A new approach for objective identification of turns and steps in organism movement data relevant to random walk modelling

1. 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. 2. 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. 3. 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. 4. 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. 5. 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.

The Sentinel-3 Mission Performance Center

As part of the Sentinel-3 mission and in order to ensure the highest quality of products, ESA in cooperation with EUMETSAT has set up the Sentinel-3 Mission Performance Centre (S-3 MPC). This facility is part of the Payload Data Ground Segment (PDGS) and aims at controlling the quality of all generated products, from L0 to L2. The S-3 MPC is composed of a Coordinating Centre (CC), where the core infrastructure is hosted, which is in charge of the main routine activities (especially the quality control of data) and the overall service management. Expert Support Laboratories (ESLs) are involved in calibration and validation activities and provide specific assessment of the products (e.g., analysis of trends, ad hoc analysis of anomalies, etc.). The S-3 MPC interacts with the Processing Archiving Centres (PACs) and the Marine centre at EUMETSAT.