From Food Production to Food Security - Global Environmental ...

Parry et al., 2005). Conducting food system research at the regional level also means that itcan address both rural and urban issues, and the relationship between them. Data collection isalso a challenge at regional levels if the region of interest includes parts, but not all of severalnations because data, especially economic and social, is often collected at the national leveland data systems may vary between countries.GEC/food security research at different scales and levelsThere have been a large number of experimental studies under the ‘food security’ banneraddressing food production. Most have addressed crop or animal productivity (i.e. yield), andhave reported research conducted at the experimental plot level (i.e. very local) over agrowing season or perhaps a few years. However, many of the issues related to regional foodproduction, and even more so to regional food security, operate at larger spatial and temporallevels, and warrant further research.Aware of the need for better links between agronomic research on crop productivity at plotlevel and regional production, and especially over time, the last decade or so has seenagronomists beginning to establish trials at landscape level (e.g. Veldkamp et al., 2001).Estimating regional production is not however just a matter of ‘scaling up’ plot-levelagronomic trials as the critically important social and institutional processes operating athigher levels need to be factored in. Put another way, studies that scale up from plot toregional level can be misleading at best and could lead to actions that impede real progresstoward food security unless social and economic components are at the heart of the process.Hence, a considerable methodological challenge to be overcome at such levels is foragronomists to work more effectively with economists and social scientists, as well as withsystem ecologists, to capture the key economic and social processes, as well as biophysicaland ecological processes at play at different spatial levels (Ingram et al., 2008). This includesnot only adopting a more interdisciplinary approach but also analysing interactions amongvariables from one level to the other. For instance, a decrease in maize yield at the plot orfield level may lead farmers to decide to shift to other crops (e.g. beans or cassava). If theshift is significant at the regional level, changes in the price of maize versus that of thealternative crops will take place. These changes in relative crop prices will trigger furtherchanges in farmers’ practices and in their adaptation of their systems to the market (Ingram etal., 2008). In contrast to agronomic studies, agricultural economic studies have oftenundertaken analyses at higher spatial levels, especially on economic and market implications,e.g. the Institute Food Policy Research Institute’s (IFPRI) IMPACT model (as discussed byRosegrant and Cline, 2003).Crop modellers have meanwhile been running simulations of crop yield over large areas forsome time. Early approaches (e.g. Rosenzweig and Parry, 1994) used point-based estimatesscaled-up using climate model output (which is only available at the higher level). Morerecent studies (e.g. Parry et al., 2005; Challinor et al., 2007) do model crop response at higher60