Description: © The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Elementa Science of the Anthropocene 5 (2017): 4, doi:10.1525/elementa.203.

Description: The deep sea encompasses the largest ecosystems on Earth. Although poorly known, deep seafloor ecosystems provide services that are vitally important to the entire ocean and biosphere. Rising atmospheric greenhouse gases are bringing about significant changes in the environmental properties of the ocean realm in terms of water column oxygenation, temperature, pH and food supply, with concomitant impacts on deep-sea ecosystems. Projections suggest that abyssal (3000–6000 m) ocean temperatures could increase by 1°C over the next 84 years, while abyssal seafloor habitats under areas of deep-water formation may experience reductions in water column oxygen concentrations by as much as 0.03 mL L–1 by 2100. Bathyal depths (200–3000 m) worldwide will undergo the most significant reductions in pH in all oceans by the year 2100 (0.29 to 0.37 pH units). O2 concentrations will also decline in the bathyal NE Pacific and Southern Oceans, with losses up to 3.7% or more, especially at intermediate depths. Another important environmental parameter, the flux of particulate organic matter to the seafloor, is likely to decline significantly in most oceans, most notably in the abyssal and bathyal Indian Ocean where it is predicted to decrease by 40–55% by the end of the century. Unfortunately, how these major changes will affect deep-seafloor ecosystems is, in some cases, very poorly understood. In this paper, we provide a detailed overview of the impacts of these changing environmental parameters on deep-seafloor ecosystems that will most likely be seen by 2100 in continental margin, abyssal and polar settings. We also consider how these changes may combine with other anthropogenic stressors (e.g., fishing, mineral mining, oil and gas extraction) to further impact deep-seafloor ecosystems and discuss the possible societal implications. 

Description: A.K. Sweetman D.O.B. Jones and R. Danovaro acknowledge funding from the European Union Seventh Framework Programme (FP7/2007–2013) under grant agreement 603418 (MIDAS), and the European Union Horizon 2020 research and innovation programme under grant agreement 689518 (MERCES). L.-A. Henry and J.M. Roberts acknowledge funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 678760 (ATLAS).

Description: The presence-absence data for macrobenthic fauna that has been collected in Mingulay Reef Complex (Scotland, UK) across 79 stations over the years 2003, 2005, 2009, 2010 and 2011. The collection of the benthic samples has been carried out using a Van-Veen grab, mainly from hard habitats (e.g. live and dead coral framework). About 60% of the macrofaunal specimens have been identified at species level using high quality taxonomic keys and advice from taxonomy experts. Most common taxonomic groups analysed here are molluscs, polychaetes, arthropods, bryozoans, anthozoans, tunicates and brachiopods. The collection of the specimens is now deposited at the National Museums of Scotland (see the attached excel file for details). The enviromental data contains information about coordinates and environmental settings at stations where macrobenthic samples mentioned above, were collected. The environmental settings that are included in the file refer to the years 2003, 2005, 2009, 2010, 2011. For more information on the environmental variables have a look in Henry et al. 2010 (doi:10.1007/s00338-009-0577-6) and Henry et al. 2013 (doi:10.5194/bg-10-2737-2013). The environmental variables included in the excel file are: type of macrohabitat (i.e. muddy sand, rubble, rock, live coral, dead framework, live & dead framework), depth (m), slope, ruggedness, broad-scale bathymetric position index, fine-scale bathymetric position index, average current speed (m/s), maximum current speed (m/s), northness, eastness, winter North Atlantic Oscillation Index (same year), winter North Atlantic Oscillation Index (previous year), annual average bottom temperature (same year), annual average bottom salinity (same year). Extraction of bathymetric (depth) and topographic data [slope, aspect, northness, eastness, ruggedness, standardised broad-scale bathymetric position index (BPI; with an inner radius of 1 cell and an outer radius of 5 cells), fine-scale BPI (with an inner radius of 1 cell and an outer radius of 3 cells)] was based on multibeam echosounder data, using the Spatial Analyst and Benthic Terrain Modeler toolboxes in ArcGIS v.10.6.1 Average and maximum current speed values (m/s) were extracted by the ArcGIS v. 10.6.1 Spatial Analyst toolbox using data generated by a high-resolution 3D ocean model created for the MRC by Moreno-Navas et al. (2014). Data for the winter NAOI (DJFM) (Hurrell et al., 2003) were downloaded from the National Center for Atmospheric Research/University Corporation for Atmospheric Research website (climatedataguide.ucar.edu; data accessed on 28/02/2019).