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

Nocturnal migration flow visualizations for Europe and the US.

<p>In all visualizations a black filled circle indicates radar location. (A) Bird migration flow visualization across Belgium and the Netherlands on 2013-04-07T05:00Z. The vector length is proportional to ground speed. Two different axes of nocturnal migration can be seen with birds arriving from the United Kingdom and travelling in an easterly direction and birds travelling along the main northeastern axis of migration. The northeastern axis can be seen in western Belgium and the west to east migration axis can be seen in the northern half of the Netherlands. Due to changes in mean ground speed and direction detected by the different radar the two flow patterns seem to converge. Note that in SE Belgium migration is almost absent. (B) TIMAMP visualization showing 6-hour migration flows in 5 strata (altitude bands) for Belgium and the Netherlands starting at 2013-04-07T18:00Z. Length and direction of lines represents the <i>u</i> and <i>v</i> components of ground speed integrated over 6 hours, the distribution of pathlines corresponds with relative density. Intense nocturnal migration occurs predominantly in SE Belgium across all altitude layers, with birds travelling at relatively high speeds. Migration track direction, however, differs between the lowest and higher altitude bands, with birds maintaining the primary northeast axis of migration at high altitudes but at the lowest altitude band in more northern areas and later in the night directions are shifted towards the north. (C) Bird migration flow visualization of the US case study showing nocturnal migration on 2010-09-09T03:45Z. Migration towards the southeast suggests initiation of over water migration, particularly from Cape Cod, Massachusetts to Chesapeake Bay, Virginia. Note that areas in northern New England, northern New York state, and the Lake Ontario region show substantially less migration activity than what occurred at more coastal locations. (D) TIMAMP visualization showing 10-hr migration flows in 5 strata for the US case study on 2010-09-11T00:00Z. Each pathline represents ca. 250,000 migrants. Migration directions during this period are typical of those described in Autumn for this region, with most birds moving toward south-southwesterly to southwesterly directions over land. Note, however, subtle change in migration direction across sites and during the night, as tracks arc more westerly as well as change in density during the night and across the region.</p

Summary of migration flow visualizations.

<p>Information on user control functionality and terminology used in web interface in parentheses. Hyperlinks to online visualizations are provided.</p

Schematic representation of the bird migration flow visualization.

<p>For each radar (Radar 1 & 2), the application will calculate a two-dimensional vector representing the <i>u</i> and <i>v</i> components of the detected ground speed of migration for that radar, altitude band and time interval (T0). Using the x and y positions of the radars, these vectors are interpolated using inverse squared distance weighting to create a vector field of interpolated ground speeds, expressed in pixels. Once the vector field is calculated, the animation starts. At animation frame 1, a streamline A (blue line) is initiated at a random position (blue dot) and the interpolated ground speed at that position is used to draw a line to a new position. This is repeated for each animation frame (2, 3, 4), creating a streamline through the vector field. At animation frame 3 an additional streamline B is initiated. After a fixed number of frames, the application will retrieve data from a new time interval (T1) and update the vector field, influencing the direction and speed of the streamlines.</p