From salmon to salmonberry: The effects of salmon‐derived nutrients on the stomatal density of leaves of the nitriphilic shrub <i>Rubus spectabilis</i>
Bibliographic record
Abstract
Abstract Nutrients derived from the carcasses of Pacific salmon have been shown to have wide‐ranging effects on riparian systems. These include changes in community species composition and an increase in leaf nitrogen concentration, with the latter effect pronounced in the nitriphilic shrub Rubus spectabilis (salmonberry). Experimental work with other species has shown that leaf stomatal density increases in response to nitrogen fertilization. We predicted that the stomatal density of salmonberry leaves would vary directly with the density of spawning salmon in salmonberry leaves collected from 16 streams in the vicinity of Bella Bella, on British Columbia’s central coast. We estimated the stomatal density along each stream, and quantified stream characteristics, including the number of spawning salmon ( Oncorhynchus spp.), canopy cover, stem density and soil moisture. We found that salmon have both direct and indirect effects on stomatal density, the latter mediated by canopy cover and stem density. Salmonberry stomatal density increased by 1.12 stomata per mm 2 (~0.5%) for every kg of salmon per metre of stream. Over the range of salmon densities observed (1.8–49.0 kg per metre of stream), stomatal density increased by almost 45 mm − 2 , or more than 20%. These data confirm that the stomatal density in salmonberry responds positively to the opportunity for greater productivity provided by salmon carcasses. The data provide insight into the physiological and morphological processes supporting nitrogen uptake, which in turn influences plant community composition. A plain language summary is available for this article.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 teacher head, 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".