Forest structure but not tree diversity differ among urban woodlands with differing conservation status
Erica Padvaiskas, Isabella C Richmond*, Carly D Ziter
* Corresponding author: isabella.richmond@mail.concordia.ca
While biodiversity conservation in urban areas is a topic of great interest, few studies have focused on the role that urban conservation areas have for preserving biodiversity. Urban woodlands, which are patches of forest habitat confined within the city’s boundaries, offer a promising approach to evaluate the importance of conservation areas within cities. Here we examined the relationship between conservation status and forest structure and composition across eleven urban woodlands in Montréal, Canada. We used field surveys to assess biodiversity, canopy cover and structural complexity (i.e., number of vegetation layers) for urban woodlands with a conservation status (nature parks), and those without a conservation status (non-status woodlands). We found that Montréal’s urban woodlands fostered similar levels of biodiversity regardless of conservation status. Similarly, all urban woodlands supported high proportions of native tree species despite differences in conservation status and associated management. Our results suggest that both conservation areas and non-status woodlands play an important role in safeguarding urban biodiversity. Woodlands specifically designated and managed as nature parks, however, had higher canopy cover and vegetative complexity, but also contained higher levels of invasive trees, particularly Rhamnus cathartica (Common Buckthorn). While the high complexity in vegetation layers observed in nature parks may provide habitat to native wildlife, these benefits may be limited by the high proportion of invasive trees.
This repository is built using a {targets} workflow. The _targets.R script was written to create individual targets, which are then used later in the workflow. 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 10 minutes to run the workflow.