Some of the most important interactions between human society and the environment occur in the agricultural sector. Agricultural production is - more than most other economic activities - affected by socio-economic and environmental conditions. Human demand for food effectively drives production and land use patterns. With respect to climate, agriculture acts as a source and a sink of greenhouse gases at the same time. The complex linkages between food production, land use and climate change can only be understood in a long-term, interdisciplinary framework. However, there is still a lack of consistent modelling approaches which take spatial variations of environmental conditions into account and represent biophysical as well as socio-economic driving forces over several decades into the future.
From an economic perspective, the importance of agriculture varies according to the level of economic development. In poor countries, agricultural and food production contributes a major share to GDP and is an important source of employment and household income. Many economists claim that there is no way out of poverty, except through agricultural and rural development (McCalla, 1999). In the process of economic development, the role of agriculture is decreasing, and in rich industrialised countries the share of agriculture in GDP and overall labour force is now below 5%. These trends occur despite wideranging government interventions to achieve the contrary. Like most economic sectors, agriculture is also strongly affected by macroeconomic conditions, lifestyles changes and consumption patterns.
From an environmental point of view, agriculture is of key importance in rich and poor countries, regardless of the level of economic development. On a global scale, agricultural production accounts for about 40% of total land use, and about 70% of all freshwater withdrawals. It also affects important nutrient cycles, contributes significantly to climate change through emissions of methane and nitrous oxide, and it is considered one of the most important causes for
F. Brouwer andB.A. McCarl (eds.), Agriculture and Climate Beyond2015, 109-129. © 2006 Springer. Printed in the Netherlands.
biodiversity loss (Kendall and Pimentel, 1994). At the same time, agricultural productivity may be strongly affected by global environmental change.
If we want to understand the interactions between human society and the biosphere in general, an in-depth understanding of the links between food consumption, agricultural production, land use and climate change is indispensable. The major challenge to this understanding is the fact that socioeconomic and environmental driving forces and impacts occur at different spatial, temporal and thematic scales. It is, for instance, not meaningful to talk about environmental impacts without looking at reasonably small regional units. However, economic analysis and the related data are often confined to nation states as the typical unit of analysis.
For the purpose of an integrated environmental-economic analysis of the food system across different scales we are presenting a coupled modelling framework. The biosphere part of the system is represented by the well established Lund-Potsdam-Jena Dynamic Global Vegetation Model (LPJ), a spatially explicit, grid-based process model which runs on a global scale. The socio-economic part is represented by a resource allocation model which we call a 'Management model of Agricultural Production and its Impact on the Environment' (MAgPIE). This model is under development and we present preliminary modelling results here.
For the analysis in this chapter, these two models run sequentially and exchange information on key economic and environmental conditions and driving forces. Changes in economic and environmental conditions can be modelled separately or in combination. Outputs of the modelling framework include standard economic variables as well as environmentally relevant information.
While the scope of our modelling work is global in principle, for the purpose of testing the coupled system and demonstrating the viability of our concept we have zoomed into a small region as a first example. We chose Germany as the sample region. It has to be stressed, though, that the resolution of our global models may be too coarse to provide convincing results for a region the size of Germany. However, we are able to show that the concept works and can be extended to the global scale with reasonable effort.
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