Marine Biology Research, 2006; 2: 260 269
ORIGINAL ARTICLE
Fish assemblages in the Barents Sea
MARIA FOSSHEIM1, EINAR M. NILSSEN1 & MICHAELA ASCHAN2*
1Norwegian College of Fishery Science, University of Tromsø, N-9037 Tromsø, Norway, & 2Institute of Marine Research, N-9291 Tromsø, Norway
Abstract Fish species inhabiting the Barents Sea display great seasonal and inter-annual variation in abundance and distribution. This study describes the assemblages and distributions of fish species in the southwestern and central part of the Barents Sea, which includes the polar front. The area has an unpredictable environment due to variable inflow of Atlantic water and fish species composition differs between Arctic and Atlantic water masses. Assemblages can be identified as distinct groups corresponding to different environmental conditions. In the period 1997 1999, 57 fish species and shrimp were identified and 29 species/species groups were used in the statistical analyses. Cluster and correspondence analyses showed that the fish community consists of four assemblages: a northern, a southern, a deep and a central group. Temperature explained 26.2% of the variation in the species data, and depth 14.5% of the variation. The assemblages are coherent with previous zoogeographical studies from the Barents Sea. To reduce research costs, one might monitor indicator species characteristic for the identified fish assemblages. Fish assemblages may be a good tool when studying ecosystem responses to fishery and marine climate change.
Key words: Correspondence analysis, distributions, indicator species, unpredictable environment, zoogeography
Introduction indicators of the environment (Horn 1980). Studies on fish assemblages conducted in the Barents Sea The Barents Sea is a highly productive ecosystem have focused on commercial and well-known and an important nursery and nourishment area for several important commercial and non-commercial species. In this study we aimed to include all fish species. Great seasonal and inter-annual varia- identifiable fish species. tion in the abundance and distribution of fish species Exploitation of most marine resources is intrinsi- has been observed (Shepherd et al. 1984; Shevelev et cally multispecies and it is therefore important to al. 1987; Loeng 1989; Nilssen & Hopkins 1992; know whether some groups of species can be Murawski 1993). Understanding these dynamics is a considered ecological entities that respond similarly matter of necessity for sustainable development of to the environment (Tyler et al. 1982; Overholtz & the area. The commercial fish species have hitherto Tyler 1985; Burgos 1989). Spatial patterns of caught the most attention, especially cod (Gadus interaction among different groups of organism (in morhua), herring (Clupea harengus) and capelin this case fish species) are important, as their (Mallotus villosus), but also haddock (Melanogram- co-occurrence suggests common ecological pro- mus aeglefinus), redfish (Sebastes marinus and S. cesses. If different fish assemblages can be identified mentella), Greenland halibut (Reinhardtius hippoglos- in the Barents Sea, this information may help the soides) and, to a limited extent, polar cod (Boreogadus authorities in monitoring and managing the area. saida) (Shevelev et al. 1987; Loeng 1989; Nakken Monitoring the fish assemblages may give informa- 1998). The non-commercial fish stocks can be tion on the biological response to factors such equally important from an ecological point of view, as fisheries or climate change. Surveys are costly for example as prey for commercial species and as and labour intensive and by identifying distinct
Correspondence: M. Fossheim, Norwegian College of Fishery Science, University of Tromsø, N-9037 Tromsø, Norway. E-mail: [email protected] Published in collaboration with the University of Bergen and the Institute of Marine Research, Norway, and the Marine Biological Laboratory, University of Copenhagen, Denmark *Present address: Norwegian College of Fishery Science, University of Tromsø, N-9037 Tromsø, Norway.
(Accepted 4 May 2006; Printed 12 September 2006) ISSN 1745-1000 print/ISSN 1745-1019 online # 2006 Taylor & Francis DOI: 10.1080/17451000600815698 Fish assemblages in the Barents Sea 261 assemblages of species and the distribution of these is the major transition area of the physical environ- assemblages one might be able to reduce the number ment (Figure 1) (Loeng 1991; Loeng et al. 1997). of stations on surveys and thus minimize costs, or A zoogeographical analysis of the Barents Sea in practicality get more research for a limited fauna demonstrated three geographical areas with amount of money (Weslawski & Kwasniewski different environmental properties (Zenkevich 1983). Identifying assemblages of species that can 1956): (i) the northernmost part of the sea is be managed adaptively as similar entities of produc- characterized by a severe temperature regime and tion has also been suggested to alleviate overfishing drift ice during a lengthy period and is considered a in the trawl fishery (Tyler et al. 1982; Jay 1996). deep Arctic area of the Arctic region; (ii) the main, To manage such ecological entities they need to be central part of the sea is considered a sub-Arctic area stable [in the sense of ‘‘resilience’’ used by Grimm & of the Arctic region; and (iii) the southwesternmost Wissel (1997)]. Especially, the assemblages need to part of the sea is a section receiving most of the consist mainly of the same species between years, Atlantic heat, with the bottom water temperature even if their combined geographical distribution being above /18C and the fauna belonging to the varies considerably. It is also important to know boreal type. Ekman (1953) classified the fish fauna where faunal discontinuity between assemblages into four zoogeographical groups: Arctic, Arctic arises and, of course, why. In the Barents Sea, it is boreal, boreal and warm water boreal [not included expected that a faunal discontinuity area will be by, but south of the area described by Zenkevich concurrent with the position of the polar front, as it (1956)].
Figure 1. The Barents Sea with main surface currents. Atlantic currents (* /), Arctic currents (--- /) and the mean position of the polar front (+++). The study area is indicated by the grey square. 262 M. Fossheim et al.
Since the middle of the twentieth century, more and one species of shrimp (Table I). Due to data on several species have emerged and the uncertain identification, some species were merged computer has offered an important tool in exploring in groups of lowest taxonomic level. Rare species, community data of a multivariable nature. defined as species with less than six individuals in Multivariate methods such as cluster analysis and total or represented on less than five stations each ordination have proven very helpful in exploring year, were excluded from the analysis because they patterns in large data sets from community sampling represented less than 5% of the station catch (Gomes et al. 1995; Greenstreet & Hall 1996; Farina (Høines et al. 1998). Pelagic species (i.e. herring, et al. 1997; Gaertner et al. 1998; Jacob et al. 1998; capelin and blue whiting) were excluded from the Ungaro et al. 1998). Ordination is also able to analyses. There were 29 species/species groups in the explore complex environmental gradients in an final analyses (Table I). Abundance data were intelligible way. Burgos (1989) used cluster analysis standardized to 20 min trawl hauls (or 1 nautical and ordination to explore the fish community of the mile) when necessary and log10(a /1) transformed southern part of the Barents Sea. Our study area prior to cluster and correspondence analyses with comprised the polar front and the data set included the purpose of downscaling very abundant species both commercial species, previously explored by and reducing skewness (ter Braak 1997). Nilssen & Hopkins (1992), as well as non-commer- Cluster analysis was used to study the concurrence cial species. of species and a hierarchical method was chosen, The main questions are thus: exploring the results as a dendrogram for each year. The cluster analysis was based on a Spearman rank (1) Can the fish community in the southwestern correlation matrix and Ward’s method was chosen to Barents Sea be divided into different assem- minimize the variance within clusters. Groupings of blages? species for the 3 years combined and their relation- (2) Is there a faunal discontinuity across the polar ship with the environmental parameters were ex- front? plored by correspondence analysis (Greenacre (3) Are the assemblages stable? 1984). Correspondence analysis ‘‘extracts’’ the ordi- (4) Can this pattern be explained by abiotic nation axes from the species data alone. Species factors such as temperature and different appearing close to one another in the ordination water masses with certain characteristics? diagram have a more similar distribution than (5) Can the assemblages be considered entities species further apart. The environmental variables suitable for management? are added afterwards and are represented as arrows that point in the direction of maximum change. The Material and methods fraction of variance accounted for by the regression Data on fish assemblages and distributions were indicates whether the environmental variable is collected during three surveys in the southwestern sufficient to predict the variation in species composi- Barents Sea in spring 1997 1999 (Figure 1). The tion that is represented by the first ordination axis study area corresponded to grids ranging from (ter Braak 1997). 70835?Nto76824?N and 16852?Eto35836?E. The After exploring the species data by correspon- depth at stations sampled varied between 167 and dence analysis, generalized additive models were 495 m. The data used in this study were collected fitted on the two first ordination axes for six selected during the annual shrimp survey conducted by the species. The six species chosen were: the target Norwegian Institute of Aquaculture and Fisheries, species of the data set (i.e. shrimp, Pandalus borealis), with R/V Jan Mayen in spring 1997 1999. A the indicator species in a previous analysis (i.e. Campelen 1800 survey trawl was used and the Atlantic hookear sculpin, Artediellus atlanticus; deep- stations were placed like a grid with 20 30 nautical water redfish, Sebastes mentella; Norway pout, Tr i- miles distance between stations. The trawl was sopterus esmarkii; Fossheim 2000), the most hauled with a speed of 3 knots for 20 min, thereby important commercial species in the data set, cod covering a distance of 1 nautical mile (Aschan & (Gadus morhua), and to explore the ecological niche Sunnana˚ 1997). In total, 317 stations were sampled, differentiation between the two redfish species, 101 stations in 1997, 116 stations in 1998 and 100 golden redfish (Sebastes marinus). stations in 1999. The main purpose of the surveys was to map the Results biomass and distribution of shrimp (Pandalus bor- ealis), but all by-catch of fish was identified, The cluster analyses resulted in a four-group pattern counted, weighed, and measured by species. We where especially the species known to have a north- identified 57 species of fish belonging to 19 families ern distribution were separated from the remaining Fish assemblages in the Barents Sea 263
Table I. Species identified in the southwestern Barents Sea in spring 1997 1999 (n /317 stations).
Scientific name Abbreviation Family Common name
Pandalus borealis Pa bo Pandalidae Shrimpa Raja clavata Ra cl Rajidae Thornback rayb Raja batis Ra ba Rajidae Blue skateb Raja radiata Ra ra Rajidae Thorny skatea Raja fyllae Ra fy Rajidae Round rayb Raja hyperborea Ra hy Rajidae Arctic skateb Breviraja spinicauda Br sp Rajidae Spinetail rayb Chimaera monstrosa Ch mo Chimaeridae Rabbit fishb Clupea harengus Cl ha Clupeidae Herringa Mallotus villosus Ma vi Osmeridae Capelina Argentina silus Ar si Argentinidae Greater argentineb Argentina sphyraena Ar sp Argentinidae Lesser argentineb Maurolicus muelleri Ma mu Sternoptychidae Pearlsidesb Benthosema glaciale Be gl Myctophidae Glacier lanternfishab Notolepis rissoi krøyeri No rk Paralepididae White barracudinaa Trisopterus esmarkii Tr es Gadidae Norway pouta Micromesistius poutassou Mi po Gadidae Blue whitinga Gadiculus argenteus thori Ga at Gadidae Silvery poutb Boreogadus saida Bo sa Gadidae Polar coda Melanogrammus aeglefinus Me ae Gadidae Haddocka Pollachius virens Po vi Gadidae Saitheab Gadus morhua Ga mo Gadidae Coda Brosme brosme Br br Gadidae Tuskb Ciliata mustela Ci mu Gadidae Fivebeard rocklingb Macrourus berglax Ma be Macrouridae Onion-eye grenadierb Gymnelus retrodorsalis Gy re Zoarcidae Eelpout sp. 1b Lycenchelys kolthoffi Ly ko Zoarcidae Eelpout sp. 2b Lycenchelys sarsii Ly sa Zoarcidae Sars’ wolf eelb Lycodes vahlii Ly va Zoarcidae Vahl’s eelpouta Lycodes esmarkii Ly es Zoarcidae Greater eelpouta Lycodes eudipleurostictus Ly eu Zoarcidae Doubleline eelpouta Lycodes frigidus Ly fr Zoarcidae Eelpout sp. 3b Lycodes pallidus Ly pa Zoarcidae Pale eelpout Lycodes reticulatus Ly re Zoarcidae Arctic eelpout Lycodes rossi Ly ro Zoarcidae Threespot eelpoutb Lycodes seminudus Ly se Zoarcidae Longear eelpout Lycodes spp Ly spp Zoarcidae Eelpout (spp.) Sebastes viviparus Se vi Scorpaenidae Norway redfishb Sebastes marinus Se ma Scorpaenidae Golden redfisha Sebastes mentella Se me Scorpaenidae Deepwater redfisha Sebastes spp Se spp Scorpaenidae Redfish (spp.) Triglops murrayi Tr spp Cottidae Moustache sculpina Triglops pingelii Tr spp Cottidae Ribbed sculpina Myoxocephalus scorpius My sc Cottidae Shorthorn sculpinb Artediellus atlanticus Ar at Cottidae Atlantic hookear sculpina Cottunculus microps Co mi Cottunculidae Polar sculpinb Leptagonus decagonus Le de Agonidae Atlantic poachera Cyclopterus lumpus Cy lu Cyclopteridae Lumpsuckera Eumicrotremus spinosus Eu sp Cyclopteridae Atlantic spiny lumpsuckerb Liparis fabricii Cy spp Cyclopteridae Gelatinous seasnaila Paraliparis bathybii Pa ba Cyclopteridae Black seasnail Careproctus reinhardti Cy spp Cyclopteridae Longfin seasnaila Lumpenus lampraetaeformis Lu la Stichaeidae Snake blennya Leptoclinus maculatus Le ma Stichaeidae Spotted snake blennya Anarhichas minor An mi Anarhichadidae Spotted wolffisha Anarhichas lupus An lu Anarhichadidae Atlantic wolffish Anarhichas denticulatus An de Anarhichadidae Northern wolffisha Glyptocephalus cynoglossus Gl cy Pleuronectidae Witch flounderb Hippoglossoides platessoides Hi pl Pleuronectidae Long rough daba Reinhardtius hippoglossoides Re hi Pleuronectidae Greenland halibuta aSpecies identified all 3 years. bSpecies excluded from the statistical analyses due to low abundance. 264 M. Fossheim et al. species as a distinct group (Figure 2). Also, species than the northern group. The groupings were some- known to have southern and deep distributions what variable between the 3 years, but conformed to seemed to form groups, but they were less distinct a clear pattern.
Figure 2. Species data from cruises in the southwestern Barents Sea in spring 1997, 1998 and 1999. Hierarchical cluster analyses (using
Ward’s method and based on a Spearman ranking correlation matrix) by grouping species with similar distributions. n /91 (1997), n /116 (1998), n /101 (1999) stations. Sculpin spp. /Triglops murrayi /T. pingelii, seasnail spp. /Careproctus reinhardti /Liparis fabricii, eelpout spp. /Lycodes spp., redfish juveniles /juveniles of Sebastes marinus /S. mentella. Fish assemblages in the Barents Sea 265
Figure 3. Data on species assemblages and distribution from the southwestern Barents Sea in spring 1997 1999, the 3 years combined. Correspondence analysis ordination plot of axes I and II relating abundance variations in species to environment (temperature, depth, latitude and longitude). n /101 (1997), n /116 (1998), n /100 (1999) stations. Scientific abbreviations are explained in Table I.
The results from the correspondence analyses of was located towards the northeast of the study area the species environment data in axes I and II are (positively correlated with the latitude and longitude presented in Figure 3 and show that latitude was vectors) and was negatively correlated with the negatively correlated with temperature and the temperature vector. The southern and deep groups major determinants of the first axes, whereas depth showed positive correlations with the latitude and was the major determinant of the second axis. depth vectors, respectively. Including pelagic species Approximately 40% of the variance in the species (i.e. herring, capelin and blue whiting) did not distribution was explained by axes I and II, which is change the results of the analysis (neither cluster adequate for the analyses to have explanatory power. nor correspondence analysis). The species environment correlations for axes I and The abundance profile of Atlantic hookear sculpin
II were strong ( /0.7, Table II) (Fowler et al. 1998). (Artediellus atlanticus) was positively correlated When the environmental variables (latitude, long- with the first ordination axis (Figure 4A), related itude, depth, temperature and year) were tested for to increasing latitude and longitude, meaning that significant contribution to variation in species abun- abundance increased in the northeast direction. The dance via forward selection, only temperature and abundance profile of shrimp increased with latitude, depth were included in the model (Monte Carlo but was also negatively correlated with the second permutation tests, PB/0.05). ordination axis (Figure 4B), related to increasing Species with a northern, southern and deep distribution could be identified as distinct groups Table II. Percentage of species distribution explained by four in the correspondence analyses corresponding to the axes in the correspondence analyses and correlations between species distribution and the environment (see Figure 3). same groups as in the cluster analyses. The grouping of species was largely sustained and especially the Axis (percentage explained) Species environment correlation northern group was persistent, with the same species assemblage (for species occurring all 3 years) 1 2341234 26.2 14.5 7.3 5.1 0.89 0.76 0.38 0.38 throughout the whole 3 year period. This group 266 M. Fossheim et al.
Figure 4. Correspondence analysis ordination biplot of axes I and II with a generalized additive model fitted to the abundance of (A) Atlantic hookear sculpin (Artediellus atlanticus), (B) shrimp (Pandalus borealis), (C) cod (Gadus morhua), (D) deepwater redfish (Sebastes mentella), (E) golden redfish (Sebastes marinus) and (F) Norway pout (Trisopterus esmarkii). depth. The abundance profile of cod was uncorre- negatively correlated with the first ordination axis lated with the first ordination axis (i.e. latitude/ but showed differing abundance profiles on the temperature), but showed a positive correlation second ordination axis, with deepwater redfish with the second ordination axis (Figure 4C), related to increasing depth (Figure 4D), whereas related to shallow depths. The two redfish species golden redfish was related to more shallow depths (Sebastes mentella and S. marinus) were both (Figure 4E). The abundance profile of Norway pout Fish assemblages in the Barents Sea 267
(Trisopterus esmarkii) was negatively correlated with species may actually be less abundant than other the first ordination axis and positively correlated species. Discriminant analysis (not shown) demon- with the second ordination axis (Figure 4F), related strated that the core species for the different to increasing temperature and shallow depths. assemblages fit this theory well, giving deepwater redfish (Sebastes mentella) as the core species for the deep group, Norway pout (Trisopterus esmarkii) for Discussion the southern group and Atlantic hookear sculpin Given that there is some subjectivity in assemblage (Artediellus atlanticus) for the northern group (Fos- analyses, for example where to conclude groups in sheim 2000). This also shows that it is important to the cluster analysis and which species to include in include rare and non-commercial species in a the correspondence analysis groups, consistency zoogeographical analysis or one might lose impor- among different approaches would enhance cred- tant indicators of assemblages. ibility. Species occurring in a cluster group usually The polar front represents a transitional area with fell within the same group in the correspondence faunal discontinuity and many species are restricted analyses. This indicates that the multivariate meth- to areas north or south of this area. However, some ods produced results consistent with the obvious species are distributed both north and south of this major distribution patterns. The resultant groups area and may in fact constitute an assemblage by also correspond well with those reported in the themselves, this being the central group in this study. historical literature and are consistent with distribu- The central group is the most variable assemblage, tions of single species, for gadoids (Bergstad et al. both in composition and distribution, which sup- 1987) and several non-commercial fish species ports the interpretation of the polar front as a (including eelpouts, blennies, sculpins, snailfishes transitional area. The polar front represents an area and others; Dolgov 1994). of high primary production and it is therefore Species that are commonly known to inhabit a expected that many species will take advantage of certain area and to co-occur with other known this larder. species seem to be reflected in the assemblages Assemblages are fairly stable entities, but their produced by both the cluster and correspondence development and distribution may vary through time analyses. A few consequences of the analyses are as species distributions and abundances fluctuate nevertheless worth mentioning. Assemblages are (Mahon et al. 1998). The data studied here were determined by (i) species that tend to co-occur all from years considered relatively ‘‘warm’’ years primarily together, and not by widespread species (Dickson et al. 2000), and as such high productivity that co-occur with many other species and (ii) years (Sakshaug 1995). It might therefore be that species that tend to co-occur at unusually high results from ‘‘cold’’ years would have given assem- frequencies, even if they are not particularly abun- blages with other species compositions, but we do dant overall. Rare species may be given more weight not believe this to be the case, as our assemblages are as it is the covariation with other species that is comparable with the zoogeographical grouping by considered important, rather than abundance. Core Ekman (1953) and Burgos (1989) (Table III). Our
Table III. Comparison of zoogeographical grouping of fish species in the Barents Sea by Ekman (1953), Burgos (1989) and Fossheim (2000).
Species Ekman (1953) Burgos (1989) Fossheim (2000)
Polar cod Arctic East (Arctic) Northern/Arctic Atlantic poacher East (Arctic) Northern/Arctic Atlantic hookear sculpin East (Arctic) Northern/Arctic Capelin Arctic Central Snake blenny Arctic boreal Northern/Arctic Seasnail spp. Arctic boreal East (Arctic) Central Long rough dab Arctic boreal Central Deep Golden redfish Boreal Vest/central Southern/boreal Cod Boreal Central Southern/boreal Haddock Boreal Central Southern/boreal Herring Boreal Southern/boreal Saithe Boreal Vest/central Norway pout Vest/central Southern/boreal Greenland halibut Boreal Northeast Deep Deepwater redfish Boreal Northeast Deep Blue whiting Warm water boreal Vest/central 268 M. Fossheim et al. northern assemblage seems to be concurrent with by-catch of juvenile fish in the shrimp fishery were Ekman’s (1953) Arctic group and Burgos’ (1989) introduced in the Barents Sea, one should take the east (Arctic) group and our southern assemblage fish assemblages into consideration when identifying seems concurrent with the boreal (Ekman 1953) and Marine Protected Areas. This study included only vest/central groups (Burgos 1989). the shrimp survey in the Barents Sea within three Burgos (1989) divided his assemblages according successive years. By including all Norwegian trawl to an east west axis, whereas the assemblages in our survey data, collected by the Institute of Marine study can be described according to a north south Research, Norway since 1980, one might study axis. The two studies can be compared because the seasonal variation and long time response in fish gradients (temperature, inflow of Atlantic water, assemblages as a response to fishery and climate etc.) in the Barents Sea are from southwest to change. This approach also gives important infor- northeast. In addition, we should expect a similar mation on marine biodiversity and may be a good pattern to emerge along the depth axis, as species tool in future ecosystem-based management. inhabiting cold areas in the north are known to submerge in deeper areas further south (Ekman Conclusions 1953). The Barents Sea is a neritic ocean with few depths below 450 m, but if we compare our assemblages to the assemblages identified on the (1) This study showed that the fish community in slope of the eastern Norwegian Sea (Bergstad et al. the southwestern Barents Sea can be divided into different assemblages. 1999), the deepest assemblages (upper slope and (2) The polar front represents a transitional area Norwegian Sea deepwater) include many of the of faunal discontinuity. same species (e.g. eelpouts) as our northern assem- (3) The consistency of the assemblages through blage. Bergstad et al. (1999) also concluded that the different approaches, including historical lit- temperature gradient seems to be a strong structur- erature, shows that the assemblages remain ing force along the Norwegian Sea slope, as well as in continuous through time and space, but furt- the southwestern Barents Sea (Burgos 1989; Nilssen her analysis from a longer time series should & Hopkins 1992). be performed to conclude stable entities. The water mass distribution and characteristics (4) The assemblage and distribution patterns can have a major influence on the production processes partly be explained by the measured environ- and the current pattern largely determines the mental factors, but this study lacked impor- zoogeographical boundaries in the area (Bergstad tant abiotic and biotic variables. et al. 1987), but the assemblage and distribution (5) Monitoring and management of entities con- patterns cannot be solely explained by abiotic factors sisting of different assemblages might be included in this study. Temperature explains 22.6% justified if the assemblages turn out to be of the variation in the species data and depth 14.5% stable entities. of the variation (Figure 3), but the data set lacks information on bottom topography as well as biotic information on primary production and important Acknowledgements non-fish prey or predator organisms. Whether the The authors wish to thank the Norwegian Institute assemblages represent biologically functional entities of Fisheries and Aquaculture A/S in Tromsø, or merely consist of species with similar responses to Norway for providing the data underlying this study environmental gradients cannot be determined by and Eggvins Fond for financial support. this study, but the consistency of the assemblages suggests that monitoring and managing these entities might be justified. References An example of how such management could be Aschan M, Sunnana˚ K. 1997. Evaluation of the Norwegian envisioned concerns the annual shrimp surveys. If shrimp surveys conducted in the Barents Sea and the Svalbard the northern area is a stable area with regard to area 1980 1997. ICES Council Meeting 1997 Y:7:23. species composition, fewer stations would be neces- Bergstad OA, Bjelland O, Gordon JDM. 1999. Fish communities on the slope of the eastern Norwegian Sea. Sarsia 84(1):67 78. sary in this area to maintain resolution. The saved Bergstad OA, Jørgensen T, Dragesund O. 1987. Life history and time could then be used to sample more stations in a ecology of the gadoid resources of the Barents Sea. Fisheries biogeographically more challenging area, such as the Research 5:119 61. polar front. Also, if by-catch of juvenile fish in the Burgos GE. 1989. The bottom fish community of the Barents Sea in the winters 1984 to 1987. Master of Philosophy Thesis, shrimp catch is high, the area may be closed for a University of Bergen. period (Reithe & Aschan 2004). If permanent Dickson RR, Osborn TJ, Hurrell JW, Meincke J, Blindheim J, Marine Protected Areas with the aim of reducing Adlandsvik B, Vinje T, Alekseev G, Maslowski W. 2000. The Fish assemblages in the Barents Sea 269
Arctic Ocean response to the North Atlantic oscillation. Journal Mahon R, Brown SK, Zwanenburg KCT, Atkinson DB, Buja KR, of Climate 13(15):2671 96. Claflin L, Howell GD, Monaco ME, O’Boyle RN, Sinclair M. Dolgov AV. 1994. Some aspects of biology of non-target fish 1998. Assemblages and biogeography of demersal fishes of the species in the Barents Sea. ICES Council Meeting O:12 east coast of North America. Canadian Journal of Fisheries and 1994:23. Aquatic Sciences 55(7):1704 38. Ekman S. 1953. The Boreal Fauna of the North Atlantic. Murawski SA. 1993. Climate change and marine fish distribu- Zoogeography of the Sea. London: Sidgwick & Jackson. p tions: forecasting from historical analogy. Transactions of the 100 41. American Fisheries Society 122(5):647 58. Farina AC, Freire J, Gonzalez Gurriaran E. 1997. Demersal fish Nakken O. 1998. Past, present and future exploitation and assemblages in the Galician continental shelf and upper slope management of marine resources in the Barents Sea and (NW Spain): spatial structure and long-term changes. Estuar- adjacent areas. Fisheries Research 37(1 3):23 35. ine. Coastal and Shelf Science 44(4):435 54. Nilssen EM, Hopkins CCE. 1992. Regional variability in fish Fossheim M. 2000. Sammensetting og fordeling av fisk i det prawn communities and catches in the Barents Sea, and their sørvestlige Barentshavet i perioden 1997 1999. Cand. scient., relationship to the environment. ICES Marine Science Sym- University of Tromsø. posium 195:331 48. Fowler J, Cohen L, Jarvis P. 1998. The strength and significance Overholtz WJ, Tyler AV. 1985. Long-term responses of the of a correlation. In: Practical Statistics for Field Biology, 2nd demersal fish assemblages of Georges Bank. Fishery Bulletin edn. Chichester: John Wiley & Sons. p 132. 83(4):507 20. Gaertner JC, Chessel D, Bertrand J. 1998. Stability of spatial Reithe S, Aschan M. 2004. Bioeconomic analysis of by-catch of structures of demersal assemblages: a multitable approach. juvenile fish in the shrimp fisheries an evaluation of manage- Aquatic Living Resources 11(2):75 85. ment procedures in the Barents Sea. Environmental & Re- Gomes MC, Haedrich RL, Villagarcia MG. 1995. Spatial and source Economics 28(1):55 72. temporal changes in the groundfish assemblages on the north- Sakshaug E. 1995. A synopsis of the biomass distribution and east Newfoundland/Labrador Shelf, north-west Atlantic, energetics of the pelagic ecosystem of the Barents Sea. ICES 1978 1991. Fisheries Oceanography 4(2):85 101. Council Meeting 1995 Mini 3:11. Greenacre MJ. 1984. Theory and Applications of Correspon- Shepherd JG, Pope JG, Cousens RD. 1984. Variations in fish dence Analysis. London: Academic Press. stocks and hypothesis concerning their links with climate. Greenstreet SPR, Hall SJ. 1996. Fishing and the ground-fish Rapport et Proce`s-Verbaux des Re´unions Conseil International assemblage structure in the north-western North Sea: an pour l’Exploration de la Mer 185:255 67. analysis of long-term and spatial trends. Journal of Animal Shevelev MS, Tereshchenko VV, Yaragina NA. 1987. Distribution Ecology 65(5):577 98. and behaviour of demersal fishes in the Barents and Norwegian Grimm V, Wissel C. 1997. Babel, or the ecological stability Seas, and the factors influencing them. In: Loeng H, editor. discussions: an inventory and analysis of terminology and a The Effect of Oceanographic Conditions on Distribution and guide for avoiding confusion. Oecologia 109(3):323 34. Population Dynamics of Commercial Fish Stocks in the Horn MH. 1980. Diversity and ecological roles of noncommercial Barents Sea. Bergen: Institute of Marine Research. p 181 90. fishes in California marine habitats. California Cooperative ter Braak CJF. 1997. Ordination. In: Jongman RHG, ter Braak Oceanic Fisheries Investigations Reports 21:37 47. CJF, van Tongeren OFR, editors. Data Analysis in Community Høines AS, Bergstad OA, Albert OT. 1998. The structure and and Landscape Ecology. Cambridge: Cambridge University temporal stability of the fish community on a coastal bank Press. p 91 173. utilized as a spawning ground by herring. ICES Journal of Tyler AV, Gabriel WL, Overholtz WJ. 1982. Adaptive manage- Marine Science 55(2):271 88. ment based on structure of fish assemblages of northern Jacob W, McClatchie S, Probert PK, Hurst RJ. 1998. Demersal continental shelves. Canadian Special Publication of Fisheries fish assemblages off southern New Zealand in relation to depth and Aquatic Sciences 59:149 56. and temperature. Deep-Sea Research I 45(12):2119 55. Ungaro N, Marano G, Vlora A, Martino M. 1998. Space time Jay CV. 1996. Distribution of bottom-trawl fish assemblages over variations of demersal fish assemblages in the South-western the continental shelf and upper slope of the US west coast, Adriatic sea. Vie et milieu Life and Environment 48(3):191 1977 1992. Canadian Journal of Fisheries and Aquatic 201. Sciences 53(6):1203 25. Weslawski M, Kwasniewski S. 1983. Application of biological Loeng H. 1989. The influence of temperature on some fish indicators for determination of the reach and origin of sea population parameters in the Barents Sea. Journal of Northwest currents within the region of Spitsbergen. Polskie Archiwum Hydrobiologii 30(3):189 97. Atlantic Fisheries Science 9(2):103 13. Loeng H. 1991. Features of the physical oceanographic conditions Zenkevich LA. 1956. The Barents Sea. Seas of the USSR, their Fauna and Flora. 2nd edn. Washington DC: US Navy of the Barents Sea. Polar Research 10(1):5 18. Hydrographic Office. p 240 73. Loeng H, Ozhigin V, .A˚ dlandsvik B. 1997. Water fluxes through the Barents Sea. ICES Journal of Marine Science 54(3): 310 17. Editorial responsibility: Aril Slotte