About the Project
This NERC CASE PhD studentship, based at the University of Aberdeen, offers a unique opportunity to work with new information derived from MeyGen, the world’s first commercial full scale tidal energy array (http://www.bbc.co.uk/news/uk-scotland-highlands-islands-37985293), and to develop real world solutions for the marine renewable industry. The PhD studentship requires a highly numerate ecologist and/or physical scientist who wishes to develop their analytical and modelling skills and work within a multi-disciplinary supervisory team. The Team will be from University of Aberdeen (UoA), St. Andrews University, Marine Scotland Science (MSS) and MeyGen (www.MeyGen.com). MeyGen will also support the student by offering them an embedded industrial placement for a minimum of 3 months.
The UoA, via the research outcomes of several NERC grants (FLOWBEC, RESPONSE, FORSITE), is at the forefront of the design, data acquisition and analysis to support the development of MeyGen and other marine renewable energy projects. At UoA we have designed systems for the collection of continuous acoustic data and developed analysis that have shown that multiple types of predator-prey interactions can be captured using a range of active acoustic instruments; multi-beam sonar (MBES which captures individual behaviour of all animals, Williamson et al. 2015 and 2016), and multi-frequency (EK60) echosounders which can be used both for the identification of fish species and measures of turbulence morphology. We have developed a method to define turbulence morphology such that turbulence effects on acoustic data can be ‘subtracted’ and fish, seabird and mammal behaviour can be tracked at all tidal states (Fraser et al. 2016). We have also developed methods to quantify changes in seabird energetics from changes in their behaviour (Chimienti et al. 2016). UoA also has an existing working relationship via a KTP with MeyGen. Therefore this PhD studentship will have access to previous data collected at the MeyGen site, as well as collecting a range of continuous real-time acoustic data from the operational array.
The cumulative environmental impacts of tidal arrays are not yet fully understood and there is the potential for marine renewable energy devices to induce individuals, whether they are fish, seabirds or mammals, to change their normal foraging, resting or migration behaviours due to: the introduction of devices to an area previously devoid of moving structures, changes to physical flow patterns and changes to acoustic conditions. Current research from UoA is showing significant changes to, at least, prey (fish) behaviour with the introduction of single turbine structures. All of these changes have potential to lead to impacts (negative and positive) at the population level of predators (seabirds & mammals) through cumulative changes in key parameters of individuals relating to:
1) the amount of energy/time used for foraging/migration
2) the success rate of predation/escape and
3) the mortality risks through collision with rotating structures
This NERC CASE PhD will develop in sequence of increasing complexity. Firstly, linking changes in behaviour with types of structures/changes in flow will use Functional Data Analysis (FDA). FDA is best used when the same location is sampled continuously (Embling et al 2012) analysing changes over time (tide/blade speed, turbulence characteristics, daylight, season). This analysis leads to the ability to determine Functional Relationships in both time and space between physical/biological aspects and the amount of change in behaviour, including predator and prey behaviours. Gaussian Mixture Models will be used to differentiate the range of behaviours within the types of species present (fish, seabirds, mammals). Creating simulation (stochastic) models that produce outputs at the population level, either in R or C++, depending on level of complexity, will be used to explore how best to link the functional relationships of quantified changes in behaviour to changes in annual and multiannual population levels.
This research will be at the forefront of detailed individual-to-population modelling and add accurate functional response relationships between changes in energy/time use in individuals so as to be able to assess the relative risks of significant changes at population levels due to the addition of large scale renewable developments. This project will be essential to creating more certainty in this new and emerging industry. This research is necessary to produce the level of understanding that is required to determine whether or not the potential changes will lead to significant impacts at the population level.
Please apply for admission to the ’Degree of Doctor of Philosophy in Biological Science’ to ensure that your application is passed to the correct college for processing.
References
1. Chimienti, M., Cornulier, T., Owen, E., Bolton, M., Davies, I., Travis, JMJ. & Scott, BE. (2016). 'The use of an unsupervised learning approach for characterizing latent behaviors in accelerometer data'. Ecology and Evolution, vol 6, no. 3, pp. 727–741. DOI: 10.1002/ECE3.1914
2. Embling, CB., Illian, J., Armstrong, E., van der Kooij, J., Sharples, J., Camphuysen, KCJ. & Scott, BE. (2012). 'Investigating fine-scale spatio-temporal predator–prey patterns in dynamic marine ecosystems: a functional data analysis approach'. Journal of Applied Ecology, vol 49, no. 2, pp. 481-492. DOI: 10.1111/J.1365-2664.2012.02114.X
3. Fraser, S., Nikora, V., Williamson, BJ. & Scott BE. (in press) Automatic active acoustic target detection in turbulent aquatic environments. Limnology and Oceanography: Methods
4. Williamson, BJ., Blondel, P., Armstrong, E., Bell, PS., Hall, CM., Waggitt, JJ. & Scott, BE. (2016). 'A Self-Contained Subsea Platform for Acoustic Monitoring of the Environment Around Marine Renewable Energy Devices–Field Deployments at Wave and Tidal Energy Sites in Orkney, Scotland'. IEEE Journal of Oceanic Engineering, vol 41, no. 1, pp. 67-81. DOI: 10.1109/JOE.2015.2410851
5. Williamson, BJ., Fraser, S., Blondel, Ph., Bell, PS., Waggitt, JJ. & Scott, BE. (in review) Multi-sensor acoustic tracking of fish and seabird behavior around tidal turbine structures in Scotland, UK. IEEE Journal of Oceanic Engineering