Posted: September 15, 2020

Bee health is currently compromised in response to numerous environmental stressors including poor nutrition, exposure to pesticides, and climate change.

One key metric to assess bee health is to quantitatively study bees’ foraging patterns to determine whether bees are able to optimize the collection of food resources to bring them back to the nest. However, studying bee foraging patterns is inherently difficult due to their small body size and the long distances they fly on a daily basis. To address this research challenge, several members of the Center for Pollinator Research (CPR) are developing a radar system to investigate in detail the foraging patterns of bees. The radar is comprised of a transmitting antenna pulsing electromagnetic energy at a given frequency (fo = 9.41 gigahertz). The signal is intercepted and re-emitted at a doubled frequency (2fo) by a transponder carried by bees. A receiving antenna intercepts the transponder’s energy (see Figure 1). A very sensitive low-noise block downconverter is connected to the receiving antenna to process the radar signal and pass the resulting information on to a software-defined radio architecture, which transfers the sampled data to a Raspberry Pi for storage and sharing. The time it takes for the pulsed energy to travel to the transponder and back to the receiving radar antenna is determined using accurate local oscillators. Also, the distance between the radar location and the transponder is obtained as bees move around in the environment. Based on the derived distance between the radar and the bee carrying the transponder, the instantaneous movement patterns of bees can be ascertained.

This past summer, as part of the Penn State REU program on Climate Science , the CPR research team worked with Elana Cope, a student from Colorado State University, on the development of a radar data acquisition and visualization software. The software development took place during the COVID-19 pandemic, and physical radar field deployment and in situ data acquisition were not possible. Therefore, envisioned and published datasets were used to perform analyses and visualization of the bee radar data. Data files generated within the Raspberry Pi system provided frequency of radar measurements, azimuthal position of bees carrying the transponders, and distances between bees and the radar site. The software processes the radar-transponder data and analyzes and visualizes in real time the insect movement patterns. Using a graphical user interface and interactive data visualization techniques, the software allows users to view and manipulate the radar information live while bees are foraging. Visualizations are based on a dashboard representation where users can track and monitor bee movements, and at the same time visualize outbound and inbound bee flights. This software makes it possible to calculate relevant information about bee foraging patterns such as step distances, visualize the resulting graphs, and display physical location and flight patterns on georeferenced maps.

The bee radar technology and associated data visualization that the team is developing will revolutionize the manner in which scientists can perform field studies on bee health and their interactions with floral resources in different types of landscapes. With the generated data sets, scientists will be able to develop controlled experiments that investigate how different environmental stressors (e.g., floral resource availability, pesticide exposure, air contaminants) influence foraging patterns and fitness of bee pollinators.

Research team include:

  • Elana Cope, Chemistry undergraduate student at Colorado State University
  • José D. Fuentes, Professor of Atmospheric Science
  • Julio Urbina, Professor of Electrical Engineering
  • Margarita M. López-Uribe, the Lorenzo L. Langstroth Early Career Professor and Assistant Professor of Entomology
  • Diego Peñaloza Aponte, Doctoral student of Electrical Engineering
  • Zachary Moon, Doctoral student of Atmospheric Science

Acknowledgements
The Penn State REU Program in Climate Science is funded by the National Science Foundation under grant number AGS-1852428.