Evaluating the Potential Impacts of Municipal Wastewater Effluent on Benthic Macroinvertebrates in the Upper Bow River
Bibliographic record
Abstract
Municipal wastewater effluent (MWWE) is a common, high-volume, point source effluent that is commonly released to urban aquatic systems. MWWE is a complex mixture containing nutrients and many emerging chemicals of concern (ESOCs), which may vary due to treatment type, receiving environments, and the population served. Outputs of MWWE have been associated with nutrient enrichment (eutrophication) but as populations grow and knowledge of ESOCs improves, it is crucial to understand how nutrient enrichment, and potential interactions of nutrients and ESOCs affect aquatic ecosystems. This study provides updated data on the basal aquatic food web of the Bow River in urban areas of its higher reaches (Canmore and Calgary) through characterizations of the benthic macroinvertebrate assemblages in the mainstem and experimental stream systems associated with Calgary’s Pine Creek wastewater treatment plant. Changes to benthic macroinvertebrate assemblages on a longitudinal gradient and cumulative exposure to MWWE in the Bow River were statistically significant and were generally associated with nutrient enrichment (particularly phosphorus). Through the use of different sampling methodologies, MWWE exposures in the experimental streams suggest that the high-quality treated effluent produced by the Pine Creek facility causes consistent, but divergent, cumulative effects in relation to background Bow River source water. In both projects, community metrics that identify types of taxa found in assemblages also described changes to communities more effectively than traditional metrics of urban disturbance such as diversity and richness.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".