A Habitat-template approach for Green Infrastructure Design in Mediterranean Urban Areas: Leveraging EVA data and plant functional traits

As part of the Evolution project, a collaboration between Teamdev, Latitudo 40 and the Universities of Palermo and Perugia, we developed an innovative method for designing green infrastructure in Mediterranean urban areas, with a particular focus on urban forests and green roofs. In response to the challenges posed by climate change and biodiversity loss, the project adopts the Habitat Template Approach1, a method based on the idea that the design of artificial ecosystems should be inspired by spontaneous plant communities found in similar ecological conditions, in order to maximize the sustainability and effectiveness of interventions. The Municipality of Perugia was chosen as a model to test and validate the proposed methodology. The process involved a phytosociological and vegetation characterization of the study area, supported by the QGIS analysis of the Vegetation Series Map2, to identify reference vegetation series, and the Natura 2000 Map3, to determine the existing habitats. From these habitats, a preliminary species list was extracted and then validated by integrating data from vegetation plots available in the EVA4 (European Vegetation Archive) database for the Province of Perugia. This step provided a representative list of the local species pool, which was further enriched with functional traits extracted from multiple sources: GIFT5 (Global Inventory of Floras and Traits), Digital Italian Flora6, and the TRY Database7. To ensure a dataset focused exclusively on native species, exotic species were excluded. The integration of these data resulted in 330 species related to our habitat templates, each annotated with the 41 most relevant functional traits. A cluster analysis was then applied to classify the species into eight functional groups, representing clusters of species with similar ecological and morphological characteristics. Finally, the cocktail method8, implemented using the JUICE software, allowed us to analyse species co-occurrences, identifying the most suitable plant associations for green infrastructure design. The effectiveness of this methodology strongly depends on the size of the dataset: a larger dataset enables greater precision in species selection and functional analysis, enhancing the robustness of the proposed solutions. Additionally, this methodology, based on open-access databases and software, is replicable in various urban contexts, and the definition of functional groups can be adjusted to meet specific design needs, making the approach flexible and applicable to different ecological planning strategies. Despite the robustness of the method, one of the main critical issues encountered is the availability gap: many of the identified species may not be readily available in the nursery market, limiting the practical implementation of the proposed solutions. This issue highlights the need for greater integration between scientific research and plant nurseries, to promote the cultivation and distribution of native species suitable for urban re-naturalization projects