Effects of elevated <scp>CO</scp><sub>2</sub> on the extractable amino acids of leaf litter and fine roots
Bibliographic record
Abstract
Elevated atmospheric CO2 concentrations can change chemistry and input rate of plant tissue to soil, potentially influencing above- and below-ground biogeochemical cycles. Given the important role played by leaf and root litter chemistry in controlling ecosystem function and vulnerability to environmental stresses, we investigated the hydrolyzable amino acid distribution and concentration in leaf and fine root litter among control and elevated CO2 treatments at the Rhinelander free air CO2 enrichment (FACE) experiment (WI, USA). We extracted hydrolyzable amino acids from leaf litter and fine (< 2 mm) roots at three depths for both control and elevated CO2 plots. We found that elevated CO2 decreased the proportion of total leaf amino acid carbon (C), but had no effect on total leaf amino acid nitrogen (N). There was no treatment effect for total root amino acid N or amino acid C for any depth. The decrease in leaf amino acids is probably a result of the shift of protein compounds to more structural compounds. Despite the decrease in leaf amino acid C concentrations, the overall increase in annual plant production under elevated CO2 would result in an increase in plant amino acids to the soil.
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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 | 0.001 |
| Scholarly communication | 0.001 | 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".