Adaptive sampling using multi-sensor fusion: Marine biodiversity assessments using eDNA metabarcoding and acoustic sensor data

Abstract To achieve the aims of the Convention on Biological Diversity’s 2030 Global Biodiversity Framework, marine legislation and management requires the use of cost- and time- effective monitoring of indicator species. Marine observation platforms, which are increasing in popularity globally, are used for such monitoring activities. These platforms allow data to be collected from a variety of sensors simultaneously, providing the opportunity for adapting where and when sampling is performed based on real-time observational data. While some recent monitoring activities are following an adaptive sampling approach, most still employ a more opportunistic method. In this study, we applied an adaptive sampling approach to detect calanoid copepods at seasonally contrasting time points using real-time acoustic sensor data, traditional plankton net sampling, and eDNA metabarcoding. We demonstrate that there are ways to move from sampling opportunistically to a more adaptive sampling approach for more cost- and time- effective monitoring of indicators.