Genotypic variation in carbon isotope discrimination and gas exchange of ponderosa pine seedlings under two levels of water stress
Bibliographic record
Abstract
As part of a program to select ponderosa pine (Pinus ponderosa Dougl. ex Laws.) genotypes for improved drought tolerance, we examined physiological and morphological characteristics of 12 half-sib families of ponderosa pine from four seed sources; New Mexico, South Dakota, Nebraska, and Wyoming. We analyzed genetic variation in carbon isotope discrimination (Δ), photosynthetic gas exchange, needle morphology, and growth of 2-year-old seedlings from the four seed sources grown under two levels of moisture availability. To gain a better understanding of within-provenance variation and identify opportunities to refine selection strategies, we also examined family within seed source variation in the traits. Water stress significantly (P < 0.05) reduced net photosynthesis (A), needle conductance to water vapor (gwv), carbon isotope discrimination (Δ), and growth of the seedlings as compared to well-watered seedlings. However, instantaneous water use efficiency (A/gwv) did not differ between water treatments. Seedlings from New Mexico had significantly lower gwv and higher A/gwv than seedlings from the other sources. Carbon isotope discrimination was lowest for seedlings from New Mexico and Nebraska. Families within seed sources varied significantly in A, gwv, stomatal density, needle length, height increment, and Δ. Carbon isotope discrimination was significantly correlated with gwv but not with A, supporting results from mature trees suggesting that variation in Δ in ponderosa pine is more related to gwv than to A. Seed source × water treatment interactions were not observed for any of the traits analyzed. These results support our previous assertion that genotype × environment interaction in Δ of mature ponderosa pine trees from these sources grown in Nebraska and Oklahoma was related to factors other than moisture availability.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.000 | 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".