Dispersal and emerging ecological impacts of Ponto-Caspian species in the Laurentian Great Lakes
Bibliographic record
Abstract
We describe, explain, and "predict" dispersal and ecosystem impacts of six Ponto-Caspian endemic species that recently invaded the Great Lakes via ballast water. The zebra mussel, Dreissena polymorpha, and quagga mussel, Dreissena bugensis, continue to colonize hard and soft substrates of the Great Lakes and are changing ecosystem function through mechanisms of ecosystem engineering (increased water clarity and reef building), fouling native mussels, high particle filtration rate with selective rejection of colonial cyanobacteria in pseudofeces, alteration of nutrient ratios, and facilitation of the rapid spread of their Ponto-Caspian associates, the benthic amphipod Echinogammarus ischnus and the round goby, Neogobius melanostomus, which feeds on zebra mussels. The tubenose goby,Proterorhinus marmoratus, which does not feed on zebra mussels, has not spread rapidly. Impacts of these benthic invaders vary with site: in some shallow areas, habitat changes and the Dreissena [Formula: see text] round goby [Formula: see text] piscivore food chain have improved conditions for certain native game fishes and waterfowl; in offshore waters, Dreissena is competing for settling algae with the native amphipod Diporeia spp., which are disappearing to the detriment of the native deep-water fish community. The predatory cladoceran Cercopagis pengoi may compete with small fishes for zooplankton and increase food-chain length.
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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 | 0.001 | 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".