Jan Mayen—a new spawning and fishing area for Atlantic cod Gadus morhua

In 2018, commercially exploitable concentrations of Atlantic cod Gadus morhua were found on the shelf around the Arctic island Jan Mayen (7 1°N, 8–9 °W) and in 2019–2021 an exploratory cod fishery with longline was carried out in the area. The total catch in the period 2018–2021 was 1737 tonnes. The first records of cod fishery in the Jan Mayen area are from the early 1930s but catches before 2018 were minimal. In 2019–2020 cod spawning was documented in this area for the first time. Catches in 2019 and 2020 were dominated by cod between 70 and 100 cm, while in 2021 the main part of the catches was cod between 60 and 100 cm. Catch rates were highest in autumn. We summarize the history of cod observations and the experience from the recent exploratory fishery in this shelf area where there has been no regular monitoring of demersal fish abundance. Further, we consider possible links with cod stocks in other Arctic and sub-Arctic areas and discuss the occurrence of cod in the Jan Mayen area in relation to the biology and recent development of other cod stocks.publishedVersio

A method for estimation of predation mortalities on capelin using a cod-capelin model for the Barents Sea

Interrelations between fish populations in the Barents Sea. Proceedings of the fifth PINRO-IMR Symposium. Murmansk, 12-16 August 1991.The Barents Sea capelin stock coliapsed during the period 1983-1986. One of the main factors causing the colIapse was a rapid increase in consumption of capelin by cod, caused by the strong 1983 cod year class. Based on measurements of stomach evacuation ra+es in the appropriate temperature interval and data from a combined Russian-Norwegian stomach sampling programrne, predation mortalities are estimated by the MR multispecies model for the Barents Sea - MULTCPEC. In order to estimate these predation mortalities, cod-capelin interaction parameters and yearly migration parameters for capelin are ako estimated

Relations between recruitment indices and occurence in cod stomachs of pre-recruits of cod and haddock in the Barents Sea

Precision and relevance of pre-recruit studies for fiskery management related to fish stocks in the Barents Sea and adjacent waters. Proceedings of the sixth IMR-PINRO Symposium Bergen, 14-17 June 1994.The predation by North-East Arctic cod on pre-recruits of cod and haddock is reviewed based on data from the joint PINRO-IMR stomach content data base. It is investigated how the abundance indices from surveys of pre-recruits are correlated with the occurence in cod stomachs of pre-recruits of these species. Estimates of the consumption of cod and haddock by cod based on a new model for the stomach evacuation rate of cod are also given

Multispecies considerations

Working document to the ICES Arctic Fisheries Working Group, Copenhagen 20-28 August 199

Feeding of mature cod (Gadus morhua) on the spawning grounds in Lofoten

Many authors state that cod (Gadus morhua) do not feed during the spawning period. However, this more or less established fact has rarely been investigated in the field. Here, the content of stomachs from Northeast Arctic cod (NEAC) and Norwegian coastal cod (NCC) sampled from the spawning ground in Lofoten were examined over a 10-year period (1996–2006). The occurrence of food in the stomachs of spawning cod, stomach fullness, diet composition, and variation in these variables between NEAC and NCC, year, and sex were analysed and compared. The analysis shows that cod do feed, even when they are in a spawning state. NCC had a lower proportion of empty stomachs and the stomachs were fuller than those from NEAC. Females had a lower proportion of empty stomachs than males and their stomachs were in general fuller. Herring (Clupea harengus) dominated the diet of cod. However, cod consumption of herring on the spawning grounds seems to be a minor source of mortality on herring. Although spawning cod do feed, the proportion of empty stomachs was higher and stomach fullness was lower than in stomachs of NEAC from the Barents Sea

Capelin distribution in winter 2004-2017: spatiotemporal correlation between density estimates from different sampling methods

The winter distribution of Barents Sea capelin is highly dynamic in space and time, as this is the time of year when mature individuals separate from the immatures and start their spawning migration to the Norwegian and Russian coasts. Due to the difficulty of sampling the entire distribution at this time of year, the stock assessment of capelin is based on data from the ecosystem survey in autumn when capelin has a more favourable distribution for acoustic abundance estimation. A stock projection model is then used to predict how much of the stock will be left and available for the fishery the coming winter. It has long been discussed if a winter survey could be used to improve accuracy of the stock prediction by estimating the maturing part of the stock just before the fishery starts. Estimations based on experimental winter surveys for capelin have so far not been able to achieve this goal. To improve on future attempts, more information on capelin distribution in winter is needed. Here we explore data on capelin distribution collected during the winter survey of the Barents Sea in 2004-2017, a survey primarily collecting data on cod and haddock. Using data from acoustics, demersal trawls, and cod stomachs, we study changes in capelin distribution patterns and correlations between densities from the different data sources during the January-March survey period, with the overarching aim of evaluating the reliability of data sources for capelin investigations. All sampling methods except acoustics showed that capelin shifted toward the south from January-March, and the correlations between capelin densities from different sampling methods varied substantially, reflecting this migration. We found support for the hypothesis that capelin may migrate in the acoustic dead zones, in particularly in the bottom zone, as they move closer to the coast. The discrepancy between sampling methods and variability in the data increased later in the period when capelin shifted south. We recommend further analysis on the vertical distribution of capelin to examine the possibility of combining demersal trawl and acoustic data for abundance estimation of maturing capelin.publishedVersio

A closed life-cycle model for Northeast Arctic cod

For Northeast Arctic cod (Gadus morhua), there is much knowledge available concerning the main population dynamics processes (growth, maturation, fecundity, recruitment, natural mortality, fishing mortality). This knowledge is incorporated into a biologically detailed age-length structured population model. The model contains four population groups: EggsandLarvae, 0-group, immatures (age 1-10) and matures (age 4-12+). Recruitment to EggsandLarvae is modelled as a function of the number of mature fish and their population characteristics (length and weight), giving a fully closed life cycle. The model is implemented using the Gadget framework for population models, and the details of the implementation are described here. Results of fitting the population model to observations are presented. The utility of such a model in the assessment of current stock status and the exploration of harvest control rules is discussed

The use of Medium-Term Forecasts in advice and management decisions for the stock of Norwegian spring spawning herring (Clupea harengus L.)

Medium-term simulations on the stock development of Norwegian spring-spawning herring (Clupea harengus L.) have been carried out since 1994 by the ICES «Atlanto-Scandian Herring and Capelin Working Group», in 1996 renamed «Northern Pelagic and Blue Whiting Fisheries Working Group. The results of the simulations have been used as a basis for advice on harvest control rules for Norwegian spring spawning herring. The present paper reviews developments of medium-term simulations carried out on this stock and results from mediumterm forecasts carried out in 1995 and 1999 are used as examples. Emphasis is put on the usefulness of the medium-term simulations in the process towards reaching an agreement on a harvest control rule in 1999