Trophic niche variation across the pan-Arctic coastal continuum
Bibliographic record
Abstract
We analyzed stable carbon and nitrogen isotope values (δ13C and δ15N, respectively) for pan-Arctic coastal primary producers and consumers to detect large-scale regional trends both temporally and spatially. To facilitate comparison, we grouped coastal habitats into fjords, lagoons, shelves, and straits as four "coastscapes". We gathered over 12,000 rows of data collected over 24 years (between 1999 and 2022) from 34 different field campaigns across the coastal Arctic (63 to 81°N and 177°W to 33°E). Our goal was to examine the isotopic patterns in pelagic and sediment particulate organic matter (pPOM and sPOM, respectively) and four consumer groups (deposit feeders, opportunists/scavengers, predators, and suspension feeders) among the four coastscapes. We found that despite the enormous spatial range of data, both pPOM and sPOM became 2.1‰ and 2.2‰ more 13C-depleted per decade, respectively, with parallel decreases in the δ13C values in consumers. The significant decrease is likely attributed to the increased contributions of 13C-depleted terrestrial organic matter across the Arctic coasts from freshwater inputs and coastal erosion in concert with diminishing sea ice that supports sympagic microalgae. Across all Arctic coastscapes, consumer groups exhibited overlapping isotopic composition, notably with wide δ13C ranges that indicated assimilation of multiple organic matter sources, including terrestrial organic matter, organic matter derived from marine phytoplankton and sea ice algae, macroalgae, and potentially benthic microalgae or degraded organic matter. This consistent pattern across coastscapes provides evidence of the trophic plasticity possessed by Arctic consumers, how coastal food webs respond to climate warming, and the signature of terrestrialization imprinted on the pan-Arctic coastal isoscape.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".