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.

Tab. 1: Muskoxen observed in the different geographical units

Muskoxen populations were surveyed in the course of 3 expeditions to North East Greenland to provide data on present status and habitat requirements in the region between 72 and 74 deg latitude North. The distribution is primarily affected by the snow cover pattern and shows densities from less than 0.1 ind/km**2 to 1.5 ind/km**2. Ranges unutilized by muskoxen prior to 1940 now support high densities. The snow cover influences also the population dynamics, as shown by the streng correlation between the calf crop and the amount of snow. The total population is estimated to be about 1000 to 1500 individuals far the whole region.

Seabird density and predation on Arctic cod (Boreogadus saida) in Allen Bay in 2010

Seabirds feed heavily on Arctic cod Boreogadus saida during the summer in the Canadian Arctic but little is known of the interactions among birds while foraging and the factors that drive feeding behaviour. The objective of this study was to describe the relationship between seabirds and Arctic cod in a productive feeding area distant from breeding colonies. Transect surveys were completed using standardized count protocols to determine the density of seabirds in Allen Bay, Cornwallis Island, Nunavut. Shore-based observation sites determined seabird foraging behaviour associated with the presence of schools and environmental variables. The density of birds (156 bird/km**2) was high compared to that of other locations in the Canadian Arctic. Several bird species were more active early in the morning and with winds from the south, possibly due to an increase in Arctic cod feeding on zooplankton at the surface. Northern fulmars Fulmarus glacialis and black-legged kittiwakes Rissa tridactyla captured Arctic cod directly from the water; however, they lost nearly 25% of captures to glaucous gulls Larus hyperboreus and parasitic jaegers Stercorarius parasiticus. These kleptoparasitic seabirds benefited the most in Allen Bay obtaining as much as 8 times more Arctic cod than species capturing cod directly. Northern fulmars captured 3 times more Arctic cod from schools, and black-legged kittiwakes captured similar proportions of schooling and non-schooling cod. We conclude that non-schooling Arctic cod are as important as schooling cod as an energy source for seabirds in nearshore areas, such as Allen Bay, during the summer.

Whale sightings, group sizes and krill biomass in West Greenland in 2005

This study combined data on fin whale Balaenoptera physalus, humpback whale Megaptera novaeangliae, minke whale B. acutorostrata, and sei whale B. borealis sightings from large-scale visual aerial and ship-based surveys (248 and 157 sightings, respectively) with synoptic acoustic sampling of krill Meganyctiphanes norvegica and Thysanoessa sp. abundance in September 2005 in West Greenland to examine the relationships between whales and their prey. Krill densities were obtained by converting relationships of volume backscattering strengths at multiple frequencies to a numerical density using an estimate of krill target strength. Krill data were vertically integrated in 25 m depth bins between 0 and 300 m to obtain water column biomass (g/m**2) and translated to density surfaces using ordinary kriging. Standard regression models (Generalized Additive Modeling, GAM, and Generalized Linear Modeling, GLM) were developed to identify important explanatory variables relating the presence, absence, and density of large whales to the physical and biological environment and different survey platforms. Large baleen whales were concentrated in 3 focal areas: (1) the northern edge of Lille Hellefiske bank between 65 and 67°N, (2) north of Paamiut at 63°N, and (3) in South Greenland between 60 and 61° N. There was a bimodal pattern of mean krill density between depths, with one peak between 50 and 75 m (mean 0.75 g/m**2, SD 2.74) and another between 225 and 275 m (mean 1.2 to 1.3 g/m**2, SD 23 to 19). Water column krill biomass was 3 times higher in South Greenland than at any other site along the coast. Total depth-integrated krill biomass was 1.3 x 10**9 (CV 0.11). Models indicated the most important parameter in predicting large baleen whale presence was integrated krill abundance, although this relationship was only significant for sightings obtained on the ship survey. This suggests that a high degree of spatio-temporal synchrony in observations is necessary for quantifying predator-prey relationships. Krill biomass was most predictive of whale presence at depths >150 m, suggesting a threshold depth below which it is energetically optimal for baleen whales to forage on krill in West Greenland.

Water chemistry of lakes in Zackenbergdalen between 1997-2003, East Greenland

The ecology of arctic lakes is strongly influenced by climate-generated variations in snow coverage and by the duration of the ice-free period, which, in turn, affect the physical and chemical conditions of the lakes (Wrona et al., 2005, http://www.acia.uaf.edu/PDFs/ACIA_Science_Chapters_Final/ACIA_Ch08_Final.pdf). Most arctic lakes are characterised by a long period (8-10 months) of ice-cover, cold water and low algal biomass. The water temperature and nutrient concentrations, and most probably the nutrient input from the catchments, are closely related to the duration of snow- and ice-cover in the lakes. In years when the ice-out is late, - that is, in late July, - phytoplankton photosynthesis is limited by the lack of light and nutrients. Less food is then available to the next link in the food chain, such as copepods and daphnids, with implication on their growth rates.