Description: Landscape maps based on multivariate cluster analyses provide an objective and comprehensive view on the (marine) environment. They can hence support decision making regarding sustainable ocean resource handling and protection schemes. Across a large number of scales, input parameters and classification methods, numerous studies categorize the ocean into seascapes, hydro-morphological provinces or clusters. Many of them are regional, however, while only a few are on a basin scale. This study presents an automated cluster analysis of the entire Atlantic seafloor environment, based on eight global datasets and their derivatives: Bathymetry, slope, terrain ruggedness index, topographic position index, sediment thickness, POC flux, salinity, dissolved oxygen, temperature, current velocity, and phytoplankton abundance in surface waters along with seasonal variabilities. As a result, we obtained nine seabed areas (SBAs) that portray the Atlantic seafloor. Some SBAs have a clear geological and geomorphological nature, while others are defined by a mixture of terrain and water body characteristics. The majority of the SBAs, especially those covering the deep ocean areas, are coherent and show little seasonal and hydrographic variation, whereas other, nearshore SBAs, are smaller sized and dominated by high seasonal changes. To demonstrate the potential use of the marine landscape map for marine spatial planning purposes, we mapped out local SBA diversity using the patch richness index developed in landscape ecology. It identifies areas of high landscape diversity, and is a practical way of defining potential areas of interest, e.g. for designation as protected areas, or for further research. Clustering probabilities are highest (100%) in the center of SBA patches and decrease towards the edges (〈 98%). On the SBA point cloud which was reduced for probabilities 〈98%, we ran a diversity analysis to identify and highlight regions that have a high number of different SBAs per area, indicating the use of such analyses to automatically find potentially delicate areas. We found that some of the highlights are already within existing EBSAs, but the majority is yet unexplored.

Description: Marine Heatwaves (MHWs) are ocean extreme events, characterized by anomalously high temperatures, which can have significant ecological impacts. The Northeast U.S. continental shelf is of great economical importance as it is home to a highly productive ecosystem. Local warming rates exceed the global average and the region experienced multiple MHWs in the last decade with severe consequences for regional fisheries. Due to the lack of subsurface observations, the depth-extent of MHWs is not well-known, which hampers the assessment of impacts on pelagic and benthic ecosystems. This study utilizes a global ocean circulation model with a high-resolution (1/20°) nest in the Atlantic to investigate the depth structure of MHWs and associated drivers on the Northeast U.S. continental shelf. It is shown that MHWs exhibit varying spatial extents, with some only occurring at depth. The highest intensities are found around 100 m depth with temperatures exceeding the climatological mean by up to 7°C, while surface intensities are typically smaller (around 3°C). Distinct vertical structures are associated with different spatial MHW patterns and drivers. Investigation of the co-variability of temperature and salinity reveals that over 80% of MHWs at depth (〉50 m) coincide with extreme salinity anomalies. Two case studies provide insight into opposing MHW patterns at the surface and at depth, being forced by anomalous air-sea heat fluxes and Gulf Stream warm core ring interaction, respectively. The results highlight the importance of local ocean dynamics and the need to realistically represent them in climate models.