Integrating stakeholder opinions and mapped data to better quantify trade-offs in ecosystem service supply from irrigation development in northern Australia

Robust quantification of changes to the supply of ecosystem services from land and water resource development and the documentation of subsequent trade-offs requires good mapped data. This is because water resource development for new irrigation will have significant impacts on ecosystem services. On the positive side, irrigation development supports agricultural intensification which increases food production and may allow land sparing for enhancing supply of ecosystem services. On the negative side, the changes in land use and the capture and extraction of water from relatively undeveloped ecosystems may have impacts on water quality, aquatic and terrestrial biodiversity, soil provision, and cultural, recreational and amenity services, among others. However, good mapped data is not always available, especially in locations undergoing development.

The Australian and Queensland Governments have contracted CSIRO to investigate the potential trade-offs of water resource development in far north Australia, a geographic area that is relatively under-developed but which has substantial water resources. Both Governments have a strong interest in developing the water resources of remote northern Queensland Rivers for food production to supply growing demands from Asia. The problem we face is that mapped ecosystem service data is limited and the potential development of water resources is highly contested. We therefore propose a methodology that uses Bayesian Belief Networks (BBNs) to elicit stakeholder opinion about the important ecosystem services supplied (and demanded) in the region and the potential impacts to those services from water resource development. We then use the BBN to integrate this stakeholder information with quantitative mapped data where it is available, and identify the trade-offs in supply of ecosystem services following development. Our work is directly relevant to the Mapping, visualisation and data access tools of ecosystem services workshop because we present a method that improves mapped ecosystem services data to support more robust trade-off analyses.