Predicting risk of invasion in a Mediterranean island using niche modelling and valuable biota

Abstract

Invasion by alien species is nowadays considered as one of the major threats to biodiversity. Thus, the identification of the areas exposed to a greater risk of invasion represents a priority for management purpose, especially in presence of habitats worthy of conservation. This paper aims to propose a method to produce a map of risk of invasion, merging together the threat of invasion by invasive plants and the distribution of habitats with high conservation value, on the case study of the Island of Elba (Tuscan Archipelago). We modelled the potential distribution of six particularly harmful invasive plants and merged these distributions into a map of threat of invasion. This map was overlapped to the map of density of Natura2000 habitats, finally obtaining a map of risk of invasion. According to our analyses, the potential distribution of the invasive species resulted highly influenced by human-related factors. The habitats more at risk are those closer to streets and anthropic habitats, which are more likely to be colonized by the invasive species we studied. We identified some rare habitats which are strongly endangered, highlighting that around 20% of the surface of the Island is exposed to some level of risk of invasion.

Keywords:

• Invasive species
• habitat suitability models
• species distribution models
• habitat conservation
• alien
• risk assessment
• Nature2000 habitat

Abbreviations:

• invasive alien species (IAS)
• species distribution models (SDMs)
• digital elevation model (DEM)
• area under the curve (AUC)
• receiver operating characteristic curves (ROC curves)

Acknowledgements

We thank the two “anonymous” reviewers for their careful reading of our manuscript and their insightful comments and suggestions.

Funding

The research was funded by the Tuscan Archipelago National Park (“Indagini sulle specie esotiche vegetali dell’Arcipelago Toscano” – Progetto Co.R.E.M. – CUP E79E1000012000). The project is also supported by the COST Action TD1209 “Alien Challenge”.