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Record W7132882779

Understanding the impacts of freshwater salinization and urbanization on aquatic biodiversity

2025· dissertation· W7132882779 on OpenAlexfundaboutno aff
Lauren Lawson

Bibliographic record

VenueTSpace · 2025
Typedissertation
Language
FieldEnvironmental Science
TopicSmart Materials for Construction
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaFisheries and Oceans CanadaUniversity of TorontoOntario Ministry of Natural Resources and ForestryMinistry of Natural Resources
KeywordsBiodiversityHabitatUrbanizationEndangered speciesBaseflowSoil salinityWater qualityClimate change
DOInot available

Abstract

fetched live from OpenAlex

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..

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.273
Threshold uncertainty score0.544

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.036
GPT teacher head0.266
Teacher spread0.230 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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