NESP MaC Project 1.29 a – Great Reef Census: a case study to integrate citizen science data into research output for marine habitat management (2022) (Citizens of the Great Barrier Reef)

This record provides an overview of the NESP Marine and Coastal Hub small-scale study - NESP MaC Project 1.29 a: Great Reef Census - a case study to integrate citizen science data into research output for marine habitat management". For specific data outputs from this project, please see child records associated with this metadata.

To maximise our understanding of our marine and coastal environment, we need to take advantage of emerging technologies and approaches. This includes citizen science, community monitoring and Indigenous Rangers. Technology has greatly reduced the gap between mainstream science and community science to the point they may become almost identical in some integrated programs, especially when involving collection of in-field information. The challenge for science is to integrate with the vast opportunities afforded by this congruence.
The Great Reef Census (GRC) is an established citizen science innovation project, designed to pilot new ways of capturing reconnaissance citizen science data. By using citizen scientists to both collect and analyse reef images, as well as a team of professional scientists to ensure program rigour, the project is an innovative approach to assessing Great Barrier Reef health that complements and enhance existing monitoring programs.

The aim of this project is to demonstrate a citizen science approach can effectively fill gaps in knowledge when assessing marine habitats to improve management outcomes. As a case study, it will demonstrate how citizen science data can be integrated into the monitoring programs across Australia’s marine and coastal environments using new digital technology platforms. The project will also complement ongoing GBR-based research and provide critical knowledge gaps through end-user engagement with GBRMPA’s CoTS Control Program and Australia’s reporting on the health of the GBR.

Our study will 1) scrutinise, validate and synthesize expert versus citizen scientist analyses of geo-referenced images collected during the Great Reef Census Year 1 field campaign and using the analysis platform, and 2) explore a re-structured online analysis platform that integrates machine learning and citizen science to extract more output from a growing image library collected during field efforts. The end product will provide a case-study evaluation of the benefits and capability of citizen-science programs as well as assisting decision-making capacity based on real-time broad spatial scale information on the Great Barrier Reef. The output will provide a demonstrated case study of meaningful citizen science application to assess marine habitats which can be applied more broadly to tropical marine habitats.

Planned Outputs
• Synthesis R data package
• Final technical report with analysed data and a short summary of recommendations for policy makers of key findings [written]