Aquatic food web response to patchy shading along forested headwater streams
Bibliographic record
Abstract
In forested streams, changes in age and structure of riparian vegetation have been shown to directly influence the amount of light reaching the stream benthos. The potential for light to directly impact primary productivity in forested streams is generally understood, but most field experiments exploring reach-scale in-stream light dynamics have evaluated large changes in riparian vegetation. Fewer studies have quantified influences of smaller changes in irradiance, particularly how patchy in-stream light developed with complex riparian forests affects stream biota. We applied patches of shade, covering ∼50% of three manipulation reaches, which were each paired with an unmanipulated reference reach. We quantified changes in stream light availability, benthic periphyton, and aquatic macroinvertebrate, fish, and salamander biomass using a before–after control–impact study design. Patchy shading decreased localized and reach-scale light and reduced periphyton, macroinvertebrate, fish, and salamander biomass in manipulation sites relative to the reference reaches. Results suggest that moderate changes in stream light, such as those that occur through stand development and small-scale disturbance processes, can impact stream biota through bottom-up processes.
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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".