Effects of the non‐indigenous cladoceran <i>Cercopagis pengoi</i> on the lower food web of Lake Ontario
Bibliographic record
Abstract
Summary 1. In North America, the invasive predatory cladoceran Cercopagis pengoi was first detected in Lake Ontario. We explored the impact of Cercopagis on the lower food web of Lake Ontario through assessments of historical and seasonal abundance of the crustacean zooplankton, by conducting feeding experiments on the dominant prey of the invader, and by estimating its food requirements. 2. Between 1999 and 2001, a decrease in the abundance of dominant members of the Lake Ontario zooplankton community (Daphnia retrocurva, Bosmina longirostris and Diacyclops thomasi) coincided with an increase in the abundance of Cercopagis. Daphnia retrocurva populations declined despite high fecundity in all 3 years, indicating that food limitation was not responsible. Chlorophyll a concentration generally increased, concomitant with a decline in the herbivorous cladoceran zooplankton in the lake. 3. Laboratory experiments demonstrated that Cercopagis fed on small‐bodied species including D. retrocurva and B. longirostris. 4. Consumption demand of mid‐summer populations of Cercopagis, estimated from a bioenergetic model of the confamilial Bythotrephes, was sufficient to reduce crustacean abundance, although the degree of expected suppression varied seasonally and interannually. 5. Predatory effects exerted by Cercopagis on the Lake Ontario zooplankton, while initially very pronounced, have decreased steadily as the species became established in the lake.
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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 | 0.001 | 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) | 0.002 | 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".