America since its first observation in 1967, the history of its emergence and spread across the United States and Canada remains unresolved. Using 17 single nucleotide polymorphic loci, we investigated the genetic population structure of 101 isolates of Oc-j from across North America. Clustering analysis revealed that the Oc-j population in North America is made up of three differentiated genetic clusters of isolates, and these genetic clusters were found to have a strong clonal structure. These results, in combination with the geographic distribution of the populations, suggest that Oc-j was introduced or has emerged in North America on more than one occasion, and these clonal lineages have since proliferated across much of the range of butternut. No evidence of genetic recombination was observed in the linkage analysis, and conservation of the distinct genetic clusters in regions where isolates from two or more genetic clusters are present, would indicate a very minimal or non-existent role of sexual recombination in populations of Oc-j in North America.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".