BioDAR: Using Weather Radars and Machine Learning to Examine Insectageddon

Overview and Scientific need:

Weather radar scan the entirety of the UK every 5 minutes, and similar types of radar are used around the world for the same purpose. These radars routinely detect insects, but since animals are not of interest to meteorologists, they are discarded as unwanted “noise”. That “noise” is a veritable treasure trove of information on insect diversity and abundance, but what is required is a way to link what a radar sees to the insects that we wish to monitor. This interdisciplinary PhD project is designed to assess to what extent these radar data can generate useful biological information that can be applied to solve contemporary ecological problems in concert with state-of-the-art meteorological and land-use data. The project will involve (and provide training in) a range of techniques from physics, ecology, radar meteorology, geography and atmospheric science.

In the first phase of the project, the student will be trained to use 3D and electromagnetic modelling techniques to simulate what the radar might see when different insects pass through the radar beam. The results of those simulations will be used to produce algorithms that can classify the radar observations into different kinds of insects based on their shape, as well as quantifying the diversity and number of insects passing through the beam.

In the second phase of the project, we will then test the classification algorithms by comparing our radar predictions against existing datasets that have used (i) special radar called “vertical looking radar” to scan small areas of sky, (ii) a network of 18 suction traps that capture insects every day, and (iii) a network of 83 light traps that catch nocturnal moths. These datasets allow us to link the theoretical classification algorithms to real-world biological data on a national scale.

In the third phase of the project, the student will combine the lessons learned about our classification algorithms in the first and second phases to produce a national map of aerial insect biodiversity and abundance that can be used to examine the causes and consequences of insect emergence and insect migrations. Moths, butterflies, hoverflies and flying ants are of specific concern. In particular, this map will be used to investigate a pressing issue in conservation: the effect of human modification of the landscape and atmosphere on insects (including impacts of regional climate change and changes in air quality). The student will examine this issue by looking at the effects of light pollution, urbanisation, and agri-environment schemes (which are designed to help nature on farmland). We would expect lower insect biodiversity and abundance near areas with high nocturnal light pollution, higher intensity of urbanisation, and in the absence of agri-environment schemes. With the help of BugLife, you will be able to test these hypotheses by examining pre- and post-restoration insect communities.

Taken together, this PhD project has an exciting interdisciplinary focus that will produce considerable impact if the work is successful. We have already identified key external partners both within the UK (notably BugLife, our CASE Partner, as well as Natural England, Centre for Ecology and Hydrology,) and abroad (in the US, Brazil, Oman and South Africa) who will be involved in the discussion and guiding the project. The project would benefit from a student with strong quantitative skills in radar analysis and an interest in solving real-world environmental problems.


Scientific Objectives

The central effort of this project is to take the progress in radar ecology and technology that has occurred in the past 20 years and produce a data analysis pipeline that can convert raw radar data from multiple radar types (X-, C- or S-band) and turn those data into meaningful biological information. This objective will represent a step-change in the way that biodiversity has been monitored around the world, opening up entirely new ways to conduct ecological research. Note that the objectives below represent a possible pathway, and the successful candidate will guide and develop the course of the project with the supervisors once they start.

Objective 1– Characterise the electromagnetic properties of key invertebrate morphotypes using microCT scanning and electromagnetic
simulation to define the taxonomic resolution possible within radar data.

Objective 2– Generate a set of “biometeor classification algorithms” (BCAs) for the analysis of invertebrate biodiversity using weather radar observations.

Objective 3– Validate the weather radar-based biodiversity metrics against conventional and novel monitoring for aerial invertebrates (VLR, suction traps, aerial sampling, pan traps, transects, experimental insect release).

Objective 4– Scale up the classification algorithms that have been validated in Obj2 to create a national map of insect biodiversity that will be compared against maps of urbanisation, light pollution, and agri-environment schemes.

As part of accomplishing the objectives of this work, there is an opportunity to travel (including possibly to Africa) and to get hands-on field experience.


Potential for High Impact Outcomes

The outputs from the project, both in terms of the analytical pipeline and the aerial biodiversity maps, will both be of direct relevance to the monitoring of the environment. These results will be significant for researchers, Statutory agencies, Policymakers, Conservation charities and the general public. As such, besides a series of high-profile papers based on the novel analysis of this work, the outputs of this PhD will allow for a new wave of evidence-based environmental policy by facilitating the evaluation of landscape-scale modifications. These might include evaluations based on our analyses: the building of new towns, part-night street lighting schemes for energy saving, or the implementation of agri-environment schemes that are designed to help nature thrive alongside agricultural productivity. Additional analyses could be conducted to evaluate the implementation of bans on pesticides or herbicides, the introduction of genetically modified crops, or invasive species. Current monitoring of such events is limited severely by cost and logistics, but BeeDAR will provide a dataset that is regularly updated, and that can be investigated using open science pipelines supplied at very low cost.



You will work directly under the supervision of Dr Ryan R. Neely III, Dr Christopher Hassall and Dr Elizabeth Duncan within both the School of Earth and Environment and School of Biology. You will also become an active member of each PIs research groups and, thus, benefit from working within a vibrant and multidisciplinary group of scientists.

This project will equip you with the necessary expertise to become a leader in the emerging field of agroecology, ready to carry out your own programme of innovative scientific research. These skills will be developed by a mixture of hands-on experience, attending external training courses, national and international conferences, and taking part in the Leeds – York NERC doctoral training partnership programme. This includes access to a broad spectrum of training workshops put on by the Faculty that consist of a range of extensive training workshops that will help you manage your degree and prepare for your viva (



A good first degree (1 or good 2-1), or a good Masters degree in a physical, mathematical or biological discipline, such as mathematics, physics, geophysics, engineering, biology, ecology, biomedical science, biochemistry, zoology or meteorology is required. Experience in programming (e.g. Python, Matlab, IDL, R…) and fieldwork is of advantage.


Contact Information

Contact is strongly encouraged before application so that we may discuss your interests and project specifics.  Help with the application process may also be provided. Enquiries should be made by contacting Dr Ryan Neely, Associate Professor of Observational Atmospheric Science (


References and Further Reading

  • Biesmeijer, JC et al. (2006), Parallel Declines in Pollinators and Insect-Pollinated Plants in Britain and the Netherlands, Science 313, 351-354.
  • Ceballos, G., P. R. Ehrlich, and R. Dirzo (2017), Biological annihilation via the ongoing sixth mass extinction signaled by vertebrate population losses and declines, Proceedings of the National Academy of Sciences, 114(30), E6089–E6096, doi:10.1073/pnas.1704949114.
  • Chilson, P. B., W. F. Frick, J. F. Kelly, K. W. Howard, R. P. Larkin, R. H. Diehl, J. K. Westbrook, T. A. Kelly, and T. H. Kunz (2012), Partly Cloudy with a Chance of Migration: Weather, Radars, and Aeroecology, Bulletin of the American Meteorological Society, 93(5), 669–686, doi:10.1175/BAMS-D-11-00099.1.
  • Chilson, P. B., E. Bridge, W. F. Frick, J. W. Chapman, and J. F. Kelly (2012), Radar aeroecology: exploring the movements of aerial fauna through radio-wave remote sensing, Biology Letters, 8(5), 698–701, doi:10.1098/rsbl.2012.0384.
  • Chilson, P. B., W. F. Frick, P. M. Stepanian, J. R. Shipley, T. H. Kunz, and J. F. Kelly (2012), Estimating animal densities in the aerosphere using weather radar: To Z or not to Z? Ecosphere, 3(8), 1–19, doi:10.1890/ES12-00027.1.
  • Dufton, D. R. L., and C. G. Collier (2015), Fuzzy logic filtering of radar reflectivity to remove non-meteorological echoes using dual polarization radar moments, Atmos. Meas. Tech., 8(10), 3985–4000, doi:10.5194/amt-8-3985-2015.
  • Gauthreaux, S. A., J. W. Livingston, and C. G. Belser (2007), Detection and discrimination of fauna in the aerosphere using Doppler weather surveillance radar, Integrative and Comparative Biology, 48(1), 12–23, doi:10.1093/icb/icn021.
  • Gürbüz, S. Z., D. R. Reynolds, J. Koistinen, F. Liechti, H. Leijnse, J. Shamoun-Baranes, A. M. Dokter, J. Kelly, and J. W. Chapman (2015), Exploring the skies: Technological challenges in radar aeroecology, pp. 0817–0822, IEEE.
  • Hu, G., K. S. Lim, N. Horvitz, S. J. Clark, D. R. Reynolds, N. Sapir, and J. W. Chapman (2016), Mass seasonal bioflows of high-flying insect migrants, Science, 354(6319), 1584–1587, doi:10.1126/science.aah4379.
  • Kunz, T. H. et al. (2007), Aeroecology: probing and modeling the aerosphere, Integrative and Comparative Biology, 48(1), 1–11, doi:10.1093/icb/icn037.
  • Mirkovic, D., P. M. Stepanian, J. F. Kelly, and P. B. Chilson (2016), Electromagnetic Model Reliably Predicts Radar Scattering Characteristics of Airborne Organisms,, 6(1), 1–11, doi:10.1038/srep35637.
  • Melnikov, V. M., M. J. Istok, and J. K. Westbrook (2015), Asymmetric Radar Echo Patterns from Insects, J. Atmos. Oceanic Technol., 32(4), 659–674, doi:10.1175/JTECH-D-13-00247.1.
  • Westbrook, J. K., R. S. Eyster, and W. W. Wolf (2013), WSR-88D doppler radar detection of corn earworm moth migration, Int J Biometeorol, 58(5), 931–940, doi:10.1007/s00484-013-0676-5.
  • Westbrook, J. K., and R. S. Eyster (2017), Doppler weather radar detects emigratory flights of noctuids during a major pest outbreak, Remote Sensing Applications: Society and Environment, 8, 64–70, doi:10.1016/j.rsase.2017.07.009.