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Experiential Knowledge Complements an LCA-Based Decision Support Framework

Author

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  • Heng Yi Teah

    (Graduate Program in Sustainability Science, Global Leadership Initiative (GPSS-GLI), Division of Environmental Studies, Graduate School of Frontier Sciences, The University of Tokyo, 332 Building of Environmental Studies, 5-1-5 Kashiwanoha, Kashiwa City, Chiba 277-8563, Japan)

  • Yasuhiro Fukushima

    (Department of Chemical Engineering, Graduate School of Engineering, Tohoku University, 6-6-07, Aramaki Aza Aoba, Aoba-ku, Sendai, Miyagi 980-8579, Japan)

  • Motoharu Onuki

    (Graduate Program in Sustainability Science, Global Leadership Initiative (GPSS-GLI), Division of Environmental Studies, Graduate School of Frontier Sciences, The University of Tokyo, 332 Building of Environmental Studies, 5-1-5 Kashiwanoha, Kashiwa City, Chiba 277-8563, Japan)

Abstract

A shrimp farmer in Taiwan practices innovation through trial-and-error for better income and a better environment, but such farmer-based innovation sometimes fails because the biological mechanism is unclear. Systematic field experimentation and laboratory research are often too costly, and simulating ground conditions is often too challenging. To solve this dilemma, we propose a decision support framework that explicitly utilizes farmer experiential knowledge through a participatory approach to alternatively estimate prospective change in shrimp farming productivity, and to co-design options for improvement. Data obtained from the farmer enable us to quantitatively analyze the production cost and greenhouse gas (GHG) emission with a life cycle assessment (LCA) methodology. We used semi-quantitative graphical representations of indifference curves and mixing triangles to compare and show better options for the farmer. Our results empower the farmer to make decisions more systematically and reliably based on the frequency of heterotrophic bacteria application and the revision of feed input. We argue that experiential knowledge may be less accurate due to its dependence on varying levels of farmer experience, but this knowledge is a reasonable alternative for immediate decision-making. More importantly, our developed framework advances the scope of LCA application to support practically important yet scientifically uncertain cases.

Suggested Citation

  • Heng Yi Teah & Yasuhiro Fukushima & Motoharu Onuki, 2015. "Experiential Knowledge Complements an LCA-Based Decision Support Framework," Sustainability, MDPI, vol. 7(9), pages 1-16, September.
    • Handle: RePEc:gam:jsusta:v:7:y:2015:i:9:p:12386-12401:d:55534
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    References listed on IDEAS

    as
    1. Tom MacMillan & Tim G. Benton, 2014. "Agriculture: Engage farmers in research," Nature, Nature, vol. 509(7498), pages 25-27, May.
    2. Matthias Finkbeiner & Erwin M. Schau & Annekatrin Lehmann & Marzia Traverso, 2010. "Towards Life Cycle Sustainability Assessment," Sustainability, MDPI, vol. 2(10), pages 1-14, October.
    3. Volker Hoffmann & Kirsten Probst & Anja Christinck, 2007. "Farmers and researchers: How can collaborative advantages be created in participatory research and technology development?," Agriculture and Human Values, Springer;The Agriculture, Food, & Human Values Society (AFHVS), vol. 24(3), pages 355-368, September.
    4. Torkamani, Javad, 2005. "Using a whole-farm modelling approach to assess prospective technologies under uncertainty," Agricultural Systems, Elsevier, vol. 85(2), pages 138-154, August.
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    Cited by:

    1. Heng Yi Teah & Tomohiro Akiyama & Ricardo San Carlos & Orlando Vargas Rayo & Yu Ting Joanne Khew & Sijia Zhao & Lingfeng Zheng & Motoharu Onuki, 2016. "Assessment of Downscaling Planetary Boundaries to Semi-Arid Ecosystems with a Local Perception: A Case Study in the Middle Reaches of Heihe River," Sustainability, MDPI, vol. 8(12), pages 1-11, November.

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