An evidence-based approach for setting desired state in a complex Great Barrier Reef seagrass ecosystem: a case study from Cleveland Bay

Implementing management actions to achieve environmental outcomes requires defining and quantifying ecological targets, but this is a complex challenge, and there are few examples of how to quantitatively set them in complex dynamic marine ecosystems. Here we develop a methodology to devise 'desired state' for tropical seagrasses in Cleveland Bay, northern Australia, in the Great Barrier Reef World Heritage Area. Analysis of diverse species assemblages was used to define seagrass communities as indicators of the region's ecological value. Multivariate regression trees assigned 8000 observations of species presence/absence and habitat characteristics from 2007 to 2017 into seven community types. Generalized Linear Models were used to assess annual variation in above-ground biomass of each seagrass community. Reference subsets of the data expressing high biomass and spatial extent were identified, and desired state was defined as the mean and 95% confidence intervals. This approach rests on the assumption that seagrass resilience and its ecosystem services are met when the diverse seagrass communities reach desired state. This method required a data set that spanned a range in seagrass conditions, but which may have been compromised by a history of pressures. Our method for defining desired state provides evidence-based targets that can be used within an adaptive management framework that prioritises and implements management actions