Abstract: A first step in the analysis of complex movement data often involves discretisation of the path into a series of step-lengths and turns, for example in the analysis of specialised random walks, such as Lévy flights. However, the identification of turning points, and therefore step-lengths, in a tortuous path is dependent on ad-hoc parameter choices. Consequently, studies testing for movement patterns in these data, such as Lévy flights, have generated debate. However, studies focusing on one-dimensional (1D) data, as in the vertical displacements of marine pelagic predators, where turning points can be identified unambiguously have provided strong support for Lévy flight movement patterns. Here, we investigate how step-length distributions in 3D movement patterns would be interpreted by tags recording in 1D (i.e. depth) and demonstrate the dimensional symmetry previously shown mathematically for Lévy-flight movements. We test the veracity of this symmetry by simulating several measurement errors common in empirical datasets and find Lévy patterns and exponents to be robust to low-quality movement data. We then consider exponential and composite Brownian random walks and show that these also project into 1D with sufficient symmetry to be clearly identifiable as such. By extending the symmetry paradigm, we propose a new methodology for step-length identification in 2D or 3D movement data. The methodology is successfully demonstrated in a re-analysis of wandering albatross Global Positioning System (GPS) location data previously analysed using a complex methodology to determine bird-landing locations as turning points in a Lévy walk. For this high-resolution GPS data, we show that there is strong evidence for albatross foraging patterns approximated by truncated Lévy flights spanning over 3·5 orders of magnitude. Our simple methodology and freely available software can be used with any 2D or 3D movement data at any scale or resolution and are robust to common empirical measurement errors. The method should find wide applicability in the field of movement ecology spanning the study of motile cells to humans.

Abstract: In summer 2007 we have established a new atmospheric monitoring station in Ivittuut (61.21°N, 48.17°W), on the western coast of South Greenland. The motivation for choosing this location was to study the role of the North Atlantic Ocean in the global and regional carbon cycle and to add a continuous measurement site in a still uncovered area. This work is part of the EU CarboOcean IP project, and was endorsed by the International Polar Year through the Polarcat project.
High precision CO2 and O2 analyzers have been developed at LSCE and installed on site together with meteorological sensors. Regular flask samples are done and independently analyzed at LSCE and MPI-BGC for quality control, and to provide complementary trace gases and isotopic measurements. Since September 2007, continuous measurements of CO2 and O2 have been recorded.
We will present the Ivittuut continuous CO2 and O2 data as well as the flask measurements, and compare both data sets to illustrate their reliability and precision. A preliminary data filtering attempt based on meteorological criteria (wind speed and direction) used to identify the origin of air masses (and corresponding CO2 and O2 concentration levels) will be compared to back trajectories from the Hysplit4 model. Concurrent measurements of atmospheric CO2 and O2 allow to calculate the Atmospheric Potential Oxygen (APO), a tracer of air-sea gas exchange of O2, and from which, given certain assumptions, the strength of marine biological activity can be elucidated. A comparison of the data-derived APO and the one obtained with the OPA-PISCES coupled ocean circulation/biogeochemical model will be presented. Based on our APO results, we will suggest an estimate of oceanic and land biotic carbon fluxes.