摘要：Biological invasions are considered among the largest threats to native biodiversity. The Mediterranean Sea, connecting the Indo-Pacific and Atlantic oceans, is characterized as a global marine invasion hotspot, due to a multitude of human pathways and vectors such as shipping, aquaculture, tourism, and the opening of the Suez Canal, which have led to the introduction of nearly 700 alien species into the Mediterranean Sea. Among the species introduced, the lionfish Pterois miles could be considered the fastest spreading invasive fish species of the last decade (2012–2022) and has been recorded in all countries of the eastern Mediterranean Sea, reaching as far north as Croatia. Here, we present a Bayesian additive regression tree modelling framework for an updated species distribution modelling invasion map under current and future climate conditions. All climate uncertainty sources have been used, as these are available from the Bio-Oracle, the unique marine predictors database. Important outputs of the current approach are the model’s inadequacy to accurately predict the most recent expansion of species in the Adriatic Sea, and the uncertainty estimation, that are high in areas with confirmed occurrence of individuals, in simulations that can help the decision makers and policy officers understand model limitations and take more informed actions.
