Litter Controls Earthworm-Mediated Carbon and Nitrogen Transformations in Soil from Temperate Riparian Buffers
Bibliographic record
Abstract
Nutrient cycling in riparian buffers is partly influenced by decomposition of crop, grass, and native tree species litter. Nonnative earthworms in riparian soils in southern Quebec are expected to speed the processes of litter decomposition and nitrogen (N) mineralization, increasing carbon (C) and N losses in gaseous forms or via leachate. A 5-month microcosm experiment evaluated the effect ofAporrectodea turgidaon the decomposition of 3 litter types (deciduous leaves, reed canarygrass, and soybean stem residue). Earthworms increased CO2and N2O losses from microcosms with soybean residue, by 112% and 670%, respectively, but reduced CO2and N2O fluxes from microcosms with reed canarygrass by 120% and 220%, respectively. Litter type controlled the CO2flux (soybean ≥ deciduous-mix litter = reed canarygrass > no litter) and the N2O flux (soybean ≥ no litter ≥ reed canarygrass > deciduous-mix litter). However, in the presence of earthworms, there was a slight increase in C and N gaseous losses of C and N relative to their losses via leachate, across litter treatments. We conclude that litter type determines the earthworm-mediated decomposition effect, highlighting the importance of vegetation management in controlling C and N losses from riparian buffers to the environment.
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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 | 0.001 | 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".