Rachel is Head of the Statistics Group in the School of Mathematics, Statistics and Actuarial Science. Much of Rachel's research to date has been motivated by a desire to reliably inform conservation strategies and she has published a number of innovative statistical solutions to overcome issues caused by complex data sets. Her most substantial contributions include developing novel approaches for efficient model selection and new diagnostic goodness-of-fit tools. For this work she was awarded the Royal Statistical Society 2020 Guy Medal in Bronze. In recognition of her academic contributions Rachel was appointed as a Fellow of the Learned Society of Wales in 2021.
Rachel completed a research fellowship in 2016, funded by the Natural Environment Research Council. The emphasis of this project was on developing individual level statistical models that make it possible to understand the wealth of detailed data being collected on a huge range of animal populations.
More recently, in 2018, Rachel was awarded an EPSRC New Investigator Research Award for a project Modelling removal and re-introduction data for improved conservation. This project will develop new statistical approaches to make the most of the information available from removal and re-introduction data.
The types of data which can be collected on animal populations are wide-ranging – for example, simple population counts, presence/absence data, presence only data, batch-marked data, and capture-recapture data. The difficulty and survey intensity required to collect these data will also depend on the associated skill set of data collectors as well as the resources available to the team or individual responsible for designing the scheme.
As well as proposing optimal study design for removal count data, the project will address how to optimise study design if multiple types of data are collected simultaneously on a population. Further, we will explore how populations could be monitored with multiple types of data collection to better determine how successfully the population has established itself following some form of intervention (such as trans-location of individuals or re-introducing a previously locally extinct species back into an area).
Three project partners will collaborate on the project: Durrell Wildlife Conservation Trust, Mauritian Wildlife Foundation and Amphibian and Reptile Conservation Trust.
These collaborations allow access to historical case studies to test new modelling approaches, and then allows us to implement suggested adaptations (in study design, types of data collected and its analysis) to evaluate their performance in a practical setting. The outcomes will immediately impact their future studies and through the partnerships we will enhance our ability to influence policy.
Rachel is an applied statistician working closely with ecologists as well as statisticians, developing new statistical methodology for the modelling of ecological data. She has worked extensively with capture-recapture data (and co-authored a book Analysis of capture-recapture data) and is particularly interested in the potential of multi-state models. Her research has included the development of goodness-of-fit assessment and model selection strategies for complex data sets. Modelling population dynamics, integrated population modelling and survey design are also current areas of interest. More recently her research has expanded into the related field of multiple systems estimation and is interested in developing robust statistical models for social science applications.
Current Postdoctoral Research Associate: Dr Fay Frost - Modelling removal and re-introduction data for improved conservation.
Former Postdoctoral Research Associate: Dr Oscar Rodriguez de Rivera Ortega - Modelling removal and re-introduction data for improved conservation.
Current PhD students:
Recently completed projects that Rachel has supervised:
Rachel has advised many PhD students from the Durrell Institute of Conservation and Ecology, University of Kent.