Assessing the vulnerability to climate change of tree species for urban afforestation

Nature-based solutions are now a key part in climate change adaptation, particularly for urban environments. The integration of natural systems within the urban fabric has the potential to increase cities’ resilience to the predicted changes in climate. Urban forests are one of the most used methods for adding ecosystem services to an urban environment and at the same time address urban-specific climate change challenges such as heat-island effect, intense rainfall and water management. However, the effects of climate change in the long-term on urban forests are not often taken into account when planning interventions such as afforestation. Species selection for urban forests should, among other factors, be based on an assessment of local future climatic conditions, so to ensure the long-term viability of the project. Here we propose a methodology easily applicable to any place in Europe. We use data from interpolated publicly available climate datasets and species distribution data from the European Tree Atlas in order to analyse climatic niches for tree species in Italy. These climatic ranges are then compared to local climatic data, obtained from homogenised time-series measured by a weather station in the city of L’Aquila. The results are summarised in a suitability matrix providing vulnerability scores for each species based on predicted climate changes for the local area. The analysis ranks the species which are less vulnerable to projected future climate conditions. The application to the pilot area of L’Aquila suggests that some species already present will still be suitable also in future climate (e.g. Quercus pubescens) while others will not (e.g. Quercus petraea), and species not traditionally present may become suitable (e.g. Quercus ilex). The importance of obtaining accurate local climate data from observations is a key aspect for municipalities to consider as results of this analysis are greatly dependent on this.