Fish community responses to multiple municipal wastewater inputs in a watershed
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Municipalities utilize aquatic environments to assimilate their domestic effluent resulting in eutrophication, anoxia, toxicity and endocrine disruption of aquatic biota. The objective of this study was to assess the potential cumulative impacts of municipal wastewater effluent (MWWE) discharges in the Grand River on the health status of a sentinel species and the fish community downstream of 2 MWWE discharges. The fish communities downstream of the MWWE outfalls demonstrated differences in the abundance and diversity, species and family richness, % tolerance and % vulnerability when compared to the fish community upstream or further downstream of these points of effluent discharge. In both years studied, the fish community exposed to MWWE in the riffle-run habitats demonstrated reductions in the proportion of the most prominent fish (Rainbow Darter, Ethoestoma caeruleum) downstream of the outfalls, and a significant increase in the proportion of large mobile, tolerant-omnivorous fish species such as suckers and sunfish. There was less variability in the responses of the fish community to MWWE in the same season between years than between seasons within the same year. An examination of how impaired health of a sentinel species exposed to MWWE discharges parallels changes in the fish community is also conducted. This study successfully demonstrates the cumulative impact of urban development, including multiple outfalls of treated wastewater effluents on fish populations and communities. Municipalities are the major source of nutrients and pharmaceuticals and personal care products to aquatic systems, and they need to consider their impacts carefully with increasing urban population growth and ageing demographics.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.002 |
| 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 it