A study of algal biofouling on pearl nets in Charles Arm, Notre Dame Bay, Newfoundland
Bibliographic record
Abstract
This study examined the development of biofouling on pearl nets used for culture of the sea-scallop (Placopecten magellanicus) in Charles Arm, Notre Dame Bay, Newfoundland over a two year period, May 1998 until July 2000. The site showed salinities of approximately 30 ISU and surface seasonal temperature fluctuation between -1.5C and 20C. The greatest part of the fouling biomass consisted of macroalgae : Chlorophyta (10 species), Phaeophyta (24 species), Rhodophyta (19 species), together with Cyanobacteria (33 species) and two species of tube dwelling diatoms. All the species recorded were common members of the local benthic flora. Fouling biomass was measured on nets placed at two, and four metre depths. Rapid colonization occurred with growth initially faster at the shallow depth, but after the first year biomass stabilized at approximately I kg per net wet weight, with no significant differences between depths. The fouling community was analyzed using two multivariate techniques, Detrended Correspondence Analysis (DECORANA) and Two-Way Indicator Species Analysis (TWINSPAN). The first year's growth showed considerable floristic changes as the algal fouling developed, with samples from the latter part of the year showing considerable differences from the late spring and early summer. After one years growth few floristic changes were noted. There was no obvious difference in the algal communities between the two depths. -- Two algal grazers, the periwinkle, Littorina littorea and the green sea urchin Strongylocentrotus droebachiensis were investigated as potential biofouling control organisms. Two experiments were conducted, one in the summer months and one over winter. The pearl nets with the urchin treatment showed no significant decrease in fouling, while the periwinkle treatments significantly reduced fouling in the summer. DECORANA and TWINSPAN analysis showed no differences in algal community structure between the experiments and controls, showing that grazing was not species preferential. -- During the course of this study there was a large, and as yet still unexplained, die-off of the cultured scallops at the site, which confounded attempts to determine if the inclusion of algal grazers in the nets affected growth and survival of the scallops. These preliminary studies, however, showed no differences in the growth rate of the scallops with depth, or treatment with snails or urchins. Survival of the scallops was, however, significantly enhanced by the snail treatment in both experiments including enhanced survival in the summer experiment, when scallop loss was greatest.
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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) | 0.001 | 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".