Characterizing spatial structures of larval fish assemblages at multiple scales in relation to environmental heterogeneity in the Strait of Georgia (British Columbia, Canada)
Bibliographic record
Abstract
Spatial structures of larval fish in the Strait of Georgia (British Columbia, Canada) were quantified in the springs of 2009 and 2010 to investigate linkages to environmental heterogeneity at multiple scales. By applying a multiscale approach, principal coordinate neighborhood matrices, spatial variability was decomposed into three predefined scale categories: broad scale (>40 km), medium scale (20∼40 km), and fine scale (<20 km). Spatial variations in larval density of the three dominant fish taxa with different early life histories (Pacific herring (Clupea pallasii), Pacific hake (Merluccius productus), and northern smoothtongue (Leuroglossus schmidti)) were mainly structured at broad and medium scales, with scale-dependent associations with environmental descriptors varying interannually and among species. Larval distributions in the central-southern Strait were mainly associated with salinity, temperature, and vertical stability of the top 50 m of the water column on the medium scale. Our results emphasize the critical role of local estuarine circulation, especially at medium spatial scale, in structuring hierarchical spatial distributions of fish larvae in the Strait of Georgia and suggest the role of fundamental differences in life-history traits in influencing the formation and maintenance of larval spatial structures.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".