Abstract

Abstract: In recent years all parts of society – individuals, companies, governments – have become keenly aware of the need to conserve the environmental life support systems on which we all depend. When it is fully developed, ecology will enable this conservation, by providing reliable, accurate models to predict how alternative human actions would translate into outcomes at the ecosystem level, e.g. changes in biodiversity, carbon storage and water cycling. But ecology is a young science, unaccustomed – and some would say, not yet ready – to build these predictive models. In this talk I will present some examples of the computational ecology being carried out in our group. At least one project will be drawn from each of our research foci: ecological networks; next-generation Earth System science; biodiversity and biogeography; and behavioural dynamics. What these projects share is a methodology of combing pre-existing and new concepts and models with large amounts of data, and an aim of carrying out science that is both relevant to society, and packaged in way that can be understood and used by as wide a variety of people as possible (whether fellow scientists, policy makers, or individuals).

Biography: Drew Purves studied ecology at Cambridge University, did a PhD in ecological modelling at the University of York (UK), and spent nearly 6 years as a postdoc in the EEB Department at Princeton University, before joining MSR Cambridge in 2007. Purves’ work, which focuses on the dynamics of populations and communities of plants, especially forests, has been published in a number of top-tier scientific journals including Science, PNAS , and Proc Roy Soc B. Dr Purves co-supervises several PhD students at European universities, and is an affiliate lecturer at Cambridge University.