Growth and physiological responses of canola (<i>Brassica napus</i>) to three components of global climate change: temperature, carbon dioxide and drought
Bibliographic record
Abstract
Elevated CO 2 appears to be a significant factor in global warming, which will likely lead to drought conditions in many areas. Few studies have considered the interactive effects of higher CO 2 , temperature and drought on plant growth and physiology. We grew canola ( Brassica napus cv. 45H72) plants under lower (22/18°C) and higher (28/24°C) temperature regimes in controlled‐environment chambers at ambient (370 μmol mol −1 ) and elevated (740 μmol mol −1 ) CO 2 levels. One half of the plants were watered to field capacity and the other half at wilting point. In three separate experiments, we determined growth, various physiological parameters and content of abscisic acid (ABA), indole‐3‐acetic acid and ethylene. Drought‐stressed plants grown under higher temperature at ambient CO 2 had decreased stem height and diameter, leaf number and area, dry matter, leaf area ratio, shoot/root weight ratio, net CO 2 assimilation and chlorophyll fluorescence. However, these plants had increased specific leaf weight, leaf weight ratio and chlorophyll concentration. Elevated CO 2 generally had the opposite effect, and partially reversed the inhibitory effects of higher temperature and drought on leaf dry weight accumulation. This study showed that higher temperature and drought inhibit many processes but elevated CO 2 partially mitigate some adverse effects. As expected, drought stress increased ABA but higher temperature inhibited the ability of plants to produce ABA in response to drought.
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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) | 0.001 | 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) | 0.001 | 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".