A new generation of Bayesian species distribution models will provide improved predictions of species occurrence in the landscape.
Identifying how species are distributed over the landscape, interact and self-organise into foodwebs are central goals in Ecology.
This project will provide innovative new Bayesian modelling tools to improve our understanding of species distributions and their foodweb networks.
It will develop a general framework for extending species distribution models to deal with multiple species, incorporating both their interactions as well as errors in detection.
Secondly, we will develop a robust Bayesian methodology for partitioning complex foodweb networks into ecologically relevant compartments as there are currently no reliable methods to achieve this.
Both projects are of relevance to conservation policy and management of threatened species.