Sustainable Intensification of Agriculture in Victoria’s Food Bowl: Optimizing Productivity with the use of Decision-Support Tools

Authors: M. Johnson, R. Faggian, V. Sposito

Abstract:

A participatory and engaged approach is key in connecting agricultural managers to sustainable agricultural systems to support and optimize production in Victoria’s food bowl. A sustainable intensification (SI) approach is well documented globally, but participation rates amongst Victorian farmers is fragmentary, and key outcomes and implementation strategies are poorly understood. Improvement in decision-support management tools and a greater understanding of the productivity gains available upon implementation of SI is necessary. This paper reviews the current understanding and uptake of SI practices amongst farmers in one of Victoria’s premier food producing regions, the Goulburn Broken; and it spatially analyses the potential for this region to adapt to climate change and optimize food production. A Geographical Information Systems (GIS) approach is taken to develop an interactive decision-support tool that can be accessible to on-ground agricultural managers. The tool encompasses multiple criteria analysis (MCA) that identifies factors during the construction phase of the tool, using expert witnesses and regional knowledge, framed within an Analytical Hierarchy Process. Given the complexities of the interrelations between each of the key outcomes, this participatory approach, in which local realities and factors inform the key outcomes and help to strategies for a particular region, results in a robust strategy for sustainably intensifying production in key food producing regions. The creation of an interactive, locally embedded, decision-support management and education tool can help to close the gap between farmer knowledge and production, increase on-farm adoption of sustainable farming strategies and techniques, and optimize farm productivity.

Keywords: Agriculture, decision-support management tools, GIS, sustainable intensification.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1316544

References:

[1] ABS, 7503.0 - Value of Agricultural Commodities Produced, Australia, 2015-16. Australian Bureau of Statistics, Australia, 2017.
[2] ABS, 7121.0 - Agricultural Commodities, Australia, 2015-16. Australian Bureau of Statistics, Australia, 2017.
[3] CSIRO, CMIP5 global climate model outputs and derived outputs. CSIRO and Bureau of Meteorology, Australia, 2015.
[4] CSIRO, Climate Change in Australia Information for Australia’s Natural Resource Management Regions: Technical Report. Australia, 2015.
[5] J. J. Nay, M. Abkowitz, E. Chu, D. Gallagher, and H. Wright, “A review of decision-support models for adaptation to climate change in the context of development,” Clim. Dev., vol. 6, no. 4, pp. 357–367, Oct. 2014.
[6] B. M. Campbell, P. Thornton, R. Zougmoré, P. van Asten, and L. Lipper, “Sustainable intensification: What is its role in climate smart agriculture,” Curr. Opin. Environ. Sustain., vol. 8, pp. 39–42, 2014.
[7] Y. Gadanakis, R. Bennett, J. Park, and F. J. Areal, “Evaluating the Sustainable Intensifications of arable farms,” J. Environ. Manage., vol. 150, pp. 288–298, 2015.
[8] T. Garnett et al., “Sustainable Intensification in Agriculture: Premises and Policies,” Sci. Mag, vol. 341, pp. 33–34, 2013.
[9] V. Ferretti and S. Pomarico, “Ecological land suitability analysis through spatial indicators: An application of the Analytic Network Process technique and Ordered Weighted Average approach,” Ecol. Indic., vol. 34, pp. 507–519, 2013.
[10] V. Sposito, R. Faggian, H. Romeijn, and M. Downey, “Expert Systems Modeling for Assessing Climate Change Impacts and Adaptation in Agricultural Systems at Regional Level,” Open J. Appl. Sci., vol. 3, pp. 369–380, 2013.
[11] R. W. Saaty, “The analytic hierarchy process—what it is and how it is used,” Math. Model., vol. 9, no. 3, pp. 161–176, 1987.
[12] H. Romeijn, R. Faggian, V. Diogo, and V. Sposito, “Evaluation of Deterministic and Complex Analytical Hierarchy Process Methods for Agricultural Land Suitability Analysis in a Changing Climate,” ISPRS International Journal of Geo-Information, vol. 5, no. 6. 2016.
[13] D. C. Rose et al., “Decision support tools for agriculture: Towards effective design and delivery,” Agric. Syst., vol. 149, pp. 165–174, Nov. 2016.
[14] R. Faggian, M. Johnson, V. Sposito, and H. Romeijn, Climate Smart Agricultural development in the Goulburn Broken Region - Technical Report: Fruit Production. Melbourne, 2016.
[15] R. Faggian, M. Johnson, V. Sposito, and H. Romeijn, Climate Smart Agricultural development in the Goulburn Broken Region - Technical Report: Vegetable Production. Melbourne, 2016.
[16] R. Faggian, M. Johnson, V. Sposito, and H. Romeijn, Climate Smart Agricultural development in the Goulburn Broken Region - Technical Report: Pasture Production. Melbourne, 2016.
[17] ABS, 7121.08 - Farm Management and Demographics, Australia - 2015-16. Australian Bureau of Statistics, Australia, 2017.
[18] S. Anthony et al., Landscape Typology - A Framework for Prioritisation of Sustainable Intensification Strategies. Report for Defra project LM0302 Sustainable Intensification Research. UK, 2016.
[19] D. Rose, L. Dicks, W. Sutherland, C. Parker, M. Lobley, and S. Twining, Identifying the characteristics of effective decision support and guidance systems in the context of integrated farm management. UK, 2016.