Patterns of trophic niche overlap of diadromous and marine Arctic fishes in Beaufort Sea coastal lagoons
Bibliographic record
Abstract
Ongoing climatic changes in the coastal Arctic can influence the food webs that support a variety of fish species and subsistence fisheries in coastal lagoons. Along the Beaufort Sea coast, lagoons provide productive summer feeding habitats for both diadromous fishes migrating from freshwater and marine fishes migrating from the shelf. We compared trophic niche size and niche overlap between diadromous species, Arctic Cisco ( Coregonus autumnalis ), Least Cisco ( Coregonus sardinella ), and Dolly Varden ( Salvelinus malma ), and marine species, Polar Cod ( Boreogadus saida ), Fourhorn Sculpin ( Myoxocephalus quadricornis ), and Saffron Cod ( Eleginus gracilis ), across lagoon systems differing in freshwater input and oceanic exchange. Using complementary biomarkers (stomach contents, bulk δ 13 C and δ 15 N, compound-specific amino acid δ 13 C, and fatty acid profiles), we found that diadromous fishes consistently exhibited broader trophic niches than marine fishes, reflecting their ability to exploit both freshwater and offshore pelagic resources. Trophic overlap occurred across the two life histories in both lagoon types, but was greater in high-exchange lagoons, primarily due to shared reliance on amphipods, mysids, and marine carbon sources. Considering the different biomarker turnover times, this overlap likely extends from late winter ice cover into open water periods. These results suggest that competition for prey is probable among species with contrasting life histories, particularly during periods of low prey abundance. By resolving seasonal and spatial patterns of trophic overlap, our findings provide important baseline knowledge for modeling future scenarios of lagoon connectivity and for informing subsistence fisheries management under ongoing changes in the Arctic.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.003 |
| 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 teacher head, 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".