It draws on the experience of the author with regard to socio-economic surveys carried out in Kenya and elsewhere in East Africa. It considers problems in sampling, farmers' responses, the interview situation, survey staff, and various problems with regard to recording accuracy and data processing. The paper concludes by noting 20 key aspects that should be taken into account when designing surveys. These include: (1) careful selection and training of staff; (2) the importance of learning the farming systems in advance; (3) where possible to choose farmers for whom the key parameters are known from other sources; (4) utilize at least one full time supervisor resident in the survey area with independent transport; and (5) allow two thirds of the total period for activities other than the field survey, ie. data processing.
This paper discusses two related questions: Are research results usable? Are the data actually used in decision-making? Both are determined by the researcher's choice of research methodology. The links between choice of research methodology and the application of results is discussed through a simple conceptual model. A satisfactory link requires a decision to allocate part of research capacity to the evaluation of previous research. To demonstrate the difficulties involved in rigorous analysis, a case study of ten years of research for agricultural development in three East African countries (Uganda, Kenya, Tanzania) is reviewed. Deficiencies in agricultural planning and in applied research for agricultural development are discussed in detail. The causes of ineffective applied research are viewed as lying in scientific culture. An example of applied research with implemented solutions is given, emphasising the benefits of participant research and management procedures for planning.
This paper emphasises the importance of understanding agroecosystems by employing cross-disciplinary approaches and drawing on of farmers' knowledge where appropriate. The systems approach and procedures for agroecosystem analysis are outlined. Pattern analysis (of time, space, flows and decision-making) are considered. The paper focuses on key questions which arise in the process of system definition, pattern analysis and discussion of system properties. These concepts are illustrated diagramatically throughout.
This paper presents agroecosystem analysis as a methodology for dealing with the complex interactions of agriculture and environment, and suggests that they should be understood as holistic systems. In contrast to farming systems research and integrated rural development approaches, the agroecosystem analysis approach developed here can deal with all levels in the hierarchy of agroecosystems, and focuses on trade-offs between different measures of performance. The linkages between agriculture and ecology, and key properties of agroecosystems are discussed. The key concepts and assumptions of agroecosystem analysis are introduced. This method of analysis is best conducted in multidisciplinary workshops. Pattern analysis (across space and time, of flows and decisions) is explained. Further sections deal with agroecosystem design, and technology assessment and development for a variety of situations, including pest management, multiple cropping, agroforestry, crop-livestock polyculture, soil ecology, social forestry, and non-agricultural production. The final section deals with implementation.
The chapter describes the procedure known as Agroecosystem Analysis. This rests on the assumption that analysis, understanding and approaches to improvement of an agroecosystem are best gained from strategic knowledge of that system, as opposed to an attempt to create a complete model. The analysis is based on a week-long workshop aimed at sythesising the approaches of people from different disciplines and attaining useful data from case-study sites. The object of such a workshop is to create key questions concerning an agroecosystem and to stimulate research into answers to those questions.
This book presents agroecosystem analysis as a methodology for dealing with the complex interactions of agriculture and environment. The first chapter discusses these linkages, and suggests that they should be understood as systems, whose analysis requires multidisciplinarity. In contrast to farming systems research and integrated rural development approaches, the agroecosystem analysis approach developed in the rest of this book can deal with all levels in the hierarchy of agroecosystems, and focuses on trade-offs between different measures of performance. The key concepts behind this approach are introduced in Chapter 2. Chapter 3 discusses agroecosystem analysis for research. Processes and stages of research exercises using this approach are explained. Chapter 4 discusses agroecosystem analysis for development action. The procedures are modified to make it action focused and less time consuming. This involves adoption of RRA methods which are introduced. The final chapter discusses challenges for agroecosystem design, technology assessment and development and implementation which arise from agroecosystem analysis.
Contains sections on the following: what is wealth ranking; why is wealth ranking needed; background work needed before carrying out wealth ranking; actual informant ranking; computing the actual score and grouping; an example of wealth ranking from Maasailand, Kenya, and from Meru district, Kenya; and finally, gives some suggested further reading. An appendix contains a check-list to help those wishing to carry out a wealth ranking exercise.
This mimeo is an appendix from a volume on farmers attitudes to forest plantation and conservation farming. It is noted that surveys are often accepted as being statistically more precise (though not necessarily accurate) that RRA. But surveys cannot tell stories about how variables are related. RRA offers this sort of understanding in a short space of time, being open-ended and flexible. It asks how should the two be combined? In an experiment, RRA was used to refine questions for a formal survey. Both methods are identified as having their advantages, and disadvantages which are discussed. Details of the experiment, relating to the use of forest resources, are given. Particular attention is paid to the style and use of questions in the survey as compared to RRA, especially sensitive questions. Some methodological conclusions are drawn.
New agricultural technologies are often inappropriate to the needs of small farmers because scientists lack information about their needs and objectives. The IPRA method is a set of procedures which has been developed to put technology designers in regular contact with small farmers so they can better exchange information which will orient research to real needs. Farmers and scientists learn from each other and work together to identify problems, plan experiments and evaluate solutions. The aim is to mobilise the expertise and resourcefulness of small farmers so they can be active partners in agricultural research. The DVD demonstrates the various stages of the IPRA method as carried out in a village in rural Colombia. During first contacts with the villagers a rapport was established as the researchers attempted to carry out routine village tasks (09). Diagnostic meetings were then held for farmers to discuss common problems and the scope for improvement (10). When the farmers priorities had been established the researchers suggested new plant varieties, fertilisers and other components. The various options were considered for testing by the farmers (13). The farmers and researchers agreed on the components of the field trials and the same trial was conducted on several farms to obtain comparative results (14). The standing crop and the harvest were assessed by the farmers (17), and their families participated in evaluating samples of the products for flavour, quality and texture (18).