Assessment of ecological impairment of Arctic streams: Challenges and future directions
Bibliographic record
Abstract
As increased growth and development put pressure on freshwater systems in Arctic environments, there is a need to maintain a meaningful and feasible framework for monitoring water quality. A useful tool for monitoring the ecological health of aquatic systems is by means of the analysis and inferences made from benthic invertebrates in a biomonitoring approach. Biomonitoring of rivers and streams within the Arctic has been under-represented in research efforts. Here, we investigate an approach for monitoring biological impairment in Arctic streams from anthropogenic land use at two streams with different exposure to urban development in Iqaluit, Nunavut, Arctic Canada. Sites upstream of development, at midpoint locations, and at the mouth of each waterbody were sampled during 6 campaigns (2008, 2009, 2014, 2015, 2018, and 2019) to address spatial and temporal variability of the macroinvertebrate community. The influence of taxonomic resolution scaling was also examined in order to understand the sensitivity of macroinvertebrates as indicators in Arctic aquatic systems. We demonstrate that standard biological metrics were effective in indicating biological impairment downstream of sources of point-source pollutants. A mixed-design ANOVA for repeated measures also found strong interannual variability; however, we did not detect intra-annual variation from seasonal factors. When examining metrics at the highest taxonomic resolution possible, the sensitivity of metrics increased. Likewise, when trait-based metrics (α functional diversity) were applied to indicators identified at high taxonomic resolution, a significant difference was found between reference and impacted sites. Our results show that even though Arctic systems have lower diversity and constrained life-history characteristics compared to temperate ecosystems, biomonitoring is not only possible, but also equally effective in detecting trends from anthropogenic activities. Thus, biomonitoring approaches in Arctic environments are likely a useful means for providing rapid and cost-effective means of assessing future environmental impact.
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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 | 0.019 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".