Swiss needle cast tolerance in British Columbia’s coastal Douglas-fir breeding population
Bibliographic record
Abstract
Abstract Substantial growth losses in Douglas-fir can be the result of Swiss needle cast, a foliar disease caused by the fungus Nothophaeocryptopus gaeumannii. Although the disease is native to western North America, it is expected to become increasingly problematic in regions where climates become warmer in winter and wetter in spring, such as in coastal British Columbia (BC), Canada. Previous research suggests that tolerance to this disease is under partial genetic control. We therefore aim to screen for tolerance and resistance to the disease in the tree breeding population of coastal Douglas-fir (Pseudotsuga menziesii var. menziesii) in BC. We evaluated if early screening for resistance or tolerance to this disease is possible. We worked with 32 families grown for 18-years on two full-sibling genetic field trial sites representing different climates. We assessed >900 trees for disease signs and symptoms from 2017 to 2019. Needle retention was assessed in the field. In the laboratory, the proportion of stomata occluded with pseudothecia was measured, deoxyribonucleic acid (DNA) was extracted, and the proportion of fungal DNA in the needles was assessed using quantitative polymerase chain reaction. Strong differences were observed among families for needle retention, stomatal occlusion and fungal load. The milder and wetter site closer to the coast was generally more severely affected. Families showed rank changes between the two sites for all response variables. Higher needle retention was correlated with increased tree volume. No correlation was found between the proportion of stomata occluded with pseudothecia, fungal DNA load and needle retention. These results indicate that a more complex pathology is involved in causing needle loss. We conclude that screening for Swiss needle cast tolerance in the coastal BC Douglas-fir breeding population is possible if needle retention can be assessed and that area-specific deployment strategies may be needed given family rank changes in different 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 | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".