Application of multi-region input-output analysis to examine biosecurity risks associated with the global shipping network.

Abstract

The vast majority of globally traded cargo is transported via maritime shipping. Whilst in port for loading and unloading, these ships can pick up local marine organisms with internal ballast water or as external biofouling assemblages and subsequently move these to destination far beyond their natural ranges. Over the past decades, this mechanism has led to the establishment of hundreds of non-indigenous species (NIS) around global coastlines. Marine NIS cause significant environmental, economic, cultural and human health impacts. Taking effective steps to preventing their dispersal and establishment is an enduring challenge for governments and conservation agencies around the world. Here we use international commodity trade data and a Nobel-Prize-winning economic analysis technique to develop a novel approach for assessing global marine NIS transfer risks. We show that by tracing the origins and destinations of seaborne trade connections, and the nature of the traded commodities, we can predict the strength of shipping vectors and associated marine biosecurity risks. We demonstrate the utility of our approach via a case-study, where we trace the spread of a hypothetical marine NIS from Japan and show the congruence of our model results with documented invasion histories from that region. Our study demonstrates that biosecurity risk can be assessed using established economic modelling frameworks on the basis of monetary transaction data alone, and without the need for detailed itineraries of the many thousand vessels making up the global commercial fleet. Novel, cost-effective tools are needed to mitigate biosecurity risks associated with maritime trade, and to meet conservation goals while enabling economic prosperity. The modelling framework presented here can be expanded to incorporate future risk factors, life-history traits of particular NIS of concern, and even adapted to simulate the dispersal of terrestrial pests or disease agents.