Incorporating uncertainty in Indigenous sea Country monitoring with Bayesian statistics: Towards more informed decision-making

Katherine Cure, Diego R. Barneche, Martial Depczynski, Rebecca Fisher, David J. Warne, James McGree, Jim Underwood, Frank Weisenberger, Elizabeth Evans-Illidge, Brendan Ford, Daniel Oades, Azton Howard, Phillip McCarthy, Damon Pyke, Zac Edgar, Rodney Maher, Trevor Sampi, Kevin Dougal

Research output: Contribution to journalArticlepeer-review

Abstract

Partnerships in marine monitoring combining Traditional Ecological Knowledge and western science are developing globally to improve our understanding of temporal changes in ecological communities that better inform coastal management practices. A fuller communication between scientists and Indigenous partners about the limitations of monitoring results to identify change is essential to the impact of monitoring datasets on decision-making. Here we present a 5-year co-developed case study from a fish monitoring partnership in northwest Australia showing how uncertainty estimated by Bayesian models can be incorporated into monitoring management indicators. Our simulation approach revealed there was high uncertainty in detecting immediate change over the following monitoring year when translated to health performance indicators. Incorporating credibility estimates into health assessments added substantial information to monitoring trends, provided a deeper understanding of monitoring limitations and highlighted the importance of carefully selecting the way we evaluate management performance indicators.

Original languageEnglish
Pages (from-to)746-763
Number of pages18
JournalAmbio
Volume53
Issue number5
DOIs
Publication statusPublished - May 2024

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