Background/Question/Methods Urbanization is a process that alters biotic and abiotic environments that can affect the evolution and ecology of communities and ecosystems. Given the global expansion of urban environments and the ongoing and strengthening impacts of climate change (e.g., increased temperatures, altered precipitation regimes), it is increasingly important to understand the concomitant impacts of urbanization and climate change. Despite increased focus on ecological and evolutionary research in urban environments, there is considerable debate on the best approach to quantify urbanization and urban environmental change. Multiple measures of urbanization have been proposed, ranging from landscape properties like distance from the urban center and impervious surface cover to an increasing push to incorporate social, political, and economic variables. In this project, we will evaluate the effectiveness of urban-rural transects versus random sampling points for capturing urbanization and how this can be applied to study the impacts of climate change in urban environments. This project (1) evaluates urban-rural transects as an accurate design for field studies in urban evolution and ecology, and (2) develops a conceptual workflow and analytical code for other researchers to use to evaluate sampling designs along urban-rural gradients in their projects.
Results/Conclusions We use data from the Global Urban Evolution (GLUE) Project to quantify urbanization and compare urbanization gradients within a city to the broader, city-wide patterns of urbanization. First, we present the conceptual workflow and describe how to quantify and compare urban-rural transects to broader, city-wide patterns of urbanization derived from random sampling of points. Second, we use an urban-rural transect from Toronto, Canada to illustrate the analytical procedure. For this project, we focused on 5 variables associated with urbanization and global climate change: (1) distance from the urban center, (2) normalized difference vegetation index, (3) daytime and (4) nighttime land surface temperature, and (5) evaporative stress index. We demonstrate how to compare these measures of urbanization from sampling locations along transects to city-wide distributions of urbanization metrics, and we also show how to identify what causes deviations between transects and reference city patterns. Finally, we expand the spatial scale to include all 160 GLUE urban-rural transects and cities. We present the results from the analytical comparisons, identifying common trends in deviations between transects and reference cities. Here, we present an optimal method to validate sampling designs for researchers studying the ecological and evolutionary impacts of climate change in urban environments.