Population differences in stable carbon isotope ratio of <i>Pinus contorta</i> Dougl. ex Loud.: relationship to environment, climate of origin, and growth potential
Bibliographic record
Abstract
Stable carbon isotope composition (δ13C) was used to examine genetic and environmental variation in water-use efficiency of 11 Pinus contorta Dougl. ex Loud. populations from western Canada. Sapwood cores from 20-year-old saplings established at three sites in British Columbia, and shoots of greenhouse-grown, first-year seedlings, were analyzed. δ13C values of whole sapwood and isolated cellulose were correlated at r = 0.990 (p << 0.0001, n = 10). There were genetic differences in δ13C among populations. A population from the wet Pacific coast (P. contorta var. contorta) stood out from the others, which were all from the drier continental interior (P. contorta var. latifolia Engelm). This population had the highest indicated water-use efficiency. δ13C values of most populations increased from the wettest to the driest site with no significant change in ranking. Mean yield (stem volume) of the P. contorta var. latifolia populations was positively correlated with δ13C. Population differences at the seedling stage were not as pronounced, but δ13C values of seedling shoots and sapling wood cores were correlated. Among the 10 P. contorta var. latifolia sapling populations, δ13C decreased with an index of summer dryness and, less so, with increased elevation. It appears, therefore, that the most water-use efficient and most productive populations originate from relatively moderate, low-elevation sites with reduced likelihood of water stress.Key words: water-use efficiency, isotope discrimination, lodgepole pine, phenotypic plasticity, provenance trials.
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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".