Movers and shakers: nutrient subsidies and benthic disturbance predict biofilm biomass and stable isotope signatures in coastal streams
Bibliographic record
Abstract
Summary Nutrient subsidies and physical disturbance from migrating species can have strong impacts on primary producers. In the north Pacific, adult salmon (Oncorhynchus spp.) transport marine‐derived nutrients back to freshwater streams and can also significantly disrupt the substratum during spawning events. We tested for effects of spawning pink (O. gorbuscha) and chum (O. keta) salmon on stream biofilm. Biofilm is a mix of algae, fungi and bacteria that provides food and habitat and forms the base of these aquatic food webs. We collected rock biofilm samples to compare stable isotopes and biomass prior to and following peak salmon spawning in 16 catchments on the central coast of British Columbia, Canada. We conducted two separate analyses. The first was a within‐stream comparison, which focused on 5 catchments that had a barrier to pink and chum salmon migration. The second was an among‐stream analysis that included all 16 catchments and explicitly considered biotic and abiotic factors, in addition to salmon density, known to influence biofilm growth and isotope ratios. Salmon density proved to be the best predictor of biofilm δ15N. Biofilm δ13C was best predicted by salmon density and catchment size. While spring chlorophyll a increased with mean salmon density, it was on average lower during spawning in the autumn, probably due to physical disturbance from spawning salmon. These results show that of the several variables considered to affect biofilm isotopes and biomass, salmon density and catchment size are among the most influential in coastal streams where salmon spawn.
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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 | 0.001 |
| 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) | 0.001 | 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".