Transportation networks play a crucial role in human mobility, the exchange of goods and the spread of invasive species. With 90 per cent of world trade carried by sea, the global network of merchant ships provides one of the most important modes of transportation. Here, we use information about the itineraries of 16 363 cargo ships during the year 2007 to construct a network of links between ports. We show that the network has several features that set it apart from other transportation networks. In particular, most ships can be classified into three categories: bulk dry carriers, container ships and oil tankers. These three categories do not only differ in the ships' physical characteristics, but also in their mobility patterns and networks. Container ships follow regularly repeating paths whereas bulk dry carriers and oil tankers move less predictably between ports. The network of all ship movements possesses a heavy-tailed distribution for the connectivity of ports and for the loads transported on the links with systematic differences between ship types. The data analysed in this paper improve current assumptions based on gravity models of ship movements, an important step towards understanding patterns of global trade and bioinvasion.

According to migration theory and several empirical studies, long-distance migrants are more time-limited during spring migration and should therefore migrate faster in spring than in autumn. Competition for the best breeding sites is supposed to be the main driver, but timing of migration is often also influenced by environmental factors such as food availability and wind conditions.Using GPS tags, we tracked 65 greater white-fronted geese Anser albifrons migrating between western Europe and the Russian Arctic during spring and autumn migration over six different years. Contrary to theory, our birds took considerably longer for spring migration (83 days) than autumn migration (42 days). This difference in duration was mainly determined by time spent at stopovers.Timing and space use during migration suggest that the birds were using different strategies in the two seasons: In spring they spread out in a wide front to acquire extra energy stores in many successive stopover sites (to fuel capital breeding), which is in accordance with previous results that white-fronted geese follow the green wave of spring growth. In autumn they filled up their stores close to the breeding grounds and waited for supportive wind conditions to quickly move to their wintering grounds. Selection for supportive winds was stronger in autumn, when general wind conditions were less favourable than in spring, leading to similar flight speeds in the two seasons. In combination with less stopover time in autumn this led to faster autumn than spring migration.White-fronted geese thus differ from theory that spring migration is faster than autumn migration. We expect our findings of different decision rules between the two migratory seasons to apply more generally, in particular in large birds in which capital breeding is common, and in birds that meet other environmental conditions along their migration route in autumn than in spring.

and 8 Vogeltrekstation -Dutch Centre for Avian Migration and Demography (NIOO-KNAW), 6708 PB Wageningen, The Netherlands Summary 1. Herbivorous birds are hypothesized to migrate in spring along a seasonal gradient of plant profitability towards their breeding grounds (green wave hypothesis). For Arctic breeding species in particular, following highly profitable food is important, so that they can replenish resources along the way and arrive in optimal body condition to start breeding early. 2. We compared the timing of migratory movements of Arctic breeding geese on different flyways to examine whether flyways differed in the predictability of spring conditions at stopovers and whether this was reflected in the degree to which birds were following the green wave. 3. Barnacle geese (Branta leucopsis) were tracked with solar GPS/ARGOS PTTs from their wintering grounds to breeding sites in Greenland (N = 7), Svalbard (N = 21) and the Barents Sea (N = 12). The numerous stopover sites of all birds were combined into a set of 16 general stopover regions. 4. The predictability of climatic conditions along the flyways was calculated as the correlation and slope between onsets of spring at consecutive stopovers. These values differed between sites, mainly because of the presence or absence of ecological barriers. Goose arrival at stopovers was more closely tied to the local onset of spring when predictability was higher and when geese attempted breeding that year. 5. All birds arrived at early stopovers after the onset of spring and arrived at the breeding grounds before the onset of spring, thus overtaking the green wave. This is in accordance with patterns expected for capital breeders: first, they must come into condition; at intermediate stopovers, arrival with the food quality peak is important to stay in condition, and at the breeding grounds, early arrival is favoured so that hatching of young can coincide with the peak of food quality. 6. Our results suggest that a chain of correlations between climatic conditions at subsequent stopovers enables geese to closely track the green wave. However, the birds' precision of migratory timing seems uninfluenced by ecological barriers, indicating partly fixed migration schedules. These might become non-optimal due to climate warming and preclude accurate timing of long-distance migrants in the future.