awareness of the GEC issues within the policy and other stakeholder communities; (ii) ithelps raise awareness of the policy and resource management issues within the GEC sciencecommunity; and (iii) it identifies, and begins <strong>to</strong> build, a team of stakeholders keen <strong>to</strong> workcollaboratively.A powerful way <strong>to</strong> facilitate stakeholder involvement is through the use of participa<strong>to</strong>ryscenario exercises. These link research activities more closely <strong>to</strong> actual decision-makingprocesses and have shown considerable potential <strong>to</strong> provide a mechanism for involving arange of stakeholders and for facilitating communication between them. As discussed inPaper 5, there are three major benefits. First, participants in a scenario development processunderstand better the issues involved via structured dialogue. Second, scenario exercises offera ‘neutral space’ <strong>to</strong> discuss future challenges as uncertainty about the future has an‘equalizing effect’; no-one can predict the future, thus no-one can be proven ‘wrong’. Thisopportunity for open discussion also helps in engendering mutual respect, understanding andtrust, which is crucial for building effective research teams for follow-up activities. Finally,the discussion of, and reflection on, possible future trends can create the ground <strong>to</strong> revealconflicts, common views about goals, or different perceptions about <strong>to</strong>day’s challenges.Methodological developments for regional researchWhile the subsections above have identified numerous contributions <strong>to</strong> the food securityscience agenda, and especially when applied <strong>to</strong> the regional level, the planning, execution andreporting of such research is far from straight forward. This is due <strong>to</strong> the number of reasons:First, the stakeholder community at regional level is highly complex, embodying a widerange of different types of ac<strong>to</strong>rs operating on different scales at different levels. While it isimportant <strong>to</strong> recognise this complexity, the primary ‘client’ for the research does need <strong>to</strong> beclarified. This could be a regional or an intergovernmental body (e.g. SADC, EU), but theseare but one of four main categories of stakeholders (research, government, business and civilsociety) who operate on a similar spatial resolution (Paper 5). Determining how and when <strong>to</strong>engage with them is challenging as cultural and institutional fac<strong>to</strong>rs affecting science-policyrelationships (e.g. aims, timescale, success measures, evidence, quality control) oftenfrustrate engagement (Scott et al., 2005). Appreciating this is critical and the systematic stepslaid out in Paper 5 (Box 3) help overcome many of these problems. This also helps <strong>to</strong>establish innovative science plans through co-design. Paper 5 also discusses when <strong>to</strong> engagestakeholders and provides insights in organizing and understanding the complexity ofstakeholder engagement, contributing <strong>to</strong> the concepts and practice of this area.Second, while the unit of analysis is defined as the region, research could require identifyinga number of case study sites so as <strong>to</strong> establish, for instance, the heterogeneity of a givenvariable across the region. Choosing case study sites can be politically and well asscientifically complex, so clear criteria are needed. Contributions <strong>to</strong> best practise includechoosing sites that lie along gradients of, for example, anticipated temperature andprecipitation change or current and anticipated grazing pressure. The sites should also112
provide sufficient representation of, for instance, (i) different governance arrangements (e.g.land tenure); (ii) different land management (e.g. principal farming systems); and (iii) keydrivers in regional scenarios (e.g. demography).Third, establishing institutional buy-in at the regional level can be difficult, as it includesnegotiating with a potentially wide range of research partners (government labs, universities,NGOs and private sec<strong>to</strong>r) and donors. Research on food security, and especially whencoupled with GEC issues, is complex and full of uncertainties. It can take time for results <strong>to</strong>become apparent, which challenges timeframes for funding and the information needs of the‘client’. Co-planning helps all partners grasp these realities, and take an active interest in theproject. An example of how and why different communities ‘buy-in’ <strong>to</strong> a research agenda ingiven in Paper 6 (Box 5).Encouraging regional research networks helps overcome many of these challenges asmembers of the network bring different skills and contacts <strong>to</strong> the other stakeholders. Teambuilding can be promoted through the adoption of standardized methods, and the use of theparticipa<strong>to</strong>ry scenario exercises, as discussed above. The use of scenarios methods can alsohelp stakeholders <strong>to</strong> see the links between spatial levels (global <strong>to</strong> regional; regional <strong>to</strong> local),although ‘downscaling’ and ‘upscaling’ scenarios both present their own methodologicalchallenges.The scientific contribution of integrating the approaches: from traditional agronomy <strong>to</strong>production ecology and agroecology <strong>to</strong> ‘food system ecology’Lessons from production ecology, agroecology and human ecologyAs discussed in the Introduction and Paper 2, much of the work on food security stems fromagricultural science generally, and empirical agronomy in particular. Such work has made amassive contribution <strong>to</strong> enhancing food production and removing the threat of famine formany, and its importance both his<strong>to</strong>rically and in<strong>to</strong> the future is clear. The interest in gaininga more mechanistic understanding of food production (and crop growth in particular) hashowever led <strong>to</strong> the development of ‘production ecology’(van Ittersum and Rabbinge, 1997)and the broader concept of ‘agroecology’(Dalgaard et al., 2003). Both have emerged overrecent decades as key areas of research and much energy has been directed <strong>to</strong>wards thedevelopment of mechanistic models <strong>to</strong> both explore the impact on crop growth of scenariosof changing environmental conditions and also <strong>to</strong> challenge theories thereby enhancingmodel structure.<strong>Production</strong> ecology initially considered limitations <strong>to</strong> crop growth, i.e. what determinesproductivity, or ‘yield’. Attention was first placed on the ‘crop system’ and in particular oncrop characteristics, radiation, temperature and CO 2 as fac<strong>to</strong>rs that fundamentally define the‘potential’ crop growth. Water and nutrients were then incorporated as fac<strong>to</strong>rs that limit cropgrowth (i.e. the ‘attainable’ yield within the ‘cropping system’). Pests, diseases, weeds and113
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