Assessment of Arctic Community Wastewater Impacts on Marine Benthic Invertebrates.
Bibliographic record
Abstract
This study sought to understand the performance of arctic treatment systems and the impact of wastewater effluent on benthic invertebrate communities in arctic receiving water habitats. Effluent quality and benthic impacts were monitored in the receiving water of five communities across Nunavut that differed in the type and level of treatment achieved by wastewater infrastructure, the volume of effluent and receiving water mixing environment. We detected minimal impacts to benthic communities (<225 m linear distance from the effluent source) in four out of the five communities (Grise Fiord, Kugaaruk, Pond Inlet, and Pangnirtung), where the population was <2000 people. In these small communities impacts were characterized by increases or decreases in species richness, diversity, evenness, and density, and some differences in benthic species composition. This was in contrast to benthic sediments in Iqaluit (population 6699), which were devoid of benthic fauna up to 580 m from the effluent source in response to sediment anoxia. Variation in benthic community response between sampling locations was attributed primarily to differences in effluent volume, with effluent quality and receiving water hydrodynamics playing secondary roles. The results of this study will help to inform the development of northern specific treatment performance standards which will aid in prioritizing community wastewater system upgrades in arctic communities.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".