Understanding the impacts of freshwater salinization and urbanization on aquatic biodiversity
Bibliographic record
Abstract
The inability of some species to persist against environmental stressors in the Anthropocene has contributed to what is considered the beginning of the 6th Mass Extinction. Understanding the response of organisms to environmental change is a key goal of ecology and conservation science. Land-use change and freshwater salinization are two persistent threats to conservation. This thesis analyzes spatial and temporal patterns of freshwater quality in relation to salinization and land-use change to assess risks to freshwater ecological communities and explore drivers of ecological change. First, I estimated the impact of baseflow chloride on freshwater biodiversity in Toronto, Ontario. I found that 25% of species were theoretically impacted by baseflow chloride concentrations at 34% of the sampled sites during summertime. Then, I collected high-frequency water quality data in habitat supporting endangered Redside Dace and determined temporal exposure patterns. I designed a novel framework for analyzing the exceedance of both the magnitude and duration of chloride exposure. I found that two-thirds of the study sites exceeded chloride guidelines, and the framework I developed can be applied to inform ecological risk assessment using other high-frequency datasets. Next, I applied a framework to determine de-icing salt loading into Redside Dace critical habitat at multiple hydrological scales. I identified residential parking areas as key contributors to salt loading. My results also suggested spatial scale can influence dominant loading sources. Finally, I leveraged long-term fish community monitoring data to understand whether fish communities changed in Toronto within sites over fifteen years. I found sites had more gains in species and/or the abundance of particular species than losses in fish communities, although land-use change and change in riverine connectivity did not explain variation among sites strongly. My thesis demonstrates that: urban water quality poses a threat to freshwater biodiversity; de-icing salt loading from residential parking areas can be a dominant driver of watershed salt loading when measured at an aggregated scale; and, fish communities may be experiencing more gains than losses, with some gains potentially indicative of environmental stressors on species composition. Collectively, my thesis developed novel tools for assessing threats to freshwater biodiversity and ecological change through time and offers insights into the potential impacts of urbanization on biodiversity..
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".