Impact of Future Elevated Carbon Dioxide on C<sub>3</sub>Plant Resistance to Biotic Stresses
Bibliographic record
Abstract
Before the end of the century, atmospheric carbon dioxide levels are predicted to increase to approximately 900 ppm. This will dramatically affect plant physiology and influence environmental interactions and, in particular, plant resistance to biotic stresses. This review is a broad survey of the current research on the effects of elevated CO2(eCO2) on phytohormone-mediated resistance of C3agricultural crops and related model species to pathogens and insect herbivores. In general, while plants grown in eCO2often have increased constitutive and induced salicylic acid levels and suppressed induced jasmonate levels, there are exceptions that implicate other environmental factors, such as light and nitrogen fertilization in modulating these responses. Therefore, this review sets the stage for future studies to delve into understanding the mechanistic basis behind how eCO2will affect plant defensive phytohormone signaling pathways under future predicted environmental conditions that could threaten global food security to inform the best agricultural management practices. [Formula: see text] Copyright © 2022 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".