Can paddock scale data integration achieve more cost effective outcomes in the Great Barrier Reef? A case study in the Fitzroy Basin. (1st November 2017)

• Record Type: Journal Article
• Authors: Star, Megan; Rolfe, John; East, Miriam; Beutel, Terry; McCosker, Kevin; Ellis, Robin; Darr, Shaun; Coughlin, Tom
• Is Part Of: Journal of environmental management. Volume 202:Part 2(2017)
• Page Start: 461
• Page End: 468
• Publication Date: 2017-11-01
• Subjects: Cost effective -- Prioritisation -- Great Barrier Reef -- Water quality improvement planning -- Grazing; Environmental policy -- Periodicals; Environmental management -- Periodicals; Environment -- Periodicals; Ecology -- Periodicals; 363.705
• DOI: 10.1016/j.jenvman.2017.04.034
• Languages: English
• ISSNs: 0301-4797

Abstract

Abstract: The decline in health of the Great Barrier Reef and the pressure on allocating funds efficiently has increased efforts to prioritise where public funds are invested. The Fitzroy basin and coastal catchments is 152, 000 square kilometres and geographically diverse. Past work has identified that sediment loads leaving the catchment are posing a high risk to the ongoing health of the Reef and that there is a need to prioritise funds to achieve cost effective outcomes. In this paper we aim to present an alternative approach to effective prioritisation of sediment reductions. The approach integrates spatial information regarding the sediment source and process, levels of adoption, bare ground cover, and cost into a function to rank neighbourhood catchments. The results demonstrate the complexity of the issue and the challenge the Fitzroy Basin Association faces when allocating funds. They also illustrate that there are effective opportunities in particular priority areas within the catchment in which on-ground actions could be undertaken, proving it to be a useful approach in prioritising future investments aimed at achieving cost effective sediment reductions to the Reef. Highlights: Sediment reductions are needed to improve water quality to the Great Barrier Reef. Drivers of sediment and cost of reductions are diverse across large catchments. Using spatial information helps predict reductions and costs at a finer scale. Using spatial bio-economic data enables prioritisation of targets and actions.