Supervisor: Brian Leung
The global shipping network (GSN) is the most significant vector of spread for non-native aquatic species. Over the past five years, it has been analyzed in considerable detail such that the connections and dynamics within the GSN are now relatively well understood. This has led to a number of studies venturing to forecast the spread of invasive species through the GSN. Many of these studies focus on climate change as an important driver to consider when forecasting spread. However, overlaying climate change scenarios for the coming decades onto today's GSN assumes the GSN will remain unchanged, despite evidence that global maritime trade has increased over 50% since 2000. The purpose of this research project is to forecast change in the GSN using statistical and computational modelling, and to examine how different network scenarios may lead to different global outcomes of invasive spread, and which invasive species may be favoured. For my first chapter, I am creating a 30-year forecast of the GSN using statistical and computational modelling. By making use of published economic projection scenarios, I will simulate a number of key future drivers of change (eg. emerging markets, opening up of northern passages, Panama Canal expansion) and create a set of possible future networks. With these future networks, I aim to show the different outcomes of species exchange between different biotic zones, thus creating different scenarios for biodiversity mixing. My forecast will also serve as a foundation for my second chapter, which is an examination of functional traits of successful invaders. Using historical data on successful invasions, I aim to use my shipping forecast to simulate spread of marine invasive species, and see which traits confer greatest success under present and future shipping network scenarios. Results from both chapters would serve as useful tools for invasive management and prevention policy.