Water quality patterns in at-risk fish habitat: Assessing frequency and cumulative duration of chloride guideline exceedance during early life stages of an endangered fish
Bibliographic record
Abstract
• Innovative approaches to analyze high frequency environmental data are needed. • Stressor indicators need to consider duration and frequency of exposure. • Frequency and duration of chloride exposure is increasing in freshwater ecosystems. • Increasing chloride may be a driver of decline for freshwater species of conservation concern. • Chloride exposure profiles exceed guidelines in more urbanized watersheds. A comprehensive understanding of the impact of contaminants on organisms requires consideration of magnitude, duration, frequency, and life-history stage of exposure. Government guidelines provide a benchmark to evaluate exposure magnitude, but solely assessing magnitude does not consider duration and frequency of exposure. High-frequency sampling of data enables better integration of temporal patterns of potential environmental stressors and can inform research about habitat suitability. We develop and demonstrate an approach to examine temporal dynamics of abiotic conditions using high-frequency sampling data to assess water quality in the habitat of a Canadian federally listed endangered fish species, the Redside Dace ( Clinostomus elongatus ). Urban stressors, including chloride and non-point source pollutants, are considered contributing factors to the decline of Redside Dace in Canada. We collected and analyzed conductivity/chloride data from nine Redside Dace sites with varying degrees of upstream urbanization in the Greater Toronto Area to understand spatial and temporal variation in chloride exposure. Chloride loading in the region is largely driven by application of winter de-icing salt contributing to year-round elevated chloride concentrations. We highlight chloride patterns during critical early life stages of Redside Dace (spring spawning through summer; ‘non-salting season’), when sensitivity to stressors may be heightened. We assessed our data against the federal Canadian and American guidelines and found that at six out of nine sites, critical early life stages were exposed to chloride concentrations that exceeded the magnitude threshold of Canadian guidelines. We found instances of chronic duration threshold exceedance at six out of nine sites. Future research can leverage our approach to identify areas of concern where magnitude and duration thresholds are exceeded, and our results can be used to inform the duration of stressor exposure to critical life-history stages during ecologically relevant laboratory-based ecotoxicology studies. We emphasize that our approach can be used for any environmental parameter sampled with high frequency to better understand temporal regimes of ecological stressors.
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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) | 0.001 | 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 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".