My pronouns are she/her
I am a PhD student based at the University of Oxford and the Zoological Society of London, with a broad interest in understanding and predicting global patterns of biodiversity loss. My research spans a range of approaches, from highly mechanistic methods (e.g. demographic and energetic modelling) to global-scale correlative models, drawing on a range of data including species traits, large-scale remote sensing datasets, and long-term abundance trends. Both within and outside of my PhD, I am particularly interested in exploring how modern data tools, such as machine learning, alongside the emerging wealth of big data, can support evidence-centred conservation science. Prior to starting my PhD at Oxford, I completed my undergraduate at the University of Cambridge in Natural Sciences (2023).
My PhD aims to advance trait-based forecasting models to understand and predict biodiversity change under complex, dynamic threat conditions, with the work broadly divided across three research themes. The first explores how traits predict changes in the rate of population decline as threat intensity increases (e.g. progressive habitat loss), aiming to identify key thresholds of intensity across threats and taxa, and better inform global estimates of biodiversity decline under forecast conditions. The second aims to support mechanistically informed conservation actions by exploring the relationships between threats and population vital rates, including the LLM-assisted compilation of a comprehensive database for demographic impacts of anthropogenic threats across vertebrate species. Finally, the third research theme extends population-level trait models to the ecosystem scale, developing a trait-based framework to predict how functional diversity and associated measures of ecosystem resilience shift under environmental change.
