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Learning by doing: a participatory methodology for systematization of experiments with agroforestry systems, with an example of its application
Participatory research methods have helped scientists to understand how farmers experiment and to seek partnerships with farmers in developing technologies with enhanced relevance and adoption. This paper reports on the development of a participatory methodology to systematize long-term experimentat...
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Published in: | Agroforestry systems 2012-06, Vol.85 (2), p.247-262 |
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Main Authors: | , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Participatory research methods have helped scientists to understand how farmers experiment and to seek partnerships with farmers in developing technologies with enhanced relevance and adoption. This paper reports on the development of a participatory methodology to systematize long-term experimentation with agroforestry systems carried out in a hotspot of biodiversity by non-governmental organizations and local farmers. A methodological guide for systematization and techniques used for Participatory Rural Appraisal formed the basis of our work. We propose an analytical framework that recognizes systems of reflexive and learning interactions, in order to make the learned lessons explicit. At the process level, the main lessons and recommendations are as follows. It is important to establish partnerships to conduct innovative and complex experimentation with agroforest. Participatory systematization allows us to improve the methodological aspects of design, implementation and management of on-farm participatory experimentation. It also serves to synthesize the main findings and to extract lessons from agroforestry systems experiments. It fosters the technical improvement of agroforestry systems. It creates possibilities for reflection on agroforestry systems by farmers, extensionists and researchers, as well as their learning with respect to management of such systems. The findings are placed in the context of current theory on participatory experimentation in agriculture. Extractive and interactive approaches help to produce rich insights of mutual interest through collaboration by identifying local, regional and global convergences, complementarities, and conflicts of interest; which affect the advance of new eco-friendly technologies, to both improve the livelihoods and to reverse biodiversity loss and environmental degradation. |
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ISSN: | 0167-4366 1572-9680 |
DOI: | 10.1007/s10457-012-9498-4 |