Large contribution of pulsed subsidies to a predatory fish inhabiting large stream channels
Bibliographic record
Abstract
Resource subsidies exert critical influences on recipient habitats with relatively higher perimeter-to-area ratios, such as headwaters in watersheds. However, little is known about how those subsidies contribute to the energy sources in recipient habitats where the perimeter-to-area ratio is low, such as large stream channels. Here, we show that the diet of small Japanese eels (Anguilla japonica) <500 mm in total length inhabiting natural shoreline areas in large stream channels consists largely of terrestrial earthworms (Metaphire spp.). Stable isotopic analyses showed that the earthworms were the prey animal that contributed most to the eels’ diet (45%–47%). Earthworms constituted the largest portion of the eels’ stomach contents (7%–93%). Eels ingested earthworms within 2 days after rainfall during spring, summer, and autumn, and their consumption increased as the precipitation increased. These findings indicate that the pulsed earthworm subsidy that is driven by rainfall could temporarily bias the eels’ diet toward this allochthonous resource, which may explain the large contribution of the subsidy for consumers inhabiting large stream channels. Furthermore, diverse earthworm species could drive multiple pulsed subsidies across seasons and provide the predators with a prolonged subsidy, enhancing the long-term contribution of the subsidy to the predators’ diet.
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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 | 0.000 |
| 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 | 0.000 | 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".