BioDAR: Using Weather Radars and Machine Learning to Examine Insectageddon

Lead Research Organisation: University of Leeds
Department Name: School of Earth and Environment


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 use physics software 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 results from the radar data 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 at 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.


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Studentship Projects

Project Reference Relationship Related To Start End Student Name
NE/S007458/1 31/08/2019 29/09/2027
2607691 Studentship NE/S007458/1 30/09/2021 29/09/2022 WIlliam Evans