MSc(Res) Behaviour, Ecology and Evolution

The Master of Science by Research degree in Behaviour, Ecology and Evolution is a 12-month, research only degree, in which the candidate will undertake a supervised research project in the broad area of Behaviour, Ecology and Evolution, in the School of Biology, University of St Andrews.

The candidate will be based in the interdisciplinary Centre for Biological Diversity (CBD), based in the centre of St Andrews. The CBD links researchers in evolution, behaviour, ecology, molecular biology and biodiversity, plus researchers in other Schools across St Andrews. Research themes include: the mechanistic causes and the ecological and evolutionary consequences of animal behaviour, with strengths in behavioural ecology, animal cognition, social evolution and social learning; evolutionary and population genetics, including the genetic basis of population divergence and speciation; animal-plant interactions, including pollinator biology; conservation biology, focusing in particular on the measurement of broad-scale patterns of biodiversity and biodiversity change. These themes are underpinned and guided by theoretical evolutionary ecologists and geneticists, asking fundamental questions about the causes and consequences of organismal interaction. Our final objective is to advance this scientific understanding of the diversity of life to contribute pro-actively to policy that helps protect and nurture biological diversity.

Candidates may approach potential supervisors in the CBD directly or via advertised projects listed below.

Projects

Social learning, individual variation in cognitive abilities, comparative cognition

Supervisor: Dr Lauren Guillette

Research area (s): Social learning; Individual variation in cognitive abilities; Comparative cognition

Research description: My current project examines social learning in nest-building behaviour in birds, asking questions such as: Who do you learn from? What do you learn? When do you learn? My work is often comparative – I study social learning in other contexts such as when animals are making foraging decisions. I also work on the neurobiological basis of social learning and individual differences in cognitive abilities. I mainly study birds (and sometimes invertebrates – antlion larvae) in the laboratory and outdoor aviaries, and have access to a population of blue tits that breed in nest boxes we provide around St Andrews.

Relevant references: Guillette, L.M., Scott, A.C.Y. & Healy, S.D. (2016) Social learning in nest-building birds: the role of familiarity. Proceedings of the Royal Society B: Biological Sciences, 283, 20152685. http://dx.doi.org/10.1098/rspb.2015.2685

Guillette, L.M., Naguib, M. & Griffin, A.S. (2017) Individual differences in cognition and personality. Behavioural Processes, 134, 1-3 http://dx.doi.org/10.1016/j.beproc.2016.12.001

Guillette, L.M. & Healy, S.D. (2017). The roles of vocal and visual interactions in social learning zebra finches: A video playback experiment. Behavioural Processes. doi: http://dx.doi.org/10.1016/j.beproc.2016.12.009

Subject area(s): Animal cognition; Animal Behaviour

Keywords: Social Learning, Birds, Individual variation, Nests

Animal cognition

Supervisor: Dr Sue Healy

Research area (s): Animal cognition

Research description: Cognition plays a central role in the lives of many animals, whether with regard to learning and remembering where to find food or home, making decisions over choices of food or mates or in interacting with others.  Current research projects are focussed on two areas (http://cognitioninthewild.wp.st-andrews.ac.uk):

  1. Determining how birds know what nest to build (behavioural and neurobiological laboratory work on zebra finches, behavioural field work on UK blue tits and African weavers);
  2. Using free-living hummingbirds (Canadian Rocky Mountains, collaborator Prof. Andy Hurly, University of Lethbridge) as a model system to investigate cognition in the wild.

Relevant references:

Subject area(s): Animal behaviour; Animal cognition

Keywords: Nest building, Birds, Foraging

Projects in Evolutionary Quantitative Genetics

Supervisor: Dr Michael Morrissey

Research area (s): Projects in Evolutionary Quantitative Genetics

Research description:Evolutionary quantitative genetics provides a general framework for modelling how natural selection and genetic variation interact to generate adaptive evolutionary change.  Conducting a research project in this field will provide a student with a solid foundation in a key area evolutionary biology, as well as broadly useful analytical skills.

Several projects are available that are suitable to an Msc by research, including:

  1. Selection of morphology and phenology in heterogeneous environments: The student will conduct a field study to collection trait, fitness, and microenvironmental data in a local wild annual plant population, and conduct analyses of selection of those traits that account simultaneously for the effects of both traits and microenvironmental variation on fitness.
  2. The genetic basis of plasticity and evolutionary consequences of non-linear reaction norms:  The student will collect trait data from fruit flies raised across a range of diet treatments.  This will allow inference of the genetic basis of plasticity, and assessment of likely changes in the mean and variance of phenotype under responses to different selective regimes.

Interested candidates should contact Dr Michael Morrissey to discuss these or other potential projects in advance of preparing an application.

Relevant references:

Subject area(s): Evolutionary Quantitative Genetics

Keywords: Genetics, Environmental, Evolutionary; Genetics

Predation, behaviour, animal communication

Supervisor: Professor Graeme Ruxton

Research area(s): Predation, behaviour, animal communication

Research description: I am interested in how prey protect themselves from predators, particularly through their appearance (e.g. camouflage and mimicry) and through grouping together. I have a number of projects in this area that should appeal to a student wanting to stretch their understanding in behavioural ecology, experimental design, animal behaviour and zoology generally. I also have a strong interest in enhancing the practice of experimental design and statistical analysis across biology, and would welcome enquiries from students with a maths and/or statistics background interested in applying their skills within whole organism biology.

Relevant references:

Subject area(s): Behavioural Ecology, Animal Communication

Keywords: Animal behaviour, Psychology, Camouflage, Signalling

Evolutionary biology, genetics

Supervisor: Professor Michael Ritchie

Research area(s): Evolutionary biology, genetics

Research description: The student will analyse genes involved in local adaptation to different environments in the fruit fly Drosophila. Genome analysis has identified genes associated with environmental variables such as cold temperature. The student will assess these candidate genes for a role in ecological adaptation by either applying mutant or new genome manipulation techniques which disturb gene function, or further comparative genomic analyses, depending on the interest of the student.

Relevant References: Parker, D. J., L. Vesala, M. G. Ritchie, A. Laiho, A. Hoikkala and M. Kankare (2015). “How consistent are the transcriptome changes associated with cold acclimation in two species of the Drosophila virilis group?” Heredity. 115: 13-21.

Vigoder, F. M., D. J. Parker, N. Cook, O. Tourniere, T. Sneddon and M. G. Ritchie (2016). “Inducing sold-sensitivity in the frigophilic fly Drosophila montana by RNAi.” Plos One 11(11).

Wolf, J. B. W. and H. Ellegren (2016). “Making sense of genomic islands of differentiation in light of speciation.” Nat Rev Genet 18(2): 87-100.

Subject area(s): Evolutionary Biology, Genetics

Keywords: Adaptation, genomics, speciation, CRSPR

Behavioural and Evolutionary Ecology of Insects

Supervisor: Dr David Shuker

Research area(s): Behavioural and Evolutionary Ecology of Insects

Research description: We study the behavioural ecology of insect reproduction. Our current research focuses on sexual behaviour in five species of seed bug (Family Lygaeidae). In particular, we are interested in instances of when “good mating systems go bad”, including heterospecific mating encounters (or “reproductive interference”) and failed copulations (“mating failure”). Both heterospecific matings and mating failure should be strongly disfavoured by natural and sexual selection, and yet both are more common that we have realised. Your project will explore one or both of these phenomena in our bugs, with a mix of behavioural and ecological experiments, grounded in mating systems theory.

Relevant References:

(1) Burdfield-Steel, E.R. & Shuker, D.M. (2011) Reproductive interference. Current Biology, 21: R450-451.

(2) Burdfield-Steel, E.R. & Shuker, D.M. (2014) The evolutionary ecology of the Lygaeidae. Ecology & Evolution, 4: 2278-2301.

(3) Greenway, E.V., Dougherty, L.R. & Shuker, D.M. (2015) Mating failure. Current Biology, 25: R534-R536.

(4) Greenway, E.V. & Shuker, D.M. (2015) The repeatability of mating failure in a polyandrous insect. Journal of Evolutionary Biology, 28: 1578-1582.

(5) Shuker, D.M., Currie, N., Hoole, T. & Burdfield-Steel, E.R. (2015) The extent and costs of reproductive interference among four species of true bug. Population Ecology, 57: 321-331.

(6) Shuker, D.M. & Simmons, L.W. (eds) (2014) The Evolution of Insect Mating Systems, Oxford University Press.

Subject area(s): Animal Behaviour, Behavioural Ecology

Keywords: Ecology, Evolution, Sexual Selection, Sexual Conflict

Pesticides and the costs to beneficial insects

Supervisor: Dr David Shuker

Research area(s): Pesticides and the costs to beneficial insects

Research description: Pesticides have an important role to play in helping us feed human populations. However, pesticides also bring negative effects, in terms of both human health and the health of the ecosystems around us. It is becoming increasingly clear that pesticides disrupt non-target species, often in ways that are more subtle than just killing them, but that still bring negative ecological consequences. We study the sub-lethal effects of controversial neonicotinoid pesticides on an important class of beneficial insects, the parasitic wasps. Your project will explore how neonicotinoids disrupt important life-history and behavioural decisions, such as sex allocation and mating.

Relevant References:

(1) Cook, N., Green, J., Shuker, D.M. & Whitehorn, P.R. (2016) Exposure to the neonicotinoid imidacloprid disrupts sex allocation cue use during superparasitism in the parasitoid wasp Nasonia vitripennis. Ecological Entomology, 41: 693-697.

(2) Ellis, C., Park, K., Whitehorn, P.R., David, A. & Goulson, D. (2017) The neonicotinoid insecticide thiacloprid impacts upon bumblebee colony development under field conditions. Environmental Science and Technology, 51: 1727-1732.

(3) Whitehorn, P.R., Cook, N., Blackburn, C.V., Gill, S.M., Green, J. & Shuker, D.M. (2015) Sex allocation theory reveals a hidden cost of neonicotinoid exposure in a parasitoid wasp. Proceedings of the Royal Society, Series B, 282: 20150389.

(4) Whitehorn, P.R., O’Connor, S., Wackers, F.L. & Goulson, D. (2012) Neonicotinoid pesticide reduces bumble bee colony growth and queen production. Science, 336: 351-352.

Subject area(s): Behavioural Ecology, Biological Control

Keywords: Ecology, Neonicotinoids, Parasitic Wasps, Sex Allocation

Computational biology

Supervisor: Dr V Anne Smith

Research area(s): Computational biology

Research description: Masters projects are available in areas of machine learning applied to molecular, neural, and ecological systems. Our group concentrates on inference of network structure from observational data, but also explores optimisation, agent-based modelling, and evolutionary algorithms, in the context of analysing biological questions. An emphasis is placed on evolutionary perspectives. Projects could be ideal bridges for students with degrees either in mathematics/computer science subjects or in biology to move into the interdisciplinary area of computational biology. Please contact Dr V Anne Smith (anne.smith@st-andrews.ac.uk) to discuss your interests and particular projects which may suit. See below references for exemplars of research.

Relevant References: W Verleyen, SP Langdon, D Faratian, DJ Harrison, VA Smith. 2015. Novel Monte Carlo approach quantifies data assemblage utility and reveals power of integrating molecular and clinical information for cancer prognosis. Scientific Reports 5:15563

I Milns, CM Beale & VA Smith. 2010. Revealing ecological networks using Bayesian network inference algorithms. Ecology 91:1892-1899

C Echtermeyer, TV Smulders & VA Smith. 2010. Causal pattern recovery from neural spike train data using the Snap Shot Score. Journal of Computational Neuroscience 29:231-252

DJ White & VA Smith. 2007. Testing measures of animal social association by computer simulation. Behaviour 144:1447-1468

Subject area(s): Biological Sciences, Computer Science

Keywords: computational biology, bioinformatics, systems biology, machine learning

Experimental Evolution in Microbial Systems

Supervisor: Dr V Anne Smith

Research area(s): Experimental Evolution in Microbial Systems

Research description: How repeatable is evolution? What happens to synthetically engineered gene circuits under adaptive pressures? How do microbial communities persist? Masters projects are available in experimental evolution in microbial systems, particularly yeast. The laboratory has access to a state-of-the-art Bioscreen C machine which propagates 200 microbial cultures simultaneously. Topics addressed can range from basic features of evolution and mechanisms underlying adaptation, to exploration of robustness and persistence of biodiversity in artificial microbiomes, to impact of evolutionary considerations on design of systems for synthetic biology. Please contact Dr V Anne Smith (anne.smith@st-andrews.ac.uk) to discuss your interests and particular projects which may suit.

Relevant References:

Subject area(s): Biological Sciences, Evolution

Keywords: experimental evolution, yeast, microbiomes, synthetic biology

Changing bird populations and implications for aviation

Supervisor: Dr V Anne Smith

Co Supervisor: Dr Guy Gratton, School of Aerospace, Transport and Manufacturing, Cranfield University

Research area(s): Changing bird populations and implications for aviation

Research description:

“Bird strikes” are a danger for aircraft and detrimental to the wildlife involved: changes in bird populations or migratory behaviour due to climate change may influence the likelihood of such events, and require modification of current measures for mitigation. This project applies statistical analysis to historical data on avian populations and their interactions with aircraft, and makes inferences for the future. You will join an international team, including climate scientists and aerospace experts, looking at the impact of elements of climate change on the aviation industry. Please contact Dr V Anne Smith (anne.smith@st-andrews.ac.uk) to discuss your interests in the project.

Relevant References:

Subject area(s): Environmental Biology, Aerospace Engineering

Keywords: climate change, aviation, avian populations, statistics

Experimental Evolution in Microbial Systems

Supervisor: Dr V Anne Smith

Research area(s): Experimental Evolution in Microbial Systems

Research description: How repeatable is evolution? What happens to synthetically engineered gene circuits under adaptive pressures? How do microbial communities persist? Masters projects are available in experimental evolution in microbial systems, particularly yeast. The laboratory has access to a state-of-the-art Bioscreen C machine which propagates 200 microbial cultures simultaneously. Topics addressed can range from basic features of evolution and mechanisms underlying adaptation, to exploration of robustness and persistence of biodiversity in artificial microbiomes, to impact of evolutionary considerations on design of systems for synthetic biology. Please contact Dr V Anne Smith (anne.smith@st-andrews.ac.uk) to discuss your interests and particular projects which may suit.

Relevant References:

Subject area(s): Biological Sciences, Evolution

Keywords: experimental evolution, yeast, microbiomes, synthetic biology

Computational neuroscience: live imaging data

Supervisor: Dr V Anne Smith

Co Supervisor: Dr Stefan Pulver, School of Psychology and Neuroscience, University of St Andrews

Research area(s): Computational neuroscience: live imaging data

Research description: Live imaging of neural activity provides a wealth of data on neural activity in living animals; however, current computational analyses lag behind technological development. Masters projects are available in collaboration between a computational biologist (Smith) and an experimental neuroscientist (Pulver), developing and applying computational methods for ‘mining’ of live imaging datasets. Projects can address various aspects of analysis, from automatic image processing to answering biological questions by inferring neural information flow. Students can work entirely computationally, or have the opportunity to gain skills in experimental neuroscience. Please contact Dr V Anne Smith (anne.smith@st-andrews.ac.uk) to discuss your interests and potential projects.

Relevant References:

Pulver SR, Bayley TG,, Taylor AL, Berni J, Bate M, Hedwig BJ. 2015. Imaging fictive locomotor patterns in larval Drosophila J. Neurophysiol. 114:2564-77

Lemon WC, Pulver SR, Höckendorf B, McDole K, Branson K, Freeman J, Keller PJ. 2015. Whole-central nervous system functional imaging in larval Drosophila. Nat. Commun. 11:7924

Echtermeyer C, Smulders TV, Smith VA. 2010. Causal pattern recovery from neural spike train data using the Snap Shot Score. Journal of Computational Neuroscience 29:231-252

Smith VA, Yu J, Smulders TV, Hartemink AJ, Jarvis ED. 2006. Computational inference of neural information flow networks. PLoS Computational Biology 2:e161.

Subject area(s): Neuroscience, Computer Science

Keywords: machine learning, live imaging, image processing, neuroinformatics

Agent-based modelling for animal behaviour

Supervisor: Dr V Anne Smith

Co Supervisor: Dr Lauren Guillette

Research area(s): Agent-based modelling for animal behaviour

Research description: Masters projects are available applying agent-based modelling to elucidate rules underlying animal cognition and behaviour. You will be jointly supervised by a computational biologist (Smith) with a background in animal behaviour, agent-based modelling and evolutionary programming, and an experimental biologist/psychologist (Guillette) whose current research concentrates on social learning during nest-building and foraging in birds, with interests in cognition and neurological bases of learning. Depending on student interest, projects may include working with extant data to build and evolve models, or incorporate significant amounts of hands-on behaviour experiments. Please contact Dr V Anne Smith (anne.smith@st-andrews.ac.uk) to discuss projects which may suit.

Relevant References:

DJ White & VA Smith. 2007. Testing measures of animal social association by computer simulation. Behaviour 144:1447-1468.

VA Smith. 2008. Evolving an agent-based model to probe behavioral rules in flocks of cowbirds. Proceedings of the Eleventh International Conference on Artificial Life MIT Press, Cambridge, MA, pp 561-568.

Guillette, L.M., Scott, A.C.Y. & Healy, S.D. 2016 Social learning in nest-building birds: the role of familiarity. Proceedings of the Royal Society B: Biological Sciences, 283, 20152685. http://dx.doi.org/10.1098/rspb.2015.2685.

Guillette, L.M. & Healy, S.D. 2017. The roles of vocal and visual interactions in social learning zebra finches: A video playback experiment. Behavioural Processes, 139, 43-49. doi: http://dx.doi.org/10.1016/j.beproc.2016.12.009.

Subject area(s): Behavioural Biology, Computer Science

Keywords: complex systems, social learning, animal behaviour, animal cognition

Evolutionary biology, developmental biology, cell biology, evo-devo, regeneration biology, genomics

Supervisor: Dr Ildiko Somorjai

Research area(s): Evolutionary biology, developmental biology, cell biology, evo-devo, regeneration biology, genomics

Research description: Have you ever wondered why some animals regenerate well, and humans do not? Are you interested in how new genes are born, and what generates diversity in animal body forms? The Somorjai lab addresses these problems from evolutionary, developmental and cell biological perspectives. We predominantly use the marine invertebrate chordate “amphioxus” due to its genetic and anatomical similarly to simple vertebrates. We also work on flatworms, which have amazing regenerative powers and multipotent stem cells. The project will depend on the student’s interests and background, but could include gene expression analyses, embryology, immunohistochemistry, confocal microscopy, genomics, and phylogenetic analyses. https://synergy.st-andrews.ac.uk/cord/

Relevant References:

Bertrand S, Escriva H. Evolutionary crossroads in developmental biology: amphioxus. Development. 2011 Nov;138(22):4819-30.

Somorjai IM, Somorjai RL, Garcia-Fernàndez J, Escrivà H. Vertebrate-like regeneration in the invertebrate chordate amphioxus. Proc Natl Acad Sci U S A. 2012 109(2):517-22.

Dailey, SC, Planas, RF, Espier, AR, Garcia-Fernandez, J & Somorjai, IML Asymmetric distribution of pl10 and bruno2, new members of a conserved core of early germline determinants in cephalochordates. Frontiers in Ecology and Evolution. 2016. 3, 156.

Subject area(s): Evolutionary Biology, Developmental Biology

Keywords: Regeneration, Development, Evo-devo, Amphioxus

DNA repair in archaea and humans

Supervisor: Professor Malcolm White and Dr Carlos Penedo

Research area(s): DNA repair in archaea and humans

Research description: DNA repair is essential for all forms of life. There are many overlapping DNA repair pathways that contribute towards the maintenance of genetic integrity. This project will be focussed on improving our understanding of the Nucleotide Excision Repair (NER) pathway in humans. It will involve training in biochemistry and molecular biology, with an emphasis on the use of cutting-edge technigues to study DNA:protein interactions.

Relevant References:

Subject area(s): Molecular Biology, Biophysics

Keywords: DNA Repair, cancer, helicase, nuclease

Entry requirements and selection process

An undergraduate Honours degree at 2:1 level or better in biological or environmental sciences. Students from backgrounds such as mathematics may be accepted under exceptional circumstances.

If you studied for your first degree outside of the UK, please see the international entry requirements

For non-native English speakers, please see the English language requirements

Applicants will be short-listed by the project supervisor, and subject to interview by the project supervisor and an additional member of the Biology Postgraduate Committee.

Fees

For details of postgraduate tuition fees relevant to our research degrees including the MSc(Res), please visit:

http://www.st-andrews.ac.uk/study/pg/fees-and-funding/research-fees/

Progression and assessment

Students in the MSc(Res) will be assigned an Internal Examiner (IE) and PG Tutor by the School. There will be a progress review meeting at three months to monitor and evaluate student progression, convened by the IE, with the student and Tutor in attendance. This meeting will be guided by a brief supervisor report and will be based on oral examination with no requirement for a written submission by the student.

The degree requires submission and examination of a dissertation at the end of the one-year program. As per 2016-2017 Senate Regulations (page 9), this thesis will consist of up to 30,000 words. The thesis will be evaluated by the IE and an External Examiner appointed at time of submission. Evaluation will be based on the written submission; there is no requirement for a viva.

Skills Training

In addition to the project-specific training that you will receive during your degree, Msc(Res) students will also have access to a wide range of training in transferable skills through the award-winning University of St Andrews GradSkills program, run by our Professional Development Unit CAPOD.

Specific post-graduate programs run within the School of Biology may also offer additional training, for instance in statistical, bioinformatics or molecular techniques.

Application

Students may apply for placement in advertised projects or contact potential supervisors directly. We strongly recommend that potential candidates make contact with a potential supervisor before applying.  See links on this page.

Biology has two dates for admission to this degree: September and January each year.

If you have decided that you would like to make a formal application to study for an MSc(Res) at St Andrews, please complete an application using the online system.

Note: If you are self-funded and interested in working with a supervisor who does not currently have a project listed, please contact that person directly: supervisors’ email addresses may be found using the links on this page.