Realized Genetic Gains in Coastal Douglas-fir in British Columbia: Implications for Growth and Yield Projections
Bibliographic record
Abstract
Abstract Realized genetic gain trials for coastal Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) at five different sites with four different spacings were assessed at age 12 to compare early gain predictions in growth from small plot progeny test designs to those obtained from large block designs. Seedlings from three genetic levels, i.e., local wild-stand controls (WS), a mid-gain seedlot (MG), and a top-cross seedlot (TC) were planted in 12 × 12 tree plots with two replications at spacings of 1.6 m, 2.3 m, 2.9 m and 4.0 m. Two replications of a “single-tree plot” design at 2.9 m spacing for the three genetic levels (30 trees per genetic level) were also established, to allow for more detailed comparisons between single-tree and multiple-tree plot means. Although these trials are still relatively young, trees in the closest spacing had the highest levels of mortality with the TC trees having the highest rate of survival. Height gains in the block trials ranged from 10.4% to 16.1% for MG and TC trees, respectively, and were relatively close to the predicted values; however, volume (individual tree and volume/ha) gains exceeded expectations. Effects of genetic entry on height at age 12 were highly significant, while spacing, genetic entry by spacing, and genetic entry by test site interactions were not significant. We also compared height growth over the first 12 years to growth estimated from the “Bruce height growth model” for Douglas-fir and found that on four of the five test sites our MG and TC seedlings follow the expected height growth trajectories.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.001 |
| 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".