Genetic variation in leaf traits and gas exchange responses to vapour pressure deficit in contrasting conifer species
Bibliographic record
Abstract
Abstract Mechanistically predicting the evolutionary response of tree species to climate change requires an understanding of genetic variation in relevant traits. Here we compared the phenotypic and genetic variation in the Leaf Economics Spectrum (LES) traits and the response of gas exchange to vapour pressure deficit (VPD) in lodgepole pine (Pico) and white spruce (Pigl), an early and a late successional species dominating the boreal forests of western Canada. We measured gas exchange, foliar nitrogen and lamina mass to area ratio in 697 c . 30‐year‐old trees in two field progeny trials. We analysed the response of gas exchange rates to VPD using a novel quantitative genetic model, the function‐valued trait approach. Pico showed greater phenotypic variation in the LES traits and greater genetic variation in photosynthetic rate than Pigl, but the species showed no significant difference in their phenotypic correlations between the LES traits. Pico showed a less sensitive stomatal response to VPD than Pigl and no significant genetic variation in stomatal sensitivity. In contrast, Pigl showed a positive correlation between the genetic values of stomatal sensitivity to VPD and stomatal conductance under low VPD. Our study region is projected to see an increase in VPD with climate change; the less sensitive and genetically diverse stomatal response to VPD in Pico could make this species more vulnerable to climate‐change‐induced droughts. A free Plain Language Summary can be found within the Supporting Information of this article.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.003 | 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 teacher head, 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".