Modeling Interactions among Carbon Dioxide, Nitrogen, and Climate on Energy Exchange of Wheat in a Free Air Carbon Dioxide Experiment
Bibliographic record
Abstract
Changes in mass and energy exchange by crops under rising atmospheric CO2 concentration (Ca) may be affected by N and weather; Ca interacts with weather on mass and energy exchange through limitations on latent heat flux imposed by stomatal conductance, which is affected by Ca, and aerodynamic conductance, which is affected by weather. We examined the bases for these interactions with the ecosystem model ecosys Simulation results were tested with energy flux data from a Free Air CO2 Enrichment (FACE) experiment in which wheat (Triticum aestivum L.) was grown under 548 vs. 363 μmol mol−1 Ca and fertilized with 7 vs. 35 g N m−2. Both model and experimental results indicated that raising Ca from 363 to 548 μmol mol−1 reduced midday latent heat fluxes by ca. 50 W m−2 for wheat fertilized with 35 g N m−2, and by ca. 100 W m−2 for wheat fertilized with only 7 g N m−2 when N deficits developed later in the growing season. These reductions were smaller under low wind speeds (<5 km h−1) and stable boundary conditions when aerodynamic conductance became the dominant constraint to transpiration. At a seasonal time scale, raising Ca from 363 to 548 μmol mol−1 reduced simulated (measured) evapotranspiration of wheat by 9% (7%) when fertilized with 35 g N m−2, and by 16% (19%) with 7 g N m−2. Changes with Ca in mass and energy exchange used in climate change studies should therefore reflect the site‐specific availability of N, as well as climate attributes such as wind speed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".