242 resultados para the wire beam electrode

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The dataset is based on samples collected in the summer of 1998 in the Western Black Sea in front of Bulgaria coast. The whole dataset is composed of 69 samples (from 22 stations of National Monitoring Grid) with data of mesozooplankton species composition abundance and biomass. Samples were collected in discrete layers 0-10, 0-20, 0-50, 10-25, 25-50, 50-100 and from bottom up to the surface at depths depending on water column stratification and the thermocline depth. Zooplankton samples were collected with vertical closing Juday net,diameter - 36cm, mesh size 150 µm. Tows were performed from surface down to bottom meters depths in discrete layers. Samples were preserved by a 4% formaldehyde sea water buffered solution. Sampling volume was estimated by multiplying the mouth area with the wire length. Mesozooplankton abundance: The collected material was analysed using the method of Domov (1959). Samples were brought to volume of 25-30 ml depending upon zooplankton density and mixed intensively until all organisms were distributed randomly in the sample volume. After that 5 ml of sample was taken and poured in the counting chamber which is a rectangle form for taxomomic identification and count. Large (> 1 mm body length) and not abundant species were calculated in whole sample. Counting and measuring of organisms were made in the Dimov chamber under the stereomicroscope to the lowest taxon possible. Taxonomic identification was done at the Institute of Oceanology by Lyudmila Kamburska using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972). Taxon-specific abundance: The collected material was analysed using the method of Domov (1959). Samples were brought to volume of 25-30 ml depending upon zooplankton density and mixed intensively until all organisms were distributed randomly in the sample volume. After that 5 ml of sample was taken and poured in the counting chamber which is a rectangle form for taxomomic identification and count. Copepods and Cladoceras were identified and enumerated; the other mesozooplankters were identified and enumerated at higher taxonomic level (commonly named as mesozooplankton groups). Large (> 1 mm body length) and not abundant species were calculated in whole sample. Counting and measuring of organisms were made in the Dimov chamber under the stereomicroscope to the lowest taxon possible. Taxonomic identification was done at the Institute of Oceanology by Lyudmila Kamburska using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972).

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The Danubs 2002 dataset contains zooplankton data collected in April, June,September and October 2002 in 11 station allong 5 transect in front of the Romanian littoral. Zooplankton sampling was undertaken at 11 stations where samples were collected using a Juday closing net in the 0-10, 10-25, and 25-50m layer (depending also on the water masses). The dataset includes samples analysed for mesozooplankton species composition and abundance. Sampling volume was estimated by multiplying the mouth area with the wire length. Taxon-specific mesozooplankton abundance was count under microscope. Total abundance is the sum of the counted individuals. Total biomass Fodder, Rotifera , Ctenophora and Noctiluca was estimated using a tabel with wet weight for each species an stage.

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The dataset is based on samples collected in the summer of 2001 in the Western Black Sea in front of Bulgaria coast (transects at c. Kaliakra and c. Galata). The whole dataset is composed of 26 samples (from 10 stations of National Monitoring Grid) with data of mesozooplankton species composition abundance and biomass. Samples were collected in discrete layers 0-10, 10-20, 10-25, 25-50, 50-75, 75-90. Zooplankton samples were collected with vertical closing Juday net,diameter - 36cm, mesh size 150 µm. Tows were performed from surface down to bottom meters depths in discrete layers. Samples were preserved by a 4% formaldehyde sea water buffered solution. Sampling volume was estimated by multiplying the mouth area with the wire length. Mesozooplankton abundance: The collected material was analysed using the method of Domov (1959). Samples were brought to volume of 25-30 ml depending upon zooplankton density and mixed intensively until all organisms were distributed randomly in the sample volume. After that 5 ml of sample was taken and poured in the counting chamber which is a rectangle form for taxomomic identification and count. Large (> 1 mm body length) and not abundant species were calculated in whole sample. Counting and measuring of organisms were made in the Dimov chamber under the stereomicroscope to the lowest taxon possible. Taxonomic identification was done at the Institute of Oceanology by Lyudmila Kamburska and Kremena Stefanova using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972). Taxon-specific abundance: The collected material was analysed using the method of Domov (1959). Samples were brought to volume of 25-30 ml depending upon zooplankton density and mixed intensively until all organisms were distributed randomly in the sample volume. After that 5 ml of sample was taken and poured in the counting chamber which is a rectangle form for taxomomic identification and count. Copepods and Cladoceras were identified and enumerated; the other mesozooplankters were identified and enumerated at higher taxonomic level (commonly named as mesozooplankton groups). Large (> 1 mm body length) and not abundant species were calculated in whole sample. Counting and measuring of organisms were made in the Dimov chamber under the stereomicroscope to the lowest taxon possible. Taxonomic identification was done at the Institute of Oceanology by Lyudmila Kamburska and Kremena Stefanova using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972).

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The Sesame dataset contains mesozooplankton data collected during April 2008 in the Levantine Basin (between 33.20 and 36.50 N latitude and between 30.99 and 31.008 E longitude). Mesozooplankton samples were collected by using a WP-2 closing net with 200 µm mesh size during day hours (07:00-18:00). Samples were taken from 0-50, 50-100, 100-200 m layers at 5 stations in Levantine Basin The dataset includes samples analyzed for mesozooplankton species composition, abundance and total mesozooplankton biomass. Sampling volume was estimated by multiplying the mouth area with the wire length. Sampling biomass was measured by weighing filters and then determined by sampling volume. The samples were sieved sequentially through meshes of 500 and 200 micron to separate the mesozooplankton into size fractions. The entire sample (1/2) or an aliquot of the taxon-specific mesozooplankton abundance and the total abundance of the mesozooplankton were was analyzed under the binocular microscope. Minimum 500 individuals of mesozooplankton were identified and numerated at higher taxonomic level. Taxonomic identification was done at the METU- Institute of Marine Sciences by Alexandra Gubanova,Tuba Terbiyik using the relevant taxonomic literatures. Mesozooplankton abundance and biomass were estimated by Zahit Uysal and Yesim Ak.

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The Sesame dataset contains mesozooplankton data collected during April 2008 in the Marmara Sea (between 40°15' - 34°00N latitude and 19°00 - 23°10'E longitude). Sampling was always performed in day hours (07:00-18:00 local time). Samples were taken at 6 stations in the Marmara Sea. Mesozooplankton samples were collected by using a WP-2 closing net with 200 µm mesh size. Sample was immediately fixed and preserved in a formaldehyde-seawater solution (4% final concentration) to be successively analyzed in the laboratory for species composition, abundance and total biomass. The algal organisms materials were then seperated from the mesozooplankton subsample at the dissecting microscope in the laboratory because of the contamination of the net samples with large-sized algae and mucilaginous organic matters. Afterwards, each samples were filtered on GF/C (pre combusted and weighed) for biomass measurements for dry weight. The dataset includes samples analyzed for mesozooplankton species composition, abundance and total mesozooplankton biomass. Sampling volume was estimated by multiplying the mouth area with the wire length. Sampling biomass was measured by weighing filters and then determined according to sampling volume. 1/2 sample or an aliquot was analyzed under the binocular microscope. Copepod species were identified and enumerated; the other mesozooplankters were identified and enumerated at higher taxonomic level (commonly named as mesozooplankton groups). Taxonomic identification was done at the METU-Institute of Marine Sciences by Tuba Terbiyik using the relevant taxonomic literatures.

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The Danubs 2000 dataset contains zooplankton data collected in April, June. October and November 2000 in 11 station allong 5 transect in front of the Romanian littoral. Zooplankton sampling was undertaken at 11 stations where samples were collected using a Juday closing net in the 0-10, 10-25, and 25-50m layer (depending also on the water masses). The dataset includes samples analysed for mesozooplankton species composition and abundance. Sampling volume was estimated by multiplying the mouth area with the wire length. Taxon-specific mesozooplankton abundance was count under microscope. Total abundance is the sum of the counted individuals. Total biomass Fodder, Rotifera , Ctenophora and Noctiluca was estimated using a tabel with wet weight for each species an stage.

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The "CoMSBlack-95" dataset is based on samples collected in the summer of 1995. The whole dataset is composed of 81 samples (28 stations) with data of zooplankton species composition, abundance and biomass. Samples were collected in discrete layers 0-10, 0-20, 0-50, 10-25, 25-50, 50-100 and from bottom up to the surface at depths depending on water column stratification and the thermocline depth. Zooplankton samples were collected with vertical closing Juday net,diameter - 36 cm, mesh size 150 µm. Tows were performed from surface down to bottom meters depths in discrete layers. Samples were preserved by a 4% formaldehyde sea water buffered solution. Sampling volume was estimated by multiplying the mouth area with the wire length. Mesozooplankton abundance: The collected material was analysed using the method of Domov (1959). Samples were brought to volume of 25-30 ml depending upon zooplankton density and mixed intensively until all organisms were distributed randomly in the sample volume. After that 5 ml of sample was taken and poured in the counting chamber which is a rectangle form for taxomomic identification and count. Large (> 1 mm body length) and not abundant species were calculated in whole sample. Counting and measuring of organisms were made in the Dimov chamber under the stereomicroscope to the lowest taxon possible. Taxonomic identification was done at the Institute of Oceanology by Asen Konsulov and Lyudmila Kamburska using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972). Taxon-specific abundance: The collected material was analysed using the method of Domov (1959). Samples were brought to volume of 25-30 ml depending upon zooplankton density and mixed intensively until all organisms were distributed randomly in the sample volume. After that 5 ml of sample was taken and poured in the counting chamber which is a rectangle form for taxomomic identification and count. Copepods and Cladoceras were identified and enumerated; the other mesozooplankters were identified and enumerated at higher taxonomic level (commonly named as mesozooplankton groups). Large (> 1 mm body length) and not abundant species were calculated in whole sample. Counting and measuring of organisms were made in the Dimov chamber under the stereomicroscope to the lowest taxon possible. Taxonomic identification was done at the Institute of Oceanology by Asen Konsulov and Lyudmila Kamburska using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972).

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The SHELF 1997 dataset contains zooplankton data collected in April, May and June 1997 5 transect in front of the Romanian littoral . Zooplankton sampling was undertaken using a Juday closing net in the 0-10, 10-25, and 25-50m layer (depending also on the water masses). The dataset includes samples analysed for mesozooplankton species composition and abundance. Sampling volume was estimated by multiplying the mouth area with the wire length. Taxon-specific mesozooplankton abundance was count under microscope. Total abundance is the sum of the counted individuals. Total biomass Fodder, Rotifera , Ctenophora and Noctiluca was estimated using a tabel with wet weight for each species an stage.

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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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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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The Gurile Dunarii 1979 dataset contains zooplankton data collected in May and September 1979 in 13 station allong 3 transect in front of the Danube Delta (45°05' - 44°45'N, 30°02'- 29°27'E). Zooplankton sampling was undertaken at 13 stations where samples were collected using a Juday closing net in the 0-10, 10-20, 20-30, 30-40 and 40-50m layer (depending also on the water masses). The dataset includes samples analysed for mesozooplankton species composition and abundance. Sampling volume was estimated by multiplying the mouth area with the wire length. Taxon-specific mesozooplankton abundance was count under microscope. Total abundance is the sum of the counted individuals. Total biomass Fodder, Rotifera , Ctenophora and Noctiluca was estimated using a tabel with wet weight for each species an stage.

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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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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.