Assessing the probability and impact of secondary invasions of Hemimysis anomala to inland lakes of Ontario
Bibliographic record
Abstract
The Great Lakes basin is regarded as one of the most heavily invaded freshwater ecosystems in the world.The most recent and relatively unstudied invader is Hemimysis anomala, a littoral freshwater mysid native to the Ponto-Caspian region.The ecological impacts of Hemimysis invasions are poorly understood, as is the potential role that recreational boating traffic could play in facilitating its secondary spread to inland lakes.In 2010, Hemimysis were detected in one of the Finger Lakes of New York State, U.S.A.To assess the potential for similar inland movement to occur in the Rideau Canal, I conducted boater surveys, bilge sampling and detection sampling at lock stations and nearby sites along the shoreline of Lake Ontario.Hemimysis were present in samples from all four Lake Ontario sites.Although absent from samples collected within the canal and from bilge wells, I still recommend increasing boater awareness and participation in decontamination procedures prior to upstream travel.I found that few boaters conducted thorough cleaning tasks and that many heavily relied on automatic pumps to expel bilge water, not controlling the release of potentially invasive species.I also conducted feeding rate experiments to test the functional response of Hemimysis in the presence of chemical cues of a North American predator, lake trout.Exposure to lake trout kairomone had no effect on the prey consumption of Hemimysis.This uninhibited feeding could enhance the impact of Hemimysis on littoral zooplankton communities and stresses the need to further understand how Hemimysis will affect North American aquatic ecosystems.My results supplement our knowledgebase of Hemimysis activity in addition to providing further insight into the role of recreational boaters as vectors of invasive species dispersal.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 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".