I am interested in population biology (population dynamics, community ecology, evolutionary ecology). Research in the group focuses on a wide range of questions such as the population and evolutionary dynamics of life history strategies (e.g. the evolution of longevity), the role of spatial structure on shared enemy and competing enemy interactions, the effects of enrichment on the diversity of ecological communities, the interplay between noise and dynamics in multispecies interactions and the evolution of resistance to microbes.
Many of these projects involve the development of theoretical models in conjunction with experiments or observations in the field or laboratory. To this end, we aim to test different ecological and evolutionary ecology theories by fitting relevant mathematical models to appropriate ecological experimental (or observational) data. Further details of my research interests can be found here.
I have a strong interest in science policy. From 2007 - 2016 I was a member of DEFRA's Advisory Committee on Releases to the Environment (ACRE) and more recently involved in science policy work with the European Food Safety Authority (EFSA). As part of science policy work with WHO (TDR) and FNIH, I was involved in producing a report on the efficacy, biosafety and regulations of GM Mosquitoes. In June 2014, this report, as a Guidance Framwork for testing GM Mosquitoes, was published. Through July to December 2015, I served as science advisor to the House of Lords Science and Technology committee - a report was published on GM insects.
I am involved with the academic management teams on several Doctoral Training Programmes and more information on these is available here.
Publications
Sleep and intrusive memories immediately after a traumatic event in emergency department patients.
2020
|
Conference paper
|
Sleep
STUDY OBJECTIVES: Intrusive memories of psychological trauma are a core clinical feature of posttraumatic stress disorder (PTSD), and in the early period post-trauma may be a potential target for early intervention. Disrupted sleep in the weeks post-trauma is associated with later PTSD. The impact of sleep and intrusive memories immediately post-trauma, and their relation to later PTSD, is unknown. This study assessed the relationship between sleep duration on the first night following a real-life traumatic event and intrusive memories in the subsequent week, and how these might relate to PTSD symptoms at 2 months. METHODS: Patients (n = 87) recruited in the emergency department completed a sleep and intrusive memory diary from the day of their trauma and for the subsequent week, with optional actigraphy. PTSD, anxiety, and depression symptoms were assessed at 1 week and 2 months. RESULTS: A U-shaped relationship was observed between sleep duration on the first night and intrusive memories over the subsequent week: sleeping "too little" or "too much" was associated with more intrusive memories. Individuals who met Clinician-Administered PTSD Scale (CAPS) criteria for PTSD at 2 months had three times more intrusive memories in the first week immediately post-trauma than those who did not (M = 28.20 vs 9.96). Post hoc analysis showed that the absence of intrusive memories in the first week post-trauma was only observed in those who did not meet CAPS criteria for PTSD at 2 months. CONCLUSIONS: Monitoring intrusive memories and sleep in the first week post-trauma, using a simple diary, may help identify individuals more vulnerable to later psychopathology.
Visualizing connectivity of ecological and evolutionary concepts – an exploration of research on plant species rarity
2020
|
Journal article
|
Ecology and Evolution
Understanding the ecological and evolutionary factors that influence species rarity has important theoretical and applied implications, yet the reasons why some species are rare while others are common remain unresolved. As a novel exploration of scientific knowledge, we used network analysis conceptually to visualize the foci of a comprehensive base of >800 studies on plant species rarity within the context of ecology and evolution. In doing so, we highlight existing research strengths that could substantiate novel syntheses and gaps that could inspire new research. Our results reveal strong integrated foci on population dynamics with other ecological concepts. In contrast, despite the potential for ecological and evolutionary processes to interact, few studies explored the interplay of environmental factors and microevolutionary patterns. The cellular and molecular biology, physiology, and plasticity of rare plant species within both ecological and evolutionary contexts similarly provide avenues for impactful future investigations.
Evolution and maintenance of microbe-mediated protection under occasional pathogen infection
2020
|
Journal article
|
Ecology and Evolution
Every host is colonized by a variety of microbes, some of which can protect their hosts from pathogen infection. However, pathogen presence naturally varies over time in nature, such as in the case of seasonal epidemics. We experimentally coevolved populations of Caenorhabditis elegans worm hosts with bacteria possessing protective traits (Enterococcus faecalis), in treatments varying the infection frequency with pathogenic Staphylococcus aureus every host generation, alternating host generations, every fifth host generation or never. We additionally investigated the effect of initial pathogen presence at the formation of the defensive symbiosis. Our results show that enhanced microbe-mediated protection evolved during host-protective microbe coevolution when faced with rare infections by a pathogen. Initial pathogen presence had no effect on the evolutionary outcome of microbe-mediated protection. We also found that protection was only effective at preventing mortality during the time of pathogen infection. Overall, our results suggest that resident microbes can be a form of transgenerational immunity against rare pathogen infection.
How and when to end the COVID-19 lockdown: an optimisation approach
2020
|
Journal article
|
Frontiers in Public Health
Countries around the world are in a state of lockdown to help limit the spread of SARS-CoV-2. However, as the number of new daily confirmed cases begins to decrease, governments must decide how to release their populations from quarantine as efficiently as possible without overwhelming their health services. We applied an optimal control framework to an adapted Susceptible-Exposure-Infection-Recovery (SEIR) model framework to investigate the efficacy of two potential lockdown release strategies, focusing on the UK population as a test case. To limit recurrent spread, we find that ending quarantine for the entire population simultaneously is a high-risk strategy, and that a gradual re-integration approach would be more reliable. Furthermore, to increase the number of people that can be first released, lockdown should not be ended until the number of new daily confirmed cases reaches a sufficiently low threshold.
We model a gradual release strategy by allowing different fractions of those in lockdown to re-enter the working non-quarantined population. Mathematical optimisation methods, combined with our adapted SEIR model, determine how to maximise those working while preventing the health service from being overwhelmed. The optimal strategy is broadly found to be to release approximately half the population two-to-four weeks from the end of an initial infection peak, then wait another three-to-four months to allow for a second peak before releasing everyone else. We also modelled an “on-off” strategy, of releasing everyone, but re-establishing lockdown if infections become too high. We conclude that the worst-case scenario of a gradual release is more manageable than the worst-case scenario of an on-off strategy, and caution against lockdown-release strategies based on a threshold-dependent on-off mechanism.
The two quantities most critical in determining the optimal solution are transmission rate and the recovery rate, where the latter is defined as the fraction of infected people in any given day that then become classed as recovered. We suggest that the accurate identification of these values is of particular importance to the ongoing monitoring of the pandemic.
The value of existing regulatory frameworks for the environmental risk assessment of agricultural pest control using gene drives
2020
|
Journal article
|
Environmental Science and Policy
The application of (synthetic) gene drives is a powerful tool to control populations of insects that are agricultural pests, vectors of diseases, or a threat to biodiversity potentially leading to the local or global eradication of a species. The potential use of gene drive organisms has triggered a heated discussion regarding their environmental impacts and regulatory oversight. However, experience exists in assessing the environmental impacts of a number of established agricultural pest control methods that require the release of living organisms, that provide high levels of area-wide control and that might be irreversible. This includes classical biological control, the sterile insect technique, the incompatible insect technique that is based on the cytoplasmic incompatibility caused by Wolbachia endosymbionts, and genetically modified insects containing self-limiting traits. The different technologies are described, the regulatory practice and experience is summarized and pathways through which these control technologies could harm valued ecosystem services are presented. With a focus on the application of gene drives in agriculture, using the invasive Drosophila suzukii (Diptera: Drosophilidae) as a case study we then discuss to what extent the existing frameworks could assist the risk assessment of insects carrying gene drives. We suggest that drawing on existing practices, experiences and legislative frameworks will provide a pragmatic and proportionate approach to evaluate the environmental risks of novel solutions based on gene drive technologies.
Assessing the potential for indirect interactions between tropical tree species via shared insect seed predatorsPalabras clave
Optimal control approaches for combining medicines and mosquito control in tackling dengue
2020
|
Journal article
|
Royal Society Open Science
Dengue is a debilitating and devastating viral infection spread by mosquito vectors, and over half the world’s population currently live at risk of dengue (and other flavivirus) infections. Here we use an integrated epidemiological and vector ecology framework to predict optimal approaches for tackling dengue. Our aim is to investigate how vector control and/or vaccination strategies can be best combined and implemented for dengue disease control on small networks, and whether these optimal strategies differ under different circumstances. We show that a combination of vaccination programmes and the release of genetically modified self-limiting mosquitoes (comparable to sterile insect approaches) is always considered the most beneficial strategy for reducing the number of infected individuals, due to both methods having differing impacts on the underlying disease dynamics. Additionally, depending on the impact of human movement on the disease dynamics, the optimal way to combat the spread of dengue is to focus prevention efforts on large population centres. Using mathematical frameworks, such as optimal control, are essential in developing predictive management and mitigation strategies for dengue disease control.
Identifying important interaction modifications in ecological systems
