First report of Melampsora epitea causing stem cankers on Salix pentandra in Alberta, Canada
Bibliographic record
Abstract
In June, 2021, laurel willow (Salix pentandra) near Slave Lake, Alberta, was found to be infected by a Melampsora sp. that produced bright yellow urediniospores in uredia that were present on catkins, leaves, and stems. All Melampsora species previously reported in Canada are recorded as infecting leaves; therefore, further investigation was undertaken to ascertain the identity of this pathogen. To assess the relationship between this specimen and other Melampsora spp. previously collected from Canada, samples of willow leaves infected by Melampsora spp. were sourced from mycological herbariums located at the Laurentian Forestry Centre (QFB) and the Northern Forestry Centre (CFB, WINF(M)). DNA sequence data from the internal transcribed spacer (ITS) ribosomal RNA region of the fresh specimen, herbarium specimens, and DNA sequence data deposited within GenBank, were used to conduct a phylogenetic analysis. Sequencing and BLAST analysis of the material from the sample resulted in a 99.3% sequence identity match to Melampsora epitea “Mel J” collected from Larix laricina in New York State. The ITS sequence from the herbarium sample WINF(M)7356 (described as M. abieti-capraearum from Manitoba) had 100.0% identity with the Alberta sample. Additionally, specimens WINF(M)11892 (Melampsora sp. from Manitoba) and CFB8931 (Melampsora sp. from the Yukon) had 99.0% sequence identity with the Alberta sample. From these results we applied the identity of M. epitea to the rust discovered in Slave Lake, AB. With the current emphasis on willows for bioenergy production in Canada, growers must remain vigilant for this pathogen and the damages it could cause to willow plantations.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".