Detritus processing, ecosystem engineering and benthic diversity: a test of predator–omnivore interference
Bibliographic record
Abstract
Summary Interference between species from different functional groups may influence ecosystem functioning and biological diversity. This study tested whether interactions between predacious cutthroat trout and an omnivorous signal crayfish modified the crayfish's trophic and engineering effects within a detrital‐based, stream benthic community. We show in a trough experiment that omnivorous crayfish through their trophic and engineering roles enhance detritus decomposition, reduce particulate organic matter (POM) accumulation, and diminish diversity in leaf packs. In crayfish troughs by day 30, leaf dry weight loss was 1·8‐fold greater, whereas POM trapped in leaf packs was 80% less, than of those in controls, and the abundance, biomass and taxon richness of benthos in leaf packs were lower than those in controls. Predatory cutthroat trout did not affect those variables and did not interfere with the crayfish. Crayfish and cutthroat trout both decreased fine material sedimentation in the troughs. Thus, with no interference from cutthroat trout, the signal crayfish acted as ecosystem processors and engineers, and strongly influenced detrital processing, benthic diversity, and the accumulation of POM and fine sediments.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".