INTEGRATED OBSERVATION, MONITORING AND PREDICTION ARCHITECTURE FOR FUNCTIONAL BIODIVERSITY OF COASTAL SEAS
DiverSea develops novel marine observation and monitoring technology by combining: 1a) The new DNA-based identification approach “DNA-marks”: This approach will harnesses low coverage/cost genomic data to document genetic diversity and discriminate beyond species, to the population and individual level. This opens revolutionary possibilities, both for environmental samples (eDNA) and for monitoring species key biological parameters beyond simple identification, and, 1b) The experimentation required to quantify uncertainties in marine eDNA/eRNA interpretation, while developing general indictor methods with novel approaches harnessing new approaches and theory on mechanisms of molecular shedding and degradation; 2) emerging molecular techniques and approaches integrated with autonomous systems satellite remote sensing, citizen science, existing monitoring program data collection and, covering EOVs/EBVs, for comprehensive mapping of important marine habitats; 3) A novel data integration processing and interrogation AI-ML architecture that processes incoming biological, physical and biogeochemical data from diverse data platforms and from case studies in (2). The analysis module overarching framework will combine EOVs/EBVs for spatial and temporal biodiversity prediction, gap analysis identifying urgent data needs and investigating causal links/feedbacks between abiotic cycles, multiple stressors, biodiversity dynamics and biogeochemical cycles 5) An interactive platform to communicate the scientific outcomes of DiverSea to policy makers, stakeholders and the general public, the “Biodiversity Services Dashboard”. The dashboard visualizes key environmental and socio-economic indicators with quantified scenarios for societal and functional biodiversity interaction, connections of biodiversity to ecosystem functions and services. This will facilitate evaluating and comparing policy and planning alternatives considering the requirements of different target stakeholders.
DiverSea develops novel marine observation and monitoring technology by combining: 1a) The new DNA-based identification approach “DNA-marks”: This approach will harnesses low coverage/cost genomic data to document genetic diversity and discriminate beyond species, to the population and individual level. This opens revolutionary possibilities, both for environmental samples (eDNA) and for monitoring species key biological parameters beyond simple identification, and, 1b) The experimentation required to quantify uncertainties in marine eDNA/eRNA interpretation, while developing general indictor methods with novel approaches harnessing new approaches and theory on mechanisms of molecular shedding and degradation; 2) emerging molecular techniques and approaches integrated with autonomous systems satellite remote sensing, citizen science, existing monitoring program data collection and, covering EOVs/EBVs, for comprehensive mapping of important marine habitats; 3) A novel data integration processing and interrogation AI-ML architecture that processes incoming biological, physical and biogeochemical data from diverse data platforms and from case studies in (2). The analysis module overarching framework will combine EOVs/EBVs for spatial and temporal biodiversity prediction, gap analysis identifying urgent data needs and investigating causal links/feedbacks between abiotic cycles, multiple stressors, biodiversity dynamics and biogeochemical cycles 5) An interactive platform to communicate the scientific outcomes of DiverSea to policy makers, stakeholders and the general public, the “Biodiversity Services Dashboard”. The dashboard visualizes key environmental and socio-economic indicators with quantified scenarios for societal and functional biodiversity interaction, connections of biodiversity to ecosystem functions and services. This will facilitate evaluating and comparing policy and planning alternatives considering the requirements of different target stakeholders.

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