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Dirnböck, T., Bezák, P., Dullinger, S., Haberl, H., Lotze-Campen, H., Mirtl, M., et al. (2013). Critical Scales for Long-Term Socio-ecological Biodiversity Research. In S. J. Singh, H. Haberl, M. Chertow, M. Mirtl, & M. Schmid (Eds.), (pp. 123–138). Long Term Socio-Ecological Research, Human-environment interactions (2). Dordrecht: Springer.
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Rolinski, S., Weindl, I., Heinke, J., Bodirsky, B. L., Biewald, A., & Lotze-Campen, H. (2014). Environmental impacts of grassland management and livestock production. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: The potential of grasslands to sequester carbon and provide feed for livestock production depends on the one hand on climatic conditions but secondly on management and grazing pressure. Using a global vegetation model considering different management and grazing options, effects of livestock density on primary productivity can be assessed. It is expected that low animal densities enhance productivity whereas increasing grazing pressure may deteriorate grass plants. Thus, the optimal animal density depend on the specific primary production of the pasture and optimal grazing intensity. Using these optimal grass yields, the impacts of livestock production on resource use is assessed by applying the global land use model MAgPIE. This model integrates a detailed representation of the livestock sector and integrates socio-economic regional information with spatially explicit biophysical data. With scenario analysis we analyze the impact of livestock production on future deforestation and land use. Our results indicate that the reduction of animal derived calory demand has a huge potential to spare land for nature and reduce deforestation. On the supply side, feeding efficiency gains can help to decrease demand for land and overall biomass requirements.
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Lotze-Campen, H. (2015). EU-level assessments and scenarios..
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Lotze-Campen, H. (2015). EU-level assessments and scenarios. In FACCE MACSUR Reports (Vol. 6, pp. SP6–8). Brussels.
Abstract: Shared socio-economic pathways are used to look at particular possible futures of major trends in global socio-economic trends (e.g. global population, GDP, urbanization, strength of political institutions, international trade). These scenarios make no inference to their likelihood of becoming true. These scenarios are used in MACSUR to assess different questions, e.g.•What is the future of agricultural prices?•How will agricultural production and food consumption evolve?•How will climate change impacts and mitigation affect…–Prices–Land use–Trade–Undernourishment No Label
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Dietrich, J. P., Schmitz, C., Lotze-Campen, H., Popp, A., & Muller, C. (2014). Forecasting technological change in agriculture-An endogenous implementation in a global, and use model. Technological Forecasting and Social Change, 81, 236–249.
Abstract: Technological change in agriculture plays a decisive role for meeting future demands for agricultural goods. However, up to now, agricultural sector models and models on land use change have used technological change as an exogenous input due to various information and data deficiencies. This paper provides a first attempt towards an endogenous implementation based on a measure of agricultural land use intensity. We relate this measure to empirical data on investments in technological change. Our estimated yield elasticity with respect to research investments is 029 and production costs per area increase linearly with an increasing yield level. Implemented in the global land use model MAgPIE (”Model of Agricultural Production and its Impact on the Environment”) this approach provides estimates of future yield growth. Highest future yield increases are required in Sub-Saharan Africa, the Middle East and South Asia. Our validation with FAO data for the period 1995-2005 indicates that the model behavior is in line with observations. By comparing two scenarios on forest conservation we show that protecting sensitive forest areas in the future is possible but requires substantial investments into technological change. (C) 2013 Elsevier Inc. All rights reserved.
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