234Th and particulate fluxes in the Kara Sea in October 1993

The mean residence time of 234Th associated with suspended matter in the Kara Sea was calculated from distributions of dissolved and suspended 234Th. Integral particulate fluxes at different levels were estimated for two stations. The flux increases only in the pycnocline; below it changes insignificantly. Two maxima of differential fluxes are noted in vertical profiles: in the surface layer where primary production is maximal, and in the interface layer where zooplankton realizing active transport of suspended matter is usually concentrated. Differential fluxes were determined at 10 stations; their space distribution is controlled by primary production, which depends usually on turbidity of river water in estuaries.

Spatially explicit estimates of length and biomass of Micromesistius poutassou (Blue Whiting) and Clupea harengus (Norwegian spring spawning herring) from acoustic and trawl surveys in the North-East Atlantic (2004-2012)

Acoustic estimates of herring and blue whiting abundance were obtained during the surveys using the Simrad ER60 scientific echosounder. The allocation of NASC-values to herring, blue whiting and other acoustic targets were based on the composition of the trawl catches and the appearance of echo recordings. To estimate the abundance, the allocated NASC -values were averaged for ICES-squares (0.5° latitude by 1° longitude). For each statistical square, the unit area density of fish (rA) in number per square nautical mile (N*nm-2) was calculated using standard equations (Foote et al., 1987; Toresen et al., 1998). To estimate the total abundance of fish, the unit area abundance for each statistical square was multiplied by the number of square nautical miles in each statistical square and then summed for all the statistical squares within defined subareas and over the total area. Biomass estimation was calculated by multiplying abundance in numbers by the average weight of the fish in each statistical square then summing all squares within defined subareas and over the total area. The Norwegian BEAM soft-ware (Totland and Godø 2001) was used to make estimates of total biomass.

Spatially explicit estimates of length and biomass of Micromesistius poutassou (Blue Whiting) from acoustic and trawl surveys in the North-East Atlantic in May 2007

Acoustic estimates of herring and blue whiting abundance were obtained during the surveys using the Simrad ER60 scientific echosounder. The allocation of NASC-values to herring, blue whiting and other acoustic targets were based on the composition of the trawl catches and the appearance of echo recordings. To estimate the abundance, the allocated NASC -values were averaged for ICES-squares (0.5° latitude by 1° longitude). For each statistical square, the unit area density of fish (rA) in number per square nautical mile (N*nm-2) was calculated using standard equations (Foote et al., 1987; Toresen et al., 1998). To estimate the total abundance of fish, the unit area abundance for each statistical square was multiplied by the number of square nautical miles in each statistical square and then summed for all the statistical squares within defined subareas and over the total area. Biomass estimation was calculated by multiplying abundance in numbers by the average weight of the fish in each statistical square then summing all squares within defined subareas and over the total area. The Norwegian BEAM soft-ware (Totland and Godø 2001) was used to make estimates of total biomass.

Spatially explicit estimates of length and biomass of Micromesistius poutassou (Blue Whiting) from acoustic and trawl surveys in the North-East Atlantic in May 2005

Acoustic estimates of herring and blue whiting abundance were obtained during the surveys using the Simrad ER60 scientific echosounder. The allocation of NASC-values to herring, blue whiting and other acoustic targets were based on the composition of the trawl catches and the appearance of echo recordings. To estimate the abundance, the allocated NASC -values were averaged for ICES-squares (0.5° latitude by 1° longitude). For each statistical square, the unit area density of fish (rA) in number per square nautical mile (N*nm-2) was calculated using standard equations (Foote et al., 1987; Toresen et al., 1998). To estimate the total abundance of fish, the unit area abundance for each statistical square was multiplied by the number of square nautical miles in each statistical square and then summed for all the statistical squares within defined subareas and over the total area. Biomass estimation was calculated by multiplying abundance in numbers by the average weight of the fish in each statistical square then summing all squares within defined subareas and over the total area. The Norwegian BEAM soft-ware (Totland and Godø 2001) was used to make estimates of total biomass.

Spatially explicit estimates of length and biomass of Micromesistius poutassou (Blue Whiting) from acoustic and trawl surveys in the North-East Atlantic in May 2008

Acoustic estimates of herring and blue whiting abundance were obtained during the surveys using the Simrad ER60 scientific echosounder. The allocation of NASC-values to herring, blue whiting and other acoustic targets were based on the composition of the trawl catches and the appearance of echo recordings. To estimate the abundance, the allocated NASC -values were averaged for ICES-squares (0.5° latitude by 1° longitude). For each statistical square, the unit area density of fish (rA) in number per square nautical mile (N*nm-2) was calculated using standard equations (Foote et al., 1987; Toresen et al., 1998). To estimate the total abundance of fish, the unit area abundance for each statistical square was multiplied by the number of square nautical miles in each statistical square and then summed for all the statistical squares within defined subareas and over the total area. Biomass estimation was calculated by multiplying abundance in numbers by the average weight of the fish in each statistical square then summing all squares within defined subareas and over the total area. The Norwegian BEAM soft-ware (Totland and Godø 2001) was used to make estimates of total biomass.

Physical and chemical oceanography in the Arctic Ocean

Data from sections across the Eurasian Basin of the Arctic Ocean occupied by the German Research Vessel Polarstern in 1987 and by the Swedish icebreaker Oden in 1991 are used to derive information on the freshwater balance of the Arctic Ocean halocline and on the sources of the deep waters of the Nansen, Amundsen and Makarov basins. Salinity, d18O and mass balances allow separation of the river-runoff and the sea-ice meltwater fractions contained in the Arctic halocline. This provides the basis for tracking the river-runoff signal from the shelf seas across the central Arctic Ocean to Fram Strait. The halocline has to be divided into at least three lateral regimes: the southern Nansen Basin with net sea-ice melting, the northern Nansen Basin and Amundsen Basin with net sea-ice formation and increasing river-runoff fractions, and the Canadian Basin with minimum sea-ice meltwater and maximum river-runoff fractions and water of Pacific origin. In the Canadian Basin, silicate is used as a tracer to identify Pacific water entering through Bering Strait and an attempt is made to quantify its influence on the halocline waters of the Canadian Basin. For this purpose literature data from the CESAR and LOREX ice camps are used. Based on mass balances and depending on the value of precipitation over the area of the Arctic Ocean the average mean residence time of the river-runoff fraction contained in the Arctic Ocean halocline is determined to be about 14 or 11 years. Water column inventories of river-runoff and sea-ice meltwater are calculated for a section just north of Fram Strait and implications for the ice export rate through Fram Strait are discussed. Salinity, tritium, 3He and the d18O ratio of halocline waters sampled during the 1987 Polarstern cruise to the Nansen Basin are used to estimate the mean residence time of the river-runoff component in the halocline and on the shelves of the Arctic Ocean. These estimates are done by comparing ages of the halocline waters based on a combination of tracers yielding different time information: the tritium 'vintage' age which records the time that has passed since the river-runoff entered the shelf and the tritium/3He age which reflects the time since the shelf waters left the shelf. The difference between the ages determined by these two methods is about 3 to 6 years. Correction for the initial tritium/3He age of the shelf waters (about 0.5 to 1.5 years) yields a mean residence time of the river-runoff on the shelves of about 3.5 ± 2 years. Comparison of the 18O/16O ratios of shelf water, Atlantic water and the deep waters of the Arctic Ocean indicate that the sources of the deep and bottom waters of the Eurasian Basin are located in the Barents and Kara seas.

Spatially explicit estimates of length and biomass of Clupea harengus (Norwegian spring spawning herring) from acoustic and trawl surveys in the North-East Atlantic in May 2005

Acoustic estimates of herring and blue whiting abundance were obtained during the surveys using the Simrad ER60 scientific echosounder. The allocation of NASC-values to herring, blue whiting and other acoustic targets were based on the composition of the trawl catches and the appearance of echo recordings. To estimate the abundance, the allocated NASC -values were averaged for ICES-squares (0.5° latitude by 1° longitude). For each statistical square, the unit area density of fish (rA) in number per square nautical mile (N*nm-2) was calculated using standard equations (Foote et al., 1987; Toresen et al., 1998). To estimate the total abundance of fish, the unit area abundance for each statistical square was multiplied by the number of square nautical miles in each statistical square and then summed for all the statistical squares within defined subareas and over the total area. Biomass estimation was calculated by multiplying abundance in numbers by the average weight of the fish in each statistical square then summing all squares within defined subareas and over the total area. The Norwegian BEAM soft-ware (Totland and Godø 2001) was used to make estimates of total biomass.

Spatially explicit estimates of length and biomass of Micromesistius poutassou (Blue Whiting) from acoustic and trawl surveys in the North-East Atlantic in May 2006

Acoustic estimates of herring and blue whiting abundance were obtained during the surveys using the Simrad ER60 scientific echosounder. The allocation of NASC-values to herring, blue whiting and other acoustic targets were based on the composition of the trawl catches and the appearance of echo recordings. To estimate the abundance, the allocated NASC -values were averaged for ICES-squares (0.5° latitude by 1° longitude). For each statistical square, the unit area density of fish (rA) in number per square nautical mile (N*nm-2) was calculated using standard equations (Foote et al., 1987; Toresen et al., 1998). To estimate the total abundance of fish, the unit area abundance for each statistical square was multiplied by the number of square nautical miles in each statistical square and then summed for all the statistical squares within defined subareas and over the total area. Biomass estimation was calculated by multiplying abundance in numbers by the average weight of the fish in each statistical square then summing all squares within defined subareas and over the total area. The Norwegian BEAM soft-ware (Totland and Godø 2001) was used to make estimates of total biomass.

Spatially explicit estimates of length and biomass of Clupea harengus (Norwegian spring spawning herring) from acoustic and trawl surveys in the North-East Atlantic in May 2006

Acoustic estimates of herring and blue whiting abundance were obtained during the surveys using the Simrad ER60 scientific echosounder. The allocation of NASC-values to herring, blue whiting and other acoustic targets were based on the composition of the trawl catches and the appearance of echo recordings. To estimate the abundance, the allocated NASC -values were averaged for ICES-squares (0.5° latitude by 1° longitude). For each statistical square, the unit area density of fish (rA) in number per square nautical mile (N*nm-2) was calculated using standard equations (Foote et al., 1987; Toresen et al., 1998). To estimate the total abundance of fish, the unit area abundance for each statistical square was multiplied by the number of square nautical miles in each statistical square and then summed for all the statistical squares within defined subareas and over the total area. Biomass estimation was calculated by multiplying abundance in numbers by the average weight of the fish in each statistical square then summing all squares within defined subareas and over the total area. The Norwegian BEAM soft-ware (Totland and Godø 2001) was used to make estimates of total biomass.

Spatially explicit estimates of length and biomass of Micromesistius poutassou (Blue Whiting) from acoustic and trawl surveys in the North-East Atlantic in May 2011

Acoustic estimates of herring and blue whiting abundance were obtained during the surveys using the Simrad ER60 scientific echosounder. The allocation of NASC-values to herring, blue whiting and other acoustic targets were based on the composition of the trawl catches and the appearance of echo recordings. To estimate the abundance, the allocated NASC -values were averaged for ICES-squares (0.5° latitude by 1° longitude). For each statistical square, the unit area density of fish (rA) in number per square nautical mile (N*nm-2) was calculated using standard equations (Foote et al., 1987; Toresen et al., 1998). To estimate the total abundance of fish, the unit area abundance for each statistical square was multiplied by the number of square nautical miles in each statistical square and then summed for all the statistical squares within defined subareas and over the total area. Biomass estimation was calculated by multiplying abundance in numbers by the average weight of the fish in each statistical square then summing all squares within defined subareas and over the total area. The Norwegian BEAM soft-ware (Totland and Godø 2001) was used to make estimates of total biomass.

Zooplankton abundance and size structure in the North Atlantic from MSM26_133-14

Data on zooplankton abundance and biovolume were collected in concert with data on the biophysical environment at 9 stations in the North Atlantic, from the Iceland Basin in the East to the Labrador Sea in the West. The data were sampled along vertical profiles by a Laser Optical Plankton Counter (LOPC, Rolls Royce Canada Ltd.) that was mounted on a carousel water sampler together with a Conductivity-Temperature-Depth sensor (CTD, SBE19plusV2, Seabird Electronics, Inc., USA) and a fluorescence sensor (F, ECO Puck chlorophyll a fluorometer, WET Labs Inc., USA). Based on the LOPC data, abundance (individuals/m**3) and biovolume (mm3/m**3) were calculated as described in the LOPC Software Operation Manual [(Anonymous, 2006), http://www.brooke-ocean.com/index.html]. LOPC data were regrouped into 49 size groups of equal log10(body volume) increments, see Edvardsen et al. (2002, doi:10.3354/meps227205). LOPC data quality was checked as described in Basedow et al. (2013, doi:10.1016/j.pocean.2012.10.005). Fluorescence was roughly converted into chlorophyll based on filtered chlorophyll values obtained from station 10 in the Labrador Sea. Due to the low number of filtered samples that was used for the conversion the resulting chlorophyll values should be considered with care. CTD data were screened for erroneous (out of range) values and then averaged to the same frequency as the LOPC data (2 Hz). All data were processed using especially developed scripts in the python programming language. The LOPC is an optical instrument designed to count and measure particles (0.1 to 30 mm equivalent spherical diameter) in the water column, see Herman et al., (2004, doi:10.1093/plankt/fbh095). The size of particles as equivalent spherical diameter (ESD) was computed as described in the manual (Anonymous, 2006), and in more detail in Checkley et al. (2008, doi:10.4319/lo.2008.53.5_part_2.2123) and Gaardsted et al. (2010, doi:10.1111/j.1365-2419.2010.00558.x).

Zooplankton abundance and size structure in the North Atlantic from MSM26_135-21

Data on zooplankton abundance and biovolume were collected in concert with data on the biophysical environment at 9 stations in the North Atlantic, from the Iceland Basin in the East to the Labrador Sea in the West. The data were sampled along vertical profiles by a Laser Optical Plankton Counter (LOPC, Rolls Royce Canada Ltd.) that was mounted on a carousel water sampler together with a Conductivity-Temperature-Depth sensor (CTD, SBE19plusV2, Seabird Electronics, Inc., USA) and a fluorescence sensor (F, ECO Puck chlorophyll a fluorometer, WET Labs Inc., USA). Based on the LOPC data, abundance (individuals/m**3) and biovolume (mm3/m**3) were calculated as described in the LOPC Software Operation Manual [(Anonymous, 2006), http://www.brooke-ocean.com/index.html]. LOPC data were regrouped into 49 size groups of equal log10(body volume) increments, see Edvardsen et al. (2002, doi:10.3354/meps227205). LOPC data quality was checked as described in Basedow et al. (2013, doi:10.1016/j.pocean.2012.10.005). Fluorescence was roughly converted into chlorophyll based on filtered chlorophyll values obtained from station 10 in the Labrador Sea. Due to the low number of filtered samples that was used for the conversion the resulting chlorophyll values should be considered with care. CTD data were screened for erroneous (out of range) values and then averaged to the same frequency as the LOPC data (2 Hz). All data were processed using especially developed scripts in the python programming language. The LOPC is an optical instrument designed to count and measure particles (0.1 to 30 mm equivalent spherical diameter) in the water column, see Herman et al., (2004, doi:10.1093/plankt/fbh095). The size of particles as equivalent spherical diameter (ESD) was computed as described in the manual (Anonymous, 2006), and in more detail in Checkley et al. (2008, doi:10.4319/lo.2008.53.5_part_2.2123) and Gaardsted et al. (2010, doi:10.1111/j.1365-2419.2010.00558.x).

Zooplankton abundance and size structure in the North Atlantic from MSM26_127-22

Data on zooplankton abundance and biovolume were collected in concert with data on the biophysical environment at 9 stations in the North Atlantic, from the Iceland Basin in the East to the Labrador Sea in the West. The data were sampled along vertical profiles by a Laser Optical Plankton Counter (LOPC, Rolls Royce Canada Ltd.) that was mounted on a carousel water sampler together with a Conductivity-Temperature-Depth sensor (CTD, SBE19plusV2, Seabird Electronics, Inc., USA) and a fluorescence sensor (F, ECO Puck chlorophyll a fluorometer, WET Labs Inc., USA). Based on the LOPC data, abundance (individuals/m**3) and biovolume (mm3/m**3) were calculated as described in the LOPC Software Operation Manual [(Anonymous, 2006), http://www.brooke-ocean.com/index.html]. LOPC data were regrouped into 49 size groups of equal log10(body volume) increments, see Edvardsen et al. (2002, doi:10.3354/meps227205). LOPC data quality was checked as described in Basedow et al. (2013, doi:10.1016/j.pocean.2012.10.005). Fluorescence was roughly converted into chlorophyll based on filtered chlorophyll values obtained from station 10 in the Labrador Sea. Due to the low number of filtered samples that was used for the conversion the resulting chlorophyll values should be considered with care. CTD data were screened for erroneous (out of range) values and then averaged to the same frequency as the LOPC data (2 Hz). All data were processed using especially developed scripts in the python programming language. The LOPC is an optical instrument designed to count and measure particles (0.1 to 30 mm equivalent spherical diameter) in the water column, see Herman et al., (2004, doi:10.1093/plankt/fbh095). The size of particles as equivalent spherical diameter (ESD) was computed as described in the manual (Anonymous, 2006), and in more detail in Checkley et al. (2008, doi:10.4319/lo.2008.53.5_part_2.2123) and Gaardsted et al. (2010, doi:10.1111/j.1365-2419.2010.00558.x).

Zooplankton abundance and size structure in the North Atlantic from MSM26_134-16

Data on zooplankton abundance and biovolume were collected in concert with data on the biophysical environment at 9 stations in the North Atlantic, from the Iceland Basin in the East to the Labrador Sea in the West. The data were sampled along vertical profiles by a Laser Optical Plankton Counter (LOPC, Rolls Royce Canada Ltd.) that was mounted on a carousel water sampler together with a Conductivity-Temperature-Depth sensor (CTD, SBE19plusV2, Seabird Electronics, Inc., USA) and a fluorescence sensor (F, ECO Puck chlorophyll a fluorometer, WET Labs Inc., USA). Based on the LOPC data, abundance (individuals/m**3) and biovolume (mm3/m**3) were calculated as described in the LOPC Software Operation Manual [(Anonymous, 2006), http://www.brooke-ocean.com/index.html]. LOPC data were regrouped into 49 size groups of equal log10(body volume) increments, see Edvardsen et al. (2002, doi:10.3354/meps227205). LOPC data quality was checked as described in Basedow et al. (2013, doi:10.1016/j.pocean.2012.10.005). Fluorescence was roughly converted into chlorophyll based on filtered chlorophyll values obtained from station 10 in the Labrador Sea. Due to the low number of filtered samples that was used for the conversion the resulting chlorophyll values should be considered with care. CTD data were screened for erroneous (out of range) values and then averaged to the same frequency as the LOPC data (2 Hz). All data were processed using especially developed scripts in the python programming language. The LOPC is an optical instrument designed to count and measure particles (0.1 to 30 mm equivalent spherical diameter) in the water column, see Herman et al., (2004, doi:10.1093/plankt/fbh095). The size of particles as equivalent spherical diameter (ESD) was computed as described in the manual (Anonymous, 2006), and in more detail in Checkley et al. (2008, doi:10.4319/lo.2008.53.5_part_2.2123) and Gaardsted et al. (2010, doi:10.1111/j.1365-2419.2010.00558.x).