Survey of <i>Phytophthora</i> Diversity Reveals <i>P. abietivora</i> as a Potential Phytophthora Root Rot Pathogen in Québec Christmas Tree Plantations
Bibliographic record
Abstract
Christmas trees are an economically and culturally important ornamental plant in North America. Many microorganisms are pathogens of firs cultivated as Christmas trees. Among those, Phytophthora causes millions of dollars in damage to plantations annually. In Canada, it is unknown which species are responsible for Phytophthora root rot (PRR) of cultivated Abies species. Between 2019 and 2021, soil and root samples were collected from 40 Christmas tree plantations in Québec province. We used soil baiting and direct isolation from unidentified root fragments to assess the diversity of culturable Phytophthora spp. The obtained isolates were identified using a multilocus sequencing and phylogenetic approach. A total of 44 isolates were identified, including eight P. chlamydospora, eight P. abietivora, seven P. gonapodyides, three P. gregata, six P. megasperma, and two P. kelmanii isolates, plus 10 isolates belonging to a previously unknown taxon that is phylogenetically close to P. chlamydospora and P. gonapodyides. Among the known species, P. abietivora was the most prevalent isolated species associated with trees showing aboveground PRR-like symptoms. Pathogenicity trials confirmed the pathogenicity potential of P. abietivora on both Fraser fir and balsam fir seedlings. Our study provides a first snapshot of the Phytophthora diversity in Québec’s Christmas tree productions and describes multiple potential first associations between Phytophthora species and Abies balsamea and A. fraseri. [Formula: see text] Copyright © 2024 His Majesty the King in Right of Canada, as represented by the Minister of Natural Resources Canada. This is an open access article distributed under the CC BY-NC-ND 4.0 International license .
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".