Agricultural decision support systems facilitating co-learning: a case study on environmental impacts of sugarcane production

• Published in: International journal of agricultural sustainability 2011-05, Vol.9 (2), p.322-333
• Main Authors: Thorburn, P.J, Jakku, E, Webster, A.J, Everingham, Y.L
• Format: Article
• Language: English
• Subjects: Agriculture; APSIM; boundary object; case studies; climate variability; Decision making; Decision support systems; Environmental impact; farmers; Great Barrier Reef; learning; natural resource management; nitrogen; nitrogen fertilizers; science and technology studies; social learning; Sugarcane; Sustainability; Sustainable agriculture
• ISSN: 1473-5903; 1747-762X
• DOI: 10.1080/14735903.2011.582359

Decision support systems (DSSs) are one of the ways in which agricultural scientists have attempted to make agricultural systems science more accessible to farmers and to foster innovation. Recently, there has been a shift towards more participatory processes in development and application of DSSs to enhance their end-user use. Apart from increasing adoption, these participatory processes are also likely to enhance co-learning resulting from development/application of DSSs. Learning is a valuable process in increasing sustainability of natural resource management, so the application of DSSs in a learning context can make a contribution to the global challenges faced by agriculture. We developed a framework, using concepts drawn from social studies of science and technology, describing the phases of the participatory DSS development/application process and its likely outcomes. We analysed experiences of participants in a case study exploring more sustainable management of nitrogen fertilizer in sugarcane production in an environmentally sensitive area of northeastern Australia. The data illustrate theoretical constructs underpinning the framework and learning processes within the case study. The framework and case study results demonstrate the value of participatory DSS development/application as a co-learning process, an outcome not traditionally valued by agricultural DSS developers and one that is likely to help address the challenges faced by agricultural sustainability.