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 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 2004

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.

Abundance and biomass of ciliates in the eastern Mediterranean Sea in April 2008

The dataset was obtained on samples taken from 6 stations in the Dardanelles Straits, Marmara Sea and Bosporus Straits. These experiments were set up according to DoW of SESAME project. Ciliate abundance: Borax-buffered formalin (final concentration 2% formaldehyde). Samples for ciliate counting were stored at 4°C in the dark until observation. For ciliate identification and enumeration, 100 ml samples were left for 24 h in sedimentation cylinders and then observed under an inverted epifluorescence microscope. Ciliate biomass: Ciliate cell sizes were measured and converted into cell volumes using appropriate geometric formulae (Peuto-Moreau 1991). For biomass estimation, the conversion factor 140 fgC µm**3 was used (Putt and Stoecker (1989), doi:10.4319/lo.1989.34.6.1097)).

Chlorophyll a concentration in plankton, biomass of different taxonomic phytoplankton groups, dominating algae species, and some parameters of coastal surface waters of the Black Sea

Based on data obtained at three stations in coastal waters of the Black Sea off Sevastopol in 2000 and 2001, we present seasonal dynamics of the carbon to chlorophyll a ratio in nano- and microphy-toplankton. This parameter varied approximately tenfold throughout the year. Its maximum values (442-500) were obtained in summer (July), when Pyrrophyta dominated in phytoplankton. Minimum values (36-56) were observed in winter (December),when diatomaceous species predominated. We derive a regression relating the carbon to chlorophyll a ratio to proportion of Pyrrophyta in total phytoplankton biomass, doing so separately for warm and cold seasons. Regression equations demonstrate coupled action of irradiance, temperature, and nutrient availability on the carbon to chlorophyll a ratio. For Pyrrophyta phytoplankton assemblage R**2 = 0.95, and for diatomaceous one R**2 = 0.87.