Predicting the spread of marine species introduced by global shipping

Significance Predicting the arrival of alien species remains a big challenge, which is assumed to be a consequence of the complexity of the invasion process. Here, we demonstrate that spreading of alien marine species can be predicted by a simple model using only global shipping intensities, environmental variables, and species occurrence data. We provide species lists of the next potentially invading species in a local habitat or species causing harmful algal blooms with their associated probability of invasion. This will help to improve mitigation strategies to reduce the further introduction of alien species. Although this study focuses on marine algae, the model approach can be easily adopted to other taxonomic groups and their respective drivers of invasion. The human-mediated translocation of species poses a distinct threat to nature, human health, and economy. Although existing models calculate the invasion probability of any species, frameworks for species-specific forecasts are still missing. Here, we developed a model approach using global ship movements and environmental conditions to simulate the successive global spread of marine alien species that allows predicting the identity of those species likely to arrive next in a given habitat. In a first step, we simulated the historical stepping-stone spreading dynamics of 40 marine alien species and compared predicted and observed alien species ranges. With an accuracy of 77%, the model correctly predicted the presence/absence of an alien species in an ecoregion. Spreading dynamics followed a common pattern with an initial invasion of most suitable habitats worldwide and a subsequent spread into neighboring habitats. In a second step, we used the reported distribution of 97 marine algal species with a known invasion history, and six species causing harmful algal blooms, to determine the ecoregions most likely to be invaded next under climate warming. Cluster analysis revealed that species can be classified according to three characteristic spreading profiles: emerging species, high-risk species, and widespread species. For the North Sea, the model predictions could be confirmed because two of the predicted high-risk species have recently invaded the North Sea. This study highlights that even simple models considering only shipping intensities and habitat matches are able to correctly predict the identity of the next invading marine species.