Fine-scale geographic variation in photosynthetic-related traits of<i>Picea glauca</i>seedlings indicates local adaptation to climate
Bibliographic record
Abstract
Climate-related variations in functional traits of boreal tree species can result both from physiological acclimation and genetic adaptation of local populations to their biophysical environment. To improve our understanding and prediction of the physiological and growth responses of populations to climate change, we studied the role of climate of seed origin in determining variations in functional traits and its implications for tree improvement programs for a commonly reforested boreal conifer, white spruce (Picea glauca (Moench) Voss). We evaluated growth, root-to-shoot ratio (R/S), specific leaf area (SLA), needle nitrogen (N(mass)), total non-structural carbohydrates (NSC) and photosynthetic traits of 3-year-old seedlings in a greenhouse experiment using seed from six seed orchards (SO) representing the different regions where white spruce is reforested in Québec. Height and total dry mass (TDM) were positively correlated with photosynthetic capacity (A(max)), stomatal conductance (g(s)) and mesophyll conductance (g(m)). Total dry mass, but not height growth, was strongly correlated with latitude of seed origin (SO) and associated climate variables. A(max), g(s), g(m) and more marginally, photosynthetic nitrogen-use efficiency (PNUE) were positively associated with the mean July temperature of the SO, while water use efficiency (WUE) was negatively associated. Maximum rates of carboxylation (V(cmax)), maximum rates of electron transport (J(max)), SLA, N(mass), NSC and R/S showed no pattern. Our results did not demonstrate a higher Amax for northern seed orchards, although this has been previously hypothesized as an adaptation mechanism for maintaining carbon uptake in northern regions. We suggest that gs, gm, WUE and PNUE are the functional traits most associated with fine-scale geographic clines and with the degree of local adaptation of white spruce populations to their biophysical environments. These geographic patterns may reflect in situ adaptive genetic differences in photosynthetic efficiency along the cline.
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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) | 0.000 | 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 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".