Effect of elevated carbon dioxide in the root atmosphere on nitrogenase activity in three actinorhizal plant species
Bibliographic record
Abstract
In wet soils, nitrogen-fixing root nodules are subjected to elevated CO2. Only a few studies have examined the effect of elevated CO2 on nitrogenase activity, and the results have been mixed. We examined intact black alder (Alnus glutinosa (L.) Gaertn.) and sweet gale (Myrica gale L.) seedlings and field-collected speckled alder (Alnus incana ssp. rugosa (Du Roi) Claus.) nodules to clarify the effects of elevated CO2. Nitrogenase activity was measured via acetylene reduction in an open, flow-through system. We found that repeated measurements of the peak rate of nitrogenase activity, the only reliable measure of nitrogenase activity, could be made on the same plant via 150-s exposures to acetylene separated by 20 min without acetylene. Our results for elevated CO2 consistently showed that it had little effect on nitrogenase activity at low concentrations and increasingly inhibited nitrogenase activity as the CO2 concentration increased. In black alder, 0.5 kPa CO2 had little effect, whereas 3.0 kPa CO2 reduced nitrogenase activity 3135%. Sweet gale, was less sensitive to elevated CO2 and was unaffected by 1.5 kPa CO2. Black alder grown with the roots, but not the shoots, in 1.3 kPa CO2 showed only minimal acclimation to elevated CO2.Key words: acetylene reduction technique, actinorhizal plants, Alnus, carbon dioxide, Myrica gale, nitrogen fixation.
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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) | 0.001 | 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) | 0.001 | 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".