Details of Award
NERC Reference : NE/P012345/1
NERC Centre for Doctoral Training in Quantitative and Modelling skills in Ecology and Evolution (QMEE)
Training Grant Award
- Lead Supervisor:
- Professor S Pawar, Imperial College London, Life Sciences
- Grant held at:
- Imperial College London, Life Sciences
- Science Area:
- Atmospheric
- Earth
- Freshwater
- Marine
- Terrestrial
- Overall Classification:
- Freshwater
- ENRIs:
- Natural Resource Management
- Pollution and Waste
- Biodiversity
- Environmental Risks and Hazards
- Global Change
- Science Topics:
- Population Ecology
- Population Genetics/Evolution
- Environmental Genomics
- Ecosystem Scale Processes
- Environmental Informatics
- Abstract:
- Species and ecosystems are affected by environmental change and human activities, which in turn affects water resources, nutrient cycles, climate, human health and well-being. Managing these impacts requires that we understand feedbacks in natural systems well enough to predict change and design interventions. Theoretical ecology, ecosystem science and evolutionary biology provide models for mechanisms influencing genes, individuals, populations, communities and ecosystems. These models can be applied to issues ranging from disease spread to conservation, sustainable agriculture, fisheries and forestry. So far, however, few developments have led to predictive ability for real-world applications. Our vision is to train the next generation of researchers with the necessary quantitative and modelling skills to bridge the gap between theory, emerging data and practice. Our students will apply state-of-the-art modelling and quantitative skills to real-world challenges, working in teams with a range of partners across academia, industry and policy sectors in order to increase their research impact and employability. Specifically, they will: - create cross-cutting theory for complex ecological, evolutionary, environmental and socio-ecological systems; - develop methods to compile and manage 'big data' that guide theory development and test emerging models; - use theory and models to solve applied challenges (such as optimizing food production to reduce environmental impacts, or controlling the evolution of resistance in pests and disease); - and make near real-time use of new data streams from multiple sensors to inform adaptive responses to climate change. A collaborative set of internationally leading institutions will deliver this ambitious doctoral training. Imperial College London and the University of Reading bring strength and breadth in ecological and evolutionary modelling of populations, communities, biodiversity, and ecosystems at local to global scales. Both institutions develop fundamental theory and new quantitative methods for application to real-world issues, such as deforestation, disease control and global environmental change. Non-academic hosting partners CEH, Cefas and ZSL bring extensive data resources, expertise in modelling and application to solve pressing environmental challenges. Non-hosting partners in industry, policy and non-governmental organisations will provide real-world research challenges, networking, and further training opportunities. Our training plan combines tried-and-tested methods and expertise with innovative new approaches. Students will first complete a 6-month pre-project period with a mixture of cohort training, individually tailored specialist training (chosen from a wealth of specialist postgraduate courses at the host institutions), and mini-project rotations across the partnership. This period will develop their multidisciplinary skills, exposing them to new disciplines and the wider context of the research, ultimately informing the design of their PhD projects. Students will then spend a further 3 years on their PhD project, supervised by at least two supervisors from different departments or institutions (one with mathematical/computational expertise, one with expertise in empirical ecology/evolution/applications). In addition, students will form 'tiger teams' in multidisciplinary groups of 4 to tackle quantitative problems for non-academic partners; for example, helping CABI develop new models for designing biocontrol of invasive species. This activity will broaden research experience and transform outputs to real-world impacts. Coupled with cohort training days and hackathons to boost modelling and big data techniques, the students will form an active, interacting cohort able to work across sectors. QMEE will form a hub to bridge biological and mathematical/physical sciences, to deliver predictive tools with real-world impact, and to transform the field.
- NERC Reference:
- NE/P012345/1
- Grant Stage:
- Awaiting Event/Action
- Scheme:
- Doctoral Training
- Grant Status:
- Active
- Programme:
- CDT
This training grant award has a total value of £2,254,331
FDAB - Financial Details (Award breakdown by headings)
Total - DSA | Total - Other Costs | Total - Fees | Total - Student Stipend | Total - RTSG |
---|---|---|---|---|
£87 | £8,821 | £428,315 | £1,553,108 | £264,000 |
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