CPM/MMU PhD Director of Studies: Dr Bruce Edmonds
Application Deadline: 15 January 2013
Funding Availability: Competition Funded PhD Project (European/UK Students Only)
In a landscape managed by multiple owners varying from homeowners and non-agricultural businesses through to estates and agri-businesses, co-ordinated management of biodiversity is a challenge. Landscape fragmentation, climate change and habitat change all pose threats to species survival, whilst pro-environmental incentives are focused on individual landowners of particular types. In a special feature of the Proceedings of the National Academy of Sciences of the USA in 2007, Ostrom (2007) espoused the idea that there are ‘no panaceas’ for governance of socio-ecosystems towards the sustainable use of environmental resources. Brondizio et al. (2009) meanwhile argue that there is no fixed scale that is most appropriate to manage ecosystems. Given the failure to meet the 2010 Convention on Biodiversity Targets noted in the Global Biodiversity Outlook 3 and the adoption of the 2020 targets at EU and national levels, it is important to address the role of spatial, social, cultural and individual context in determining the effectiveness of measures aimed at promoting biodiversity. Since one way of evaluating such effectiveness is to use computer simulations of socio-environmental systems, such models need to address context. The goal of this work is to measure various ways in which context affects modelling and simulation work, focusing on how contextual variables influence path-dependence in a coupled socio-ecosystem model. In so doing, questions of how to address context in model design, whether context affects outcomes in the real world, and whether the context of the research affects model boundary will also need to be investigated.
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 and, crucially, when context has to be taken into account. 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.
The studentship is funded under the JHI/MMU Joint PhD programme and will be undertaken in conjunction with the MMU. Bruce Edmonds of the Centre for Policy Modelling will be the primary university supervisor on this project.
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 non-EU applicants who possess suitable self-funding are also invited to apply.
The studentship is jointly run by the JHI and the CPM/MMU. The successful candidate will be based in Aberdeen, but will visit Manchester a few times a year. The studentship is for 3 years and provides: (A) a stipend of £13,590 per year for living expenses (non-taxable) (B) 3 years PhD student fees (EU/UK student rate) (C) support for travel to Manchester (6 trips of 2-3 days duration a year) and/or international conferences up to a maximum total of £5130). The PhD will be awarded by the MMU. The JHI and the MMU will jointly provide training and support for the period of study. The candidate must be willing to live near the JHI in Aberdeen, travel to Manchester for discussions and occasionally travel to international conferences.
1. Look at the general information about PhD Studentships 2012 opportunities at the JH Institute (http://www.hutton.ac.uk/news/phd-studentships-2012-opportunities)
2. Look at the JH website on their modelling of Socio-ecological systems and Agent-based Modelling (http://www.macaulay.ac.uk/fearlus/)
3. Look at the CPM website on agent-based modelling (http://cfpm.org) and Bruce Edmonds’ recent invited talk at iEMSs on “Context in Environmental Modelling” (http://www.slideshare.net/BruceEdmonds/context-in-environmental-modelling-the-room-around-the-elephant)
5. Download the application form from: http://www.hutton.ac.uk/sites/default/files/files/PhD-application-James-Hutton-Institute.doc
Brondizio, E.S., Ostrom, E. and Young. O.R. (2009) Connectivity and the Governance of Multilevel Social-Ecological Systems: The Role of Social Capital. Annual Review of Environment and Resources, 34: 253-278.
Edmonds, B. & Meyer, R. (eds.) (in press) Handbook of Simulating Social Complexity, Springer.
Edmonds, B. (2012) Complexity and context-dependency. Foundations of Science. DOI 10.1007/s10699-012-9303-x
Edmonds, B. (2012) Context in social simulation: Why it can’t be wished away. Computational and Mathematical Organization Theory 18 (1), 5-21.
Edmonds, B. (2007) The practical modelling of context-dependent causal processes – a recasting of Robert Rosen’s thought. Chemistry and Biodiversity 4 (1), 2386-2395.
Edmonds, B. (2002) Learning and exploiting context in agents. Proceedings of the 1st International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), Bologna, Italy, July 2002. ACM Press. 1231-1238.
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.
Ostrom, E. (2007) A diagnostic approach for going beyond panaceas. Proceedings of the National Academy of Sciences, 104(39):15181-15187.
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.