Geographic variation in ecophysiological traits of black cottonwood (<i>Populus trichocarpa</i>)This article is one of a selection of papers published in the Special Issue on Poplar Research in Canada.
Bibliographic record
Abstract
Variation in traits related to photosynthesis and water-use were examined within and between geographic sources (provenances) of black cottonwood in two range-wide common garden experiments in British Columbia, Canada. In the first experiment, CO2 assimilation (A), stomatal conductance (gs), instantaneous intrinsic water use efficiency (WUEi), stomatal density, specific leaf area, growth height, and foliar N were measured on five 2-year-old trees of 20 clones from five widely separated provenances (i.e., 4 clones per source). Leaf disks were analysed for stable carbon isotope composition (δ13C) to provide a more long-term measure of WUE. Photosynthetic rate per unit leaf nitrogen was used as a measure of nitrogen use efficiency (NUE). A differed between (p < 0.001), but not within provenances, and increased with latitude of origin (R2 = 0.70). NUE and WUEi also varied between (p = 0.034 and p = 0.039, respectively), but not within provenances. In contrast, no variation among provenances was detected for δ13C, but there were strong differences between clones within provenances (p < 0.001). Variation in A was well correlated with foliar nitrogen, gs, and stomatal density and adaxial:abaxial distribution ratio; hence, WUEi, δ13C and NUE were mostly unrelated to latitude or associated climate variables. Species-wide patterns in stomatal density and distribution were confirmed in the second experiment which utilized 140 clones. Stomatal density on the adaxial (but not the abaxial) leaf surface was strongly correlated with latitude (p <0.001). We speculate that northern provenances may have inherently higher A and gs to compensate for shorter growing seasons.
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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 | 0.001 |
| 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".