968 resultados para Basin Scale Analysis, Synthesis and Integration (European Commission Grant Agreement 264 933)


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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.

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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.

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Analysis for micro-molar concentrations of nitrate and nitrite, nitrite, phosphate, silicate and ammonia was undertaken on a SEAL Analytical UK Ltd, AA3 segmented flow autoanalyser following methods described by Kirkwood (1996). Samples were drawn from Niskin bottles on the CTD into 15ml polycarbonate centrifuge tubes and kept refrigerated at approximately 4oC until analysis, which generally commenced within 30 minutes. Overall 23 runs with 597 samples were analysed. This is a total of 502 CTD samples, 69 underway samples and 26 from other sources. An artificial seawater matrix (ASW) of 40g/litre sodium chloride was used as the inter-sample wash and standard matrix. The nutrient free status of this solution was checked by running Ocean Scientific International (OSI) low nutrient seawater (LNS) on every run. A single set of mixed standards were made up by diluting 5mM solutions made from weighed dried salts in 1litre of ASW into plastic 250ml volumetric flasks that had been cleaned by washing in MilliQ water (MQ). Data processing was undertaken using SEAL Analytical UK Ltd proprietary software (AACE 6.07) and was performed within a few hours of the run being finished. The sample time was 60 seconds and the wash time was 30 seconds. The lines were washed daily with wash solutions specific for each chemistry, but comprised of MQ, MQ and SDS, MQ and Triton-X, or MQ and Brij-35. Three times during the cruise the phosphate and silicate channels were washed with a weak sodium hypochlorite solution.

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The tuna stomach database from AZTI-Tecnalia corresponds to 7 years of sampling from 2004 to 2011. Due to the absence of continuity in the different projects dealing with the feeding ecology of tunas, the sampling could not be performed every year for both species, and no sample was collected in 2008. However, the fish stomach content record contents composition - by prey weight - of 1525 albacore caught in the Bay of Biscay and surrounding waters of the North Atlantic Drift Region in 2005 (n=397), 2006 (n=196), 2007 (n=37), 2009 (n=95), 2010 (n=566) and 2011 (n=234) ; and of 686 bluefin tunas caught in the Southeastern Bay of Biscay in 2004 (n=32), 2005 (n=36), 2006 (n=3), 2009 (n=257), 2010 (n=233) and 2011 (n=125). Samples have been obtained from scientific research surveys (using a variety of different fishing gears), from commercial fisheries catches, from individual fish voluntarily sampled by recreational fishermen and from fish accidentally stranded on coastlines. Each predator is identified by an ID and its length and wet weight are given. In case the wet weight could not be measured, it was estimated through a length-weight relationship equation and is indicated in the comment for the Predator mass column. The total weight of each prey is given, as well as the weight of each prey taxonomic group in each stomach.

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The pre-bloom grazing and egg production rates of Calanus finmarchicus were studied at in situ temperature and chlorophyll concentration during spring on North Atlantic cruise. The sampled transects covered the Iceland, Irminger and Labrador basins.

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Elemental C and N percent composition and natural abundance of stable C and N isotopes of plankton species and/or size-fractions collected in several cruises on the N Atlantic Ocean from Greenland to Norway and around Iceland. Determinations included key copepod and krill species. Lipid extraction was performed in some samples to determine carbón isotope depletion factors.

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Data on zooplankton abundance and biovolume were collected in concert with data on the biophysical environment during the development of the phytoplankton spring bloom at 4 stations in the North Atlantic. Station 1 in the Icelandic Basin was visited four times (26 March, 8 April, 18 April, 27 April), Station 2 in the southern Norwegian Sea was visited three times (30 March, 13 April, 23 April), Station 3 in the North Sea was visited twice (2 April, 15 April) and one intermediate station was visited once. The data were sampled 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). 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 (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). 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 (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).

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Data on zooplankton abundance and biovolume were collected in concert with data on the biophysical environment during the development of the phytoplankton spring bloom at 4 stations in the North Atlantic. Station 1 in the Icelandic Basin was visited four times (26 March, 8 April, 18 April, 27 April), Station 2 in the southern Norwegian Sea was visited three times (30 March, 13 April, 23 April), Station 3 in the North Sea was visited twice (2 April, 15 April) and one intermediate station was visited once. The data were sampled 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). 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 (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). 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 (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).

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Data on zooplankton abundance and biovolume were collected in concert with data on the biophysical environment during the development of the phytoplankton spring bloom at 4 stations in the North Atlantic. Station 1 in the Icelandic Basin was visited four times (26 March, 8 April, 18 April, 27 April), Station 2 in the southern Norwegian Sea was visited three times (30 March, 13 April, 23 April), Station 3 in the North Sea was visited twice (2 April, 15 April) and one intermediate station was visited once. The data were sampled 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). 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 (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). 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 (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).