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Reports - 2013

IMR ecosystem activity in the Arctic Ocean (IMR report no. 4 - 2013)

The Arctic Ocean is experiencing major transformations. The ongoing changes in the Arctic sea ice extent have already opened up large areas in the waters under Norwegian jurisdiction in the Arctic, enabling an increasing human presence and activity. These developments put pressures on Arctic Ocean ecosystems, and new challenges for their sustainable management arise (AC, 2004). The reduction in extent, thickness and age of the Arctic Ocean sea ice is a visible sign of climate change. The direction of change has been predicted by global models, but the speed of change has been underestimated (AC, 2011). The area in the Arctic Ocean covered by ice reached an all-time low in September 2012 (3.6 million km2).

2013.04.11 10:33

Annual report on health monitoring of wild anadromous salmonids in Norway (Rapport fra Havforskningen nr. 6-2013)


The Norwegian Veterinary Institute (NVI) and the Institute of Marine Research (IMR) were in 2012 commissioned by the Norwegian Food Safety Authority to carry out a health monitoring of anadromous salmonids in Norway (salmon, Salmo salar, and sea trout , Salmo trutta). IMR was given responsibility for the seawater phase whereas NVI was given responsibility for the freshwater phase (returning brood fish). 
2013.03.18 14:15

Studies of Antarctic krill, krill predators and trawl gear, at South Orkney Islands, 2013 (IMR report no. 8 - 2013)

This project is intended to build time series of E. superba abundance and demography patterns related to hydrography and abundance and distribution patterns of E. superba predators, in the South Orkney Islands area. The report describes preliminary results from the third cruise conducted during this project by using a commercial fishing vessel as research platform.

2013.04.11 13:49

Antarctic krill and apex predators in the South Orkney Islands area 2012 (Report from IMR no. 9 2013)

The fishing operations for Antarctic krill (Euphausia superba) are concentrated within CCAMLR (Commission on the Conservation of Antarctic Marine Living resources) subareas 48.1, 48.2 and 48.3 in the Southern Ocean. Krill are abundant in this region, but available data sources for use in scientific advisory to the fisheries management are scarce.

Surveyed with the commercial fishing vessel Juvel.

2013.09.30 11:04

Genome sequencing Part 1 (IMR report no. 11 - 2013)

Copepods comprise the largest animal marine biomass, but they have been poorly studied by molecular tools, and no genome has so far been sequenced. Copepods are common as parasites on fishes, and the salmon louse (Lepeophtheirus salmonis) is the most important species in terms of economical significance. Due to emerging resistance development, new tools (vaccine and new drugs) for lice control is needed. One of the factors limiting research supporting development of new treatments has been the lack of a complete genome sequence. Consequently a joint effort to sequence the salmon louse genome was embarked.

2013.04.22 09:21

BarEcoRe: Barents Sea Ecosystem resilience under global environmental change (IMR report no 16 - 2013)

BarEcoRe, (Barents Sea Ecosystem Resilience under global environmental change) was conducted to investigate how the Barents Sea ecosystem can respond to anticipated changes in climate or human pressures.These investigations reveal how the Barents Sea ecosystem has responded to such perturbations in the past an  what can make it more resilient to perturbations in the future.

2014.03.05 12:33

Simulating spreading of salmon lice with Ladim (Rapport fra Havforskningen nr. 31 - 2013)

When creating a salmon farm, knowing where salmon lice can spread from that location is of interest. Using ladim (Lagrangian Advection and Diffusion Model) one can get an estimate of this, but the question remains of how a simulation should be done, to get a general spreading field. Specifically, for how long a period should the simulation run. As the regional distribution could depend on the length of the simulations, a period should be found so that the distribution doesn’t change significantly for longer simulations, the hope being that this would capture the general variability around the site.

2013.12.02 14:27