Trait-based approaches for predicting mosquito distributions under environmental change

Mosquito-borne diseases cause substantial mortality and morbidity worldwide and are changing in distribution and impact due to globalisation and environmental change. Invasive mosquitoes have become widely established across Europe this century, with subsequent outbreaks of dengue and chikungunya virus. Species distribution models (SDM) are widely used to inform policy responses to these threats, for example to understand how invasive mosquito vectors might spread following arrival and where vectors might overlap with key hosts to permit transmission.

However, insect vector distributions are most commonly modelled species-by-species, even though new statistical methods for analysing communities are available. For other insect taxa, a mechanistic understanding of likely environmental change impacts has been gained by modelling and comparing distributional responses simultaneously across multiple species with different ecological traits. The availability of new continental-scale distribution data, of environmental predictors appropriate to mosquito habitats and statistical methods for dealing with species interactions, dispersal limitation and biased recording effort, mean we can now use similar trait-based approaches to understand and predict mosquito responses to environmental change.

The aim of this project is to investigate the role of ecological traits, invasion status, and environmental factors in constraining the distribution and seasonality of insect vectors in temperate environments. The student will develop and apply novel statistical joint distribution models for communities across Europe, combining distribution and seasonality data from VectorNet (a European data-sharing Network, funded by ECDC and EFSA) with a traits database, to analyse whether species responses are linked to broad ecological traits like breeding site and host preferences and whether these responses vary with scale and invasion status.

The student will then generate virtual species distributions with similar traits and invasion status and range of responses to environmental drivers to those of European mosquitoes, sampled with biased and unbiased recording effort. The resulting distributions will be analysed using alternative statistical single-species and community modelling algorithms to understand how distribution modelling for insect vectors might best account for dispersal limitation and biased recording effort. Finally the student will analyse the impact of under-recording mosquito distributions on the utility of such models for policy and in predictions of where mosquito-borne transmission will occur.

The successful candidate will have a strong background in quantitative ecology, biology, statistics or mathematics. A demonstrated interest in population ecology, distribution modelling and/or vector-borne disease ecology is desirable.

The student will receive training in a number of quantitative skills and ecological skills including: high-level scientific computing on cluster environments; simulation modelling (virtual species); statistical model fitting; handling large datasets; mosquito biology; disease vector ecology.

An exciting aspect of this project is the opportunity to network with researchers, public health specialists and policy makers within platforms such as VectorNet (https://ecdc.europa.eu/en/about-us/partnerships-and-networks/disease-and-laboratory-networks/vector-net) and engage with the ZOON Species Distribution Modelling initiative (https://zoonproject.wordpress.com/). Through the industrial supervisors, the student will gain experience of how ecological model outputs inform policy and can be tailored to the needs of stakeholders, contrasting approaches of Small and Medium Enterprises/Consultancies with those of academic research institutions.

Logistics & Application:

The project will be primarily based at the Centre for Ecology & Hydrology (CEH) in Wallingford. It will be jointly supervised by Drs Beth Purse and Steven White at CEH, Dr Amanda Callaghan (University of Reading), Dr William Wint (Oxford University + ERGO consultancy), Francis Schaffner (University of Zurich + Francis Schaffner consultancy).

Applicants for a studentship must have obtained, or be about to obtain, a 2.1 degree or higher. If you have a 2.2 degree, but have also obtained a masters qualification, you are also eligible.

Details of how to apply are provided here: https://www.imperial.ac.uk/qmee-cdt/how-to-apply/