Stressors of different nature are affecting coastal ecosystems. Yet their combined impacts on biodiversity are poorly understood because the majority of studies focuses on the impact of a single stressor and traditional monitoring approaches are often limited to a small number of taxa. Therefore, more integrated approaches are needed. Environmental DNA (eDNA) is now recognized as a powerful tool for obtaining comprehensive and standardized biodiversity surveys. Here, we propose to combine eDNA biomonitoring data with field measures of anthropogenic pressures into cutting-edge statistical models allowing to disentangle effects of each stressor on communities and identify key stressors.
Three estuaries, subjected to different types of disturbances, have been studied in Northern Queensland, Australia. At each sampling location, water and sediment samples were collected for eDNA analyses along with a suite of environmental contaminant measures (nutrients, pesticides...). Several taxonomic groups of interest (from diatoms to fish) were targeted for characterizing community composition.
Results/Conclusions
Although response differs between taxa, results show strong responses of communities to disturbance levels, not necessarily in term of diversity but rather community composition. This pattern was particularly important for small organisms (e.g. diatoms). These data are then combined into Bayesian Network Relative Risk Models that weights the relative importance of stressors on specified endpoints (here, biodiversity metrics and relative proportion of taxonomic groups), and rank their importance in each location. This information will be further used to make predictive models and explore management scenarios.
The notion of studying a single stressor on a small number of taxa is now out-dated. This research aims to provide a proof-of-concept for the integration of eDNA biodiversity data into ecological risk assessment models at a scale relevant for managers. This approach can provide comprehensive information on biological communities as well as key information for guiding management actions.