Genetic Variation in Picea glauca for Growth and Phenological Traits From Provenance Tests in Ontario
Bibliographic record
Abstract
Abstract Ecologically based management of white spruce (Picea glauca [Moench] Voss.) requires an understanding of its patterns of adaptive variation. This understanding will become increasingly important under changing climate conditions. Five common garden tests and a greenhouse trial established in 2002 across Ontario were used to assess levels of genetic variation and relate this variation to local climate. Growth and phenological variables, including height, root collar diameter, survival, timing of spring budflush, and timing of fall budset were measured. Intraclass correlation coefficients were calculated for all traits to determine levels of genetic variation. Simple linear regressions were used to relate these differences to local climate conditions. After two growing season’s levels of between-provenance genetic variation ranged from 0 percent for several of the budflush variables to 22 percent for 2003 survival at the Englehart field trial. Overall, growth variables showed higher levels of between-provenance variation than phenological variables. Variation was predominately explained by longitude, a surrogate for precipitation patterns in Ontario, and temperature variables related to the growing season with r2 values ranging from 0.03 to 0.55. Generally, patterns of adaptive variation followed a southeast to northwest trend across Ontario. Northern sources flushed earlier and set bud earlier, while southern sources demonstrated superior growth. Results support previous white spruce genecology studies showing superior growth of sources from the Ottawa valley region of Ontario and Quebec.
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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".