Spatial pattern and patchiness during ontogeny: post-settled Gadus morhua from coastal Newfoundland
Bibliographic record
Abstract
We tested the hypothesis that patchiness increases after settlement to the bottom in a marine broadcast spawner, the Atlantic cod Gadus morhua . Patchiness P=1+1/k was estimated from the dispersion parameter k of the negative binomial distribution. Estimates were based on length frequency distributions of fish from 18–330 mm that were seined from shallow nursery areas (<10 m depth) during autumn. Patchiness was highest for small cod (<24 mm) in the process of settling to benthic or epibenthic habitats. Settling cod were only collected from coastal sites located in deep fjords where adults overwinter and spawn. Patchiness was lowest for fish newly settled to benthic habitats (c. 50 mm SL) and increased thereafter with length to 200 mm SL. Our analyses suggest that patchiness in G. morhua > 200 mm depends on a shifting balance between establishment of home ranges (tending to reduce patchiness) and schooling behaviour (tending to increase patchiness). Patchiness generally increased for G. morhua between 25–200 mm SL when examined at different spatial (major bays along the northeast coast of Newfoundland) and temporal (years) scales suggesting processes responsible for these patterns may be consistent among the bays and years examined. Our results show that more is learned about the distribution of fish by examining the zeroth, first, and second moments (presence/absence, mean abundance and patchiness) than by examining only one measure. We hypothesize that patchiness continues to increase for larger juvenile and adult G. morhua that were not examined in this study. We propose that patchiness may then decrease for the very largest cod, “mother fish” that may not undergo extensive annual spawning migrations.
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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 | 0.001 |
| 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".