Geospatially enabled modelling of values and decisions in agro-ecological landscapes

Effective resource management requires an understanding of the complex associations that occur between natural ecosystems, managed environments, and a variety of economic, social and political factors. Many aspects of resource management are location dependent. They are defined or affected by physical aspects of the immediate or proximal environment, by statutory or legal aspects of the immediate or proximal location, by economic values associated with location, or by relationships with a potentially large variety of policies that create rights, responsibilities, risks or opportunities associated with location, or with attributes that are associated with location. This study explores the capacity to geospatially enable the representation, analysis and communication of values that inform decision making in complex agro-ecological landscapes. Integrated ecological economic modelling provides one framework in which to account for these various and complex interconnections and interactions. The research begins with a review of spatially enabled integrated ecological economic models to reveal the state-of-the-art and the knowledge gap. A spatially enabled model is then designed to close the knowledge gap and is implemented in software as a tool for application to the analysis of decisions that lead to changes in land use. In order to demonstrate the utility of the model and its implementation, a model farm is constructed that exhibits a variety of land capability and land uses typical of a farm within the Tasmanian Midlands region, Australia. Historical land use records are used to develop land use change scenarios and a semi-structured stakeholder survey is used to collect stakeholder values with which to populate the model. Outputs from this case study show how complex spatial and a-spatial data can be integrated and modelled, to deliver valuable information, to communicate that information both quantitatively and visually in order to inform policy processes. This study contributes to the development of models that can be used in complex decision-making settings and that have capacity to be catalysts for, and to inform and support, dialogue between interested parties, supported by spatial reasoning, and providing for socially, environmentally and economically acceptable solutions.