Population Differentiation and Climatic Adaptation for Growth Potential of White Spruce (Picea glauca) in Alberta, Canada
Bibliographic record
Abstract
Abstract Genetic differentiation among white spruce populations in Alberta, Canada, was studied using time series data of height and diameter and a climatic index developed by principal component analysis. The objectives were to discern patterns of variation for growth potential and predicted optimum climate; compare optimum climate between populations, between height and diameter at the same age and between height or diameter at different ages; and to see if optimum climate differed from the climate inhabited by populations. Using cluster analysis we found that: (1) populations from mid-latitudes (54° - 57°N) and mid-elevations (600 - 800 m) were grouped together and exhibited high growth potential; populations from north of 57°N were grouped with those from elevations higher than 900m in the Rocky Mountains and exhibited low growth potential; and (2) With minor exceptions, populations from similar climates or geography were grouped together in terms of predicted optimum climate. (3) Analysis of variance showed that optimum climate differed significantly (P < 0.05) among populations; among heights at different ages; among diameters at different ages and between height and diameter at the same ages. However, there was no consistent trend in the direction of change in optimum climate with tree age. (4) The range of climate inhabited by the populations (P I₁ = -5.792 to 4.483) was much wider than the range of their predicted optimum climate (P̂ Ō₁ = -1.001 to 0.842), which suggests that in terms of growth potential some populations inhabit sub-optimal climates. Implications of the results on management of white spruce in Alberta are discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".