A species-specific approach to predicting the introduction and establishment of marine non-native species transported through biofouling on ships’ hulls

Abstract

Non-native species (NNS) are organisms introduced by human activity into new environments beyond their natural range. Those that cause ecological, economic, or social harm to their introduced environment are considered invasive. In marine systems, shipping - particularly biofouling on vessel hulls - is the dominant anthropogenic vector of NNS introductions. With maritime traffic projected to double by 2050 and ocean conditions shifting due to climate change, the risk of NNS introductions is expected to increase. Predictive tools are urgently needed to inform targeted, cost-effective interventions.
Despite decades of research, biofouling invasion risk models still lack species-specific physiological data - crucial for understanding environmental tolerances and predicting invasion success. Physiological tolerances define the geographic limits of marine species, as environmental factors including temperature and salinity influence metabolic function and survival. However, physiological data for many marine biofouling species remain scarce.
This study integrates species distribution modelling (SDM) for 32 biofouling species, with global vessel traffic data (2009–2018) to assess invasion risks under current and projected (2050) climatic conditions. Results show that no species is at equilibrium with its environment, indicating a persistent global risk of introductions. Modelled species range shifts indicate a consistent poleward movement and identify temperate ports with high connectivity and vessel traffic as potentially high-risk introduction hubs.
To address physiological data gaps, a novel method was developed to estimate species’ thermal tolerance ranges from habitat suitability models, which yielded values consistent with published empirical data (albeit limited). From this, a species-specific framework integrating SDM, vessel traffic analysis, and physiological tolerance estimation, was developed and applied to a case study on Ciona spp. in the Antarctic. It revealed lower overall invasion risk estimates compared to previous models and identified the drivers most strongly influencing introduction risk across Antarctic regions.
These findings support more accurate and climate-resilient biosecurity strategies. While developed and tailored to the marine biofouling vector, its principles are broadly applicable to other invasion vectors and environmental contexts.