Abstract: Sunflower is one of the major oilseeds produced in Tanzania, but due to insufficient domestic production more than half of the country’s demand is imported. The improvement of the sunflower food value chain (FVC) understanding is important to ensure an increase in the production, availability, and quality of edible oil. In order to analyse causes and propose solutions to increase the production of sunflower oil, a conceptual framework that proposes the combined use of different models to provide insights about the sunflower FVC was developed. This research focus on the identification of agricultural models that can provide a better understanding of the sunflower FVC in Tanzania, especially within the context of food security improvement. A FVC scheme was designed considering the main steps of sunflower production. Thereafter, relevant models were selected and placed along each step of the FVC. As result, the sunflower FVC model in Tanzania is organized in five steps, namely (1) natural resources; (2) crop production; (3) oil processing; (4) trade; and (5) consumption. Step 1 uses environmental indicators to analyse soil parameters on soil-water models (SWAT, LPJmL, APSIM or CroSyst), with outputs providing data for step 2 of the FVC. In the production step, data from step 1, together with other inputs, is used to run crop models (DSSAT, HERMES, MONICA, STICS, EPIC or AquaCrop) that analyse the impact on sunflower yields. Thereafter, outputs from crop models serve as input for bio-economic farm models (FSSIM or MODAM) to estimate production costs and farm income by optimizing resource allocation planning for step 2. In addition, outputs from crop models are used as inputs for macro-economic models (GTAP, MAGNET or MagPie) by adjusting supply functions and environmental impacts within steps 3, 4, and 5. These models simulate supply and demand, including the processing of products to determine prices and trade volumes at market equilibrium. In turn, these data is used by bio-economic farm models to assess sunflower returns for different farm types and agro-environmental conditions. Due to the large variety of models, it is possible to assess significant parts of the FVC, reducing the need to make assumptions, while improving the understanding of the FVC.

Abstract: Assessing the impact of macro-level policy driven land use changes on regional sustainability is an important task that can facilitate complex decision making processes of introducing reforms. The research work demonstrates the ability of Sustainability Impact Assessment Tool (SIAT), a meta-model, in conducting ex ante spatially explicit cross sectoral impact assessments of changes in common agricultural policy (CAP). The meta-model is able to appraise impacts of CAP amendments on land use and their repercussions on multiple indicators of sustainability. The presented study comprehensively analyses the possible impacts of discontinuing direct financial support to farmers under CAP. The simulations of the meta-model are able to reveal the land use changes both at EU and regional levels as well as to bring forth the subsequent changes in a number of indicators representing the regional sustainability (for five case study regions). In a nutshell, the simulations indicate that a reduction in direct support brings in general, a decrease in farmed area, an increase in forested land, less fluctuation in natural vegetation coverage, increase in abandoned arable land area and negligible changes in built-up area despite regionally diverging land use trends. The simulated changes in sustainability indicators for the study regions in consequence to these land use changes show that the discontinuation of subsidies evokes responses that are in general climate friendly (reduction in methane and N2O emissions, diminishing energy use and reduction in global warming potential), economically beneficial (increase in gross value of agriculture) and socially desired (decrease in unemployment rate) as well as environmentally harmful (increase in pesticide use). Even though the appraisals of diversity indicators such as forest deadwood and farmland birds are not conclusive for all regions, the changes are positive for the former indicator and slightly negative for the latter in general. The trade-offs among these regional sustainability indicators using their directional associations are also presented for a comprehensive assessment of the impacts. (C) 2013 Elsevier Ltd. All rights reserved.

Abstract: The objective of the Tanzanian case study region is to provide MACSUR II a platform to concentrate climate research to a focal region in Morogoro and Dodoma in Tanzania. Hence, synergies among a number of other research projects will be used, which all focus on food security related to climate change.Within the case study region the projects aim at improving the food situation for the most-vulnerable rural poor population in Tanzania. They are designed to identify successful food securing upgrading strategies and innovations along local and regional food value chains, test and adjust them to site-specific, sustainable settings and tailor these concepts to be disseminated for national outreach. After the project lifetime, the results can be implemented at different levels of policy, extension and research.The basic concept applies the following steps in an iterative and partly recurrent procedure: (1) A stakeholder involvement process will be set up from the beginning as an integral part of most analytical steps; (2) case study sites within the focal regions Morogoro and Dodoma will be selected, set up and typologies of food value chains developed; (3) success stories of secure food production and/or good practice along the food value chains will be screened and inventoried; (4) an integrated in-depth analyses of food value chain components, their costs, benefits and impacts will be carried out; (5) a few of the most promising good practices with regard to positive impacts and implementation will be participatively discussed and identified for subsequent in-depth testing; (6) an in-depth participative field testing and/or analysis of selected, most promising technologies will be conducted for all food value chain components and requirements for implementation identified; (7) transferability and implementation capability will be assessed for different scenarios and for future condition simulations (model analysis); (8) a meta-model analysis including risk analysis and final proofing will identify hot spots of most sensitive, fragile regions and the potentials for alleviating food insecurity. Hence, the research concept`s main focuses on local and regional food security related to climate change, but the research design implies a national outreach for Tanzania as a whole.The research activities will be embedded into local and regional strategies to assess potential impacts and trade-offs and to be able to up-scale lessons learnt in a generic manner to regions with specific bio-physical, socio-cultural and economic conditions.Spatial Design: Conducting a literature research on relevant characteristic a considering the spatial design:two focal regions in Tanzania (Morogoro, Dodoma),each region with two case study sites (CSS) consisting of at least one local marketplace and surrounding 2-3 villages,the two CSS among the target regions are selected to differ in factors such as market and capital access for investments, remoteness, population density, land availability, soil types, infrastructure, facilities, and others,create sufficiently diverse environmental and socio-economic conditions for investigating food securing technologies along FVC and allowing for testing the transfer of results to other Tanzanian regions.Main selection criteria for regions: two climates types:semi-arid Dodoma (350-500mm),semi-humid Morogoro region (600-800mm)clear distinction between the regions.other criteria within the regions:rather similar climate (must) +-80mm,weak and good market access (must) (=market and capital access for investments),rainfed crop–livestock systems oriented, not too strongly paddy rice oriented (< 20% rice) (must),village size: approx. 800-1500 households (must)Stunting cases, logistics and infrastructure, different wards, land availability, facilities, capital, soil types, and population density etc. No Label