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Farming

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    In our research we assess the sustainability performance of 400 smallholder farms practicing organic (i.e. certified or non-certified) and non-organic agriculture (i.e. conventional or other) using the Sustainability Monitoring and Assessment RouTine (SMART)-Farm Tool and examine differences between these farm categories using multivariate analyses. We also identify general gaps in sustainability performance for all farms. Murang'a County, Kajiado County.

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    The table includes sowing, harvesting dates, sowing/planting rates of Maize and Cassava in different Agro-ecological zones in Ghana.

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    This set of interviews is part of the 'Farmer Empowerment' project that focused on the impact of farmer organizations (FOs) on the socio-economic development of their FO-members. The interviews were conducted within a second field research in order to gather information on specific impact pathways of selected FOs that work to empower respective FO-members.

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    This set of interviews is part of the 'Farmer Empowerment' project that focused on the impact of farmer organizations (FOs) on the socio-economic development of their FO-members. The interviews were conducted within a second field research in order to gather information on specific impact pathways of selected FOs that work to empower respective FO-members.

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    The table includes sowing, harvesting dates, sowing/planting rates of Maize in different Agro-ecological zones in Ethiopia.

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    In our research we assess the sustainability performance of 400 smallholder farms practicing organic (i.e. certified or non-certified) and non-organic agriculture (i.e. conventional or other) using the Sustainability Monitoring and Assessment RouTine (SMART)-Farm Tool and examine differences between these farm categories using multivariate analyses. We also identify general gaps in sustainability performance for all farms.

  • Categories  

    This set of interviews is part of the 'Farmer Empowerment' project that focused on the impact of farmer organizations (FOs) on the socio-economic development of their FO-members. The interviews were conducted within a second field research in order to gather information on specific impact pathways of selected FOs that work to empower respective FO-members.

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    There is an increasing interest of acquiring farmland abroad, especially following the food price crisis in 2007/08. East Africa is a hotspot of activities, and given the high prevalence of poor people in the area, impacts on rural livelihoods are expected to be substantial. Following significant primary data collection in Ethiopia and Uganda, the study analyses the impact of two such large-scale land acquisitions on the rural economy and the local population’s livelihood, using Theory-based Impact Evaluations (Hemmer 2011) within an analytical framework of layered social analysis (Williamson 2000). Impact is assumed to manifest through five major channels: land, labour, natural resources, technological & organisational innovation and institutional change. The study consists of five chapters: The introduction surveys the global trend, reviews existing evidence and relevant theory to elaborate a conceptual and an analytical framework for the research. The second chapter takes stock of trend and types of large-scale land acquisitions in Eastern Africa, using national official data from Ethiopia and Uganda. While there is a clear increase in number of land transactions, media reports are only confirmed in a small fraction. Investors are coming from Europe, the Arabic peninsula as well as other emerging economies in the global South (South Africa and India, specifically). However, a surprisingly large number of acquisitions is done by domestic investors. The third chapter analyses the early stage impact of a large scale land acquisition in the far western lowlands of Ethiopia. A Saudi-Ethiopian investor tries to develop 10,000 ha for irrigated rice production. Building on primary household data and qualitative information gathered in the area in 2010, a mathematical programming model is calibrated to quantify likely impacts ex-ante. The investment is found to have poverty reducing potential, mainly due to employment creation and growth of the rural non-farm economy. However, the local population has to bear uncompensated costs of lost forestland and local inequalities are likely to widen in consequence of unequal participation on employment and business opportunities. The fourth chapter examines a forty year old large-scale investment in Uganda to understand long-term impacts, especially regarding technological and organisational innovation, as well as institutional change. Using an institutional economic analysis, changes at the organisational structure of the investment can be related to broader changes in the surrounding rural economy, indicating the significant impact a LSLAs can have on rural transformation. Again, the investment has overall contributed to poverty reduction, but organisational flaws and the collapse of a contract farming scheme indicate the difficulties to govern the large farm well. The emergence of a land market for wetlands, adoption of rice as a new crop and organisational improvements among smallholders can be considered as major outcomes of the investment’s activities. The fifth chapter synthesises the early three empirical chapters and locates the findings within a broader set of trends regarding the commercialisation of the agri-food system, the discussion on optimal farm size for production and poverty reduction, and the importance of functioning land and labour markets for poverty reduction and rural transformation in developing economies.

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    Land degradation in this dataset is defined as the persistent reduction or loss of land ecosystem services, notably the primary production service. The long-term trend of inter-annual mean Normalized Difference Vegetation Index (NDVI), over the period 1982–2006, is used as a proxy for the persistent decline or improvement in the Net Primary Productivity (NPP) of land, thereby delineating land degradation hotspots. The Global Inventory Modelling and Mapping Studies (GIMMS) dataset of 64 km2-resolution of NDVI data employed has been corrected for rainfall variation effect and atmospheric fertilization effect in addition to the masking of ineligible pixels. The data is used to calculate the area of NDVI decline in km2 and in percentages for corresponding land covers. The dataset provided contains different files (GIS files, a table and a report). The report,"BIOMASS PRODUCTIVITY-BASED MAPPING OF GLOBAL LAND DEGRADATION HOTSPOTS", contains a detailed description of how the global land degradation hotspots, based on biomass productivity, were identified. A summary of the “ground truthing” methods is also presented. The GIS files map the global land degradation hotspots versus main land cover/use types. In addition, the GIS files map the areas with above ground biomass improvement. The area (km2) of long-term (1982-2006) NDVI decline (with correction of RF and AF effects and masking of saturated NDVI zone) versus main land cover/use types counted for each country are then presented in the excel table.

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    In four kebeles (smalles administrative unit in Ethiopia: Bonda Megela, Gaba, Wabo, Wangene) in Oromia district gender-disaggregated focus group discussions on socio-economic aspects of farming communities were conducted. Aspects have been the institutional network of the village (with the help of the Venn Diagram tool, income and livelihood sources (with land, without land, with irrigation, without irrigation) with a focus on cash and food crops and vegetable production, market access, marketing structure and prices, land titles and inheritance arrangements, role of extension services, access to credit, contractfarming and future plans of children. Discussions were part of the NutriHAF project, which aims at diversifying diets and livelihoods through the promotion of multi-storey cropping in biosphere hotspots in Ethiopia and Madagascar.