Plant carbon metabolism and climate change: elevated <scp>CO</scp><sub>2</sub> and temperature impacts on photosynthesis, photorespiration and respiration
Bibliographic record
Abstract
Contents Summary 32 I. The importance of plant carbon metabolism for climate change 32 II. Rising atmospheric CO2 and carbon metabolism 33 III. Rising temperatures and carbon metabolism 37 IV. Thermal acclimation responses of carbon metabolic processes can be best understood when studied together 38 V. Will elevated CO2 offset warming‐induced changes in carbon metabolism? 40 VI. No plant is an island: water and nutrient limitations define plant responses to climate drivers 41 VII. Conclusions 42 Acknowledgements 42 References 42 Appendix A1 48 Summary Plant carbon metabolism is impacted by rising CO 2 concentrations and temperatures, but also feeds back onto the climate system to help determine the trajectory of future climate change. Here we review how photosynthesis, photorespiration and respiration are affected by increasing atmospheric CO 2 concentrations and climate warming, both separately and in combination. We also compile data from the literature on plants grown at multiple temperatures, focusing on net CO 2 assimilation rates and leaf dark respiration rates measured at the growth temperature ( A growth and R growth , respectively). Our analyses show that the ratio of A growth to R growth is generally homeostatic across a wide range of species and growth temperatures, and that species that have reduced A growth at higher growth temperatures also tend to have reduced R growth , while species that show stimulations in A growth under warming tend to have higher R growth in the hotter environment. These results highlight the need to study these physiological processes together to better predict how vegetation carbon metabolism will respond to climate change.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.020 | 0.002 |
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".