About the Project
New tracking technologies have enabled researchers to unravel previously unknown animal movement strategies and migratory routes. The use of animal tracking devices that collect high temporal and spatial precision data, including altitude information has been increasing in recent years. Altitude data is necessary to estimate birds’ collision risk with offshore wind turbines, electricity cables or other energy infrastructure. This information is key and part of the decision-making process for proposed renewable developments. Areas with high collision risk should be avoided. This project has two components, first it will examine existing animal movement data, from devices that provide accurate elevation information and will examine bird collision risk with the energy infrastructure in Europe. This is important to identify areas with high collision risk that need mitigation actions. The second part of the project will focus on the development of new technology to determine when a bird actually collides. The devices will be tested during the PhD and the results of this project will open new avenues for identification of risk of collision, an issue that is increasing in importance worldwide.
We will use data on the movement of migratory birds from a variety of projects freely available on Movebank. Movement characteristics (altitude, speed, direction, flight type and distance moved) will be used to determine locations of high collision risk. This project will also take advantage of existing high temporal and spatial resolution data from ~80 white storks and will use newly developed features to identify collision events. The student will be involved in the development of the new features. The collision risk with energy infrastructure will be determined using GIS approaches.
The student will benefit from the expertise in data analyses and field techniques provided by the supervisory team and collaborating partners.
The NEXUSS CDT provides state-of-the-art, highly experiential training in the application and development of cutting-edge Smart and Autonomous Observing Systems for the environmental sciences, alongside comprehensive personal and professional development. There will be extensive opportunities for students to expand their multi-disciplinary outlook through interactions with a wide network of academic, research and industrial / government / policy partners.
This project will train the PhD student on the interface between ecology and engineering. The student will be involved in assembling and testing tracking devices, and will be able to assess their performance in lab conditions and in the field, by deploying the devices on birds.
- Assembling testing tracking devices (HWU and UEA)
- Deployment of tracking devices storks (UK/Portugal)
- Movement and behavior data analyses and interpretation (UEA)
- GIS analyses of the collision risk (UEA).
Secondary supervisors: Dr Joao Paulo Silva (University of Porto), Dr Phil Atkinson (BTO), Dr Paul Record (Herriot Watt).
The student will be registered and hosted at the School of Environmental Sciences, University of East Anglia (UEA).
For further information, please visit www.enveast.ac.uk/nexuss
For more information on the supervisor for this project, please go here: http://www.uea.ac.uk/environmental-sciences/people/profile/a-franco
Type of programme: PhD
Start date of project: October 2018
Mode of study: Full time or part time
Length of studentship: 3 years, 8 months
Acceptable first degree: Biology, Engineering or any numerate discipline.
Standard minimum entry requirement: 2:1 or equivalent.
(ii) Thaxter CB, Buchanan GM, Carr J, Butchart SHM, Newbold T, Green RE, Tobias JA, Foden WB, O'Brien S, Pearce-Higgins JW (2017) Bird and bat species' global vulnerability to collision mortality with wind farms revealed through a trait-based assessment. Proc. R. Soc. B.
(iii) B.Kranstauber, A.Cameron, R.Weinzerl, T.Fountain, S.Tilak, M.Wikelski, R.Kays (2011) The Movebank data model for animal tracking. Environmental Modelling and Software, 26 (6), 834-835.
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