Global change factors reshape the links between litter properties, decomposers, and decomposition in mature oak forests
Bibliographic record
Abstract
Abstract 1.) Increasing atmospheric CO 2 concentrations alongside more frequent and severe droughts are key global change factors impacting litter decomposition and global carbon cycles. Yet, we have a poor understanding of how these perturbations impact interactions between initial litter chemical properties and the abiotic and biotic properties of the decomposition environment, especially under field conditions. 2.) We tested how drought and elevated atmospheric CO 2 concentrations modify litter decomposition via litter properties and decomposition environment using two separate, long-term manipulative drought or elevated CO 2 field experiments in mature oak woodlands. Litterbags were deployed in a reciprocal transplant design within each experiment, where we measured litter mass loss, carbon-biochemistry, C:N ratios, moisture content, and microbial and mesofaunal properties. 3.) We found that litter placed in droughted plots decomposed slower than in control plots and experimental litter derived from elevated CO 2 plots decomposed slower over the first three harvests compared to control litter. Under drought, litter mass loss rates and C:N ratio was regulated by initial litter properties and the decomposition environment, while elevated CO 2 impacted mass loss via changes in initial litter properties. 4.) Synthesis : We show that drought and elevated atmospheric CO 2 can modify the decomposability of litter prior to litterfall and during the subsequent decomposition, highlighting the need to disentangle their individual and interactive effects to better predict how global change factors influence decomposition.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.001 |
| 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 teacher head, 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".