Effects of Urbanization on the Evolutionary Ecology Population Genetics of Common Milkweed
Bibliographic record
Abstract
Urbanization is intensely transforming environments throughout the world, yet we understand little about how the rapid rise of cities affects the ecology and evolution of populations. My thesis explores how urban environmental conditions and aspects of urban landscapes influence adaptive and non-adaptive evolutionary processes in a native plant species of conservation value: common milkweed (Asclepias syriaca). Throughout my thesis, I use a combination of observational and experimental approaches to examine patterns of phenotypic and genetic variation in common milkweed growing across the Greater Toronto Area. In my first chapter, I reviewed the literature to describe how urban environments can impact the ecology of plants, herbivores, and pollinators, and how these changes can consequently affect evolution. Next, I performed a literature review describing the observed and predicted impacts of urbanization on the ecology and evolution of plant-herbivore interactions in general. I concluded that some plants and arthropods can tolerate urban environments while others will likely decline in abundance, which may dramatically alter urban plant-herbivore interactions. In my third chapter, I performed an observational study showing that urbanization and proximity to a green corridor influenced multiple aspects of reproduction in common milkweed and pollinator community structure, but without consistent relationships between plant reproductive success and the pollinator community in both the presence, and absence, of a green corridor. Next, I performed a common garden experiment showing that urbanization and an urban green corridor did not strongly influence genetic divergence in phenotypic traits in common milkweed. In my fifth chapter, I found mostly similar genetic diversity and little genetic differentiation in urban and rural habitats in the GTA, suggesting a single genetic population with little spatial genetic structure. Long-term anthropogenic landscape changes, rather than urbanization, may have been the primary factor shaping demographic processes in this population. Lastly, I synthesize key thesis findings, discuss how these results contribute to decades of research in ecology and evolutionary biology, and provide recommendations for future studies. By integrating perspectives from landscape ecology and urban evolutionary biology, this work facilitates the development of a more holistic understanding about how urban environments influence ecological and evolutionary processes.
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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 | 0.000 |
| 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 | 0.000 |
| 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 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".