The direct impacts of an introduced seaweed Mazzaella japonica on benthic seaweed communities in Baynes Sound and possible interaction with the invasive seaweed Sargassum muticum.
Bibliographic record
Abstract
Marine introduced algae have become established in coastal communities around the globe. There is great lack of understanding of how this trophic group in general impacts the habitats they are introduced to. Mazzaella japonica is an introduced, red seaweed that is thought to have been brought to Canada via the aquaculture trade as a hitch hiker with the Japanese oyster (Crassostrea gigas). While C. gigas and other hitch hikers (such as the brown seaweed Sargassum muticum) have become invasive all over the world, M. japonica has only been reported as introduced to Baynes Sound. As this species has never been previously studied it is essential to understand how its presence impacts the native seaweed communities of Baynes Sound. To understand the direct impact that M. japonica is having on its host ecosystem a long-term, in situ study was established in April, 2013. M. japonica was removed from half of the established experimental plots at two sites and the native seaweed recovery was quantified by over time and compared to control plots. Removal of M. japonica resulted in a significant community shift. Number of native species and percent cover of native species significantly increased over time. Perhaps the most interesting result is the establishment of another introduced seaweed Sargassum muticum in some of the removal plots where none had been previously recorded during the course of the experiment. It appears that the removal of this novel introduced species allows for a significant increase or recovery of native species indicating that it is having a negative impact on native seaweeds. Preliminary ecological and management implications will also be discussed.
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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 | 0.001 |
| 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".