Increasing atmospheric <scp>CO</scp><sub>2</sub> reduces metabolic and physiological differences between isoprene‐ and non‐isoprene‐emitting poplars
Bibliographic record
Abstract
Isoprene, a volatile organic compound produced by some plant species, enhances abiotic stress tolerance under current atmospheric CO2 concentrations, but its biosynthesis is negatively correlated with CO2 concentrations. We hypothesized that losing the capacity to produce isoprene would require stronger up-regulation of other stress tolerance mechanisms at low CO2 than at higher CO2 concentrations. We compared metabolite profiles and physiological performance in poplars (Populus × canescens) with either wild-type or RNAi-suppressed isoprene emission capacity grown at pre-industrial low, current atmospheric, and future high CO2 concentrations (190, 390 and 590 ppm CO2 , respectively). Suppression of isoprene biosynthesis led to significant rearrangement of the leaf metabolome, increasing stress tolerance responses such as xanthophyll cycle pigment de-epoxidation and antioxidant levels, as well as altering lipid, carbon and nitrogen metabolism. Metabolic and physiological differences between isoprene-emitting and suppressed lines diminished as growth CO2 concentrations rose. The CO2 dependence of our results indicates that the effects of isoprene biosynthesis are strongest at pre-industrial CO2 concentrations. Rising CO2 may reduce the beneficial effects of biogenic isoprene emission, with implications for species competition. This has potential consequences for future climate warming, as isoprene emitted from vegetation has strong effects on global atmospheric chemistry.
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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".