An Urban Forest Diversification Software to Improve Resilience to Global Change

Abstract

Abstract The importance of urban tree diversity for improving resilience is increasingly understood by decision makers. Urban foresters want to prevent the overrepresentation of species on their streets and in their city, which could result in a significant loss of canopy cover in the event of a large-scale disturbance such as a drought or an exotic pest or disease. Although numerous software and tools exist to visualize tree inventories and plan tree maintenance work, only a few offer support for increasing tree diversity. After reviewing the existing tools available for urban forest managers, we present SylvCiT, a novel decision-support and open-source software available on a web platform designed to consolidate information related to the urban forest in one place and facilitate decision-making at different scales. While the first interfaces provide the user with a spatially explicit portrait of the urban forest (species richness, functional diversity, structural diversity, i.e., diameter classes) and associated ecosystem benefits (e.g., stored carbon, ornamental value), the software is designed to produce a list of functional groups and appropriate species to plant considering tree species already present. Based on an artificial intelligence algorithm, SylvCiT identifies the types of trees (species and functional groups) that are absent or underrepresented at different scales to make recommendations that increase species and functional diversity to improve resilience to global change. SylvCiT will continue to be developed to evaluate other ecosystem benefits and integrate criteria such as site characteristics into the recommendation algorithm.