This paper reports on the experimental design process and considerations of a choice experiment conducted in collaboration with farmers in northern Australia. The purpose of the research is to inform the design of effective and efficient payments-for-ecosystem services schemes to safeguard north Australia’s biodiversity values. It promotes the contractual provision of biodiversity conservation services by farmers, in particular pastoralists operating in Australia’s tropical savannas.The paper focuses on the discrete choice experimental (DCE) aspects. The DCE is employed to estimate farmers’ preference heterogeneity for supplying ecosystem services, specifically their willingness to accept remuneration for the on-farm conservation of biodiversity, based on potential programme attributes. The design of the choice experiment draws on best practice standards (Hoyos, 2010), a recognition of the benefits of embedding design in a consultative process (Klojgaard et al., 2012) and recent advances in accounting for response certainty (Brouwer et al., 2010; Hensher et al., 2012).DCE design decisions relating to attribute selection, attribute levels, alternatives and choice tasks are explained based on literature, focus group discussions, expert input and an iterative process of Bayesian D-efficient DCE design. Additional design aspects include measuring choice certainty and stated attribute attendance, embedding the DCE within a discrete-continuous approach, capturing relevant respondent-related attributes with socio-economic-psychological questions and scales, and devising appropriate data collection logistics

The Pastoral Properties Futures Simulator (PPFS) is a dynamic systems model, developed within a participatory action research partnership with the pastoral industry of Australia's Northern Territory. The model was purpose-built to support the industry's strategic planning capacity in the face of environmental, market and institutional uncertainty. The mediated modelling process sought to maximise social learning of industry stakeholders. Simulations were conducted using scenarios representing combinations of climatic, market, institutional and technological assumptions. Stochastic parameters included rainfall and product prices. Economic and environmental performance of model farms, including greenhouse gas emissions, were estimated. A critical evaluation of the tool finds the PPFS fit for purpose. However, limitations include lack of output validation, small number of scenarios and simplistic treatment of environmental impact dimensions. With further development, the PPFS can provide a platform (a) to assist with industry planning across the whole of Northern Australia and beyond, and (b) for policy analysis and development in the context of the Australian pastoral industry