Influence of zebra (Dreissena polymorpha) and quagga (Dreissena rostriformis) mussel invasions on benthic nutrient and oxygen dynamics
Bibliographic record
Abstract
Although invasive zebra ( Dreissena polymorpha ) and quagga ( Dreissena rostriformis ) mussels are known to increase water column concentrations of nitrogen and phosphorus, the relative roles of direct nutrient release by the mussels and mussel-induced alterations to sediment fluxes are little understood. In short-term microcosm experiments comparing the presence and absence of mussels on sediments from Oneida Lake, New York, USA, both dreissenid species approximately doubled benthic oxygen consumption and fluxes of ammonium. The impact on soluble reactive phosphate (SRP) flux varied from 40% to 140% depending on whether mussels were located in the water column or directly on sediments. The additional flux was attributable directly to release by the mussels, with fluxes from the sediments remaining largely unchanged. However, mussels located directly on sediment surfaces released twice as much SRP as mussels located higher in the water column, with a molar N:P ratio as low as 4:1. The high rate of SRP release by mussels on sediment, possibly caused by mobilization of iron-bound phosphorus from sediment particles in the anoxic guts of the mussels, could contribute to observed increases in SRP, abundance of nuisance algae such as Cladophora , and abundance and toxicity of the cyanobacteria Microcystis in dreissenid invaded ecosystems.
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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 | 0.001 |
| 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".