Nonsymbiotic nitrogen fixation in 3-year-old Jeffrey pines and the role of elevated [CO<sub>2</sub>]
Bibliographic record
Abstract
Increased belowground labile C inputs under elevated [CO2] could stimulate nonsymbiotic N2 fixation, thereby enhancing growth responses of vegetation to elevated [CO2] on nutrient-poor sites. To test this hypothesis, nonsymbiotic N2 fixation rates in soils planted with 3-year-old Jeffrey pine (Pinus jeffreyi Grev. & Balf.) trees grown under 365 and 700 µL·L1 atmospheric [CO2] were measured by exposing the soil to 15N2-enriched air for 78 d. Nitrogen fixation rates were estimated by measuring 15N content of trees and soil. Compared with the ambient CO2 treatment, the elevated CO2 treatment did not affect biomass, N content, or δ15N of individual plant parts and soils, indicating that elevated [CO2] did not stimulate nonsymbiotic N2 fixation. Because belowground C inputs did not increase under elevated [CO2], the initial hypothesis could not be accepted or rejected. The results from the 15N2 labeling study agree with other studies showing that nonsymbiotic N2 fixation is not likely to provide a large input of N in forest ecosystems. The 15N2 labeling technique was promising for studying N2 fixation in plantsoil systems, but the preliminary nature of this study did not allow for firm conclusions with regard to the effects of elevated [CO2].
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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 | 0.000 |
| 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".