Improving interdisciplinary collaboration in bio-economic modelling for agricultural systems. (March 2016)

• Record Type: Journal Article
• Authors: Kragt, M.E.; Pannell, D.J.; McVittie, A.; Stott, A.W.; Vosough Ahmadi, B.; Wilson, P.
• Is Part Of: Agricultural systems. Volume 143(2015)
• Page Start: 217
• Page End: 224
• Publication Date: 2016-03
• Subjects: Interdisciplinary research -- Integrated modelling -- Bioeconomics -- Agricultural economics -- Farm systems; Q51 -- Q57; Agricultural systems -- Periodicals; Agriculture -- Environmental aspects -- Periodicals; 338.16
• DOI: 10.1016/j.agsy.2015.12.020
• Languages: English
• ISSNs: 0308-521X

Abstract

Abstract: Interest in models that integrate biophysical and economic components of agri-environmental systems has increased, largely in recognition of the multiple services provided by agri-environmental systems and reflecting the complexity of 'multi-functional' agriculture. We discuss the challenges of bio-economic modelling projects where biophysical and social-science research is integrated. Specific interdisciplinary challenges arise from, for example, differences in language and system understanding between disciplines, limited rewards for interdisciplinary research in the current academic merit system, and the time demands of interdisciplinary projects. Drawing on the authors' collective experiences in developing and applying bio-economic models, we discuss ways to overcome these challenges. Important lessons for future integrated modelling projects are to invest enough time at the start of the project to align research expectations, recognising the central role of communication, and training research 'integrators' who can facilitate collaboration within interdisciplinary teams. Highlights: Developing bio-economic models with interdisciplinary research teams faces many challenges We discuss key challenges such as cross-disciplinary communication, disparities in types of data, or in scales of analysis We also examine differences in publication strategies and academic merit for interdisciplinary research We suggest short-term practical solutions to improve interdisciplinary collaboration We propose that long-term 'system' changes will be needed to overcome integrated modelling challenges