An ecological carrying capacity assessment for shellfish aquaculture in Baynes Sound, British Columbia
Bibliographic record
Abstract
Baynes Sound (BS), located in the waters of Georgia Strait, British Columbia (B.C.), is considered one of the most prolific production sites for bivalve culture in B.C.. Bivalve production is influenced by a balance of water quality, hydrodynamics (bay flushing), and food supply (plankton). An ecological carrying capacity assessment is required to assess this balance, where mathematical models can integrate these complex interactions using a high resolution spatially-explicit model. The Finite Volume Community Ocean Model (FVCOM) was coupled with a Bivalve Culture Ecosystem Model (BiCEM) resorting to the Dynamic Energy Budget (DEB) to simulate bivalve physiology and their interactions with the ecosystem. These models were previously developed to address aquaculture issues in the Broughton Archipelago and Discovery Islands regions of B.C. The physical oceanographic conditions are simulated using FVCOM, analogous to previous aquaculture-motivated applications in the Broughton Archipelago and Discovery Islands. Both oceanographic observations and FVCOM outputs show a characteristic two-layered estuarine circulation over BS. This estuarine circulation appears to be strengthened or weakened by river run-off and atmospheric forcing on a seasonal scale and constitutes an overall key feature for the Sound’s water inner circulation and exchange with the Strait of Georgia (SoG). The biogeochemical processes are simulated using BiCEM, which predicted that wind forcing, tidal mixing, and estuarine residual circulation contribute to the regular nutrient replenishment from the deep waters of the SoG, leading to high levels of pelagic primary productivity (phytoplankton). In turn, this phytoplankton productivity supports the potential for secondary production of zooplankton and bivalve culture. In general, the response of zooplankton and wild bivalve populations to the existing shellfish aquaculture activity indicates a system within the bounds of its ecological carrying capacity. Although the planned expansion of additional farm coverage and stock, currently under review, would impose an increased demand on the Sound’s pelagic resources, the results do not indicate that the additional bivalve production could not be sustained. However, a precautionary approach should be considered with high-stocking scenarios and concentrated areas, such as, Fanny, Mud, and Deep Bays. Gradual aquaculture development in concert with proper monitoring of environmental and cultured shellfish conditions (Research Paper #2) in sensitive areas may provide sustainability of BS.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".