Research themes
Global biodiversity change and conservation
Work in the global biodiversity change and conservation theme uses large datasets to answer applied questions at large - often global - scales. Currently, we have three main projects within this theme: (i) trying to understand, and predict, the impacts of invasive species on ecological communities, (ii) using tools from mathematics to transform our ability to monitor the health of communities, and (iii) using large datasets of population trends to understand the patterns and processes of global biodiversity change. We are also involved in side projects to assess how well evidence of the effectiveness of conservation interventions is conserved across space, and to explore how planetary boundaries interact to affect sustainable food production. Other past side projects in this theme include trying to understand the impacts of protected areas on species populations worldwide; assessing the global impacts of land-use change on biodiversity; exploring the evidence for worldwide insect declines; and assessing the costs and benefits of high-yield farming.
Applied remote sensing
Work in this theme uses remote sensing systems – such as satellites or LIDAR sensors – to deliver applied insights. Currently, our main project in this area is using novel machine learning methods and satellite data to forecast the productivity of the Amazon rainforest. Other areas of interest include forecasting deforestation and spatial prioritisation of nature-based climate change solutions.
Technology for conservation
Technology has enabled a wide range of automated and relatively inexpensive sensors to be deployed. These include camera traps, microphones for bioacoustics, environmental data loggers, phenology cameras and GPS tags. We’re interested in using these sensors to solve conservation problems. Current work in this theme includes using deep learning to automate the detection of rare species in camera trap images, and combining camera traps and bioacoustics to automatically monitor lion populations in Africa.