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Integrated Assessment of Health and Sustainability of Agroecosystems - Chapter 9 pdf

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This work demonstrates that a holistic approach to investigating agroeco-system health AESH and beginning to implement sustainable processes for AESH improvement is feasible even with co

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1 This work demonstrates that a holistic approach to investigating agroeco-system health (AESH) and beginning to implement sustainable processes for AESH improvement is feasible even with complex field situations

2 Communities were able to use the concept of health to discuss and model approaches to improve their livelihoods The approach provides a simple, yet highly specialized language—understood by the communities, researchers, extension agents, development agents, and policymakers—for discussing issues relating to AESH and sustainability

3 Although remarkably similar to traditional methods of integrated commu-nity development, the AESH framework is based on the principles of sys-tems theory and practice, participatory and action research methods, and conventional research methods combined into a transdisciplinary frame-work The AESH framework as applied in this study is a metaphor to struc-ture how people think about their actions—social or economic—and their implication on the biophysical world to improve their own well-being and

to conserve the natural resource base on which their survival depends

4 A unique feature in this process was that communities, researchers, and development agents played complementary roles While the communities’ role was crucial to understanding the system and in defining the criteria for health, the role of the researchers as experts in methods and that of the development and extension agent as subject experts was critical to the over-all success of the project

5 Cognitive maps, graph theory, and pulse process models were useful in analyzing community perceptions of factors that influence AESH and sus-tainability That communities easily understood and applied cognitive maps

to depict their perceptions combined with the fact that the cognitive maps were largely in agreement with findings from the participatory workshops indicate the potential of this method In an action research process, cogni-tive maps can be reevaluated and updated in each action research cycle

as the local theory develops In this way, they can serve as a record of the developing local theory, an analytical tool, and a means for assessing new goals and objectives

6 Rich pictures were useful in helping communities to analyze the different perspectives that existed on a problem situation and in guiding consensus building, negotiation, and compromise

7 Communities used the information derived using indicators to reevaluate their action plans, objectives, and goals This demonstrates the success of the AESH approach in operationalizing the concepts of AESH and sustainability and in incorporating them into the decision-making processes of the communities

© 2009 by Taylor & Francis Group, LLC

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204 Integrated Assessment of Health and Sustainability of Agroecosystems

8 Technical improvements, such as geographical information systems and remote sensing, self-reporting systems, and automated and integrated com-puter-based data-gathering techniques, would be needed to make indicator data more reliable and cost-effective in the long term

9 Both community-driven and researcher-based indicators were useful because the two suites provided complementary but fundamentally differ-ent information Because communities often lack the capacity to develop and measure quantitative indicators, while researchers and policymakers lack the knowledge and mandate to make value-based judgments, it seems that decision support systems for such integrated and adaptive approaches

as sustainability and AESH should include both components to provide a balanced assessment

10 MCA (multiple correspondence analysis) was useful in summarizing and presenting indicator data for two reasons: (1) the incorporation of targets and thresholds in the process of categorizing the indicators, thus providing

an intuitive interpretation, and (2) projection of data from the initial and subsequent measurements into a multidimensional space

© 2009 by Taylor & Francis Group, LLC

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