Genotypic variation in C and N isotope discrimination suggests local adaptation of heart-leaved willow
Bibliographic record
Abstract
Plants acquire multiple resources from the environment and may need to adjust and/or balance their respective resource-use efficiencies to maximize grow and survival, in a locally adaptive manner. In this study, tissue and whole-plant carbon (C) isotopic composition (δ13C) and carbon/nitrogen (C/N) ratios provided long-term measures of use efficiencies for water (WUE) and nitrogen (NUE), and a nitrogen (N) isotopic composition (δ15N)-based mass balance model was used to estimate traits related to N uptake and assimilation in heart-leaved willow (Salix eriocephala Michx.). In an initial common garden experiment consisting of 34 populations, we found population-level variation in δ13C, C/N ratio and δ15N, indicating different patterns in WUE, NUE and N uptake and assimilation. Although there was no relationship between foliar δ13C and C/N ratios among populations, there was a significant negative correlation between these measures across all individuals, implying a genetic and/or plastic trade-off between WUE and NUE not associated with local adaptation. To eliminate any environmental effect, we grew a subset of 21 genotypes hydroponically with nitrate as the sole N source and detected significant variation in δ13C, δ15N and C/N ratios. Variation in δ15N was mainly due to genotypic differences in the nitrate efflux/influx ratio (E/I) at the root. Both experiments suggested clinal variation in δ15N (and thus N uptake efficiency) with latitude of origin, which may relate to water availability and could contribute to global patterns in ecosystem δ15N. There was a tendency for genotypes with higher WUE to come from more water-replete sites with shorter and cooler growing seasons. We found that δ13C, C/N ratio and E/I were not inter-correlated, suggesting that the selection of growth, WUE, NUE and N uptake efficiency can occur without trade-off.
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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".