Large-scale biological networks - cargo ship traffic and bird migration

Kurzfassung der Dissertation an der Mathematisch-Naturwissenschaftlichen Fakultät der Carl von Ossietzky-Universität Oldenburg, betreut von Herrn Prof. Dr. Bernd Blasius und Herrn Prof. Dr. Franz Bairlei

The complex network of global cargo ship movements

Transportation networks play a crucial role in human mobility, the exchange of goods, and the spread of invasive species. With 90% 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 which set it apart from other transportation networks. In particular, most ships can be classified in 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 analyzed in this paper improve current assumptions based on gravity models of ship movements, an important step towards understanding patterns of global trade and bioinvasion.Comment: 7 figures Accepted for publication by Journal of the Royal Society Interface (2010) For supplementary information, see http://www.icbm.de/~blasius/publications.htm

Simulation experiment to test strategies of geomagnetic navigation during long-distance bird migration

The project was funded by the Leverhulme Trust (Research Project Grant RPG-2018-258).Background Different theories suggest birds may use compass or map navigational systems associated with Earth’s magnetic intensity or inclination, especially during migratory flights. These theories have only been tested by considering properties of the Earth’s magnetic field at coarse temporal scales, typically ignoring the temporal dynamics of geomagnetic values that may affect migratory navigational capacity. Methods We designed a simulation experiment to study if and how birds use the geomagnetic field during migration by using both high resolution GPS tracking data and geomagnetic data at relatively fine spatial and temporal resolutions in comparison to previous studies. Our simulations use correlated random walks (CRW) and correlated random bridge (CRB) models to model different navigational strategies based on underlying dynamic geomagnetic data. We translated navigational strategies associated with geomagnetic cues into probability surfaces that are included in the random walk models. Simulated trajectories from these models were compared to the actual GPS trajectories of migratory birds using 3 different similarity measurements to evaluate which of the strategies was most likely to have occurred. Results and conclusion We designed a simulation experiment which can be applied to different wildlife species under varying conditions worldwide. In the case of our example species, we found that a compass-type strategy based on taxis, defined as movement towards an extreme value, produced the closest and most similar trajectories when compared to original GPS tracking data in CRW models. Our results indicate less evidence for map navigation (constant heading and bi-gradient taxis navigation). Additionally, our results indicate a multifactorial navigational mechanism necessitating more than one cue for successful navigation to the target. This is apparent from our simulations because the modelled endpoints of the trajectories of the CRW models do not reach close proximity to the target location of the GPS trajectory when simulated with geomagnetic navigational strategies alone. Additionally, the magnitude of the effect of the geomagnetic cues during navigation in our models was low in our CRB models. More research on the scale effects of the geomagnetic field on navigation, along with temporally varying geomagnetic data could be useful for further improving future models.Publisher PDFPeer reviewe

Simulating geomagnetic bird navigation using novel high-resolution geomagnetic data

The project was funded by the Leverhulme Trust [Research Project Grant RPG-2018-258].Birds rely on precise navigational mechanisms, especially for long-distance migrations. One debated mechanism is their use of the geomagnetic field. It is unclear if and how different species of birds are using intensity or inclination (or both) for navigation. Previous geomagnetic modelling research is based on static geomagnetic data despite a temporally and spatially varying geomagnetic field. Animals supposedly have a high sensitivity to those changes of the geomagnetic field. In order to understand how birds respond in real-time to its temporal variation, we need to use accurate geomagnetic information linked to the position of the bird through co-location in space and time. We developed a data-driven approach to simulate geomagnetic migratory strategies, using, for the first time, accurate contemporaneous geomagnetic data obtained from Swarm satellites of the European Space Agency. We created biased correlated random walk models which were based on both GPS data from greater white-fronted geese (Anser albifrons) during fall migration between north-west Russia and central Europe and contemporaneous satellite geomagnetic data. Different strategies of geomagnetic navigation associated with different geomagnetic values were translated into probability surfaces, built from geomagnetic data, and included into the random walk models. To evaluate which strategy was most likely, we compared the measured GPS trajectories to the simulated trajectories using different trajectory similarity measurements. We propose this as an approach to track many bird species for future comparative studies. We found that navigational strategies in these geese using magnetic intensity were closer to the observed data than those using inclination. This was the case in 80% of the best models and is an indication that it should be more beneficial for these geese to use intensity over inclination. Additionally, our results supported results from a previous study, that navigation based on taxis and compass mechanisms were more similar to the observed data than other mechanisms. We therefore suggest that these geese may use a combination of these strategies for navigation at a broad-scale. Overall, it seems likely that for successful navigation to the target location more than one mechanism is necessary; indicating a multifactorial navigation mechanism of these migratory geese in the study area. The satellite geomagnetic data are available at a higher temporal resolution and the use significantly improved the fit of the modelled simulations in comparison to the modelled geomagnetic data. Therefore, using annotated geomagnetic data could greatly improve the modelling of animal geomagnetic navigation in future research.Publisher PDFPeer reviewe

Habitat use during spring migration: Remote sensing meets movement ecology

Forage availability during spring migration is crucial for the survival and successful reproduction of many migratory species. With careful timing in relation to spring growth and small-scale selection of suitable food sites, large avian herbivory migrants are known to maximise foraging rate during spring. However, especially for Arctic breeders, the recent levels of climate and habitat change alter the conditions that they meet at their spring stopover and breeding sites. In the EO-MOVE project we examine the habitat use of greater white-fronted geese (Anser albifrons) along their spring migration route between central Europe and northern Russia. This species is known to be sensitive to land-use intensity, phenology and landscape configuration, which calls for the exploitation of high resolution tracking and remote sensing technologies. To characterise the movement of geese within their spring stopovers, we use over 150 highly resolved GPS tracks of individual adult geese from the years 2006-2017. Since 2014 we have additionally collected acceleration data to classify the animals' behaviour and energy expenditure. We select within-stopover GPS positions that are classified as flight or feeding and overlay the movements connecting different small-scale feeding sites with optical and SAR time series data (20Ã-20m) from the Sentinel 1 and 2 satellite missions using step selection functions. Habitat preference outcomes are then set into context with vegetation indices and compared between individuals, years and stopover sites. First results indicate that white-fronted geese generally select for highly green, low and young vegetation, but also that there are large differences between stopovers. We expect to reveal in detail how the birds select for suitable feeding sites in relation to availability and recent levels of habitat change, potentially allowing for site selection prediction, an important prerequisite for spatially or temporally targeted conservation schemes

Hotspots in the grid: Avian sensitivity and vulnerability to collision risk from energy infrastructure interactions in Europe and North Africa

Wind turbines and power lines can cause bird mortality due to collision or electrocution. The biodiversity impacts of energy infrastructure (EI) can be minimised through effective landscape-scale planning and mitigation. The identification of high-vulnerability areas is urgently needed to assess potential cumulative impacts of EI while supporting the transition to zero carbon energy. We collected GPS location data from 1,454 birds from 27 species susceptible to collision within Europe and North Africa and identified areas where tracked birds are most at risk of colliding with existing EI. Sensitivity to EI development was estimated for wind turbines and power lines by calculating the proportion of GPS flight locations at heights where birds were at risk of collision and accounting for species' specific susceptibility to collision. We mapped the maximum collision sensitivity value obtained across all species, in each 5 × 5 km grid cell, across Europe and North Africa. Vulnerability to collision was obtained by overlaying the sensitivity surfaces with density of wind turbines and transmission power lines. Results: Exposure to risk varied across the 27 species, with some species flying consistently at heights where they risk collision. For areas with sufficient tracking data within Europe and North Africa, 13.6% of the area was classified as high sensitivity to wind turbines and 9.4% was classified as high sensitivity to transmission power lines. Sensitive areas were concentrated within important migratory corridors and along coastlines. Hotspots of vulnerability to collision with wind turbines and transmission power lines (2018 data) were scattered across the study region with highest concentrations occurring in central Europe, near the strait of Gibraltar and the Bosporus in Turkey. Synthesis and applications. We identify the areas of Europe and North Africa that are most sensitive for the specific populations of birds for which sufficient GPS tracking data at high spatial resolution were available. We also map vulnerability hotspots where mitigation at existing EI should be prioritised to reduce collision risks. As tracking data availability improves our method could be applied to more species and areas to help reduce bird-EI conflicts

Biological Earth observation with animal sensors

Space-based tracking technology using low-cost miniature tags is now delivering data on fine-scale animal movement at near-global scale. Linked with remotely sensed environmental data, this offers a biological lens on habitat integrity and connectivity for conservation and human health; a global network of animal sentinels of environmen-tal change

Migration routes and stepping stones along the western flyway of Lesser White-fronted Geese (Anser erythropus)

In 2015 and 2016 four Lesser White-fronted Geese (Anser erythropus), a globally threatenedspecies, were caught and tagged during spring migration representing nearly 10% of the entire Swedish breeding population at the time. Two of the birds were followed over more than one season. Tracking data revealed an unexpected wide network of migration corridors and staging sites. Autumn and spring migration differed by stepping-stone sites and migration speed. So farunknown key stopover sites were discovered in Denmark, northern Germany, and Sweden. By using dynamic Brownian bridge movement models, the potential areas that Lesser Whitefronted Geese used during migration are described and conservation implications spotlighted.This study provides another important piece of the puzzle describing the migration of Lesser White-fronted Geese in Western Europe

Supplementary data References

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