Identifying climate refugia for vulnerable marine ecosystem indicator taxa under future climate change scenarios.

Vulnerable Marine Ecosystems (VMEs) are recognised as having high ecological significance and susceptibility to disturbances, including climate change. One approach to providing information on the location and biological composition of these ecosystems, especially in difficult-to-reach environments such as the deep sea, is to generate spatial predictions for VME indicator taxa. In this study, the Random Forest algorithm was used to model the spatial distribution of density for 14 deep-water VME indicator taxa under current environmental conditions and future climate change scenarios (SSP2-4.

Recovery of deep-sea meiofauna community in Kaikōura Canyon following an earthquake-triggered turbidity flow.

Turbidity flows can transport massive amounts of sediment across large distances with dramatic, long-lasting impacts on deep-sea benthic communities. The 2016 M 7.8 Kaikōura Earthquake triggered a canyon-flushing event in Kaikōura Canyon, New Zealand, which included significant submarine mass wasting, debris, and turbidity flows.

Probabilistic ecological risk assessment for deep-sea mining: A Bayesian network for Chatham Rise, Pacific Ocean.

Increasing interest in seabed resource use in the ocean is introducing new pressures on deep-sea environments, the ecological impacts of which need to be evaluated carefully. The complexity of these ecosystems and the lack of comprehensive data pose significant challenges to predicting potential impacts. In this study, we demonstrate the use of Bayesian networks (BNs) as a modeling framework to address these challenges and enhance the development of robust quantitative predictions concerning the effects of human activities on deep-seafloor ecosystems.

Volcaniclastic density currents explain widespread and diverse seafloor impacts of the 2022 Hunga Volcano eruption.

The impacts of large terrestrial volcanic eruptions are apparent from satellite monitoring and direct observations. However, more than three quarters of all volcanic outputs worldwide lie submerged beneath the ocean, and the risks they pose to people, infrastructure, and benthic ecosystems remain poorly understood due to inaccessibility and a lack of detailed observations before and after eruptions. Here, comparing data acquired between 2015 - 2017 and 3 months after the January 2022 eruption of Hunga Volcano, we document the far-reaching and diverse impacts of one of the most explosive volcanic eruptions ever recorded.

Towards a scientific community consensus on designating Vulnerable Marine Ecosystems from imagery.

Management of deep-sea fisheries in areas beyond national jurisdiction by Regional Fisheries Management Organizations/Arrangements (RFMO/As) requires identification of areas with Vulnerable Marine Ecosystems (VMEs). Currently, fisheries data, including trawl and longline bycatch data, are used by many RFMO/As to inform the identification of VMEs. However, the collection of such data creates impacts and there is a need to collect non-invasive data for VME identification and monitoring purposes.