Variation in seedling budburst phenology and structural traits among southwestern ponderosa pine provenances
Bibliographic record
Abstract
We used a common garden study to investigate genetic variation in spring budburst phenology, growth, and structural traits of ponderosa pine (Pinus ponderosa Lawson & C. Lawson var. scopulorum Engelm.) seedlings from 10 provenances of different elevations in Arizona and New Mexico, United States. Seedlings were grown with ample resources for two growing seasons in a greenhouse in northern Arizona. Budburst date was measured at the onset of the second growing season; seedling growth, biomass, biomass ratios (shoot:root ratio, root mass ratio, stem mass ratio, and leaf mass ratio), and specific leaf area were measured at the end of the second season. Low-elevation provenances (<2000 m) had earlier budburst and lower specific leaf area than middle- (2000–2500 m) and high-elevation (>2500 m) provenances. Height, leaf length, biomass, and biomass ratios were similar for elevational groups. Total biomass was positively correlated (r = 0.824) with provenance mean annual precipitation. Shoot:root ratio was positively correlated (r = 0.652) with longitude. Results suggest adaptation of low-elevation provenances to warm spring temperatures (early budburst) and aridity (low specific leaf area), inherently faster growth of provenances from wet locations, and greater allocation to shoots in eastern provenances. Such information about geographic patterns of genetic variation may be useful for selecting seed sources for planting in a changing climate.
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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 | 0.000 |
| 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 | 0.000 | 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".