Study type and plant litter identity modulating the response of litter decomposition to warming, elevated CO<sub>2</sub>, and elevated O<sub>3</sub>: A meta‐analysis
Bibliographic record
Abstract
Abstract Plant litter decomposition is one of the most important ecosystem carbon flux processes in terrestrial ecosystems and is usually regarded as sensitive to climate change. The goal of the present study was to examine the effects of changing climate variables on litter decomposition. By synthesizing data from multiple terrestrial ecosystems, we quantified the response of the litter decomposition rate to the independent effects of warming, elevated carbon dioxide (CO2), elevated ozone (O3), and the combined effects of elevated CO2 + elevated O3. Across all case studies, warming increased the litter decomposition rate significantly by 4.4%, but this effect could be reduced as a result of the negatively significant effects of elevated CO2 and elevated CO2 + elevated O3. The combined effects of elevated CO2 + elevated O3 decreased the litter decomposition rate significantly, and the magnitude appeared to be higher than that of the elevated CO2 per se. Moreover, the study type (field versus laboratory), ecosystem type, and plant litter identity and functional traits (growth form and litter form) were all important moderators regulating the response of litter decomposition to climate warming and elevated CO2 and O3. Although litter decomposition rate may show a moderate change as a result of the effects of multiple changing climate variables, the process of litter decomposition would be strongly altered due to the differing mechanisms of the effects of each climate change variable, suggesting that the global carbon cycle and biogeochemistry could be substantially affected.
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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 | 0.011 | 0.011 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.025 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".