Tracing biogeochemical subsidies from glacier runoff into Alaska's coastal marine food webs
Bibliographic record
Abstract
Abstract Nearly half of the freshwater discharge into the Gulf of Alaska originates from landscapes draining glacier runoff, but the influence of the influx of riverine organic matter on the trophodynamics of coastal marine food webs is not well understood. We quantified the ecological impact of riverine organic matter subsidies to glacier‐marine habitats by developing a multi‐trophic level Bayesian three‐isotope mixing model. We utilized large gradients in stable (δ13C, δ15N, δ2H) and radiogenic (Δ14C) isotopes that trace riverine and marine organic matter sources as they are passed from lower to higher trophic levels in glacial‐marine habitats. We also compared isotope ratios between glacial‐marine and more oceanic habitats. Based on isotopic measurements of potential baseline sources, ambient water and tissues of marine consumers, estimates of the riverine organic matter source contribution to upper trophic‐level species including fish and seabirds ranged from 12% to 44%. Variability in resource use among similar taxa corresponded to variation in species distribution and life histories. For example, riverine organic matter assimilation by the glacier‐nesting seabirds Kittlitz's murrelet (Brachyramphus brevirostris) was greater than that of the forest‐nesting marbled murrelet (B. marmoratus). The particulate and dissolved organic carbon in glacial runoff and near surface coastal waters was aged (12100–1500 years BP 14C‐age) but dissolved inorganic carbon and biota in coastal waters were young (530 years BP 14C‐age to modern). Thus terrestrial‐derived subsidies in marine food webs were primarily composed of young organic matter sources released from glacier ecosystems and their surrounding watersheds. Stable isotope compositions also revealed a divergence in food web structure between glacial‐marine and oceanic sites. This work demonstrates linkages between terrestrial and marine ecosystems, and facilitates a greater understanding of how climate‐driven changes in freshwater runoff have the potential to alter food web dynamics within coastal marine ecosystems in Alaska.
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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 | 0.000 | 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) | 0.001 | 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".