Ancient CO2 Levels Favor Nitrogen Fixing Plants Over a Broader Range of Soil N Compared to Present
Bibliographic record
Abstract
Abstract Small inreases in CO2 stimulate nitrogen fixation and plant growth. Increasing soil N can inhibit nitrogen fixation. However, no studies to date have tested how nitrogen fixing plants perform under ancient CO2 levels (100 MYA) when nitrogen fixers evolved, with different levels of N additions. The aim of this study was to assess if ancient CO2, compared to present, favors nitrogen fixers over a range of soil nitrogen concentrations. Nitrogen fixers (Alnus incana ssp. rugosa, Alnus viridis ssp. crispa, and Alnus rubra) and their close non-nitrogen fixing relatives (Betula pumila, Betula papyrifera, Betula glandulosa) were grown at ancient CO2 (1600 ppm) or present CO2 (400 ppm) over a range of soil N levels, equivalent to 0, 10, 50, and 200 kg N ha-1 year-1. The growth of non-N fixing plants increased more than N fixing plants in response to the increasing N levels. When grown at an ancient CO2 level, the N level at which non-nitrogen fixing plant biomass exceeded nitrogen fixing plant biomass was twice as high (61 kg N ha-1 y-1) as the N level when plants were grown at an ambient CO2 level. Specific nodule activity was also reduced with an increasing level of soil N. Our results showed there was a greater advantage in being a nitrogen fixer under ancient levels of CO2 compared with the present CO2 level.
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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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".