Response of annual growth ring components to soil moisture deficit in young, plantation-grown Douglas-fir in coastal British Columbia
Bibliographic record
Abstract
The response of 10 annual growth ring variables to drought in coastal Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco var. menziesii) was examined using 16- and 17-year-old trees growing in six progeny test sites in southwestern British Columbia. Width, density, and mass components of individual rings common to the same 11-year period were measured on 16 trees at each site using X-ray densitometry of increment cores. For each ring variable and site, the slope of the linear regression of the annual ring component (after adjusting for age trends across the core) on the log of the total growing season soil moisture deficit (SMD) for the same year was used to derive a drought response coefficient (DRC). DRCs quantified the sensitivity of ring components to changing annual moisture conditions across the 11 years on a particular site. SMD appeared to materially influence ring variables on only the driest of the six sites where mean SMD was two to three times greater than at any other site. On this site, DRCs of eight growth ring variables were significantly (p < 0.05) related to SMD. On the remaining sites only six of a total of 50 DRCs were significantly different from zero. These results suggest that the response of annual growth ring variables to drought may be useful for assessing drought hardiness of genotypes in Douglas-fir breeding programs, but only on sites where average SMD is high enough to elicit a drought response.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".