Modeling acacia saligna invasion in mediterranean coastal dunes. An integrative analysis using lter infrastructure data

Invasive alien species pose a major threat to biodiversity and ecosystem services worldwide. Even if preventing biological invasions should be the most cost-effective way to minimize the impact of Invasive Alien Species (IAS) on biodiversity, new efforts are necessary to identify the early signs and to assess invasion risk. In this context, the implementation of invasive Species Distribution Models (iSDMs) could represent a sound instrument that merit of further research. Acacia saligna, is an Australian vascular plant introduced in Europe during the last half century, it represents one of the most dangerous Invasive Alien Species in the Mediterranean basin and its spread is particularly worrisome in Italy and Europe. With this work, we propose an iSDM-based methodology to: a) explore the role of multiple drivers in the invasion process, and b) assess the risk posed by A. saligna in coastal dune ecosystems. The research was carried out on the Adriatic coast of central Italy (Molise region) including two sites of the international LTER network and three Sites of Conservation Interest. We examined the statistical relationship between Propagule pressure, Abiotic and Biotic variables (here after PAB) and A. saligna occurrence by using a Generalized Linear Model (GLM) with a binomial distribution of errors. We effectively modeled the occurrence of A. saligna and we identified the specific role of the PAB variables in determining the alien species presence. The invasion by A. saligna varies across the coastal landscape and preferentially occurs close to the coastal pine forests, and close to existing stands, on road borders and at intermediate distances from the coastline namely in the first fixed dunes facing the sea. According to the predicted occurrence, we identified coastal tracts with different invasibility values supporting site-specific management strategies. Our results encourage the use of iSDMs as a means of evaluating the risk posed by IAS, and, at the same time, represent an attempt to fill the gap between theory and practice in conservation decision-making.