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Rolinski, S.; Heinke, J.; Weindl, I. |
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Title |
Grazing effects on grassland productivity – Linking livestock production to grass yields |
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2014 |
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Livestock, Climate Change and Food Security, Madrid, Spain, 2014-05-19 to 2014-05-20 |
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MA @ admin @ |
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2752 |
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Rolinski, S.; Weindl, I.; Heinke, J.; Bodirsky, B.L.; Biewald, A.; Lotze-Campen, H. |
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Title |
Environmental impacts of grassland management and livestock production |
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2014 |
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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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FACCE MACSUR Mid-term Scientific Conference |
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3(S) Sassari, Italy |
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FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy |
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MA @ admin @ |
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5078 |
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Topp, K.; Eory, V.; Bannink, A.; Bartley, D.J.; Blanco-Penedo, I.; Cortignani, R.; Del Prado, A.; Dono, G.; Faverdin, P.; Graux, A.-I.; Hutchings, N.; Lauwers, L.; Özkan Gülzari, Ş.; Rolinski, S.; Ruiz Ramos, M.; Sandars, D.L.; Sándor, R.; Schoenhart, M.; Seddaiu, G.; van Middelkoop, J.; Weindl, I.; Kipling, R.P. |
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Modelling climate change adaptation in European agriculture: Definitions and Current Modelling |
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2017 |
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FACCE MACSUR Reports |
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10 |
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L2.3.2-D |
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Confidential content, in preparation for a peer-reviewed publication. |
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LiveM |
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MA @ admin @ |
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4959 |
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Hutchings, N.; Weindl, I.; Topp, C.F.E.; Snow, V.O.; Rotz, A.; Raynal, H.; Özkan Gülzari, Ş.; Martin, R.; Holzworth, D.P.; Graux, A.-I.; Faverdin, P.; Del Prado, A.; Eckard, R.; Bannink, A. |
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Does collaborative farm-scale modelling address current challenges and future opportunities |
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2017 |
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FACCE MACSUR Reports |
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10 |
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L1.4-D2 |
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Resources required increasing, resources available decreasing Farm-scale modellers will need to make strategic decisions Single-owner models May continue with additional resources Risk of ‘succession’ problem Community modelling is an alternative Need to continue building a community of farm modellers |
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LiveM |
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MA @ admin @ |
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4978 |
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Biewald, A.; Lotze-Campen, H.; Otto, I.; Brinckmann, N.; Bodirsky, B.; Weindl, I.; Popp, A.; Schellnhuber, H.J. |
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Title |
The Impact of Climate Change on Costs of Food and People Exposed to Hunger at Subnational Scale |
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2015 |
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PIK Report |
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128 |
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73 |
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Climate change and socioeconomic developments will have a decisive impact on people exposed to hunger. This study analyses climate change impacts on agriculture and potential implications for the occurrence of hunger under different socioeconomic scenarios for 2030, focusing on the world regions most affected by poverty today: the Middle East and North Africa, South Asia, and Sub-Saharan Africa. We use a spatially explicit, agroeconomic land-use model to assess agricultural vulnerability to climate change. The aims of our study are to provide spatially explicit projections of climate change impacts on Costs of Food, and to combine them with spatially explicit hunger projections for the year 2030, both under a poverty, as well as a prosperity scenario. Our model results indicate that while average yields decrease with climate change in all focus regions, the impact on the Costs of Food is very diverse. Costs of Food increase most in the Middle East and North Africa, where available agricultural land is already fully utilized and options to import food are limited. The increase is least in Sub-Saharan Africa, since production there can be shifted to areas which are only marginally affected by climate change and imports from other regions increase. South Asia and Sub-Saharan Africa can partly adapt to climate change, in our model, by modifying trade and expanding agricultural land. In the Middle East and North Africa, almost the entire population is affected by increasing Costs of Food, but the share of people vulnerable to hunger is relatively low, due to relatively strong economic development in these projections. In Sub-Saharan Africa, the Vulnerability to Hunger will persist, but increases in Costs of Food are moderate. While in South Asia a high share of the population suffers from increases in Costs of Food and is exposed to hunger, only a negligible number of people will be exposed at extreme levels. Independent of the region, the impacts of climate change are less severe in a richer and more globalized world. Adverse climate impacts on the Costs of Food could be moderated by promoting technological progress in agriculture. Improving market access would be advantageous for farmers, providing the opportunity to profitably increase production in the Middle East and North Africa as well as in South Asia, but may lead to increasing Costs of Food for consumers. In the long-term perspective until 2080, the consequences of climate change will become even more severe: while in 2030 56% of the global population may face increasing Costs of Food in a poor and fragmented world, in 2080 the proportion will rise to 73%. |
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Potsdam |
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Potsdam-Institut für Klimafolgenforschung |
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MA @ admin @ |
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5000 |
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