Leaf litter diversity and structure of microbial decomposer communities modulate litter decomposition in aquatic systems
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Leaf litter decomposition is a major ecosystem process that can link aquatic to terrestrial ecosystems by flows of nutrients. Biodiversity and ecosystem functioning research hypothesizes that the global loss of species leads to impaired decomposition rates and thus to slower recycling of nutrients. Especially in aquatic systems, an understanding of diversity effects on litter decomposition is still incomplete. Here we conducted an experiment to test two main factors associated with global species loss that might influence leaf litter decomposition. First, we tested whether mixing different leaf species alters litter decomposition rates compared to decomposition of these species in monoculture. Second, we tested the effect of the size structure of a lotic decomposer community on decomposition rates. Overall, leaf litter identity strongly affected decomposition rates, and the observed decomposition rates matched measures of metabolic activity and microbial abundances. While we found some evidence of a positive leaf litter diversity effect on decomposition, this effect was not coherent across all litter combinations and the effect was generally additive and not synergistic. Microbial communities, with a reduced functional and trophic complexity, showed a small but significant overall reduction in decomposition rates compared to communities with the naturally complete functional and trophic complexity, highlighting the importance of a complete microbial community on ecosystem functioning. Our results suggest that top‐down diversity effects of the decomposer community on litter decomposition in aquatic systems are of comparable importance as bottom‐up diversity effects of primary producers. A plain language summary is available for this article.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it