8 The global cargo ship network layers (see Electronic Supplementary Material). While some ports rank highly in all cate- gories (e.g. Suez Canal, Shanghai), others are specialized on certain ship types. For example, the German port of Wilhelmshaven ranks tenth in terms of its world-wide betweenness for oil tankers, but is only 241st for bulk dry carriers and 324th for container ships. We can gain further insight into the roles of the ports by examining their community structure. Communities are groups of ports with many links within the groups but few links between different groups. We calculated these communities for the three subnetworks with a modularity optimization method for directed networks (Leicht & Newman 2008) and found that they differ significantly from modularities of corresponding Erd¨ os-Renyi graphs (Fig. 3, Guimer´ a et al. 2004). The network of container trade shows 12 communities (Fig. 3a). The largest ones are located (1) on the Arabian, Asian, and South African coasts, (2) on the North American east coast and in the Caribbean, (3) in the Mediterranean, the Black Sea, and on the European west coast, (4) in Northern Europe, and (5) in the Far East and on the American west coast. The transport of bulk dry goods reveals 7 groups (Fig. 3b). Some can be interpreted as geographic entities (e.g. North American east coast, trans- Pacific trade) while others are dispersed on multiple continents. Especially interesting is the community structure of the oil transportation network which shows 6 groups (Fig. 3c): (1) the European, north and west African market (2) a large community comprising Asia, South Africa and Australia, (3) three groups for the Atlantic market with trade between Venezuela, the Gulf of Mexico, the American east coast and Northern Europe, and (4) the American Pacific Coast. It should be noted that the network includes the transport of crude oil as well as commerce with already refined oil products so that oil producing regions do not appear as separate communities. This may be due to the limit in the detectability of smaller communities by modularity optimization (Fortunato & Barth´ elemy 2007), but does not affect the relevance of the revealed ship traffic communities. Because of the, by definition, higher transport intensity within communities, bioinvasive spread is expected to be heavier between ports of the same community. However, in Fig. 3 it becomes clear that there are no strict geographical barriers between communities. Thus, spread between communities is very likely to occur even on small spatial scales by shipping or ocean currents between close-by ports that belong to different communities. Despite the differences between the three main cargo fleets, there is one unifying feature: their motif distribution (Milo et al. 2002). Like most previous studies, we focus here on