Biophysical Factors Impacting Sea Lice Settlement and Survival
Bibliographic record
Abstract
Atlantic salmon (Salmo salar L.) aquaculture production in Maine is a valuable contributor to the economy, the expansion of which has been challenged by the parasitic salmon louse Lepeophtheirus salmonis. As planktonic organisms, the life of the salmon louse is primarily dictated by the physical conditions of the environment: the temperature for development time, salinity for survival, and current velocity for transport. Salmon lice are obligate parasites for whom the successful infection of a suitable host is critical to completion of their life cycle. However, little is understood about the effects of current velocity on infection success. Hydrodynamic models are tools that describe the physical conditions of the marine environment and have been combined with particle tracking models to predict the dispersal of sea lice in salmon-farming areas in other countries, including Norway, Scotland, Canada, and the Faroe Islands. These models vary in scope, however, many lack a parameter for the effect of velocity on attachment. The purpose of the experiments conducted as part of this thesis is to provide such a parameter for inclusion in a model for sea lice dispersal in Cobscook Bay, one of the primary sites of net pen salmon farming in the United States. PIT-tagged Atlantic salmon were challenged with a standardized dose of salmon lice at low, moderate, and high current velocities commonly experienced by salmon in net-pens in Cobscook Bay at 5, 10, and 15 cm sec-1 (0.10, 0.19, and 0.29 knots), respectively. Mean percent settlement was calculated for each velocity group, and a permutation-based ANOVA was conducted to determine if significant differences existed between groups. Percent settlement was significantly different in all three velocity groups, with optimum settlement occurring at moderate velocity, with high velocity resulting in the lowest average settlement success. The results of this study exhibit similar patterns to what has been observed in other studies and are discussed with respect to sentinel cage surveys previously conducted in Cobscook Bay.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.010 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".