MAgPIE – Model of Agricultural Production and its Impact on the Environment

Description of the global land use allocation model MAgPIE

The Model of Agricultural Production and its Impact on the Environment (MAgPIE) is a global land use allocation model, which is coupled to the grid-based dynamic vegetation model LPJmL, with a spatial resolution of 0.5°x0.5°. It takes regional economic conditions such as demand for agricultural commodities, technological development and production costs as well as spatially explicit data on potential crop yields, land and water constraints (from LPJmL) into account. Based on these, the model derives specific land use patterns, yields and total costs of agricultural production for each grid cell. The objective function of the land use model is to minimize total cost of production for a given amount of regional food and bioenergy demand. Regional food energy demand is defined for an exogenously given population in 10 food energy categories, based on regional diets. Future trends in food demand are derived from a cross-country regression analysis, based on future scenarios on GDP and population growth.

Figure 1. Simplified MAgPIE flowchart of key processes (demand and trade implementation, data inputs from LPJmL and spatially explicit water shadow prices). With exogenous data about population and GDP development, we calculate regional demand and the livestock share. The former is then translated to regional supply depending on the international trade scenario. Further inputs for MAgPIE are socioeconomic data like production costs and biophysical inputs from LPJmL. After the optimization of MAgPIE, one of the outputs is cropping patterns of the different crops, which is the basis for the calculation of water shadow prices.

Food and feed energy for the demand categories can be produced by 20 cropping activities and 3 livestock activities. Feed for livestock is produced as a mixture of crops, crop residuals, processing byproducts, green fodder produced on crop land, and pasture. Variable inputs of production are labour, chemicals, and other capital (all measured in US$). Costs of production are derived from the Global Trade Analysis Project (GTAP) Database. The model can endogenously decide to acquire yield-increasing technological change at additional costs. The costs for technological change for each economic region are based on its level of agricultural development, measured as agricultural land-use intensity. These costs grow with further investment in technological change. The use of technological change is either triggered by a better cost-effectiveness compared to other investments or as a response to resource constraints, such as land scarcity.

For future projections the model works on a time step of 10 years in a recursive dynamic mode. The link between two consecutive periods is established through the land-use pattern. The optimized land-use pattern from one period is taken as the initial land constraint in the next. If necessary, additional land from non-agricultural areas can be converted into cropland at additional costs. Potential crop yields for MAgPIE are originally computed with LPJmL at a 0.5° resolution, as weighted average of irrigated and non-irrigated production, if part of the grid cell is equipped for irrigation according to the global map of irrigated areas. In case of purely rain-fed production, no additional water is required, but yields are generally lower than under irrigation. If a certain area share is irrigated, additional water for agriculture is taken from available water discharge in the grid cell. Each cell of the geographic grid is assigned to 1 of 10 economic world regions: Sub-Saharan Africa (AFR), Centrally Planned Asia including China (CPA), Europe including Turkey (EUR), the Newly Independent States of the Former Soviet Union (FSU), Latin America (LAM), Middle East/North Africa (MEA), North America (NAM), Pacific OECD including Japan, Australia, New Zealand (PAO), Pacific (or Southeast) Asia (PAS), and South Asia including India (SAS). The regions are initially characterized by data for the year 1995 on population, gross domestic product (GDP), food energy demand, average production costs for different production activities, and current self-sufficiency ratios for food. Land-conversion activities provide for potential expansion and shifts of agricultural land in specific locations. For the base year 1995, total agricultural land is constrained to the area currently used within each grid cell, according to the dataset of as extended by. Cropland can be converted into rangeland, and vice versa. If additional land is required for fulfilling demand, this can be taken from the pool of non-agricultural land at additional costs. These land-conversion costs force the model to utilize available cropland and rangeland first, and land conversion will become relevant only if land becomes scarce in a certain location or if the marginal cost reductions by producing crops on converted land outweigh the costs of conversion.


Selected MAgPIE publications

Wang X, Biewald A, Dietrich J, Schmitz C, Lotze-Campen H, Humpenöder F, Bodirsky B, Popp A. (2016) Taking Account of Governance: Implications for Land-Use Dynamics, Food Prices, and Trade Patterns. Ecological Economics 122, 12-24

Weindl I., Lotze-Campen H., Popp A., Müller C., Havlík P.,Herrero M., Schmitz C. and Rolinski S. (2015) Livestock in a changing climate: production system transitions as an adaptation strategy for agriculture . Environmental Research Letters 10, 094021

Bodirsky B., Rolinski S., Biewald A., Weindl I., Popp A., Lotze-Campen H. (2015) Food Demand Projections for the 21st Century. PLoS ONE 10 (11) DOI: 10.1371/journal.pone.0139201

Humpenöder, F., Popp, A., Stevanovic, M., Müller, C., Bodirsky, B., Bonsch, M., Dietrich, J., Lotze-Campen, H., Weindl, I., Biewald A., Rolinski, S. (2015) Land-Use and Carbon Cycle Responses to Moderate Climate Change: Implications for Land-Based Mitigation? Environmental Science and Technology. 49 (11), 6731–6739.

Bonsch, M., Popp, A., Biewald A., Rolinski, S., Schmitz, C., Hoegner, K., Heinke, J. Ostberg, S., Dietrich, J. P., Bodirsky, B., Lotze-Campen, H., Stevanovic, M., Humpenöder, F., Weindl, I. (2015) Environmental flow provision: implications for agricultural water and land-use at the global scale. Global Environmental Change. 30, 113–132.

Popp A., Humpenöder F., Weindl. I., Bodirsky B., Bonsch M., Lotze-Campen H., Müller C., Biewald A., Rolinski S., Stevanovic M., Dietrich JP. (2014) Land use protection for climate change mitigation. Nature Climate Change 4, 1095–1098.

Humpenöder F, Popp A, Dietrich J, Klein D, Lotze-Campen H, Bonsch M, Bodirsky B, Weindl I, Stevanovic M, Müller C (2014): Investigating afforestation and bioenergy CCS as climate change mitigation strategies. Environmental Research Letters 9 (6): 064029. doi:10.1088/1748-9326/9/6/064029.

Bodirsky BL, Popp A, Lotze-Campen H, Dietrich JP, Rolinski S, Weindl I, Schmitz C, Müller C, Bonsch M, Humpenöder F, Biewald A, Stevanovic M (2014): Reactive nitrogen requirements to feed the world in 2050 and potential to mitigate nitrogen pollution, Nature Communications, 5, 3858

Dietrich J.P., Schmitz S, Lotze-Campen, H., Popp, A. and Müller, C. (2014): Forecasting technological change in agriculture - An endogenous implementation in a global land use model.Technological Forecasting and Social Change, 81, 236–249

Schmitz, C., Lotze-Campen, H., Gerten, D., Dietrich, J.P., Bodirsky, B., Biewald, A. and Popp, A. (2013): Blue water scarcity and the economic impacts of future agricultural trade and demand, Water Resources Research.v 49(6): 3601-3617

Popp, A., Dietrich, J.P., Lotze-Campen H., Klein, D., Bauer, N., Krause, M., Beringer, T., Gerten, D., Edenhofer, O. (2011): The economic potential of bioenergy for climate change mitigation with special attention given to implications for the land system. Environmental Research Letters 6 034017

Lotze-Campen, H., Popp, A., Beringer, T., Müller, C., Bondeau, A., Rost, S., Lucht, W. (2010): Scenarios of global bioenergy production: The trade-offs between agricultural expansion, intensification and trade. Ecological Modelling  221: 2188-2196

Popp A., Lotze-Campen H. and Bodirsky B. (2010) Food consumption, diet shifts and associated non-CO2 greenhouse gas emissions from agricultural production. Global Environmental Change 20: 451-462

Lotze-Campen, H., Müller, C., Bondeau, A., Jachner, A., Popp A., Lucht, W. (2008) Food demand, productivity growth and the spatial distribution of land and water use: a global modelling approach. Agricultural Economics, 39(3): 325-338



MAgPIE technical description


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