Urban stressors alter the trophic basis of secondary production in an agricultural stream
Bibliographic record
Abstract
We compared the invertebrate production and stable isotope signatures of key ecosystem compartments of urban sites subjected to the input of tertiary-treated wastewater with those of upstream sites in an agricultural lowland stream. We detected a significant shift in the trophic basis of invertebrate production from upstream, natural and agricultural resources, to urban resources, i.e., wastewater-derived organic matter as well as autochthonous primary production based on wastewater-derived nutrients. Invertebrate production was higher at urban sites than at agricultural sites. However, the median contribution of the most important secondary producer, the shredder Gammarus roeseli , to total invertebrate production was lower at urban sites (9%) than at agricultural sites (61%). The low production of G. roeseli at urban sites was associated with the absence of allochthonous coarse particulate organic matter (CPOM) habitats, rather than the loss of CPOM as a food resource. Our results suggest that contemporary urban stressors in developed countries affect secondary producers less severely than historically recorded, but still profoundly change the matter fluxes and ecosystem functioning of running waters. Restoration of the native riparian vegetation, channel naturalization, and adequate dilution of tertiary-treated wastewater may partially mitigate adverse effects on invertebrate communities and their secondary production.
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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".