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

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

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  • Media type: E-Article
  • Title: Incorporating uncertainty in Indigenous sea Country monitoring with Bayesian statistics: Towards more informed decision-making
  • Contributor: Cure, Katherine; Barneche, Diego R.; Depczynski, Martial; Fisher, Rebecca; Warne, David J.; McGree, James; Underwood, Jim; Weisenberger, Frank; Evans-Illidge, Elizabeth; Ford, Brendan; Oades, Daniel; Howard, Azton; McCarthy, Phillip; Pyke, Damon; Edgar, Zac; Maher, Rodney; Sampi, Trevor; Dougal, Kevin; Bardi Jawi Traditional Owners
  • Published: Springer Science and Business Media LLC, 2024
  • Published in: Ambio, 53 (2024) 5, Seite 746-763
  • Language: English
  • DOI: 10.1007/s13280-024-01980-2
  • ISSN: 1654-7209; 0044-7447
  • Origination:
  • Footnote:
  • Description: AbstractPartnerships 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.