Research in the School is organised into three major interdisciplinary centres: the Scottish Oceans Institute (SOI), Biomedical Sciences Research Complex (BSRC) and Centre for Biological Diversity (CBD). Together these centres encompass the full spectrum of research in biological sciences, spanning investigations on the properties and behaviour of individual molecules to planetary environmental dynamics.
In REF2014 Biological Sciences in
St Andrews was rated top in Scotland and second across the UK.
Biomedical Sciences Research Complex
World class innovative multi-disciplinary research focussed on the broad theme of infection and immunity
Centre for Biological Diversity
Advancing science that underpins the diversity of life
Scottish Oceans Institute
A key focus for research excellence in marine-related science
21 Feb 2017
CBD Seminar: Conflicts between biodiversity conservation and human livelihoods: an interdisciplinary approach
Seminar Room, Dyers Brae: 1:00 PM, 21 Feb 2017
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Conflicts between human livelihoods and biodiversity conservation are increasing in scale and intensity and have been shown to be damaging for both biodiversity and humans. Managing a specific natural resource often results in conflict between those stakeholders focussing on improving livelihoods and food security and those focussed on biodiversity conversation. Uncertainty, for example from climate change, decreases food security, puts further pressure on biodiversity and exacerbates conflicts. I will present first results towards developing a novel model that integrates game theory and social-ecological modelling to develop new approaches to manage conservation conflicts. The project has importance for society at large because ecosystems and their services are central to human wellbeing and unlocking these conflicts will provide great potential for a more sustainable future.
23 Feb 2017
SOI seminar: From physical seascape to top predators: an integrative approach to understand and manage dynamic ecoystems in the Southern Ocean
Bute Building, Theatre D (C42), Bute: 12:00 PM, 23 Feb 2017
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Note: SOI seminar earlier than usual time. **12-13h**
21 Mar 2017
CBD Seminar: How did the butterfly get its colours? The genetic control of colour and pattern diversity in Heliconius butterflies
Seminar Room, Dyers Brae: 1:00 PM, 21 Mar 2017
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Butterfly wing patterns are a striking example of biological diversity.The neotropical Heliconius butterflies in particular have extensive within and between species diversity in their wing colour patterns. Some of this diversity is due to variation at the gene cortex, which has repeatedly been targeted by natural selection, both to produce mimetic colour pattern resemblances within Heliconius and remarkably to shift camouflage in the peppered moth. I will also talk about ongoing work in my lab to identify genes controlling iridescent structural colour.
Seminar Room, Dyers Brae: 1:00 PM, 28 Mar 2017
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Lecture theatre D, Bute: 1:00 PM, 06 Apr 2017
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The winter North Atlantic Oscillation (NAO) is the primary mode of atmospheric variability in the North Atlantic sector. It has a profound impact on surface conditions over the North Atlantic ocean and temperature & precipitation over Europe and North America. The NAO exhibits pronounced interannual variability, particularly in the last decade, with strong positive NAO leading to mild & stormy European winters (e.g. 2011/12, 2013/14) and strong negative NAO winters giving cold & dry winters (e.g. 2009/10, 2010/11). Until recently seasonal forecasting systems have had no significant skill in predicting the winter NAO, leading many to assume that the NAO was largely a chaotic mode of atmospheric variability and inherently unpredictable. Here I will outline our recent work using the Met Office high-resolution climate models to show that the NAO is indeed predictable both one month ahead of winter and that significant skill still remains one year ahead. I will examine the drivers of predictability on these two timescales and show that the discovery of NAO predictability is at odds with the skill of the model predicting itself. This surprising result indicates that the real-world is in fact far more predictable than we previously thought and it is likely that even the latest high-resolution climate models are unable to realistically represent the physical processes and feedbacks operating in the real world, resulting in too little signal and/or too much noise. Finally, I show how these new skilful NAO predictions are beginning to be used to aid decision making in government and industry.