Pacific herring spawn events influence nearshore subtidal and intertidal species
Bibliographic record
Abstract
As intermediaries between the bottom and top of food webs, forage fish fuel a diversity of coastal consumers and are of socioecological importance throughout the world's oceans.Many forage fish are migratory, but despite their recognized importance, relatively little is known about their role in providing spatial subsidies, which are the movements of energy, material, and organisms across ecosystems.Until recently, spatial subsidies associated with Pacific herring Clupea pallasii, a dominant migratory forage fish that spawns in subtidal and intertidal zones, received little scrutiny.Building on research that traced links between herring spawns and coastal ecosystems, we used stable isotopes of carbon (δ 13 C) and nitrogen (δ 15 N) to assess whether herring spawning events influenced isotopic signatures of 10 macrophyte and invertebrate species across beaches where spawning did or did not occur.Overall, species collected from spawning beaches had significantly greater δ 15 N levels (general linear mixed model parameter estimate = 1.58 ± 0.17 SE, F 1, 370 = 83.77,p < 0.001); no significant effects were detected for δ 13 C (parameter estimate = 0.03 ± 0.23 SE, F 1, 343 = 0.01, p = 0.914).In terms of total nitrogen, macrophytes from spawning beaches had significantly elevated concentrations (parameter estimate = 5.03 ± 0.94 SE, F 1,180 = 28.71,p < 0.001).Using directional statistics, mean angles of isotopic change differed significantly between species collected from spawning and non-spawning beaches (Watson-Williams F-test; F 1, 48 = 10.44,p = 0.002).Our study identifies multiple species as recipients of herring-derived nutrients at spawning events, providing additional evidence of the broad ecological influence of Pacific herring.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".