Bibliographic record
Abstract
Abstract. The negative effects of tropospheric ozone (O3) on vegetation can lead to reduced photosynthesis, accelerated leaf senescence, and other negative outcomes which affect crop yields and biodiversity. This study presents a flux-based assessment of the global impact of O3 on bread wheat (Triticum aestivum) for the 21st century, under various climate scenarios (Shared Socioeconomic Pathways, SSPs). A dual-sink big-leaf dry deposition model is employed to estimate the phytotoxic ozone dose (POD) absorbed by wheat through stomata, integrating data from two Earth System Models (ESMs) from the Coupled Model Intercomparison Project 6 (CMIP6). The study explores spatial and temporal variations in O3 concentrations and the effects of climate variables on stomatal conductance, explaining changes in POD from the present time to the century’s end. The results indicate significant regional disparities in O3 dose for wheat, particularly under weak O3 precursor emissions control scenarios. The most vulnerable regions include Northern Europe, East China, and the Southern and Eastern edges of the Tibetan Plateau, where the POD increase by the end of the century is expected to be most pronounced. Conversely, POD decreases worldwide under stringent pollution emission control scenarios. However, in some regions, changes in POD may be driven more by climate variables and their interaction with O3, rather than by O3 concentrations alone. Therefore, this study emphasizes the need for effective emission mitigation policies of both O3 precursors and greenhouse gases to preserve global food security from O3 damages.
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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.015 | 0.007 |
| Insufficient payload (model declined to judge) | 0.374 | 0.219 |
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".