Changepoints for a Changing Planet: A new UKRI grant success for CEEDS

Members of CEEDS have been awarded a £240,000 feasibility study from UKRI under the SPF Constructing a Digital Environment Programme to look at enhancing virtual labs with data science methods, particularly changepoint methods, to look for signs of significant or catastrophic change in ecosystems.

Virtual labs are emerging as a key component in the construction of future digital environments, with significant emphasis on this concept within CEEDS. Virtual labs abstract over the complexities of the underlying distributed networks of sensors and associated computational infrastructure and offer a transdisciplinary collaboration space hosted in the cloud that allows different stakeholders to access a range of data, analytical methods and assessment tools, and to execute these analyses using the elastic capacity of a cloud. In the environmental science community, most existing virtual labs focus on the problem of integrating often complex and heterogeneous data. In this project, the team seeks to significantly advance the state-of-the-art by enhancing virtual labs with sophisticated methodological capability, embracing state-of-the-art data science techniques to assist in the societally-relevant interpretation of these data.

As mentioned above, the team will focus on a particular family of data science techniques, that is, changepoint detection methods, designed to identify fundamental changes and anomalous behaviour in data, typically within time-series, but also applicable across space and time and to complex, multivariate problems. This feasibility study will therefore bring together a cross-disciplinary team working on virtual labs, changepoint methods and evidence for impacts of global environmental change on ecosystem structure and function. The project builds on the rich, complex, multi-faceted data available from the Environmental Change Network (ECN), which offers detailed multivariate 25-year long data sets for a range of ecosystems in the UK.

The broader vision is to understand the role of data science, including, but not limited to changepoint detection, in the construction of environmental early warning alert systems capable of operating at a variety of scales, from catchments to global planetary level systems.

The investigator team on this project is: Gordon Blair, Idris Eckley and Rebecca Killick from Lancaster University and John Watkins, Don Monteith and Peter Henrys (UK CEH), and we are joined by Will Simm, Aaron Lowther, Lindsay Banin, Susannah Rennie, Michael Tso and Mike Hollaway in delivering this exciting research.