Next-generation biodiversity indicators

Project overview

Ecosystems consist of plants and other species that interact in different ways, and these interactions between plants and their environment and with other species are mediated by their functional traits (key adaptations concerned with growth and reproduction rates).

Traits help to determine species’ range sizes, niche breadth and ecological dominance, their susceptibility to extinction, invasiveness potential, and also show adaptations to different vectors of pollination and dispersal, along with their environment.

We have developed and are continuing to improve a range of AI tools that can extract and predict the functional traits of potentially any plant species, taken from their taxonomic descriptions, from digital images of specimens of the species or otherwise inferred from those of their close relatives (known as phylogenetic imputation) and have a large dataset of traits covering tens of thousands of plant species.

We are using this information to measure spatial variation in plant functional diversity and phylogenetic diversity relative to the number of species found in a given area.

This PhD project will make use of these data or adapt such tools to develop and assess additional biodiversity indicators for plants in order to produce a suite of comparable indicators covering the different facets of biodiversity captured by the Essential Biodiversity Variables.

In particular, different metrics measuring aspects of habitat structure, habitat function and community composition could be derived from a full spectrum of plant trait data. The project will focus on correlations between plant species traits and the 3 axes of rarity, using published studies as validated data points, in order to try and predict such associations in unstudied species and thus their susceptibility to extinction or potential for invasiveness, in order to gauge the likelihood of compositional turnover in an established plant community.

Species Distribution Modelling techniques also offer a different avenue for determining the probability of species’ geographical co-occurrence within similar ecological conditions. The study will focus on a specific ecosystem, the choice of which is open but for which data already exists for several regions in Africa, and could be extended to compare multiple ecosystems and other organismal groups beyond plants.

Project Specific Training

All project-specific training can be provided through a combination of one-to-one instruction by the supervisory team or wider research group, through self-learning or via external partners where necessary.