BioCast: Using Weather Radars and Numerical Weather Forecast to Predict Changes in Biodiversity

Overview and Scientific need:

Weather radars scan the entirety of the UK every 5 minutes, and similar radars are used worldwide for the same purpose. Such radar routinely insects and other animal life in the atmosphere, 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 observes to our ability to predict the onset of insect migrations, mass emergences or pest invasions. This interdisciplinary PhD project is designed to assess how radar data, numerical weather forecasts and ecological models can be used together to generate biologically useful information that can be applied to solve contemporary ecological problems. The project will involve (and provide training in) a range of techniques from physics, ecology and meteorology.

 

In the first phase of the project, the student will be trained to use the output of the NERC-funded BioDAR and DRUID projects, which have used the UK’s weather radars to map insect abundance and diversity through time, in combination with high-resolution numerical weather forecast output to assess different movements of aerial fauna across the UK with regards to the detailed atmospheric conditions that may or may not be driving them. This could potentially include the annual “fly ant day” that is well documented in the UK Met Office’s radars, in situ sampling systems run by Rothamsted Research and citizen science data collection campaigns organised by researchers at the University of Leeds, outbreaks of aphids and or migrations of moths.

 

In the second phase of the project, the student will select a set of case studies and put the “bugs” into the computer.  By this, we mean the student will use a high-resolution numerical weather forecasting model to simulate the movement and behaviours of the selected fauna groups. This will be achieved by coupling the widely used Weather Research Forecast (WRF) model to a “fauna” simulation module developed by the student in a manner similar to how WRF has been coupled to aerosol and chemistry modules to model air quality.

 

In the third phase of the project, the developed model will be used to investigate a pressing issue in conservation: the effect of human modification of the landscape on insects. The student will possibly examine this issue in one of three ways, by looking at the impacts of light pollution, urbanisation, and or agri-environment schemes (which are designed to help nature on farmland) depending on the insects chosen in the second phase.

 

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 (Natural England, Centre for Ecology and Hydrology, BugLife) and abroad (in the US and South Africa) who will be involved in discussions 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.

 

Potential for High Impact Outcomes

The outputs from the project will 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 assessments based on our own analyses: the building of new towns, part-night street lighting schemes for energy saving, or the implementation of agri-environment schemes 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.

 

Training

You will work directly under the supervision of Prof. Stephen Mobbs, Dr Ryan R. Neely III and Dr Christopher Hassall within both the School of Earth and Environment, School of Biology and NCAS. You will also become an active member of each PI’s research groups and, thus, benefit from working within a dynamic 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 participating 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 (http://www.emeskillstraining.leeds.ac.uk/).

 

Requirements

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. In addition, experience in programming (e.g. Python, Matlab, IDL, R…) and fieldwork is advantageous.

 

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 (R.Neely@leeds.ac.uk).

 

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.