Potential effects of road proximity on zooplankton communities and water quality in lakes in the Northwest Territories
Bibliographic record
Abstract
Studies conducted along Canada’s Dempster Highway in the Northwest Territories have shown that road dust can affect water quality in roadside lakes, leading to higher calcium, conductivity, and pH levels. These water quality changes have the potential to affect important members of the lower aquatic food web, such as zooplankton.\nFor my thesis research, I had two main objectives: 1) To determine if changes in water chemistry caused by deposition of road dust affects zooplankton communities; and 2) To examine if the type of roadside vegetation influences the effects of road dust on aquatic habitats. To achieve these objectives, I collected biological and water quality data from 18 lakes along the Dempster and Inuvik-Tuktoyaktuk Highways in the Northwest Territories and measured the transport of dust from the highways to the surrounding landscape. I selected my study lakes using a stratified random sampling design, with distance from the road (0-300 m, 300-600 m, and > 600 m) and region of study (boreal forest, tundra) as the two factors. Transportation of dust was measured using funnel traps placed in transects from the highways. I hypothesized that zooplankton communities in lakes near the road would show significant differences in community structure, and that dense boreal forest vegetation would provide a better roadside buffer than tundra shrubs, limiting the impacts of road dust to shorter distances in the boreal forest region.\nMy dust measurements indicated that the majority of dust fell within 300 m from the highway, and that dust moved furthest in the tundra. However, there were no clear differences in water quality or zooplankton communities among lakes based on distance from the highway. In addition, while there were differences in communities between regions, these did not appear to be related to the effects of the road. The lack of clear water quality differences related to the effects of road dust are contrary to results from other studies in the region. I speculate that the small sample size for my study combined with natural variability, may have masked the effects of road dust pollution. While my results suggest that gravel roads may have less of an impact on lakes than predicted, further studies with larger sample sizes and more powerful study designs are needed to better understand the issue.
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How this classification was reachedexpand
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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".