Innovative Visualizations Shed Light on Avian Nocturnal Migration

We acknowledge the support provided by COST–European Cooperation in Science and Technology through the Action ES1305 ‘European Network for the Radar Surveillance of Animal Movement’ (ENRAM) in facilitating this collaboration. We thank ENRAM members and researchers attending the EOU round table discussion ‘Radar aeroecology: unravelling population scale patterns of avian movement’ for feedback on the visualizations. We thank Arie Dekker for his feedback as jury member of the bird migration visualization challenge & hackathon hosted at the University of Amsterdam, 25–27 March 2015. We thank Willem Bouten and Kevin Winner for discussion of methodological design. We thank Kevin Webb and Jed Irvine for assistance with downloading, managing, and reviewing US radar data. We thank the Royal Meteorological Institute of Belgium for providing weather radar data.Globally, billions of flying animals undergo seasonal migrations, many of which occur at night. The temporal and spatial scales at which migrations occur and our inability to directly observe these nocturnal movements makes monitoring and characterizing this critical period in migratory animals’ life cycles difficult. Remote sensing, therefore, has played an important role in our understanding of large-scale nocturnal bird migrations. Weather surveillance radar networks in Europe and North America have great potential for long-term low-cost monitoring of bird migration at scales that have previously been impossible to achieve. Such long-term monitoring, however, poses a number of challenges for the ornithological and ecological communities: how does one take advantage of this vast data resource, integrate information across multiple sensors and large spatial and temporal scales, and visually represent the data for interpretation and dissemination, considering the dynamic nature of migration? We assembled an interdisciplinary team of ecologists, meteorologists, computer scientists, and graphic designers to develop two different flow visualizations, which are interactive and open source, in order to create novel representations of broad-front nocturnal bird migration to address a primary impediment to long-term, large-scale nocturnal migration monitoring. We have applied these visualization techniques to mass bird migration events recorded by two different weather surveillance radar networks covering regions in Europe and North America. These applications show the flexibility and portability of such an approach. The visualizations provide an intuitive representation of the scale and dynamics of these complex systems, are easily accessible for a broad interest group, and are biologically insightful. Additionally, they facilitate fundamental ecological research, conservation, mitigation of human–wildlife conflicts, improvement of meteorological products, and public outreach, education, and engagement.Yeshttp://www.plosone.org/static/editorial#pee

Advanced kinetic modelling strategies: Towards adoption in clinical PET imaging

Positron emission tomography (PET) is a highly quantitative imaging modality that can probe a number of functional and biological processes, depending on the radio-labelled tracer used. Static imaging, followed by analysis using semi-quantitative indices, such as the standardised uptake value, is used in the majority of clinical assessments in which PET has a role. However, considerably more information can be extracted from dynamic image acquisition protocols, followed by application of appropriate image reconstruction and tracer kinetic modelling techniques, but the latter approaches have mainly been restricted to drug development and clinical research applications due to their complexity in terms of both protocol design and parameter estimation methodology. To make dynamic imaging more feasible and valuable in routine clinical imaging, novel research outcomes are needed. Research areas include non-invasive input function extraction, protocol design for whole-body imaging application, and kinetic parameter estimation methods using spatiotemporal (4D) image reconstruction algorithms. Furthermore, with the advent of sequential and simultaneous PET/magnetic resonance (MR) data acquisition, strategies for obtaining synergistic benefits in kinetic modelling are emerging and potentially enhancing the role and clinical importance of PET/MR imaging. In this article, we review and discuss various advances in kinetic modelling both from a protocol design and a methodological development perspective. Moreover, we discuss future trends and potential outcomes, which could facilitate more routine use of tracer kinetic modelling techniques in clinical practice