Dr. Simon Rolph

Simon is interested in how data science methods, including integrated species distribution modelling, can be used in the analysis and collection of biodiversity data to improve the evidence base upon which environmental decisions are made. He has a particular interest in approaches that can be used to support biological recorders (and citizen scientists more broadly) to produce more informative data. Simon works to achieve this through the development and evaluation of model-based adaptive sampling approaches, using existing data and models, including integrated species distribution modelling, to determine the highest priority places to record new data.

Furthermore, Simon also explores the potential of creating digital twins of ecological systems. These digital twins offer a powerful means to simulate and analyze the behavior of ecosystems, allowing for more informed decision-making and a deeper understanding of the impacts of environmental changes. To facilitate approaches such as adaptive sampling and the development of digital twins, Simon believes that it is essential to communicate the data needs in order to prompt changes in citizen science behavior. Therefore, his work also focuses on how digital engagements can be used to 'nudge' behaviours through technology such as apps and targeted messaging.