21 research outputs found
Dynamics of food systems in Sub-Saharan Africa : Implications for consumption patterns and farmersâ position in food supply chains
This paper looks into the dynamics in the food system in SSA countries, describing developments in drivers of the food system, analysing food consumption patterns in selected SSA countries, investigating the pace of change of the regional food retail formats and the impacts it has on how local production is connected to modern food retailers. More specifically, the research objectives are to: Depict the trends in population growth, urbanisation rates, income growth and the food-system environment as drivers of change in dietary patterns; Investigate the trends in food consumption patterns in a range of SSA countries, with attention to differences between urban and rural consumption trends; Illustrate the changing food retail and provisioning system in the SSA region with examples and data from selected countries; Analyse the effects of modernising food systems on small farmersâ position in local and regional supply chains and explore whether dynamics in the SSA food retail structure and consumption patterns have had implications for food import dependency in certain countries in the region
Conservation Costs Drive Enrolment in Agglomeration Bonus Scheme
Agglomeration bonus schemes have become important policy tools when the environmental benefit hinges on spatial coordination of conservation sites. We here analyse how spatial factors affect the uptake of an agglomeration payment scheme in a Swiss mountain region, which seeks to establish a network of conservation areas to conserve favourable conditions for biodiversity. We use a combination of spatially explicit farm census (44,279 parcels) and survey data in a spatially lagged explanatory variable model. In addition, we also consider the collaborative process in establishing the eligibility of parcels for receiving the bonus payment. We find that parcels that are more distant from the farm as well as those at steeper slopes are more likely to enter the scheme. This implies that conservation costs are an important driver of the farmers' decisions. The results remain robust when controlling for a wide range of parcel, farm and farmers' characteristics. The analysis also showed that the collaborative process increased the enrolment of parcels cultivated by larger farmers managing their land more intensively. We conclude that the collaborative process increased the weight given to biodiversity from connecting conservation sites in the planning process of the agglomeration bonus scheme
A framework to assess the resilience of farming systems
Agricultural systems in Europe face accumulating economic, ecological and societal challenges, raising concerns
about their resilience to shocks and stresses. These resilience issues need to be addressed with a focus on the
regional context in which farming systems operate because farms, farmersâ organizations, service suppliers and
supply chain actors are embedded in local environments and functions of agriculture. We define resilience of a farming
system as its ability to ensure the provision of the system functions in the face of increasingly complex and
accumulating economic, social, environmental and institutional shocks and stresses, through capacities of robustness,
adaptability and transformability. We (i) develop a framework to assess the resilience of farming systems, and (ii)
present a methodology to operationalize the framework with a view to Europeâs diverse farming systems. The
framework is designed to assess resilience to specific challenges (specified resilience) as well as a farming systemâs
capacity to deal with the unknown, uncertainty and surprise (general resilience). The framework provides a heuristic to
analyze system properties, challenges (shocks, long-term stresses), indicators to measure the performance of system
functions, resilience capacities and resilience-enhancing attributes. Capacities and attributes refer to adaptive cycle
processes of agricultural practices, farm demographics, governance and risk management. The novelty of the
framework pertains to the focal scale of analysis, i.e. the farming system level, the consideration of accumulating
challenges and various agricultural processes, and the consideration that farming systems provide multiple functions
that can change over time. Furthermore, the distinction between three resilience capacities (robustness, adaptability,
transformability) ensures that the framework goes beyond narrow definitions that limit resilience to robustness. The
methodology deploys a mixed-methods approach: quantitative methods, such as statistics, econometrics and
modelling, are used to identify underlying patterns, causal explanations and likely contributing factors; while qualitative
methods, such as interviews, participatory approaches and stakeholder workshops, access experiential and contextual
knowledge and provide more nuanced insights. More specifically, analysis along the framework explores multiple
nested levels of farming systems (e.g. farm, farm household, supply chain, farming system) over a time horizon of 1-2
generations, thereby enabling reflection on potential temporal and scalar trade-offs across resilience attributes. The
richness of the framework is illustrated for the arable farming system in Veenkoloniën, the Netherlands. The analysis
reveals a relatively low capacity of this farming system to transform and farmers feeling distressed about
transformation, while other members of their households have experienced many examples of transformation
Quantifying and Insuring Extreme Weather Risks in Agriculture: The Role of Remote Sensing and Weather Station Data
Insuring Weather Risks in European Agriculture
Smart insurance designs (e.g. tailoring insurances to the individual farm) and technological progress (e.g. advances in satellite technology) enable improvements in insurance schemes. Spatially and temporally more detailed information as well as better knowledge of the relationship between weather and yields losses can reduce basis risk of insurances. However, the use of new and better data does not automatically lead to better insurance schemes. The SUREâFarm project contributes to the understanding of weather risks and new insurance mechanisms as possible tools to increase the resilience of European agriculture to weather extremes. Therefore, we aim to show how to integrate newly available data sources for different agricultural outputs, namely grassland, crop and dairy production in different European regions. In the four contributions summarised here, we evaluate currently existing index insurance schemes and provide fundamental insights for future developments of index insurances for the crop and livestock sector in Europe. We first summarise and discuss existing indexâbased weather insurances. Second, we investigate the drought risk reduction potential of different drought indicators in two case studies on different crops in Eastern Germany. Third, we examine the relationship between hot and humid weather and milk yield losses for dairy producers in Flanders. © 2020 Agricultural Economics Society and European Association of Agricultural Economist
Satellite support to insure farmers against extreme droughts
Extreme weather events are a major risk to agricultural production. Droughts, for example, can ruin a whole yearâs production despite major investments made by farmers to mitigate their effects. Climate change is expected to increase the frequency and magnitude of extreme weather events, resulting also in increased agricultural drought risks. Coping with droughts is thus paramount for agricultural production and farmersâ income stability.ISSN:2662-135
Index insurances for grasslands â A review for Europe and North-America
Grassland based farming systems are exposed to extreme weather events causing volatile farm incomes. Grazing and lacking yield measurements make it largely impossible to insure grassland production with traditional insurance products. In contrast, index insurance products have the potential to insure grasslands, as their payoff relies on an endogenous index that is highly correlated to, but independent of, the actual grass yield. To support future development of these products, we provide the first systematic overview of 12 index insurances put into practise for grasslands in Europe and North America. Additionally, based on this overview, we present prevailing findings that are important for further research and insurance practitioners. We find that a large diversity of index insurance types is applied in practise, including insurance solutions based on regional yield levels, weather variables or satellite imagery. We reveal separated insurance markets (i.e. country-specific products), which prevent knowledge spillovers and lead to largely isolated product developments. Thus, grassland insurance schemes can be improved by knowledge exchange and combining methods that are applied elsewhere. More specifically, insurances tailored to single farm's risk exposure, the combination of satellite with other geodata (e.g. land use information) or adapting legal specifications that disadvantage some types of insurances can improve an insurance's risk reducing capacity and make grassland based farming systems more resilient to weather extremes. This paper provides an entry point for such process, ensuring the development of efficient measures for farmers to cope with climatic risks