Benthic-pelagic trophic coupling in an Arctic marine food web along vertical water mass and organic matter gradients
Bibliographic record
Abstract
Understanding drivers of benthic-pelagic coupling in Arctic marine ecosystems is key to identifying benthic areas that may be sensitive to climatedriven changes in hydrography and surface production.We coupled algal biomass and sedimentary characteristics with stable isotope data for 113 fishes and invertebrates in the Canadian Beaufort Sea and Amundsen Gulf to examine how trophic structure was influenced by the vertical water mass structure and by organic matter input regimes, from 20 to 1000 m depths.Indices of community-level trophic diversity (isotopic niche size, 13 C enrichment relative to a pelagic baseline, and δ 13 C isotopic range) increased from west to east, coincident with the use of more diverse dietary carbon sources among benthic functional groups.Data suggested benthic-pelagic trophic coupling was strongest in the western study region where pelagic sinking flux is relatively high, intermediate in the central region dominated by riverine inputs of terrestrial organic matter, and weakest in the east where strong pelagic grazing is known to limit sinking flux.Differences in δ 13 C between pelagic and benthic functional groups (up to 5.7‰) increased from west to east, and from the nearshore shelf to the upper slope.On the upper slope, much of the sinking organic matter may be intercepted in the water column, and dynamic hydrography likely diversifies available food sources.In waters >750 m there were no clear trends in benthic-pelagic coupling or community-level trophic diversity.This study represents the first description of fish and invertebrate food web structure >200 m in the Canadian Beaufort Sea. KEY WORDS: Water column • Benthic food supply • Beaufort Sea • Niche dimensionsMobile benthic predators and scavengers collected in the Canadian Beaufort Sea.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".