Isotopic evidence for episodic nitrogen fixation in switchgrass (Panicum virgatum L.)
Bibliographic record
Abstract
Perennial grasses can assimilate nitrogen (N) fixed by non-nodulating bacteria living in the rhizosphere and the plant's own tissues, but many details of associative N fixation (ANF) remain unknown, including ANF's contribution to grass N nutrition, the exact location of fixation, and composition of the associated microbial community. We examined ANF in switchgrass ( Panicum virgatum L.), a North American perennial grass, using 15 N-enriched N 2 isotopic tracer additions in a combination of in vitro , greenhouse, and field experiments to estimate how much N is assimilated, where fixation takes place, and the likely N-fixing taxa present. Using in vitro incubations, we documented fixation in root-free rhizosphere soil and on root surfaces, with average rates of 3.8 μg N g root −1 d −1 on roots and 0.81 μg N g soil −1 d −1 in soil. In greenhouse transplants, N fixation occurred only in the early growing season, but in the field, fixation was irregularly detectable throughout the 3-month growing season. Soil, leaves, stems, and roots all contained diazotrophs and incorporated fixed N 2 . Metagenomic analysis suggested that microbial communities were distinct among tissue types and influenced by N fertilizer application. A diverse array of microbes inhabiting the rhizosphere, and possibly aboveground tissues, appear to be episodically contributing fixed N to switchgrass.
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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".