On the use of socioeconomic typologies for improved integrated management of data-poor regions: explorations from the Australian north

Abstract

Managers operating in data-poor environments are often required to use data from one region to draw inferences about another. The quality of decisions made using this ‘typology’ approach will depend, at least in part, upon the degree of similarity between the two regions. Using data from a variety of sources relating to several different domains in 55 separate catchments in northern Australia, this paper uses statistical clustering techniques to test if it is possible to identify socioeconomically ‘similar’ catchments. It finds that regions which are socioeconomically ‘similar’ are not always adjacent, and that assessment of ‘similarity’ depends upon the type of data used. Evidently, the typology approach offers itself as a useful framework for management, but still requires reliable baseline data with which to construct the typologies.

Keywords:

• cluster analyses
• data gaps
• integrated catchment management
• social impact assessment
• multidimensional scaling

Acknowledgements

We gratefully acknowledge Tropical Rivers and Coastal Knowledge (TRaCK), CSIRO Sustainable Ecosystems Division and James Cook University for funding this study. TRaCK receives major funding for its research through the Australian Government's Commonwealth Environment Research Facilities initiative, the Australian Government's Raising National Water Standards Program, Land and Water Australia and the Queensland Government's Smart State Innovation Fund. We also thank Dr Kostas Alexandridis and Ms Michelle Esparon for assistance with data collection and analyses. Useful comments on earlier drafts were kindly provided by Dr Kirsten Maclean and Ms Ally Lankester.