Clément Violet1, Amelia Curd1, Mathieu Chevalier1, Frédérique Viard2
1Ifremer, France - 2CNRS-ISEM, France
Non-indigenous species (NIS) present a significant threat to marine biodiversity, contributing to its global redistribution and imposing substantial ecological and economic burdens. In this study, we aim to determine how projected climate change will influence the environmental suitability of European seas for over 400 NIS—spanning both the Plantae and Animalia kingdoms—and how these shifts may facilitate their establishment and spread across Europe. We expect that climate change will shift the ranges of many NIS in Europe, although the magnitude and direction of these shifts are likely to vary among species and across European ecoregions.
To test this, we compiled occurrence data from both the source and recipient ranges of each species, capturing their global environmental tolerances. We then derived key environmental predictors from BioOracle v3.0 under three Shared Socioeconomic Pathway (SSP) scenarios (SSP1-1.9, SSP3-7.0, and SSP4-6.0). Using these predictors, we calculated a Niche Margin Index (NMI) for each European marine pixel by measuring the distance of that pixel to the boundary of each species’ environmental envelope.
Using examples from temperate reef communities, we demonstrate how the NMI framework allowed us to identify potential hotspots where environmental conditions may favour NIS establishment, thereby highlighting zones at heightened risk of future colonisation by novel species. These findings will provide valuable insights into how different taxonomic or functional groups might respond to changing climatic conditions, offering a robust foundation for proactive monitoring and management strategies. Ultimately, this research underscores the importance of niche-based approaches in predicting biological invasions and informing management efforts under ongoing climate change.
Biography
Dr Clément Violet is a postdoctoral researcher with a strong interest in numerical ecology and the use of advanced statistical modelling and machine learning techniques to better understand species distribution patterns in a world increasingly affected by climate change. His research focuses on examining how abiotic factors, biological traits, and species interactions influence the composition of marine communities and either hinder or facilitate their colonisation by non-indigenous species.