Adaptations of white spruce to climate: strong intraspecific differences in cold hardiness linked to survival
Bibliographic record
Abstract
Understanding local adaptation of tree populations to climate allows the development of assisted migration guidelines as a tool for forest managers to address climate change. Here, we study the relationship among climate, a wide range of physiological traits, and field performance of selected white spruce provenances originating from throughout the species range. Tree height, survival, cold hardiness, hydraulic, and wood anatomical traits were measured in a 32-year-old common garden trial, located in the center of the species range. Provenance performance included all combinations of high versus low survival and growth, with the most prevalent population differentiation for adaptive traits observed in cold hardiness. Cold hardiness showed a strong association with survival and was associated with cold winter temperatures at the site of seed origin. Tree height was mostly explained by the length of the growing season at the origin of the seed source. Although population differentiation was generally weak in wood anatomical and hydraulic traits, within-population variation was substantial in some traits, and a boundary analysis revealed that efficient water transport was associated with vulnerable xylem and low wood density, indicating that an optimal combination of high water transport efficiency and high cavitation resistance is not possible. Our results suggest that assisted migration prescriptions may be advantageous under warming climate, but pronounced trade-offs between survival and cold hardiness require a careful consideration of the distances of these transfers.
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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".