Planktonic invaders of the St. Lawrence estuarine transition zone: environmental factors controlling the distribution of zebra mussel veligers
Bibliographic record
Abstract
The St. Lawrence estuarine transition zone (ETZ) is a productive ecosystem supporting a larval fish nursery. Since 1994, Dreissena polymorpha veligers have become the dominant zooplankton (up to 260 individuals·L1). The environmental factors controlling their distribution across the ETZ and their potential impact on the plankton were determined. Their horizontal distribution was limited by salinity, with maximum decreases in concentration at 2. A sharp decline in prey availability at >2 may be a secondary stressor for the veligers, in addition to the direct effects of salinity. Their vertical distribution was homogeneous throughout the water column, even in the presence of a pycnocline. Redundancy analysis showed that veliger concentrations were positively correlated with temperature and turbidity and negatively correlated with salinity and total phosphorus. Veligers were also positively correlated with chlorophyll a and picophytoplankton concentrations, suggesting little effect on their phytoplankton prey. Moreover, the veligers were positively correlated with the sestonic ratio of particulate to total phosphorus, indicating their positive association with good food quality. The veligers appear to have no severe negative impacts on the ETZ plankton community and are restricted to favourable conditions for their survival in the upstream, low salinity region of the ETZ.
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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 | 0.001 | 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".