1 Department of Mathematics Simon Fraser University Burnaby British Columbia Canada.
2 Department of Biological Sciences Simon Fraser University Burnaby British Columbia Canada.
3 Department of Biology University of Toronto Mississauga Mississauga Ontario Canada.
4 Centre for Urban Environments University of Toronto Mississauga Mississauga Ontario Canada.
5 Department of Biology Concordia University Montreal Quebec Canada.
6 CNRS, ThéMA Université Marie et Louis Pasteur Besançon France.
7 Department of Ecology and Evolutionary Biology University of Toronto Toronto Ontario Canada.
8 Department of Computational Biology Cornell University Ithaca New York USA.
9 Department of Biology University of Florida Gainesville Florida USA.
10 Department of Biology University of Ottawa Ottawa Ontario Canada.

Urbanization drives rapid and extreme environmental change, profoundly shaping the ecology and evolution of populations. In this Perspective, we call for the integration and development of evolutionary theory and empirical research through collaboration between theoretical and experimental biologists to provide new insights into urban evolutionary ecology. We argue that mathematical models derived from ecological and evolutionary theory can be tailored to provide a powerful framework for generating predictions that can guide empirical research in urban ecology and evolution. At the same time, empirical results can motivate and inform the development and analysis of new theoretical models specific to urban systems. We illustrate how existing evolutionary theory can be harnessed to generate specific predictions of how urbanization can influence evolution. These predictions span the range of urban impacts on all main evolutionary processes, including mutation, gene flow, genetic drift, non-random mating, and selection. We provide a summary of evidence supporting each prediction and outline empirical approaches available to test them. Importantly, these predictions require distinct modeling approaches that can be applied more broadly to better utilize theory for research on urban environments. To facilitate this, we provide an overview of these existing modeling approaches ranging from the application and syntheses of classic model results to the development of novel probabilistic predictions. We advocate for increased integration of theoretical and empirical research through the development of novel models using parameterization specific to urban systems, empirical tests grounded in theoretical models, model-based empirical tests, and model-based data analysis and inference to advance our understanding of evolution in urban environments.