Relationship between photosynthesis and leaf nitrogen concentration in ambient and elevated [CO2] in white birch seedlings
Bibliographic record
Abstract
To study the effects of elevated CO2 concentration ([CO2]) on relationships between nitrogen (N) nutrition and foliar gas exchange parameters, white birch (Betula papyrifera Marsh.) seedlings were exposed to one of five N-supply regimes (10, 80, 150, 220, 290 mg N l(-1)) in either ambient [CO2] (360 micromol mol(-1)) or elevated [CO2] (720 micromol mol(-1)) in environment-controlled greenhouses. Foliar gas exchange and chlorophyll fluorescence were measured after 60 and 80 days of treatment. Photosynthesis showed a substantial down-regulation (up to 57%) in response to elevated [CO2] and the magnitude of the down-regulation generally decreased exponentially with increasing leaf N concentration. When measured at the growth [CO2], elevated [CO2] increased the overall rate of photosynthesis (P(n)) and instantaneous water-use efficiency (IWUE) by up to 69 and 236%, respectively, but decreased transpiration (E) and stomatal conductance (g(s)) in all N treatments. However, the degree of stimulation of photosynthesis by elevated [CO2] decreased as photosynthetic down-regulation increased from 60 days to 80 days of treatment. Elevated [CO2] significantly increased total photosynthetic electron transport in all N treatments at 60 days of treatment, but the effect was insignificant after 80 days of treatment. Both P(n) and IWUE generally increased with increasing leaf N concentration except at very high leaf N concentrations, where both P(n) and IWUE declined. The relationships of P(n) and IWUE with leaf N concentration were modeled with both a linear regression and a second-order polynomial function. Elevated [CO2] significantly and substantially increased the slope of the linear regression for IWUE, but had no significant effect on the slope for P(n). The optimal leaf N concentration for P(n) and IWUE derived from the polynomial function did not differ between the CO2 treatments when leaf N was expressed on a leaf area basis. However, the mass-based optimal leaf N concentration for P(n) was much lower in seedlings in elevated [CO2] than in ambient [CO2] (31.88 versus 37.00 mg g(-1)). Elevated [CO2] generally decreased mass-based leaf N concentration but had no significant effect on area-based leaf N concentration; however, maximum N concentration per unit leaf area was greater in elevated [CO2] than in ambient [CO2] (1.913 versus 1.547 g N m(-2)).
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".