oceans
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Average September sea ice extent in 1979 (blue) compared with 2016 (white) and the median sea ice extent (yellow line) from 1981 to 2010 (Data: NSDIC 2016). STATE OF THE ARCTIC MARINE BIODIVERSITY REPORT - <a href="https://arcticbiodiversity.is/marine" target="_blank">Chapter 2</a> - Page 27 - Figure 2.4
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Workflow of the Circumpolar Biodiversity Monitoring Program (CBMP). STATE OF THE ARCTIC MARINE BIODIVERSITY REPORT - <a href="https://arcticbiodiversity.is/marine" target="_blank">Chapter 1</a> - Page 13 - Figure 1.1
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Circumpolar map of known polynyas. Note that polynyas are dynamic systems and some may no longer exist in the form known from their recent history. Adapted from Meltofte (2013) and based on Barber and Massom (2007). STATE OF THE ARCTIC MARINE BIODIVERSITY REPORT - <a href="https://arcticbiodiversity.is/marine" target="_blank">Chapter 2</a> - Page 28 - Figure 2.5
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Abundance of the copepod Calanus glacialis in the Chukchi Sea, 1945-2012 (after Ershova et al. 2015b). STATE OF THE ARCTIC MARINE BIODIVERSITY REPORT - <a href="https://arcticbiodiversity.is/findings/plankton" target="_blank">Chapter 3</a> - Page 75 - Figure 3.2.6
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Megafauna distribution of biomass (g/15 min trawling) in the Barents Sea in 2007, 2011 and 2015. The green circles show the distribution of the snow crab as it spreads from east to west, and the blue triangles show the invasion of king crab along the coast of the southern Barents Sea. Data from Institute of Marine Research, Norway and the Polar Research Institute of Marine Fisheries and Oceanography, Murmansk, Russia. STATE OF THE ARCTIC MARINE BIODIVERSITY REPORT - <a href="https://arcticbiodiversity.is/findings/benthos" target="_blank">Chapter 3</a> - Page 95 - Figure 3.3.2 The annual joint Norwegian–Russian Ecosystem Survey provides from more than 400 stations and during extensive cruise tracks covering more or less the whole Barents Sea in August– September. The sampling is based on a regular grid spanning about 1.5 millionkm2 with fixed positions of stations which make it possible to measure changes in spatial distribution over time. The trawl is a Campelen 1800 bottom trawl rigged with rock-hopper groundgear and towed on double Warps. The mesh size is 80 mm (stretched) in the front and 16–22 mmin the cod end, allowing the capture and retention of smaller fish and the largest benthos from the seabed (benthic megafauna). The horizontal opening was 11.7 m, and the vertical opening 4–5 m (Teigsmark and Øynes, 1982). The trawl configuration and bottom contact was monitored remotely by SCANMAR trawl sensors. The standard distance between trawl stations was 35 nautical miles (65 km), except north and west of Svalbard where a stratified sampling was adapted to the steep continental shelve. The standard procedure was to tow 15 min after the trawl had made contact with the bottom, but the actual tow duration ranged between 5 min and 1 h and data were subsequently standardized to 15 min trawl time. Towing speed was 3 knots, equivalent to a towing distance of 0.75 nautical miles (1.4 km) during a 15 min tow. The trawl catches were recorded using the same procedures on the Russian and the Norwegian Research vessels to ensure comparability across Barents Sea regions. The benthic megafauna was separated from the fish and shrimp catch, washed, and sorted to lowest possible taxonomic level, in most cases to species, on-Board the vessel. Species identification was standardized between the researcher teams by annually exchanging the benthic expert’s among the vessels and taxon names were fixed each year according toWORMSwhen possible.This resulted in an Electronic identification manual and photo-compendium as a tool to standardize taxon identifications, in addition to various sources of identification literature. Difficult taxa were photographed and, in some cases, brought back as preserved voucher specimens for further identification. Wet-weight biomass was recorded with electronic scales in the ship laboratories for each taxon.The biomass determination included all fragments.
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For the background of data production and data interpretation we refer to the PAME report “Modelling Arctic oceanographic connectivity to further develop PAME’s MPA toolbox”. The uploaded data consist of two main types: 1. Connectivity matrices describing the seascape connectivity in the model domain consisting of 40893 model grid cells. The connectivity matrices describe the probability of dispersal between any two selected model grid cells. 2. GIS shape files of dispersal distance (km) from each model grid cell within the model domain.
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Temperature and copepod abundance in Zackenberg, northeastern Greenland. Temperature is measured at 80 m for Microcalanus and 5 m for Pseudocalanus (Arendt et al. 2016). STATE OF THE ARCTIC MARINE BIODIVERSITY REPORT - <a href="https://arcticbiodiversity.is/findings/plankton" target="_blank">Chapter 3</a> - Page 76 - Figure 3.2.7
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<img width="80px" height="67px" alt="logo" align="left" hspace="10px" src="http://geo.abds.is/geonetwork/srv/eng//resources.get?uuid=7d8986b1-fbd1-4e1a-a7c8-a4cef13e8eca&fname=cbird.png">The Circumpolar Seabird Monitoring Plan is designed to 1) monitor populations of selected Arctic seabird species, in one or more Arctic countries; 2) monitor, as appropriate, survival, diets, breeding phenology, and productivity of seabirds in a manner that allows changes to be detected; 3) provide circumpolar information on the status of seabirds to the management agencies of Arctic countries, in order to broaden their knowledge beyond the boundaries of their country thereby allowing management decisions to be made based on the best available information; 4) inform the public through outreach mechanisms as appropriate; 5) provide information on changes in the marine ecosystem by using seabirds as indicators; and 6) quickly identify areas or issue in the Arctic ecosystem such as declining biodiversity or environmental pressures to target further research and plan management and conservation measures. - <a href="http://caff.is" target="_blank"> Circumpolar Seabird Monitoring plan </a>
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Ice algal community similarity of central Russian Arctic drifting stations from the 1980s to 2010s based on unpublished data by I.A. Melnikov, Shirshov Institute of Oceanology. The closer two samples (symbols) are to each other in this multi-dimensional scaling plot, the more similar their algal communities were, based on presence/absence of algal species. Samples from the same year tend to be similar and group together on the plot, with some exceptions. Dispersion across the plot suggests that community structure has changed over the decades, although sampling locations in the central Arctic have also shifted, thus introducing bias. An analysis of similarity (PRIMER version 6) with a high Global R=0.80 indicates strong community difference among decades (global R=0 indicates no difference, R=1 indicates complete dissimilarity). Regional differences were low (global R=0.26) and difference by ice type moderate (global R=0.38). Grey arrows point to the very different and only two samples from 2013. STATE OF THE ARCTIC MARINE BIODIVERSITY REPORT - <a href="https://arcticbiodiversity.is/findings/sea-ice-biota" target="_blank">Chapter 3</a> - Page 47 - Figure 3.1.8 "For the analysis of possible interannual trends in the ice algal community, we used a data set from the Central Arctic, the area most consistently and frequently sampled (Melnikov 2002, I. Melnikov, Shirshov Institute, unpubl. data). Multivariate community structure was analysed based on a presence-absence matrix of cores from 1980 to 2013. The analysis is biased by the varying numbers of analysed cores taken per year ranging widely from 1 to 24, ice thickness between 0.6 and 4.2 m, and including both first-year as well as multiyear sea ice. Locations included were in a bounding box within 74.9 to 90.0 °N and 179.9°W to 176.6°E and varied among years."
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It has not been possible to identify available trend data for Arctic Ocean sea surface temperatures because there is not enough data to calculate reliable long-term trends for much of the Arctic marine environment (IPCC 2013, NOAA 2015). Here, sea surface temperature for July 2015 is shown from CAFF’s Land Cover Change Index. MODIS Sea Surface Temperature (SST) provided a four-kilometre spatial resolution monthly composite snapshot made from night-time measurements from the NASA Aqua Satellite. The night-time measurements are used to collect a consistent temperature measurement that is unaffected by the warming of the top layer of water by the sun. STATE OF THE ARCTIC MARINE BIODIVERSITY REPORT - <a href="https://arcticbiodiversity.is/marine" target="_blank">Chapter 2</a> - Page 25 - Figure 2.3
CAFF - Arctic Biodiversity Data Service (ABDS)