Relative influence of bioturbation and predation on organic matter processing in river sediments: a microcosm experiment
Bibliographic record
Abstract
Summary 1. Our objective was to measure the effects of bioturbation and predation on the physical characteristics and biogeochemical processes in river sediments. 2. We investigated the impacts of tubificid worms tested separately and together with an omnivore (Gammarus pulex), which does feed on tubificids, on sediment distribution, water flux, sediment organic carbon, biofilm biomass and microbial activities, and the concentrations of dissolved oxygen, dissolved organic carbon, PO , NO , NO and NH in slow filtration sand–gravel columns. We hypothesised that gammarids, which exploit the top 2–3 cm of the sediment, would modify the impact of worms at the sediment surface. 3. In experiments both with and without gammarids, bioturbation by the tubificids modified both the distribution of surface particles in the sediment column and water flux. In addition, microbial aerobic (oxygen consumption) and anaerobic (denitrification and fermentative decomposition of organic matter) processes in the sediment were stimulated in the presence of tubificid worms. However, G. pulex did not affect either the density or bioturbation activity of the tubificid worms. 4. Bioturbation by the benthos can be a major process in river habitats, contributing to the retention of organic matter in sediment dynamics. The presence of at least one predator had no effect on bioturbation in sediments. In such systems, physical heterogeneity may be sufficient for tubificids to escape from generalist predators, though more specialised ones might have more effect.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".