Novel environmental conditions alter subsidy and engineering effects by introduced Pacific salmon
Bibliographic record
Abstract
We demonstrate that the major ecological functions of Pacific salmon (Oncorhynchus spp.) can be altered or re-ordered in non-native habitats where environmental conditions differ from native ranges. We compared subsidy and engineering effects of spawning Pacific salmon in six streams within their introduced range (Laurentian Great Lakes) with responses reported in their native range (northern Pacific Rim). Streamwater nutrient responses (i.e., subsidy effects) in Great Lakes streams were generally weak compared with those reported in native streams, whereas disturbance (i.e., engineering effects) was often strong where salmon were abundant. We attribute the relatively weak nutrient response to high background nutrient concentrations and low salmon biomass. In contrast, in Great Lakes streams with high salmon biomass, sediment routing was intense and pervasive and, consequently, benthic biofilm and macroinvertebrate abundance often declined by over 90% during the salmon run. These strong disturbance effects were likely facilitated by the small sediments that typified the Great Lakes streams. Our study provides evidence that salmon effects are context-dependent at much broader spatial scales than has been reported previously.
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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 | 0.001 |
| 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".