Impacts of <i>Dreissena</i> invasions on benthic macroinvertebrate communities: a meta‐analysis
Bibliographic record
Abstract
ABSTRACT Dreissenid mussels (the zebra mussel Dreissena polymorpha and the quagga mussel Dreissena bugensis ) have invaded lakes and rivers throughout North America and Europe, where they have been linked to dramatic changes in benthic invertebrate community diversity and abundance. Through a meta‐analysis of published data from 47 sites, we developed statistical models of Dreissena impact on benthic macroinvertebrates across a broad range of habitats and environmental conditions. The introduction of Dreissena was generally associated with increased benthic macroinvertebrate density and taxonomic richness, and with decreased community evenness (of taxa excluding Dreissena ). However, the strength of these effects varied with sediment particle size across sites. The effects of Dreissena differed among taxonomic and functional groups of macroinvertebrates, with positive effects on the densities of scrapers and predators, particularly leeches (Hirudinea), flatworms (Turbellaria), and mayflies (Ephemeroptera). Gastropod densities increased in the presence of Dreissena , but large‐bodied snail taxa tended to decline. Dreissena was associated with declines in the densities sphaeriid clams and other large filter‐feeding taxa, as well as burrowing amphipods ( Diporeia spp.), but had strong positive effects on gammarid amphipods. These patterns are robust to variation in the methodology of primary studies. The effects of Dreissena are remarkably concordant with those of ecologically similar species, suggesting universality in the interactions between introduced byssally attached mussels and other macroinvertebrates.
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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 | 0.013 | 0.017 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.039 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".