Genetic and geographic determinants of nitrogen isotope discrimination in black cottonwood (<i>Populus trichocarpa</i>)
Bibliographic record
Abstract
Genotypic variation in nitrogen-use traits remains largely unexplored in trees on a range-wide scale, either in field studies or under controlled experiments. Understanding natural variation in nitrogen-related traits and their relationships to climate is essential for studying local adaptation and advancing breeding efforts. In this study, we took advantage of a large collection of black cottonwood genotypes covering a major portion of the species' natural range, to study the genetic variation in nitrogen isotope discrimination (Δ15N). Nearly 350 unrelated wild genotypes were grown under steady-state hydroponic conditions and analyzed for growth and Δ15N-related traits. Differences in biomass, root-to-shoot ratio, whole-plant and organ-level nitrogen percentages, and Δ15N were found between genotypes and populations. Leaf nitrogen percentage and root-to-shoot ratio were significantly correlated to geographic and climatic variables, implying natural selection for lower leaf nitrogen and lower root-to-shoot ratio in regions with longer growing seasons and a lower risk of drought. Root Δ15N and (less so) leaf Δ15N correlated with geographic and climatic variables, and measurements from either tissue provide a reasonable indication of plant nitrogen uptake efficiency. A genome-wide association study was conducted on leaf and root Δ15N, leaf nitrogen percentage and root-to-shoot ratio. The analysis identified a candidate gene encoding glutaminyl-tRNA synthetase linked to root Δ15N, but found no significant associations with genes involved in nitrate transport or assimilation. However, multiple associations were detected for root-to-shoot ratio and leaf nitrogen percentage, both of which affect isotope-based calculations of root nitrogen efflux/influx and leaf nitrogen assimilation activity.
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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".