Effects of off‐bottom shellfish aquaculture on winter habitat use by molluscivorous sea ducks
Bibliographic record
Abstract
Abstract Shellfish farming is an expanding segment of marine aquaculture, but environmental effects of this industry are only beginning to be considered. The interaction between off‐bottom, suspended oyster farming and wintering sea ducks in coastal British Columbia was studied. Specifically, the habitat use of surf scoters ( Melanitta perspicillata ) and Barrow's goldeneyes ( Bucephala islandica ), the most abundant sea duck species in the study area, was evaluated in relation to natural environmental attributes and shellfish aquaculture. The extent of shellfish farming was the best‐supported habitat variable explaining variation in surf scoter densities, and the only habitat attribute from the considered set that was a strong predictor of Barrow's goldeneye densities. In both cases, the findings indicated strong positive relationships between densities of sea ducks and shellfish aquaculture operations. These relationships are presumably the result of large numbers of wild mussels ( Mytilus trossulus ) that settle and grow on aquaculture structures and are preferred prey of these sea ducks. Previous work has shown that aquaculture structures provide good conditions for recruiting and growing mussels, including refuge from invertebrate predators, which in turn provides higher densities of higher quality prey for sea ducks than available in intertidal areas. This offers a rare example in which introduction of an industry leads to positive effects on wildlife populations, which is particularly important given persistent declines in numbers of many sea ducks. Copyright © 2008 John Wiley & Sons, Ltd.
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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 | 0.000 | 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) | 0.002 | 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".