Technologies like eDNA and metagenomics are revealing unprecedented diversity in the “ocean genome”,¹⁴ aided by sampling programmes such as Tara Oceans.¹⁵ Bio-logging enables remote tracking of animal behaviour,¹⁶ while acoustic sensors are increasingly contributing to biodiversity assessments.¹⁷ Furthermore, machine learning can be used to make sense of vast datasets, for example characterising the functional traits of plankton.¹⁸ There remains a need for consistent identifiers across different kinds of biodiversity data so researchers can make links between databases.

The immense variety of microbial marine life¹⁹ is only now coming to light²⁰ — as are the complex ecosystems found in deep-sea water, as well as on and In the deep seabed.^21,22,23,24 As the climate warms, some species are moving to new areas, creating an urgent need to understand which ones are becoming invasive.²⁵ More broadly, there is a need for more tracking of biodiversity, both to establish baselines and to follow trends as climate change²⁶ and other human impacts mount up.²⁷ Although warming is slower in the deep ocean, research suggests that its biodiversity is no less exposed than that of surface waters because of free-drifting (pelagic) larval stages in many deep-ocean organism life cycles and because of most deep-sea organisms’ adaptation to cold and stable conditions. Indeed, projections indicate that, while mitigation could limit threats to surface biodiversity, deep-ocean biodiversity will face an unavoidable escalation in threat.²⁸ The ongoing threats to ocean biodiversity will limit the potential of marine genetic resource use.