利兹大学招收气候科学博士
About the Project
Malaria is a climate sensitive vector-borne disease that was responsible for an estimated 619,000 deaths from 247 million malaria cases worldwide in 2021; 95% of these malaria cases were in Africa (WHO, 2022). Detailed mapping of current malaria transmission is vital for distribution of health resources and targeting of control measures. Moreover, an understanding of environmental conditions required for malaria transmission is necessary for predicting areas subject to future outbreaks. Future climate change is likely to alter the distribution and intensity of malaria transmission, though the exact nature and extent of this influence has been the subject of recent debate (Caminade et al., 2014; Ryan et al., 2020; Smith et al., 2020).
The availability of water suitable for mosquito breeding is a critical control on malaria transmission, particularly where predominant mosquito vectors are adapted to exploit new water arising from seasonal rains and flooding. Such understanding is crucial if we are to make the link to climate and estimate the impact of projected climate change. Moreover, this knowledge can contribute to malaria adaptation/mitigation, namely the identification of mosquito larval ‘hotspots’ that could be targeted in malaria control programmes.
Ambient air temperature controls the rate of several components of the malaria transmission cycle including sporogonic and gonotrophic development rates, biting rate and individual longevity. Malaria climatic suitability is thus modelled based on well-established thermal response curves (e.g. Mordecai et al., 2012); however, water body availability is afforded no such detailed treatment. Instead, simple rainfall thresholds are used to represent water availability (see the review in Smith et al., 2013). Recent and current research by the project team is coupling continental-scale hydrological models with malaria thermal response curves to provide a more physically-based estimate of malaria hydro-climatic suitability (Smith et al, 2020).
Meanwhile, at the landscape scale, previous and ongoing work is focused on establishing a greater understanding of the hydrological and geomorphological impact of habitat suitability at the landscape scale (e.g. Hardy et al., 2013). This includes linking detailed hydraulic models with agent-based mosquito spatial ecology modelling to identify larval hotspots and model the dynamics with the passing of annual flood waves at high resolution. Recently, surface water dynamics representation has been improved in process-based malaria transmission models such as VECTRI (Asare et al., 2016) and LMM (Ermert et al., 2011).
The major aim of this project will be to bridge the scale gap between continental-scale and landscape-scale efforts of modelling malaria hydro-climatic suitability.
Objectives
In this project, you will work with a team of scientists at the University of Leeds and a network of international collaborators to embed hydrological and geomorphological understanding into continental-scale models of malaria hydro-climatic suitability. In particular, according to their research interests, the successful student could:
(1) Input daily runoff data into hydro-dynamic river routing models to then evaluate hydro-climatic suitability for malaria across Africa both for the present day and up until 2100;
(2) Expand this modelling approach to cover each continent and evaluate potential changes in hydro-climatic malaria suitability;
(3) Compare predictions of the above for different emissions pathways;
(4) Evaluate the global hydro-dynamic modelling output with more detailed modelling of individual field sites (particularly the Barotse floodplain of the Zambezi).
Fit to NERC Science
This project is aligned to the NERC ‘Terrestrial and freshwater environments’, ‘Geosciences’ and ‘Climate & climate change’ research areas. Specifically, the project aligns to the following NERC research areas: (1) Hydrological processes / Earth surface processes – by modelling fluvial hydro-dynamics across Africa; (2) Ecosystem scale processes – by evaluating the impact of flooding on mosquito larval habitats across entire landscapes; (3) Climate and climate change – by predicting changes in malaria hydro-climatic suitability between the present day and 2100.
Potential for high impact outcome
The coupling of hydrological and hydro-dynamic models with more conventional thermal response curves is an emerging focus of research (Smith et al., 2020). This area of research bridges disciplines and scales and has a clear global impact. The project will produce several outputs including: (i) 3-4 academic publications, at least one of which we anticipate being suitable for submission to a high-impact journal; and (ii) a contribution to the malaria control programme of Zambia where the project team have a proven track record of establishing clear links of communication with the Ministry of Health.
Training
The successful student will work under the supervision of Dr Mark Smith (School of Geography, Uni. of Leeds) and Prof Mark Trigg (School of Civil Engineering, UoL). The successful candidate will develop a range of research skills including GIS and Remote Sensing, hydraulic modelling, python scripting, statistical analysis, data presentation, academic writing skills and giving presentations. While fieldwork is not a core part of this project, it is anticipated that some field work may be useful to help ground-truth the model predictions. Training will be provided in field health and safety procedures.
The student will be supported throughout the studentship by a comprehensive PGR skills training programme that follows the VITAE Research Development Framework and focuses on knowledge and intellectual abilities; personal effectiveness; research governance and organisation; and engagement, influence and impact. Training needs will be assessed at the beginning of the project and at key stages throughout the project and the student will be encouraged to participate in the numerous training and development course that are run within the NERC DTP and the University of Leeds to support PGR students, including statistics training (e.g. R, SPSS), academic writing skills, grant writing etc. (http://www.emeskillstraining.leeds.ac.uk/). Supervision will involve regular meetings between supervisors and further support of a research support group.
Student profile
The student should have a keen interest in environmental issues with a strong background in a physical geography, earth sciences, environmental sciences, ecology or related discipline. Strong GIS/remote sensing/statistical/fieldwork skills are desirable but not essential, as training will be provided during the PhD.
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