We present the first digital seafloor geomorphic features map (GSFM) of the global ocean. The GSFM includes 131,192 separate polygons in 29 geomorphic feature categories, used here to assess differences between passive and active continental margins as well as between 8 major ocean regions (the Arctic, Indian, North Atlantic, North Pacific, South Atlantic, South Pacific and the Southern Oceans and the Mediterranean and Black Seas). The GSFM provides quantitative assessments of differences between passive and active margins: continental shelf width of passive margins (88 km) is nearly three times that of active margins (31 km); the average width of active slopes (36 km) is less than the average width of passive margin slopes (46 km); active margin slopes contain an area of 3.4 million km2 where the gradient exceeds 5°, compared with 1.3 million km2 on passive margin slopes; the continental rise covers 27 million km2 adjacent to passive margins and less than 2.3 million km2 adjacent to active margins. Examples of specific applications of the GSFM are presented to show that: 1) larger rift valley segments are generally associated with slow-spreading rates and smaller rift valley segments are associated with fast spreading; 2) polar submarine canyons are twice the average size of non-polar canyons and abyssal polar regions exhibit lower seafloor roughness than non-polar regions, expressed as spatially extensive fan, rise and abyssal plain sediment deposits – all of which are attributed here to the effects of continental glaciations; and 3) recognition of seamounts as a separate category of feature from ridges results in a lower estimate of seamount number compared with estimates of previous workers. Reference: Harris PT, Macmillan-Lawler M, Rupp J, Baker EK Geomorphology of the oceans. Marine Geology.

Norwegian Download service for INSPIRE Sea Regions.

The data on observation of white whales (-lt;i-gt;Delphinapterus leucas-lt;/i-gt;) during the planned sailing of the research scientific ship "Mikhail Somov" (Arkhangelsk–Wrangel Island–Arkhangelsk) from September 6 to December 6 2010 are presented. The results obtained confirm and correct the existing ideas of the distribution of white whales and directions of their migrations in seas of the Russian Arctic. Original provider: Institute of Ecology and Evolution of Russian Academy of Sciences Dataset credits: Boris Solovyev, Institute of Ecology and Evolution of Russian Academy of Sciences Marine Mammal Council Supplemental information: Aerial surveys were conducted on board a helicopter based at he Scientific-Expedition Ship Mikhail Somov. The tracks represent those of the helicopter. Tracks were provided as summarized shapefiles and are not registered in the OBIS-SEAMAP database. Thus, spatial and temporal exploration of the tracks is not available online. Among them, the tracks on 2010-10-08 are not shown due to the technical issue.

ARCOD is the acronym for the data rescue project Archive of Ocean Data, former Arctic Ocean Sediment Data. The projects aim is to make data evailable in electronic, machine-readable form which are available in Russian archives and literature. The project is carried out since 2003 by Dr. Evgeny Gurvich.

Dataset information available at http://www.arcodiv.org/Database/Data_overview.html

Abstract: Acoustic detections of odontocetes from over 30,000km of survey effort from the Arctic, Atlantic, Southern and Indian Oceans, using a streamlined workflow for increasing the speed of acoustic analysis for large datasets utilizing existing modules within PAMGuard. Original provider: Thomas Webber, University of St Andrews Dataset credits: Thomas Webber, University of St Andrews Supplemental information: Each record represents species presence only. Records of "SONAR" were dropped. Survey trackline is provided as a static image online.

GLAMAP2000 is a joint effort to reconstruct Atlantic sea-surface temperatures (SST) during the Last glacial maximum (LGM). Contributing institutes are GEOMAR, Kiel for the Arctic, University of Kiel for the North Atlantic, University of Bremen for the South Atlantic, and Alfred Wegener Institute (AWI), Bremerhaven, for the Southern Ocean.

Happywhale.com is a resource to help you know whales as individuals, and to benefit conservation science with rich data about individual whales. Original provider: Happywhale Dataset credits: Happywhale and contributorsSupplemental information: Sightings and images were submitted to Happywhale by contributors. A portion of the Happywhale data were transferred to OBIS-SEAMAP upon the agreement between Happywhale and OBIS-SEAMAP. There may be duplicate records among Happywhale datasets and other OBIS-SEAMAP datasets. The precision of date/time vary per record. Some records have date accuracy up to year only. This dataset includes sightings and photos from the following 8 contributors in alphabetic order: Andrew Thompson; Greta Henderson; Hondius; Marilia Olio; MS Maud; Nacho Oria; Sigrún Helgudóttir; steve

In 1997 and 1998 soft-bottom fauna of the arctic glacial fjord Kongsfjorden was extensively sampled and major communities were identified along the fjord axis, which were believed to be related to the diminishing influence of the glacial activity. This set of data was collected as part of a PhD programme and was the result of repeated sampling in search for natural or climate driven community changes.

The study of long-distance migration provides insights into the habits and performance of organisms at the limit of their physical abilities. The Arctic tern Sterna paradisaea is the epitome of such behavior; despite its small size (-lt;125 g), banding recoveries and at-sea surveys suggest that its annual migration from boreal and high Arctic breeding grounds to the Southern Ocean may be the longest seasonal movement of any animal. Our tracking of 11 Arctic terns fitted with miniature (1.4 g) geolocators revealed that these birds do indeed travel huge distances (more than 80,000 km annually for some individuals). As well as confirming the location of the main wintering region, we also identified a previously unknown oceanic stopover area in the North Atlantic used by birds from at least two breeding populations (from Greenland and Iceland). Although birds from the same colony took one of two alternative southbound migration routes following the African or South American coast, all returned on a broadly similar, sigmoidal trajectory, crossing from east to west in the Atlantic in the region of the equatorial Intertropical Convergence Zone. Arctic terns clearly target regions of high marine productivity both as stopover and wintering areas, and exploit prevailing global wind systems to reduce flight costs on long-distance commutes. Purpose: The Arctic tern is known to make the longest annual migration in the animal kingdom. During its breeding season, it is found far to the north where summer days are long, and it winters far south in the southern hemisphere, where the days are longest during November to February. This means that the Arctic tern probably experiences more sun light during a calendar year than any other creature on Earth. The long-distance travel of the Arctic tern is well-known both amongst researchers and in the broader public. Now, for the first time, technological advances allow us to follow the Arctic tern on its immense journey, practically from pole to pole. Supplemental information: Four erroneous points were removed from the original dataset: ARTE_410, 9/17/2007 noon; ARTE_370, 9/13/2007 noon; ARTE_373, 9/15/2007 noon and 9/16/2007 noon. Sand Island (74.263 degrees N, 20.160 degrees W), northeast Greenland, is the breeding colony for these Arctic terns and was placed on the map (red-orange square). Sand Island can be used as the beginning and end of all tracks, but since exact dates of the starting and ending of the migration were not available (high-Arctic zone = continuous day light during summer = poor positions when using geolocators), the tracklines for each animal were not mapped to and from the breeding colony. Original provider: Greenland Institute of Natural Resources Dataset credits: Greenland Institute of Natural Resources