Sixteen years of winter stress: an assessment of cold hardiness, growth performance and survival of hybrid poplar clones at a boreal planting site
Bibliographic record
Abstract
In recent years, thousands of hectares of hybrid poplar plantations have been established in Canada for the purpose of carbon sequestration and wood production. However, boreal planting environments pose special challenges that may compromise the long-term survival and productivity of such plantations. In this study, we evaluated the effect of winter stress, that is, frequent freeze-thaw and extreme cold events, on growth and survival of 47 hybrid poplar clones in a long-term field experiment. We further assessed physiological and structural traits that are potentially important for cold tolerance for a selected set of seven clones. We found that trees with narrow xylem vessels showed reduced freezing-induced embolism and showed superior productivity after 16 growing seasons. With respect to cold hardiness of living tissues, we only observed small differences among clones in early autumn, which were nonetheless significantly correlated to growth. Maximum winter cold hardiness and the timing of leaf senescence and budbreak were not related to growth or survival. In conclusion, our data suggest that reduction of freezing-induced embolism due to small vessel diameters is an essential adaptive trait to ensure long-term productivity of hybrid poplar plantations in boreal planting environments.
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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 | 0.000 | 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 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".