Chemical changes to leaf litter from trees grown under elevated CO<sub>2</sub>and the implications for microbial utilization in a stream ecosystem
Bibliographic record
Abstract
Chemical alterations to leaf litter associated with growth under elevated CO2may impact aquatic ecosystems that rely on terrestrial leaf litter as a carbon source. This study examined how elevated CO2altered the chemistry and subsequent response of stream microorganisms growing on the leaf litter of three riparian tree species. Quaking aspen (Populus tremuloides), white willow (Salix alba), and sugar maple (Acer saccharum) were grown under ambient (360 parts per million) and elevated (720 parts per million) CO2for an entire growing season and senesced leaf litter was incubated in a stream for 80 days. Elevated-CO2effects on the chemistry of senesced litter were species-specific. Aspen leaves contained higher concentrations of lignin, maple leaves contained higher concentrations of soluble phenolic compounds, and willow leaves contained higher concentrations of carbohydrate-bound condensed tannins. Initially higher concentrations of soluble phenolic compounds in maple leaves were rapidly leached in stream water. However, higher concentrations of carbohydrate-bound tannins in elevated-CO2-grown willow leaves persisted and were correlated with reduced phenol oxidase activities of attached microbiota. Overall, altered leaf chemistry associated with growth under elevated CO2did not strongly suppress microbial activity during stream incubation. In cases where there was evidence of suppression, it was largely species-specific.
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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) | 0.001 | 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".