scholarly journals Recruitment of shrimp (Pandalus borealis) in the Barents Sea related to spawning stock and environment

2009 ◽  
Vol 56 (21-22) ◽  
pp. 2012-2022 ◽  
Author(s):  
Michaela Aschan ◽  
Randi Ingvaldsen
Keyword(s):  
Barents Sea ◽  
Pandalus Borealis ◽  
The Barents Sea ◽  
Spawning Stock

scholarly journals The genetic structure of Pandalus borealis in the Northeast Atlantic determined by RAPD analysis

2006 ◽  
Vol 63 (5) ◽  
pp. 840-850 ◽  
Author(s):  
Iciar Martinez ◽  
Michaela Aschan ◽  
Taran Skjerdal ◽  
Salah M. Aljanabi
Keyword(s):  
Genetic Structure ◽  
Barents Sea ◽  
Rapd Analysis ◽  
Rapd Marker ◽  
Arbitrary Primers ◽  
Pandalus Borealis ◽  
Northeast Atlantic ◽  
The Barents Sea ◽  
Local Selection ◽  
Significant Difference

Abstract The genetic structure of shrimp (Pandalus borealis) in the Northeast Atlantic was examined by RAPD analysis on specimens caught at eight stations in the Barents Sea, three off Svalbard, two off Jan Mayen, and in two northern Norwegian fjords (19 < n > 31 per station). A total of 34 polymorphic markers generated by seven 10-mer arbitrary primers was used to assess the genetic population structure using analysis of molecular variance (AMOVA). There was considerable RAPD diversity (>90%) among shrimp at all stations. The two Norwegian fjords and the Jan Mayen stations were different from all the others, and the Jan Mayen stations also differed from each other. More than 98% of the genetic variation between Barents Sea and Svalbard was ascribed to individual diversity, and there was no significant difference between the two areas, although there seemed to be a subpopulation structure in the Barents Sea. Principal component analysis on the frequency of each RAPD marker on each sampled station confirmed the presence of three populations: Barents Sea and Svalbard, northern Norwegian fjords, and Jan Mayen. We postulate that the large genetic variability found at an individual level may provide the total population with a diverse genetic pool from which traits can be selected to respond to variations in local environmental conditions, and that this local selection may be the cause of the subpopulation structure observed.

scholarly journals Comparison of shortest sailing distance through random and regular sampling points

2004 ◽  
Vol 61 (1) ◽  
pp. 140-147 ◽  
Author(s):  
Alf Harbitz ◽  
Michael Pennington
Keyword(s):  
Random Sampling ◽  
Minimum Distance ◽  
Barents Sea ◽  
Pandalus Borealis ◽  
The Barents Sea ◽  
Theoretical Sampling ◽  
Sampling Points ◽  
Regular Sampling ◽  
The Mean ◽  
The Difference

Abstract The shortest sailing distance through n sampling points is calculated for simple theoretical sampling domains (square and circle) as well as for a rather irregular and concavely shaped real sampling domain in the Barents Sea. The sampling sites are either located at the nodes of a square grid (regular sampling) or they are randomly distributed. For n less than ten, the exact shortest sailing distance is derived. For larger n, a traveling salesman algorithm (simulated annealing) was applied, and its bias (distance from true minimum) was estimated based on a case where the true minimum distance was known. In general, the average minimum sailing distance based on random sampling was considerably shorter than for regular sampling, and the difference increased with sample size until an asymptotic value was reached at about n=60 for a square domain. For the sampling domain in the Barents Sea used for shrimp (Pandalus borealis) abundance surveys (n=118 stations), the cruise-track lengths based on random sampling were approximately normally distributed. The mean sailing distance was 18% shorter than the cruise track for regular sampling and the standard deviation equalled 2.6%.

scholarly journals Bycatch reduction in the deep-water shrimp (Pandalus borealis) trawl fishery by increasing codend mesh openness

2021 ◽  
Author(s):  
Nadine Jacques ◽  
Hermann Pettersen ◽  
Kristine Cerbule ◽  
Bent Herrmann ◽  
Ólafur A. Ingólfsson ◽  
...  
Keyword(s):  
Deep Water ◽  
Barents Sea ◽  
Juvenile Fish ◽  
Size Selectivity ◽  
Pandalus Borealis ◽  
Trawl Fishery ◽  
Bycatch Reduction ◽  
Drag Forces ◽  
The Barents Sea ◽  
Trawl Fisheries

In most trawl fisheries, drag forces tend to close the meshes in large areas of diamond mesh codends, negatively affecting their selective potential. In the Barents Sea deep-water shrimp (Pandalus borealis) trawl fishery, selectivity is based on a sorting grid followed by a diamond mesh codend. However, the retention of juvenile fish as well as undersized shrimp is still a problem. In this study, we estimated the effect of applying different codend modifications, each aimed at affecting codend mesh openness and thereby selectivity. Changing from a 4-panel to a 2-panel construction of the codend did not affect size selectivity. Shortening the lastridge ropes of a 4-panel codend by 20% resulted in minor reductions for juvenile fish bycatch, but a 45% reduction of undersized shrimp was observed. Target-size catches of shrimp were nearly unaffected. When the codend mesh circumference was reduced while simultaneously shortening the lastridge ropes, the effect on catch efficiency for shrimp or juvenile fish bycatch was marginal compared to a 4-panel codend design with shortened lastridge ropes.

scholarly journals Fisheries change spawning ground distribution of northeast Arctic cod

2009 ◽  
Vol 6 (2) ◽  
pp. 261-264 ◽  
Author(s):  
Anders Frugård Opdal
Keyword(s):  
Barents Sea ◽  
Size Structure ◽  
Sudden Increase ◽  
Spawning Grounds ◽  
Norwegian Coast ◽  
Trawl Fishery ◽  
Climatic Variations ◽  
The Barents Sea ◽  
Spawning Stock

Prior to the 1920s, the northeast Arctic (NA) cod were caught at spawning grounds ranging from the southernmost to the northernmost parts of the Norwegian coast, but have for the last 50 yr mainly been caught around the Lofoten archipelago and northwards. The NA cod have their feeding and nursery grounds in the Barents Sea, and migrate south towards the Norwegian coast in the winter to spawn. This study uses commercial fisheries' data from landing ports along the entire Norwegian coast during the period 1866–1969 as evidence of long-term truncation and northerly shift of spawning grounds. Nearly all spawning grounds south of Lofoten have been abandoned, while an increasing proportion of the spawning stock only uses the northernmost areas of the Norwegian coast, Troms and Finnmark. The truncation can hardly be attributed to long-term climatic variations, but may result from an intensive size-selective trawl fishery in the Barents Sea causing a sudden increase in fishing mortality, probably altering the size structure and migratory capacity of the stock.

scholarly journals Stock–environment recruitment models for Norwegian spring spawning herring (Clupea harengus)

2002 ◽  
Vol 59 (2) ◽  
pp. 211-217 ◽  
Author(s):  
Øyvind Fiksen ◽  
Aril Slotte
Keyword(s):  
Barents Sea ◽  
Temperature Data ◽  
Clupea Harengus ◽  
Larval Life ◽  
Temperature Index ◽  
The Barents Sea ◽  
Stock Biomass ◽  
Average Annual Temperature ◽  
Spawning Stock ◽  
Stock Recruitment

Different stock–environment recruitment models for Norwegian spring spawning herring (Clupea harengus) are fitted to a time series of spawning stock, recruitment, and temperature data extending back to 1907. In addition to the traditional temperature index from the Barents Sea (the average annual temperature in the Kola transect), we also developed a new index based on the temperature in the larval drift trajectories during early larval life. The models show highly significant effects of both spawning stock and temperature. The inclusion of the temperature term in the stock–recruitment models removes the autocorrelation from the residuals and improves their explanatory ability by 6–9%. We explore the interdependence between recruitment success and subsequent spawning stock biomass and conclude that this is not likely to generate the stock–recruitment relationship. Our analysis suggests that the collapse of the Norwegian spring spawning herring stock in the period 1950–1970 was not caused by reduced recruitment, but by the drop in spawning stock biomass induced by the increased fisheries in this period.

Method application of optimal multi-parameter analysis to assess the distribution of water masses as an example of CTD data of the Barents Sea in summer 2017

2019 ◽  
pp. 38-51
Author(s):  
Valeriy G. Yakubenko ◽  
Anna L. Chultsova
Keyword(s):  
Barents Sea ◽  
Field Measurements ◽  
Structural Similarity ◽  
Water Masses ◽  
Parameter Analysis ◽  
Water Dynamics ◽  
Phosphorus Concentration ◽  
Nitrogen And Phosphorus ◽  
The Barents Sea ◽  
Expert Assessments

Identification of water masses in areas with complex water dynamics is a complex task, which is usually solved by the method of expert assessments. In this paper, it is proposed to use a formal procedure based on the application of the method of optimal multiparametric analysis (OMP analysis). The data of field measurements obtained in the 68th cruise of the R/V “Academician Mstislav Keldysh” in the summer of 2017 in the Barents Sea on the distribution of temperature, salinity, oxygen, silicates, nitrogen, and phosphorus concentration are used as a data for research. A comparison of the results with data on the distribution of water masses in literature based on expert assessments (Oziel et al., 2017), allows us to conclude about their close structural similarity. Some differences are related to spatial and temporal shifts of measurements. This indicates the feasibility of using the OMP analysis technique in oceanological studies to obtain quantitative data on the spatial distribution of different water masses.

Sign in / Sign up

Export Citation Format

Share Document