Structure of marine predator and prey communities along environmental gradients in a glaciated fjord
Bibliographic record
Abstract
Spatial patterns of marine predator communities are influenced to varying degrees by prey distribution and environmental gradients. We examined physical and biological attributes of an estuarine fjord with strong glacier influence to determine the factors that most influence the structure of predator and prey communities. Our results suggest that some species, such as walleye pollock (Theragra chalcogramma), black-legged kittiwake (Rissa tridactyla), and glaucous-winged gull (Larus glaucescens), were widely distributed across environmental gradients, indicating less specialization, whereas species such as capelin (Mallotus villosus), harbor seal (Phoca vitulina), and Kittlitz's murrelet (Brachyramphus brevirostris) appeared to have more specialized habitat requirements related to glacial influence. We found that upper trophic level communities were well correlated with their mid trophic level prey community, but strong physical gradients in photic depth, temperature, and nutrients played an important role in community structure as well. Mid-trophic level forage fish communities were correlated with the physical gradients more closely than upper trophic levels were, and they showed strong affinity to tidewater glaciers. Silica was closely correlated with the distribution of fish communities, the mechanisms of which deserve further study.
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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 | 0.001 | 0.000 |
| 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".