A Geostatistical Approach to Estimate High Resolution Nocturnal Bird Migration Densities from a Weather Radar Network

Abstract

Quantifying nocturnal bird migration at high resolution is essential for (1) understanding the phenology of migration and its drivers, (2) identifying critical spatio-temporal protection zones for migratory birds, and (3) assessing the risk of collision with artificial structures. We propose a tailored geostatistical model to interpolate migration intensity monitored by a network of weather radars. The model is applied to data collected in autumn 2016 from 69 European weather radars. To validate the model, we performed a cross-validation and also compared our interpolation results with independent measurements of two bird radars. Our model estimated bird densities at high resolution (0.2 latitude–longitude, 15 min) and assessed the associated uncertainty. Within the area covered by the radar network, we estimated that around 120 million birds were simultaneously in flight (10–90 quantiles: 107–134). Local estimations can be easily visualized and retrieved from a dedicated interactive website. This proof-of-concept study demonstrates that a network of weather radar is able to quantify bird migration at high resolution and accuracy. The model presented has the ability to monitor population of migratory birds at scales ranging from regional to continental in space and daily to yearly in time. Near-real-time estimation should soon be possible with an update of the infrastructure and processing software.

Consistency of spatio‐temporal patterns of avian migration across the Swiss lowlands

“…; Nussbaumer et al. ). These systems offer the unique possibility to monitor and forecast bird migration at the continental scale, but they are not adequate to provide migration forecasts over a complex terrain, such as the mountainous Swiss landscape, because of the inadequate coverage of low flight altitudes (Hüppop et al.…”

High-Resolution Spatial Distribution of Bird Movements Estimated from a Weather Radar Network

“…Future research using these radars will provide more insight into the spatial variability of the vertical distribution, by providing more insight into the effects of elevation or habitat on the vertical distribution. This work paves the way toward developing methods that make more accurate assumptions on the local vertical profile compared to the nearest neighbor interpolation (taking the vertical profile of the closest radar) that is currently used; for example, by taking into account the full auto-correlation structure between profiles [44]. Combining weather radar with local bird radars is a powerful combination in which weather radar can provide the context for bird radars.…”

“…These provide a powerful tool for experts to gain insight into a range of migratory phenomena. Future improvements are approaches that can account for regional variations in altitudinal distributions [44,45], as well as tools to exclude non-biological signals to ease the interpretation and work toward fully quantitative analysis. Lin et al [46] already took important initial steps by segmenting out rain from the projected images using machine learning; alternatively, dual-polarization metrics can be used, e.g., [47].…”

Quantifying year-round nocturnal bird migration with a fluid dynamics model

“…Continental networks of weather radars are becoming an essential tool for monitoring large-scale migratory movements (Bauer et al, 2019). However, most studies so far have focused on migratory flights (Dokter et al, 2018; Nilsson et al, 2019; Nussbaumer et al, 2019; Van Doren & Horton, 2018), and a few modelled the stop-over distribution of birds on the ground (Buler et al, 2017; McLaren et al, 2018). Yet, none have linked these two stages and we therefore lack a comprehensive model of the entire migratory journey including the explicit consideration of the successive stages of take-off, flight and landing.…”

“…More specifically, we combine interpolated maps of both bird density and velocity field (i.e. the vector field of bird’s flight speed and direction) inferred from weather radar (Nussbaumer et al, 2019) into a discretized flow model (Figure 1). Since we assume that the mass of birds moving from one grid cell to another is conserved, any change of bird density (in the air) is explained by movements to and from the ground.…”