Biodiversity is often thought of as a multifaceted concept comprising ‘genes, species and ecosystems’ but, in addition to these, species’ traits are what mediate the interaction between genes and the environment. Functional differences between species are reflected in adaptations to particular environments that can help distinguish different biomes and ecosystems. The diversity of traits is contained in species’ taxonomic descriptions but functional diversity has historically received less attention than species-based metrics of diversity such as richness and endemism, largely due to a lack of readily available trait information. This situation is now changing rapidly with new sources of structured trait data, and pioneering work at the NHM allows taxonomic literature to be automatically mined for trait values. This allows functional diversity values to be determined for a range of ecosystems, and different classifications of the way we view the world’s vegetation to be tested. Indices of change in ecosystem extent, function and complexity are increasingly being derived from remotely sensed data, and there is a need for independent validation of such approaches as applied to international conservation policy objectives. This project would do exactly this, utilising existing trait and distribution data for plants around the world, compiling biodiversity indices measuring different ecosystem-based Essential Biodiversity Variables, and comparing the use of these to monitor the state of plant diversity and its resulting provision of ecosystem services with remote sensing products. A successful student will learn techniques of spatial analysis, biodiversity measurement and its monitoring for a topic with direct policy implementation.