Oomycete communities are influenced by land use and disease status in Christmas tree production in Southern Québec, Canada
Bibliographic record
Abstract
Abstract Forests are threatened by many natural stressors intensified by climate change and anthropogenic activities, which tend to increase their susceptibility to pests and pathogens. Consequently, oomycete‐related forest decline or dieback cases are increasing in natural, urban, and agricultural landscapes. It is in this context that Christmas tree growers from Southern Québec, Canada, are experiencing root rot problems, with reported incidences up to 25%. In a previous study, seven Phytophthora spp. were associated with this root rot problem, but the overall diversity of oomycetes has not yet been investigated. Hence, in this study, we use a metabarcoding approach to provide an overview of the diversity, richness, and composition of the oomycete community in fir plantations compared to surrounding natural forests. We showed that the P. cryptogea cluster, P. europaea cluster, P. sansomeana , and P. chlamydospora cluster were significantly more abundant in soils collected from plantations under diseased trees and confirmed that the P. europaea cluster (including P. abietivora ) was most frequently associated with trees showing Phytophthora root rot‐like symptoms. Finally, we report that land use (anthropogenic activities) shapes oomycete diversity, while plantations can act as a gateway for invading natural forests. In fact, the results presented here suggested that the P. europaea cluster might already have crossed this boundary and that other species might follow, advocating the importance of improved surveillance of oomycete diversity in various environments.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".