Our fundamental objectives are to monitor the aerial migrations of animals (birds, insects and bats) using weather radar networks, understand global patterns in the intensity, routes and timing of aerial migrations, and to forecast how these migrations are likely to respond to global change:
We will tap into the potential of continental weather radar networks to monitor aerial migrations. We will use algorithms for retrieving and classifying biological targets in radar signals, which have already been designed, calibrated and validated on a small subset of radars. We will also develop new methods for refining the spatial information currently extracted from radar signals, such as information on the body shape and alignment of aerial migrants from dual-polarization radars. We will setup an automated data processing pipeline running on cloud infrastructure to retrieve biological information from European and US weather radar data as these become available, with the capacity to run over the long-term. For the first time, we will establish a two-year dataset of aerial migration from approx. 70 weather radar stations in Europe and combine it with the existing data archive in the USA. We will make the resulting information on aerial migrations available as open data, supporting researchers in accessing, processing and analysing weather radar data and vertical profiles of aerial migrants.
We aim to use weather radars to monitor the movements of aerial migrants such as a) birds (image by Barth Bailey/Unsplash.com) and b) insects (image by aaabbbccc/Shutterstock.com).
We will quantify the biomass flows of aerial migrants both in Europe and the US at a variety of scales: across regions and continents, between seasons and years, and also across taxa. We will test different spatial analytical approaches to fill data gaps among radars, enabling us to more easily visualize and better identify spatio-temporal patterns of migration. Ultimately, we will produce maps depicting distributions of migration intensity, flight direction, altitude, and ground speed of avian and insect migrants at various spatial and temporal scales. This will enable us to answer fundamental questions such as where and when do the highest densities of aerial migrants occur, what are the long-term changes in the abundance of aerial migrants, and how is the phenology of their movements changing? Next, we will identify the abiotic and biotic drivers, such as weather, habitat, artificial light and wind energy installations, of the observed patterns in biomass flows of aerial migrants. We aim to identify overarching similarities in functional relationships with external variables and variation in these relationships among seasons, regions, continents and taxa.
Average intensities of bird migration, inferred from weather radar data, across a) Europe over 3 weeks in autumn 2016 (from Nilsson et al. 2019), and b) during spring across the US between 1995-2017 (from Horton et al. 2019).
We will predict the potential consequences of future environmental change for migratory populations at different scales and levels of complexity. Developing future scenarios for the main biotic and abiotic drivers of biomass flows, we will investigate the consequences of changes in these variables for movements and abundance of migratory populations using simulation behavioural-based models that generate predictions of migration behaviour, intensity and fate of migrant populations. In parallel, we will develop network models to assess the demographic consequences of environmental changes on migratory populations, in which migratory pathways are represented as systems of nodes connected through the flows of individuals along migration routes. Testing these models under future scenarios will allow us to identify core locations and sensitive times during the annual cycle at which aerial migrants may be most impacted by change. Ultimately, these different models will provide complementary insights into the degree to which migration flows are expected to shift in time and space under environmental change and therefore, at which locations and at which times the loss or novel occurrence of migrants might alter interactions within communities and ecosystems.
Simulated spring migrations of Afro-Palearctic migratory birds, from preliminary behaviour-based models developed within GloBAM.