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.