Benthic bioturbator enhances CH<sub>4</sub> fluxes among aquatic compartments and atmosphere in experimental microcosms
Bibliographic record
Abstract
We utilized laboratory microcosms to evaluate the effects of a benthic sediment bioturbator ( Heteromastus similis ; Polychaeta; conveyor-belt deposit feeder) on vertical distributions of CH4 in sediment and net CH4 fluxes across sediment–water–air interfaces. The effect of H. similis on sediment CH4 concentration ([CH4]) varied depending on sediment depth and was strongest at higher animal densities. In comparison with defaunated controls, microcosms with the highest density of H. similis exhibited an increase in [CH4] of 3.7-fold, on average, at the sediment surface (0–2 cm), but these concentrations decreased by ~2-fold in deeper sediment layers (2–8 cm). However, irrespective of sediment depth, the density of H. similis resulted in an overall nonlinear reduction of bulk sediment [CH4]. Most of the observed CH4 losses from the sediment were due to CH4 oxidation, but the bioturbatory activities of H. similis also promoted significant increases in [CH4] in both the water column and the microcosm headspace. These results suggest that benthic invertebrates can mediate CH4 turnover between compartments in aquatic ecosystems, with further consequences for the coupling between benthic–pelagic food chains via the methanotrophic-mediated microbial loop, as well as increase CH4 emissions to the atmosphere.
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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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".