Attenuation of sunlight measured from moored radiometers to assess depletion of suspended particles caused by bivalve aquaculture
Bibliographic record
Abstract
Bivalve suspension‐feeding can produce horizontal gradients of particulate suspended matter, or seston, which may impair bivalve growth among other impacts to the coastal ecosystem. We proposed a method to assess the concentration of seston at different locations along a shellfish farm by means of measurements of the depth‐averaged diffuse attenuation coefficient of downwelling irradiance at 490 nm, K̅, from at least two autonomous buoys equipped with a vertical array of irradiance sensors. Two approaches were compared. First, horizontal gradients of chlorophyll plus phaeopigments (Chl) were calculated from K̅ using an empirical algorithm derived from water samples. In the second approach, gradients of particulate suspended matter were calculated after correcting K̅ for the attenuation due to water and riverine colored dissolved organic matter (CDOM), estimated from continuous in situ measurements of salinity. The method was assessed in a mussel farm in Ship Harbour (Nova Scotia, Canada). The proposed method is relatively insensitive to the angular distribution of downwelling irradiance, biofouling, frame‐shading, and wave focusing; but it cannot be easily applied in places with strong and sustained sediment resuspension. This method can complement and validate current modeling studies of seston depletion, and it can assist managerial activities and legislative requirements of shellfish aquaculture. This method can also be used to assess gradients of other ecologically relevant substances (i.e., CDOM, phytoplankton, and seston) in applications associated with sewage discharges, river runoff, harmful algal blooms, suspension‐feeding invasive bivalves, and other horizontally variable phenomena in the coastal ocean.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".