Movement through space and time; realistic movement for species abundance methods

About the project

About the Project Evidence-based conservation and ecology are reliant on wildlife surveys. As a result, there exists a range of methods that have been developed specifically with the aim of estimating animal abundance and animal distribution. Traditionally data have been collected by humans and are often modelled as a ‘snapshot’ of the system at a particular moment in time. However, we often have more information available to us such as a precise time of observation. This is particularly true when the data are instead collected using digital devices such as camera traps or acoustic arrays that are generally recording and collecting data continuously. The combination of spatial and temporal information lets us consider the potential for incorporating realistic animal movement by considering the spatio-temporal clustering of observations. This PhD would explore some of these ideas such as: movement models for spatial capture-recapture data; temporal clustering to assist identification in spatial count models; self-exciting processes to model observation hotspots; or integrating movement and the hazard function in distance sampling and other observation processes. This PhD is likely to appeal to candidates with a keen interest in statistical simulation and computation, an interest in stochastic differential equations would likely also be beneficial.

Research areas