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    Managing uncertainty, ambiguity and ignorance in impact assessment by embedding evolutionary resilience, participatory modelling and adaptive management

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    Date
    2015
    Author
    Bond, Alan
    Morrison-Saunders, Angus
    Pope, Jenny
    Retief, Francois
    Gunn, Jill A.E.
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    Abstract
    In the context of continuing uncertainty, ambiguity and ignorance in impact assessment (IA) prediction, the case is made that existing IA processes are based on false ‘normal’ assumptions that science can solve problems and transfer knowledge into policy. Instead, a ‘post-normal science’ approach is needed that acknowledges the limits of current levels of scientific understanding. We argue that this can be achieved through embedding evolutionary resilience into IA; using participatory workshops; and emphasising adaptive management. The goal is an IA process capable of informing policy choices in the face of uncertain influences acting on socio-ecological systems. We propose a specific set of process steps to operationalise this post-normal science approach which draws on work undertaken by the Resilience Alliance. This process differs significantly from current models of IA, as it has a far greater focus on avoidance of, or adaptation to (through incorporating adaptive management subsequent to decisions), unwanted future scenarios rather than a focus on the identification of the implications of a single preferred vision. Implementing such a process would represent a culture change in IA practice as a lack of knowledge is assumed and explicit, and forms the basis of future planning activity, rather than being ignored
    URI
    http://hdl.handle.net/10394/18666
    https://doi.org/10.1016/j.jenvman.2014.12.030
    https://www.sciencedirect.com/science/article/pii/S0301479714006094
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