Riparian buffers maintain aquatic trophic structure in agricultural landscapes
Bibliographic record
Abstract
Local and regional habitat conditions associated with agricultural activity can fundamentally alter aquatic ecosystems. Increased nutrient inputs, channelization and reduced riparian habitat both upstream and locally contribute to the degradation of stream ecosystems and their function. Here, we examine stream food webs in watersheds that feed into Lake Erie to determine the effects of agricultural land cover on major food web energy pathways and trophic structure. Given that higher agricultural intensity can increase nutrient runoff and reduce the riparian zone and litter in-fall into streams, we predicted that generalist fish would derive less energy from the terrestrial pathway and become more omnivorous. Consistent with these predictions, we show that both mean terrestrial energy use and trophic position of the resident top consumer, creek chub ( Semotilus atromaculatus ), decrease with local agricultural intensity but not with watershed-level agriculture intensity. These findings suggest that local riparian buffers can maintain trophic structure even in the face of high whole-watershed agricultural intensity.
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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 | 0.000 | 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".