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.

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 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.

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 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.

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 2009

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.

(Table 2) Weight percent organic carbon from ODP Site 138-847

As the length of marine cores increases and sampling intervals decrease, the need for rapid and inexpensive means of determining sediment composition has become apparent. In this study we examine one potentially useful technique for assessing compositional changes in marine cores, diffuse reflectance spectrophotometry. We examined near-ultraviolet, visible, and near-infrared reflectance spectra from five data sets. Each data set consists of calibration samples and test samples. The calibration samples' spectra were related to a sediment component using multiple linear regression. The resulting regression or calibration equations were then evaluated using the test samples. Calibration equations were written relating spectra to several sediment components incduding carbonate (Atlantic and east Pacific Rise ODP Site 847), organic carbon content (Atlantic and east Pacific Rise), and opal content (east Pacific Rise). The correlation coefficients for the regression equations ranged from a high of 0.99 for carbonate and opal at ODP Site 847 to a low of 0.97 for Atlantic carbonate indicating that spectral variations are highly correlated to sediment composition. All of the equations include a substantial number of variables from shorter visible and longer near ultraviolet wavelengths suggesting that these wavelengths are especially important for devices designed specifically to scan marine cores. Although equations for estimating organic and carbonate content appear independent of other sediment components, the opal equation is strongly dependent on carbonate content indicating that opal concentration is correlated to carbonate content. Tests of the calibration equations indicated that all our equations reasonably estimate the pattern of changes, either down core or in surface sediments. Where our spectral estimates have difficulty is with absolute values, frequently over or underestimating observed values by a substantial amount. Within these limitations diffuse reflectance spectrophotometry can be a useful tool for characterizing marine cores and as our understanding of the relationship between spectra and mineralogy improves so will estimates of absolute values.

Spatially explicit estimates of length and biomass of Micromesistius poutassou (Blue Whiting) from acoustic and trawl surveys in the North-East Atlantic in May 2009

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 2010

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 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.

Total length, and lipid and toxaphene content in blubber of minke whales (B. acutorostrata) from the North Atlantic

Toxaphene contamination of minke whales (Balaenoptera acutorostrata) from North Atlantic waters was examined for the first time. Total toxaphene and SumCHB (sum of 11 chlorobornanes) concentrations in blubber samples ranged from 170 ± 110 and 41 ± 39 ng/g lipid weight (l.w.) for female minke whales from southeastern Greenland to 5800 ± 4100 and 1100 ± 780 ng/g l.w. for males from the North Sea, respectively. Very large variations in toxaphene concentrations among sampling areas were observed suggesting a spatial segregation of minke whales. However, much of the apparent geographical discrimination was explained by the seasonal fluctuation of animal fat mass. Patterns of CHBs in males revealed that recalcitrant CHBs were in higher proportions in animals from the more easterly areas than in animals from the more westerly areas. This trend may be influenced by the predominance of the US, over the European, input of toxaphene to North Atlantic waters.

Hydrocarbon concentrations from pressurized cores in the northern Gulf of Mexico

Two newly developed coring devices, the Multi-Autoclave-Corer and the Dynamic Autoclave Piston Corer were deployed in shallow gas hydrate-bearing sediments in the northern Gulf of Mexico during research cruise SO174 (Oct-Nov 2003). For the first time, they enable the retrieval of near-surface sediment cores under ambient pressure. This enables the determination of in situ methane concentrations and amounts of gas hydrate in sediment depths where bottom water temperature and pressure changes most strongly influence gas/hydrate relationships. At seep sites of GC185 (Bush Hill) and the newly discovered sites at GC415, we determined the volume of low-weight hydrocarbons (C1 through C5) from nine pressurized cores via controlled degassing. The resulting in situ methane concentrations vary by two orders of magnitudes between 0.031 and 0.985 mol kg**-1 pore water below the zone of sulfate depletion. This includes dissolved, free, and hydrate-bound CH4. Combined with results from conventional cores, this establishes a variability of methane concentrations in close proximity to seep sites of five orders of magnitude. In total four out of nine pressure cores had CH4 concentrations above equilibrium with gas hydrates. Two of them contain gas hydrate volumes of 15% (GC185) and 18% (GC415) of pore space. The measurements prove that the highest methane concentrations are not necessarily related to the highest advection rates. Brine advection inhibits gas hydrate stability a few centimeters below the sediment surface at the depth of anaerobic oxidation of methane and thus inhibits the storage of enhanced methane volumes. Here, computerized tomography (CT) of the pressure cores detected small amounts of free gas. This finding has major implications for methane distribution, possible consumption, and escape into the bottom water in fluid flow systems related to halokinesis.

(Table 1) Age, fork length, and tissue d15N and element concentration of arctic char (Salvelinus alpinus) from Lake Hazen

Arctic char (Salvelinus alpinus L.), the top predator in High Arctic lakes, often is used as a bioindicator of Hg contamination in Arctic aquatic ecosystems. The present study investigated effects of trophic position, size, and age of Arctic char in Lake Hazen, the largest lake in the Canadian High Arctic (81°50'N, 70°25'W), on Hg bioaccumulation. In addition, several essential (Se, K) and nonessential elements (Tl, Cs) in char muscle tissue were examined to compare their behavior to that of Hg. Trophic position of Arctic char was identified by stable isotope (d15N) signature. Temporal trends of Hg from seven sampling campaigns over a 16-year period (1990-2006) were investigated for the overall data and for one trophic class. Concentrations of Hg were not correlated with age but were positively related to fork length and trophic position. Large char with greater d15N signatures (>12 per mil) had larger Hg concentrations (0.09-1.63 µg/g wet wt) than small char with smaller d15N signatures (<12 per mil, 0.03-0.32 µg/g wet wt), indicating that Hg concentrations increased with trophic position. Nonessential Cs and Tl showed relationships to age, length, and trophic position similar to those of Hg, indicating their potential to bioaccumulate and biomagnify. Essential Se and K did not show these relationships. Concentrations of Hg were adjusted using d15N, leading to less within-year variability and a more consistent temporal trend. The d15N-adjusted trend showed no decline of Hg in Arctic char from Lake Hazen (1990-2006) in the overall data set and in the small morphotype. Trends for the same period before the adjustment were not significant for the overall data set, but a slight decrease was apparent in the small morphotype. The results confirm the need to consider trophic position and fish size when monitoring temporal trends of Hg, particularly for species with different morphotypes.

(Table 1) Age, fork length, tissue d15N and d13C and mercury content of arctic char (Salvelinus alpinus) across the Canadian Arctic

Among-lake variation in mercury (Hg) concentrations in landlocked Arctic char was examined in 27 char populations from remote lakes across the Canadian Arctic. A total of 520 landlocked Arctic char were collected from 27 lakes, as well as sediments and surface water from a subset of lakes in 1999, 2002, and 2005 to 2007. Size, length, age, and trophic position (d15N) of individual char were determined and relationships with total Hg (THg) concentrations investigated, to identify a common covariate for adjustment using analysis of covariance (ANCOVA). A subset of 216 char from 24 populations was used for spatial comparison, after length-adjustment. The influence of trophic position and food web length and abiotic characteristics such as location, geomorphology, lake area, catchment area, catchment-to-lake area ratio of the lakes on adjusted THg concentrations in char muscle tissue were then evaluated. Arctic char from Amituk Lake (Cornwallis Island) had the highest Hg concentrations (1.31 µg/g wet wt), while Tessisoak Lake (Labrador, 0.07 µg/g wet wt) had the lowest. Concentrations of THg were positively correlated with size, d15N, and age, respectively, in 88,71, and 58% of 24 char populations. Length and d15N were correlated in 67% of 24 char populations. Food chain length did not explain the differences in length-adjusted THg concentrations in char. No relationships between adjusted THg concentrations in char and latitude or longitude were found, however, THg concentrations in char showed a positive correlation with catchment-to-lake area ratio. Furthermore, we conclude that inputs from the surrounding environment may influence THg concentrations, and will ultimately affect THg concentrations in char as a result of predicted climate-driven changes that may occur in Arctic lake watersheds.

Prosome length as well as carbon and nitrogen content of Calanus finmarchicus from the North Atlantic collected during Maria S. Merian cruise MSM26 in spring 2013

The prosome length of copepods from each station was measured on board with a dissecting microscope equipped with an ocular micrometer. Individuals were placed in pre-weighed tin caps and dried for 48 h at 60°C on board. Dry samples were transferred to the AWI and weighed again. Copepod dry mass was then calculated as the difference between the empty weight and the weight of the tin cap containing one individual. The content of carbon (C) and nitrogen (N) then was analysed with a CN-analyser (EuroEA Element Analyser, Hekatech) with acetanilide as standard.