About the Project
This PhD is co-supervised with Dr. Bruce Edmonds (http://bruce.edmonds.name/) at the Centre for Policy Modelling (http://cfpm.org/), Manchester Metropolitan University (http://mmu.ac.uk/). For more information, see http://cfpm.org/jobs/PhD-position-context-dependeny.html
In complex socio-environmental systems, simple explanations of relationships among observed phenomena are likely to be the exception rather than the rule. Hence, in considering such relationships it is necessary to consider how they are influenced by context. In addition to spatio-temporal aspects, context has dimensions pertaining to agent interconnectedness at different levels and scales: social and environmental, involving interpersonal and interspecific interactions. Existing results from a landscape-scale model of farm decision-making and biodiversity (FEARLUS-SPOMM) have demonstrated in theory that the effectiveness of policy implementation options aimed at increasing biodiversity can be significantly influenced by context.
The objectives of this research are to study the role of context in simulation of socio-environmental systems at three levels, with a focus on the second:
1. Context in the simulation: How should our understanding of context influence the way decision-making is represented in agent-based models? How can we efficiently represent ‘context-aware’ agents?
2. Context of the simulation: What constraints are imposed by context on where a socio-environmental system can go: how do initial conditions and exogenous scenario variables influence model behaviour? What evidence is there for the influence of context variables on system outcome in the real world?
3. Context of the research: How does the context of the research influence representation in the model and model boundary? What is the sensitivity of model predictions to variations in context? How should we reflect context when presenting results to different audiences?
The outcome of the research will be an evidence-based understanding of how context influences pro-environmental behaviour with respect to land management, and how to address it in models designed to explore possible outcomes from pro-environmental incentive mechanisms.
Funding Notes
The studentship is funded under the JHI/University Joint PhD programme. The university partner is Manchester Metropolitan University, who are providing half the funding. Candidates are urged strongly to apply as soon as possible so as to stand the best chance of success. A more detailed plan of the studentship is available to suitable candidates upon application. Funding is available for European applications, but Worldwide applicants who possess suitable self-funding are also invited to apply.
References
Gimona, A. and Polhill, J. G. (2011) Exploring robustness of biodiversity policy with a coupled metacommunity and agent-based model. Journal of Land Use Science 6 (2-3), 175-193.
Gimona, A., Polhill, G. and Davies, B. (2011) Sinks, sustainability and conservation incentives. In Liu, J., Hull, V., Morzillo, A. and Wiens, J. (eds.) Sources, Sinks and Sustainability. Cambridge University Press. pp. 155-178.
Parker, D. C., Brown, D. G., Polhill, J. G., Deadman, P. J. and Manson, S. M. (2008) Illustrating a new “conceptual design pattern” for agent-based models of land use via five case studies—the MR POTATHOEAD framework. In López Paredes, A. and Hernández Iglesias, C. (eds.) Agent Based Modelling in Natural Resource Management. Valladolid, Spain: INSISOC. pp. 23-51.
Polhill, J. G., Gimona, A. and Gotts, N. (2010) Analysis of incentive schemes for biodiversity using a coupled agent-based model of land use change and species metacommunity model. In Swayne, D. A., Yang, W., Voinov, A. A., Rizzoli, A. and Filatova, T. (eds.) Modelling for Environment’s Sake: 2010 International Congress on Environmental Modelling and Software, Ottawa, Ontario, Canada, 5-8 July 2010.
Polhill, J. G, Gimona, A. and Gotts, N. M. (subm.) Nonlinearities in biodiversity incentive schemes: A study using an integrated agent-based and metacommunity model. Environmental Modelling and Software.
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