Small stonefly predators affect microbenthic and meiobenthic communities in stream leaf packs
Bibliographic record
Abstract
Summary Predators affect benthic communities and ecological processes through consuming and scaring prey as well as through engineering effects on the habitat. Experimental evidence of top–down predatory effects in leaf packs comes from studies assessing how large predators affect shredders and therefore the litter decomposition rate. In this study, we investigated the effects of smaller invertebrate predators on micro‐ and meiobenthic communities. In outdoor, flow‐through stream channels, we created a gradient in the density of predacious Chloroperlidae stonefly larvae in enclosures containing alder leaf litter and exposed to natural colonisation by invertebrates and decomposers. We expected that: (i) predators would reduce the biomass and density of invertebrate colonisers, (ii) the strength of predator effects on invertebrates would vary with prey body size; and (iii) increasing predator numbers in enclosures would diminish the per capita strength of predator–prey interactions due to intraguild interference. We also anticipated that litter decomposition would be slower in the presence of predators providing that microbial decomposers did not compensate for the reduction in shredders by an increase in their biomass. Chloroperlidae had negative effects on the biomass of most major invertebrate taxa, including rotifers, nematodes and larvae of the Chironomidae Corynoneura and Brillia (the dominant shredder in leaf packs). The predatory effect on nematode biomass was strongest for dominant small‐bodied species. Fungal biomass in leaf litter was reduced in the presence of predators, whereas bacterial biomass was not affected. In addition to feasible direct predation on Chironomidae, Chloroperlidae apparently inhibited meiofauna colonisation of leaf litter, probably through the bioturbation of fine sediment trapped on leaf surfaces. At the end of the experiment, the mortality of Chloroperlidae in enclosures was considerable at the highest predator density treatment. This observation, along with evidence of the reduced per capita strength of predator–prey interactions with increasing predator density, suggested that intraguild interference moderates the effect of predators in leaf packs. Our findings are consistent with a key role of small predators in determining the abundance of invertebrates and microbial decomposers in leaf packs. However, in our study, there was no cascade down to the standing stock of leaf litter.
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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 | 0.000 | 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".