The Impacts of the Non-native Macrophyte Cabomba caroliniana
Bibliographic record
Abstract
ABSTRACT. An established population of Cabomba caroliniana now covers extensive littoral areas in the shallow waters of Kasshabog Lake (Ontario). This is the first known naturalized population of this non-native aquatic macrophyte, commonly called fanwort, on the Canadian side of the Great Lakes basin, despite the fact that it was first reported in the 1930s. High dispersal potentials combined with the ability to adapt and grow in a range of environmental conditions have made C. caroliniana a nuisance species in Australia, Japan, and parts of the United States. However, little is known about the broader ecological implications of its introduction and establishment. Using a survey approach, we conducted a preliminary assessment of water chemistry, macrophyte, epiphytic algae, and macroinvertebrate communities found in C. caroliniana beds and compared them with native macrophyte beds in Kasshabog Lake. Light pene-tration was significantly reduced in the C. caroliniana beds and was the only sampled physio-chemical parameter that differed between bed types. We also found several notable differences in the structure and composition of biological communities within macrophyte beds. While native macrophytes were present in dense C. caroliniana beds, abundance was considerably low and unevenly distributed. Significantly more epiphytic algae was present on C. caroliniana plants, however community composition was compa-rable with epiphytic algae found on native macrophytes. The taxonomic composition of macroinverte-
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".