Stress differentially causes roots of tree seedlings to exude carbon
Bibliographic record
Abstract
How carbon (C) flows through plants into soils is poorly understood. Carbon exuded comes from a pool of non-structural carbohydrates (NSC) in roots. Simple models of diffusion across concentration gradients indicate that the more C in roots, the more C should be exuded from roots. However, the mechanisms underlying the accumulation and loss of C from roots may differ depending on the stress experienced by plants. Thus, stress type may influence exudation independent of NSC. We tested this hypothesis by examining the relationship between NSC in fine roots and exudation of organic C in aspen (Populus tremuloides Michx.) seedlings after exposure to shade, cold soils and drought in a controlled environment. Fine root concentrations of NSC varied by treatment. Mass-specific C exudation increased with increasing fine root sugar concentration in all treatments, but stress type affected exudation independently of sugar concentration. Seedlings exposed to cold soils exuded the most C on a per mass basis. Through 13C labeling, we also found that stressed seedlings allocated relatively more new C to exudates than roots compared with unstressed seedlings. Stress affects exudation of C via mechanisms other than changes in root carbohydrate availability.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".