Spawning salmon density influences fruit production of salmonberry (<i>Rubus spectabilis</i>)
Bibliographic record
Abstract
Abstract Annual spawning migrations by Pacific salmon can provide substantial subsidies to nutrient‐limited freshwater and riparian ecosystems, which can affect the abundance, diversity, and physical characteristics of plant and animal species in these habitats. Here, we provide the first investigation of how salmon subsidies affect reproductive output in plants, focusing on a common riparian shrub, salmonberry ( Rubus spectabilis ). We studied 14 streams with a range of spawning salmon densities on the central coast of British Columbia, Canada. We determined the effects of chum ( Oncorhynchus keta ), pink ( O. gorbuscha ), and total salmon spawning density on the number of fruits per shrub, number of seeds per fruit, fruit weight, and estimated sugar content (° Brix) of salmonberry fruits. We found that the number of fruits per salmonberry shrub increased with increasing salmon density. However, we found no effect of salmon density on the number of seeds per fruit, fruit weight, or sugar content. The effect of salmon density was species‐dependent; the number of fruits per shrub increased with chum salmon density but was not affected by pink salmon density. This could be because chum salmon occur at higher densities and are transferred from water to land at higher rates than pink salmon in our study area. Higher salmonberry fruit production could lead to a larger input of salmonberry fruits to coastal food webs. These results demonstrate how salmon can cross ecological boundaries and influence reproductive output of terrestrial species.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.004 | 0.001 |
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; both teacher heads agree on what is shown here.
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".