Incubation time, functional litter diversity, and habitat characteristics predict litter-mixing effects on decomposition
Why this work is in the frame
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Bibliographic record
Abstract
Plant diversity influences many fundamental ecosystem functions, including carbon and nutrient dynamics, during litter breakdown. Mixing different litter species causes litter mixtures to lose mass at different rates than expected from component species incubated in isolation. Such nonadditive litter-mixing effects on breakdown processes often occur idiosyncratically because their direction and magnitude change with incubation time, litter species composition, and ecosystem characteristics. Taking advantage of results from 18 litter mixture experiments in streams, we examined whether the direction and magnitude of nonadditive mixing effects are randomly determined. Across 171 tested litter mixtures and 510 incubation time-by-mixture combinations, nonadditive effects on breakdown were common and on average resulted in slightly faster decomposition than expected. In addition, we found that the magnitude of nonadditive effects and the relative balance of positive and negative responses in mixtures change predictably over time, and both were related to an index of functional litter diversity and selected environmental characteristics. Based on these, it should be expected that nonadditive effects are stronger for litter mixtures made of functionally dissimilar species especially in smaller streams. Our findings demonstrate that effects of litter diversity on plant mixture breakdown are more predictable than generally thought. We further argue that the consequences of current worldwide homogenization in the composition of plant traits on carbon and nutrient dynamics could be better inferred from long-duration experiments that manipulate both functional litter diversity and ecosystem characteristics in "hotspots of biodiversity effects," such as small streams.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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 it