Marie C Dade, Isabella C Richmond, Jesse T Rieb, Erin TH Crockett, Kayleigh Hutt-Taylor, Serena Sinno, Karina Benessaiah, Catherine Destrempes, Jacqueline Hamilton, Fatemeh Izadi, L Emily Kroft, Lingshan Li, Michael A Paulauskas, Klara J Winkler, Elena M Bennett, Carly D Ziter
Urban Forestry & Urban Greening (2024), DOI: https://doi.org/10.1016/j.ufug.2024.128472
Urban green infrastructure – the network of greenspaces across cities – provides ecosystem services that are important for urban sustainability. Because of this, cities are increasingly redeveloping underused alleys into green infrastructure to improve ecosystem service capacity. But it remains unclear if these green alleys are delivering on the promise of supplying particular ecosystem services. The indicators usually used within green infrastructure to measure ecosystem services may not be suitable for green alleys because of the unique structure, vegetative features and level of community engagement of these alleys. Here we developed and tested a rapid assessment approach to evaluate ecosystem service capacity appropriate for use by community members and practitioners, using a green alley network in Montréal (Canada) as a case study. We collected data on green alley vegetation, structural form and indicators of four ecosystem services (food provision, habitat for pollinators, anthropogenic noise regulation and air temperature regulation). We modelled the relationships between vegetation, structural form, and ecosystem services, to determine if these rapidly assessed features of green alleys are appropriate indicators to evaluate ecosystem service capacity. Our results show that a rapidly assessed measure of vegetative ground cover is strongly associated with habitat for pollinators, highlighting potential for vegetative ground cover as an indicator for this service. Rapid assessments of alley vegetation were not associated with air temperature or anthropogenic noise, contrasting the findings of previous studies. Lack of relationships between the explanatory variables and the four ecosystem services suggests that further research is required to untangle these complex relationships. Our research provides a starting point for developing indicators of ecosystem service capacity that are tailored specifically to the unique structure and features of green alleys, a crucial step in testing the efficacy of this increasingly popular sustainable development strategy.
This repository is built using a {targets} workflow. Scripts are written to create individual targets, which are then used later in the workflow. Scripts are located in the scripts/ folder. All individual targets are created using functions, which can be found in the R/ folder. For more information on how targets workflows work, please watch the introductory video in their book linked above. To run the analysis from this paper, clone this repository, run install.packages('renv') and then install all dependencies using renv::restore() . After successfully installing packages, run targets::tar_make() in the console to run the entire workflow. To load any individual step of the workflow to your environment, use targets::tar_load(TARGET_NAME). Please note that package installation can take up to 1 hour depending on your operating system + approximately 15 minutes to run the workflow using the subsetted noise data provided.
The noise data used in this analysis is too large to host on GitHub or Zotero (~ 715 GB). I have set up this repository to include a small subset of the data used so the code can run as published, however, you will get different results for the noise portion of the analyses using this small subset. If you would like to use this code to process your own data, please change the file pathway found in the _targets.R file. If you would like to rerun the workflow in full with the entire dataset, please email me and I will be more than happy to share the full dataset with you.
For any questions related to code, data, or workflow please email isabella.richmond@mail.concordia.ca