Interactions between fish communities and shellfish aquaculture in Baynes Sound, British Columbia
Bibliographic record
Abstract
Shellfish aquaculture is a developing industry along northeast Pacific coastlines and represents another potential stressor to already impacted nearshore ecosystems. The industry is particularly prominent in Baynes Sound, British Columbia (BC), Canada. The region hosts the operations which account for approximately 35% of all clams and 50% of all oysters produced in BC. Concurrently, it represents one of the most ecologically valuable areas in the northeast Pacific. In this study, I examined the interactions of benthic intertidal shellfish aquaculture with nearshore fish communities using abundance, biodiversity (species richness, diversity, and evenness), and functional diversity (Rao’s quadratic entropy and functional evenness) metrics. Also, I measured habitat complexity, as defined by a contour distance:linear distance ratio, at all fish sampling sites because it has often been identified as a driver of community variation. Fish abundance, biodiversity, and functional diversity did not vary between aquaculture and non-aquaculture sites. Additionally, habitat complexity, while on average was 1.2x greater at aquaculture beaches compared to non-aquaculture reference beaches, was not a strong driver of these indicators. Fish communities in Baynes Sound are relatively homogenous on a small scale and are highly functionally redundant, meaning that there is considerable overlap of species’ roles in the ecosystem. In summary, the presence of shellfish aquaculture in Baynes Sound is not associated with either a positive or negative response of fish communities. Furthermore, these communities are functionally redundant and therefore are likely resilient to ecosystem disturbances.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".