Computational ecology · Bioacoustics · Applied research
Understanding ecological change at scale
I use macroecological modelling, machine learning and acoustic sensing to understand forests, biodiversity and biological stress — and to turn research into practical tools.
Macroecology
Forecasting future forest systems.
My macroecological research examines how North American forest communities, functional traits and ecosystem properties may change under future climates.
Future forest communities
Identifying where present-day forest groups may persist, switch or give way to no-analogue communities.
Explore research →Trait–environment compatibility
Testing which ecological strategies and trait combinations remain compatible with future conditions.
Explore research →Traits and ecosystem services
Modelling how climate, forest structure and functional composition shape carbon, biodiversity and other functions.
Explore research →Forest viewer
Explore projected community compatibility and no-analogue forests across North America.
Launch viewer →Bioacoustics
Using sound to reveal biological states that are difficult to observe directly.
My bioacoustics work spans plants, elephants and gibbons, alongside software for validating and managing the outputs of automated acoustic classifiers.
Ultrasonic drought detection
Testing whether acoustic emissions from grapevine xylem can provide an automated early warning of hydraulic stress.
Explore research →Forest elephant vocalisations
Using transfer learning to infer demographic and behavioural information from rare-species calls.
Explore research →Gibbon monitoring
Turning classifier detections into structured, validated evidence across large acoustic datasets.
Explore research →PAMalytics
An open-source platform for reviewing, validating and analysing passive acoustic monitoring detections.
Explore software →Background
Ecological researcher and AI-business founder.
Before focusing on ecological research, I spent fifteen years founding, scaling and exiting an AI analytics business. That experience now informs how I define research problems, build computational methods and translate technical outputs into usable evidence.