Meta-Analysis of Salmon Trophic Ecology Reveals Spatial and Interspecies Dynamics Across the North Pacific Ocean
Bibliographic record
Abstract
We examined spatial patterns in diet, trophic niche width and niche overlap for chum, pink and sockeye salmon across the North Pacific during 1959–1969. This is a baseline period before major hatchery enhancement occurred coinciding with a negative phase of the Pacific Decadal Oscillation. Large-scale (between regions) and fine-scale (within regions) spatial and interspecies differences were apparent. In the Western Subarctic, all species tended to consume zooplankton. In the Bering Sea, chum consumed zooplankton, while sockeye and pink alternated between zooplankton and micronekton. In the Gulf of Alaska/Eastern Subarctic, chum and sockeye specialized on gelatinous zooplankton and cephalopod prey, respectively, while pink consumed a mixture of zooplankton and micronekton. The highest diet overlap across the North Pacific was between pink and sockeye (46.6%), followed by chum and pink (31.8%), and chum and sockeye (30.9%). Greater diet specialization was evident in the Gulf of Alaska/Eastern Subarctic compared to the Western Pacific. Generally, species had higher niche width and overlap in areas of high prey availability, and this was particularly evident for chum salmon. In addition to the large-scale trophic patterns, our data revealed novel fine-scale spatial patterns, including latitudinal, onshore-offshore, and cross-gyre gradients. Our results showed that pink tended to be more generalist consumers, and their diets may be a better reflection of overall prey presence and abundance in the environment. Conversely, chum and sockeye tended to be more specialist consumers, and their diets may provide a better reflection of interspecies dynamics or prey availability. This study provides a baseline for comparison with current and future changes in salmon marine ecology and North Pacific ecosystems. Finally, we identify two important data gaps that need addressing, that of improved taxonomic resolution diet data for Pacific salmon and focused research on sub-mesoscale oceanographic features that may play an important role in salmon health and productivity.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".