Journal of Fish Biology (2014) 84, 1904–1925 doi:10.1111/jfb.12407, available online at wileyonlinelibrary.com

Distinction among North Atlantic cod Gadus morhua stocks by tissue fatty acid profiles H. Joensen* and O. Grahl-Nielsen † ‡ *Department of Science and Technology, University of the Faroe Islands, Nóatún 3, FO-100 Tórshavn, Faroe Islands and †Department of Chemistry, University of Bergen, Allegaten 41, N-5007 Bergen, Norway (Received 22 October 2013, Accepted 14 March 2014) The fatty acid (FA) profiles of the white muscle and heart tissues of cod Gadus morhua from five locations, Faroe Bank, Faroe Plateau, North-West Iceland, Norway–Barents Sea and Denmark–Skagerrak, were population dependent. The interregional differences of FAs were significantly dissimilar (P < 0⋅01) in most cases. By way of a rapid and simple analytical method, the stock dependence and harvest location of individual G. morhua were chemometrically determined by multivariate principal component analysis. The difference among the stocks was correlated with the average water temperature at the harvest locations. It thus appears that the tissue FA profile is a phenotypic trait that is partly temperature driven. © 2014 The Fisheries Society of the British Isles

Key words: biological marker; fillet; harvest location; heart tissue; identification of individuals.

INTRODUCTION Cod Gadus morhua L. 1758 in the North Atlantic Ocean has been a major target for fisheries for centuries and has also been an essential commodity in the commerce among nations (Kurlansky, 1997). In line with the advancing technological development of fishing gear and vessels during recent decades, many of the local G. morhua stocks have been exploited so intensively that some are seriously reduced and others are over-fished. Loss of genetic variability due to heavy harvesting of genetically different populations can lead to diminution of productivity of future generations (Imsland & Jónsdóttir, 2003). Identification and thorough understanding of stock structure are necessary prerequisites for designing appropriate proactive management regulations in fisheries where multiple stocks are differentially exploited (Ricker, 1981). Recent improvements in large-scale genetic sequencing and advances in bioinformatics have led to new markers, single nucleotide polymorphisms (SNPs), with the highest discriminatory power ever known, outperforming even the strongly segregating microsatellites (Helyar et al., 2011). Even if SNPs are expected to be quite invariable, analysis of temporally replicated samples of G. morhua from three different fishing grounds revealed some non-significant changes in SNP allele frequencies (Nielsen ‡Author to whom correspondence should be addressed. Tel: +47 55583447; email: Otto.Grahl-Nielsen@ kj.uib.no

1904 © 2014 The Fisheries Society of the British Isles

D I S T I N G U I S H I N G G A D U S M O R H UA S TO C K S

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et al., 2012). As a consequence, the authors recommend a regular validation of the SNP database because the effect of fluctuating environmental variables is not well known. Moreover, genome studies of the gene-associated SNPs, which may be under direct or indirect selection, imply strongly that G. morhua populations adapt genetically to local environmental conditions despite substantial gene flow (Nielsen et al., 2012). Considerable research has been carried out to investigate potential G. morhua populations in the North Atlantic Ocean. In addition to genetic methods, such as mtDNA (Carr & Marshall, 1991), minisatellites (Galvin et al., 1995) and microsatellites (Ruzzante et al., 1996), many non-genetic techniques, such as morphology (Pepin & Carr, 1993), meristics (Pepin & Carr, 1993), biochemical methods (Cross & Payne, 1978), allozymes (Pogson et al., 1995), haemoglobin (Jamieson & Birly, 1989; Jónsdóttir et al., 1999), synaptophysin (Jónsdóttir et al., 1999), pantophysin (Case et al., 2005), restriction fragment length polymorphism (RFLP) (Pogson et al., 1995), otolith shape analysis (Jónsdóttir et al., 2006), otolith microchemistry (Svedäng et al., 2010; Thorisson et al., 2011; D ́ Avignon & Rose, 2013), electronic data storage tags (Righton et al., 2010) and conventional tags (E. Magnussen, unpubl. data) have been used. Probably owing to weak genetic differentiation (Pampoulie et al., 2008a), the investigations have not led to an unambiguous conclusion about the population structure, and some findings are even contradictory (Jónsdóttir et al., 2003; Pampoulie et al., 2008b) The relatively new fatty acid (FA) profile method (FAPROM) may identify diet-induced stock differences when applied to triacylglyceride-rich tissues, such as intestinal fat or brown muscle tissue, and genetically induced stock differences when applied to phospholipid-rich tissues, such as white muscle and heart tissue (Joensen et al., 2000; Joensen, 2002; Grahl-Nielsen, 2005). FAPROM is a multivariate approach and has the ability to discriminate at species level, stock level and individual level. It is relatively fast, inexpensive and requires a comparatively small sample size. The results are displayed in easy interpretable, clear and detailed principal component (PC) plots. Quantitative measures of differences may also be applied. The purpose of this study was to pursue this method further by determining the FAs in the phospholipid-rich white muscle and heart tissues of G. morhua from five harvest locations in the north-east Atlantic Ocean. The objective was to investigate if the tissue FA composition can be used as a non-genetic marker for differentiation among the various populations, and whether individual G. morhua could be reassigned to its harvest location. White muscle and heart have different FA lipid compositions, so obtaining similar results with both tissues would strengthen the conclusions.

MATERIALS AND METHODS SAMPLING Gadus morhua were caught by research vessels and a commercial fishing boat in five areas in the North Atlantic Ocean (Fig. 1) in the autumn of 2003. The fish were 3–4 years of age and of both sexes (Table I). Except for the Danish G. morhua, the specimens were frozen immediately after killing, subsequently glazed with water and ice and kept frozen (−20∘ C) until excision of sub-samples 2–6 weeks later. The fish from Denmark were purchased at the fish market in Hirtsals and shipped as frozen goods to the Faroe Islands. The exact harvest location and corresponding depth in Skagerrak were not reported. The viscera had been removed, so the sex and the FA profile of the heart could not be determined.

© 2014 The Fisheries Society of the British Isles, Journal of Fish Biology 2014, 84, 1904–1925

n

25

25 25

23

25

3⋅6 ± 1⋅8a

9⋅3 ± 0⋅3b 8⋅3 ± 1⋅2a

6⋅4 ± 2⋅1a

7⋅2 ± 2⋅2a

NW Iceland

Faroe Bank Faroe Plateau

Norway (Barents Sea) Denmark (Skagerrak)*

–

Bjarni Sæmundsson Mascot Magnus Heinason Johan Hjort

Vessel

xx October 2003

12 September 2003

20–22 October 2003 17 October 2003

5 October 2003

Sampling date

–

72∘ 58′ N –

31∘ 12′ E

–

279

107−132 94

61∘ 00′ N 08∘ 57′ W 62∘ 23′ N 07∘ 27′ W

Depth (m) 91

Longitude

65∘ 46′ N 23∘ 42′ W

Latitude

Position Mass (g)

2600 ± 600

450 ± 170

3200 ± 800 2000 ± 200

825 ± 125

n, sample size. *The eviscerated Danish Gadus morhua was bought at a fish market; the vessel, sampling date, exact position and depth were not given. a From Righton et al. (2010). b From Magnussen (2007) and Nielsen et al. (2007).

Sampling location

Annual mean water temperature (∘ C)

65 ± 5

38 ± 5

68 ± 6 58 ± 2

45 ± 2

Total length (cm)

3⋅9 ± 0⋅6

3⋅2 ± 0⋅4

2⋅7 ± 0⋅6 3⋅9 ± 0⋅5

4⋅0 ± 0⋅4

Age (year)

–

41

60 52

40

–

59

40 48

60

Female Male

Sex

Table I. The five sampling locations in the north–east Atlantic Ocean. The start positions of the hauls are given. Values are means ± s.d.

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© 2014 The Fisheries Society of the British Isles, Journal of Fish Biology 2014, 84, 1904–1925

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40° W

30° W

20° W 10° W 0° E 10° E

20° E

30° E

40° W Greenland

N

70° N 70° N 30° E

30° W

I Iceland

P 60° N

B

60° N

Faroe Islands

Norway 20° E D Denmark

20° W

U.K. 50° N 50° N

10° W

0° E

10° E

Fig. 1. Gadus morhua were harvested at the following locations: Iceland (I), Norway–Barents Sea (N), Faroe Plateau (P), Faroe Bank (B) and Denmark–Skagerrak (D).

T E M P E R AT U R E D ATA Temperature data were obtained with implanted electronic data-logging tags from 384 recaptured adult G. morhua from eight geographical fishery areas in the north-east Atlantic Ocean from 1999 to 2007 (Righton et al., 2010). The tags were programmed to record depth and temperature regularly. Annual mean temperature data from four of these eight marine locations were utilized as direct observations of the thermal niches preferred by local G. morhua stocks (Table I). These four geographical areas, north-west of Iceland, Faroe Plateau, Barents Sea and Skagerrak described in the study by Righton et al. (2010), coincide

© 2014 The Fisheries Society of the British Isles, Journal of Fish Biology 2014, 84, 1904–1925

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H . J O E N S E N A N D O . G R A H L- N I E L S E N

with the fishing grounds where the 2003 autumn sampling was carried out. The temperature on the Faroe Bank was measured directly with a calibrated data logger, MINILOG (Vemco, http://vemco.com/products/minilog-ii-t/), for 1997–2005 (Magnussen, 2007; unpubl. data).

M E T H A N O LY S I S Tissue samples, weighing c. 30–50 mg, were processed immediately upon thawing. The heart was carefully washed with distilled water to remove blood and dried on filter paper, and a sub-sample was cut from the tip. For the muscle samples, sub-samples from each fish were excised separately from the anterior dorsal part of the right and left fillets, carefully avoiding red muscle, skin and bone. The sub-samples were transferred immediately to weighed, thick-walled, 15-ml glass vials with teflon-lined screwcaps, and the mass was accurately determined. Earlier, 50⋅0 μl of a chloroform (puriss p.a. 99⋅0–99⋅4%, Sigma-Aldrich; www.sigmaaldrich.com) solution with an accurately determined concentration of the 19:0 FA methyl ester (FAME) had been added to the vials, and the chloroform was subsequently evaporated. This left an accurately known amount of 19:0 FAME as internal standard and 0⋅5 ml of anhydrous methanol, containing 2 mol l−1 hydrogen chloride (HCl), was added to each vial. The reagent was made by bubbling HCl gas, generated by letting concentrated hydrochloric acid (37%, Merck; www.merck.com) slowly into concentrated sulphuric acid (96%, Merck), into methanol (HPLC grade, 99⋅9%, Sigma-Aldrich). After exchange of the atmosphere in the tubes with nitrogen gas, the tubes were closed securely and placed in an oven for 2 h at 90∘ C for complete methanolysis (Meier et al., 2006). After methanolysis, approximately half of the MeOH/HCl solution was evaporated using nitrogen gas and 0⋅5 ml of distilled water was added to reduce the solubility of the formed FAMEs. They were extracted twice with 1⋅0 ml hexane (HPLC grade, Rathburn; www.rathburn.co.uk). The solution was mixed by vigorous shaking by hand for 1 min, followed by 6 min of centrifugation (600g). The hexane was withdrawn using a Pasteur pipette. C H R O M AT O G R A P H Y One microlitre of the combined hexane extracts was injected splitless (the split was opened after 4 min) and chromatographed on a 25 m × 0⋅25 mm (internal diameter) fused silica column with polyethylene glycol (PEG) for the stationary phase, with a thickness of 0.2 μm (CP-WAX 52CB Chrompack; www.chrompack.net), and with helium at 137 895 Pa for the mobile phase. The column was mounted in a Hewlett-Packard 5890A gas chromatograph (www.agilent.com) equipped with a Hewlett-Packard 7673A autosampler and a flame ionization detector (FID). The injector temperature was set at 260∘ C and the detector temperature at 330∘ C. The oven was programmed as follows: 90∘ C for 4 min, 30∘ C min−1 to 165∘ C and then 3∘ C min−1 to 225∘ C, where it was left isothermally for 10⋅5 min before cooling for the next run. The FID signal was converted from analogue to digital, recorded, stored and treated by VG-Multichrome software. A total of 37 chromatographic peaks were identified by comparison with a chromatogram of a standard mixture of 20 FAMEs, gas liquid chromatography reference standard 68D from Nu-Chek-Prep (www.nu-chekprep.com), by chromatographing selected samples under identical conditions with mass spectrometric detection on a Fison 800 GC-MS (www.thermoscientific.com), and based on experience from previous gas chromatograph (GC) analyses of FAMEs under identical conditions. To monitor the performance of the column in the standard FAME mixture was chromatographed at regular intervals for each 10th sample. Empirical response factors relative to 18:0 FAME were computed for the 20 FAMEs present in known amounts in the standard mixture. The response factors for each of the FAME not present in the standard mixture were estimated by comparison with the standard FAME that resembled them most closely in terms of chain length and number of double bonds. The areas of the FAME peaks were corrected with the response factors, and the relative amount of each FA in a sample was expressed as the per cent its area made up of the total area of all FAs in the sample. Two degradation products of cholesterol, cholesta-3,5-diene and cholesta-2,5-diene, were present in the chromatograms. It has been shown that the decomposition of cholesterol is reproducible, and these two peaks were used to determine the level of cholesterol in the tissue sample. The response factor for their combined areas was found to be 0⋅27 ± 0⋅02 relative to 19:0 (Kwetegyeka et al., 2008).

© 2014 The Fisheries Society of the British Isles, Journal of Fish Biology 2014, 84, 1904–1925

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The absolute amount of lipid in the samples, expressed as total FAs, was determined by comparison of the total area of the FAs with the area of the internal standard, 19:0. The mean of the two parallel fillet samples from each fish was used for evaluation of the results.

M U LT I VA R I AT E A N A LY S I S The relative values of the FAs were log10 transformed, thereby levelling out differences among FAs present in different amounts. With each sample positioned in the multidimensional space described by the log10 -transformed variables, the FAs, the two principal components (PCs) that described the largest and second largest variance among the samples were computed using the programme package SIRIUS 8.0 (Pattern Recognition Systems AS; www.prs.no) (Kvalheim & Karstang, 1987). In this manner, the relationship among the samples could be described in two dimensions, instead of the original 37, without considerable loss of the total original variance. The dominating, systematic variance among the samples will be manifested in the PCs. The samples were displayed via the co-ordinate system of PC1 v. PC2. PC analysis (PCA) is only of a qualitative nature. The significance of the observed difference among groups of samples was determined by soft independent modelling of class analogies (SIMCA) (Wold & Sjøstrøm, 1977) which was also available in the SIRIUS software package. Here space-filling PC models for the samples in each group were computed. The number of significant PCs for each model was determined by cross validation (Wold, 1978). In this study, one fifth of the data were omitted during the computation of the PCs and the omitted data were then predicted and compared to the actual values. This was repeated for the other four fifths of the data. The PC model that yielded the minimum prediction error for the omitted data was retained. Outliers were detected, and the models were recomputed after exclusion of the outliers. The outer limits of the models based on the residual s.d. (RSD) of the samples were calculated at 99% level of significance. The distances, expressed as RSD, of all 123 samples to each of the five models were calculated. Thus it was determined if the individual samples belonged to a model or not. To investigate if there was any temperature correlation between the locations and also if the sexes had different FA composition, the partial least square (PLS) method was used. A new response variable, i.e. a dependent variable, was added to the data matrix. For the temperature correlation, the dependent variable was the annual average water temperature at the five locations (Table I). The independent variables were the average values for the FAs (given in Tables II and III) and PLS co-ordinates were placed as vectors through the centroid of the samples in such a way that maximum correlation with the dependent variables was obtained. A PLS model with the best predictive performance was based on the significant PLS components, as determined by cross validation (Wold, 1978): one PLS component for the muscle samples and two PLS components for the heart samples. To facilitate the interpretation of the model for the heart samples, the two PLS components were combined into a single target-projected component (Rajalahti et al., 2009), which represented the direction of optimal correlation with the temperature. For the investigation of sex, the dependent variable was given the value of +1 for the males and −1 for the females. Each stock was investigated separately. With the samples positioned in the 37 dimensional space, one dimension for each FA, the first PLS co-ordinate will then be in the direction of the largest difference between the sexes, the second PLS co-ordinate will be orthogonal to the first and in the direction of the second largest difference between the groups, and so on.

RESULTS P R O P O RT I O N S O F FAs A N D L I P I D C O N T E N T

The white muscle and the heart contained the same array of FAs, although in different proportions (Tables II and III). The most conspicuous components in both tissues were polyunsaturated FAs (PUFAs) 22:6n3 (cervonic acid) and 20:5n3 (timnodonic acid), the monounsaturated FA (MUFA) 18:1n9 (oleic acid) and the saturated FA (SAFA) 16:0 (palmitic acid). The lipid content of the white muscle, determined as the sum of the FAs, ranged from 7⋅4 mg g−1 wet mass in the fish from the Faroe Plateau to 11

© 2014 The Fisheries Society of the British Isles, Journal of Fish Biology 2014, 84, 1904–1925

14:0 14:1n5 Iso-15:0 15:0 16:0 Iso-16:0 16:1n7 16:1n5 16:2n11 16:2n6 16:3n4 16:4n3 16:4n1 17:0 18:0 18:1n9 18:1n7 18:1n5 18:2n6 18:3n3 18:4n3 20:0 20:1n9 20:2n6 20:4n6

FA

1⋅1 ± 0⋅2 0⋅01 ± 0⋅01 0⋅08 ± 0⋅01 0⋅22 ± 0⋅02 17⋅9 ± 0⋅7 0⋅04 ± 0⋅01 1⋅6 ± 0⋅3 0⋅28 ± 0⋅03 0⋅31 ± 0⋅05 0⋅09 ± 0⋅02 0⋅18 ± 0⋅03 0⋅16 ± 0⋅02 0⋅10 ± 0⋅02 0⋅27 ± 0⋅04 3⋅8 ± 0⋅3 7⋅4 ± 0⋅6 2⋅6 ± 0⋅2 0⋅30 ± 0⋅04 0⋅7 ± 0⋅07 0⋅27 ± 0⋅06 0⋅44 ± 0⋅08 0⋅03 ± 0⋅01 2⋅4 ± 0⋅4 0⋅16 ± 0⋅02 1⋅5 ± 0⋅2

Iceland (n = 25)

0⋅9 ± 0⋅2 0⋅02 ± 0⋅01 0⋅09 ± 0⋅02 0⋅23 ± 0⋅03 17⋅4 ± 0⋅9 0⋅04 ± 0⋅02 1⋅2 ± 0⋅2 0⋅28 ± 0⋅03 0⋅33 ± 0⋅03 0⋅09 ± 0⋅02 0⋅17 ± 0⋅03 0⋅14 ± 0⋅03 0⋅10 ± 0⋅04 0⋅32 ± 0⋅06 4⋅4 ± 0⋅2 6⋅8 ± 0⋅6 2⋅6 ± 0⋅3 0⋅25 ± 0⋅04 0⋅7 ± 0⋅1 0⋅24 ± 0⋅08 0⋅28 ± 0⋅07 0⋅03 ± 0⋅01 1⋅9 ± 0⋅3 0⋅16 ± 0⋅03 1⋅9 ± 0⋅4

Norway (n = 23)

1⋅0 ± 0⋅6 0⋅04 ± 0⋅03 0⋅08 ± 0⋅02 0⋅23 ± 0⋅02 19⋅2 ± 0⋅9 0⋅03 ± 0⋅01 0⋅9 ± 0⋅1 0⋅22 ± 0⋅03 0⋅37 ± 0⋅04 0⋅1 ± 0⋅02 0⋅21 ± 0⋅03 0⋅19 ± 0⋅03 0⋅11 ± 0⋅03 0⋅47 ± 0⋅06 5⋅5 ± 0⋅3 6⋅1 ± 0⋅5 2⋅1 ± 0⋅3 0⋅24 ± 0⋅02 0⋅6 ± 0⋅1 0⋅31 ± 0⋅07 0⋅40 ± 0⋅06 0⋅04 ± 0⋅01 0⋅8 ± 0⋅2 0⋅15 ± 0⋅02 1⋅9 ± 0⋅4

Faroe Plateau (n = 25) 0⋅53 ± 0⋅05 0⋅03 ± 0⋅01 0⋅06 ± 0⋅02 0⋅25 ± 0⋅03 18⋅7 ± 0⋅9 0⋅03 ± 0⋅02 1⋅0 ± 0⋅2 0⋅18 ± 0⋅03 0⋅41 ± 0⋅05 0⋅08 ± 0⋅02 0⋅29 ± 0⋅05 0⋅27 ± 0⋅06 0⋅10 ± 0⋅02 0⋅53 ± 0⋅07 5⋅7 ± 0⋅2 6⋅3 ± 0⋅5 2⋅1 ± 0⋅3 0⋅20 ± 0⋅03 0⋅5 ± 0⋅1 0⋅18 ± 0⋅05 0⋅21 ± 0⋅05 0⋅04 ± 0⋅01 0⋅47 ± 0⋅06 0⋅17 ± 0⋅03 2⋅7 ± 0⋅6

Faroe Bank (n = 25) 1⋅0 ± 0⋅2 0⋅03 ± 0⋅01 0⋅10 ± 0⋅03 0⋅36 ± 0⋅05 19 ± 1 0⋅07 ± 0⋅04 1⋅4 ± 0⋅4 0⋅30 ± 0⋅04 0⋅44 ± 0⋅09 0⋅17 ± 0⋅08 0⋅30 ± 0⋅07 0⋅24 ± 0⋅06 0⋅12 ± 0⋅03 0⋅48 ± 0⋅06 4⋅8 ± 0⋅4 6±1 3±1 0⋅24 ± 0⋅05 0⋅7 ± 0⋅2 0⋅3 ± 0⋅1 0⋅5 ± 0⋅1 0⋅04 ± 0⋅01 1⋅1 ± 0⋅4 0⋅23 ± 0⋅05 3⋅0 ± 0⋅9

Denmark (n = 25)

** ** **

**

**

**

** ** ** ** ** ** ** **

** ** ** ** ** ** ** **

** **

** ** ** ** **

I v. B ** ** ** ** ** ** ** ** **

**

I v. P

**

**

**

** ** **

**

**

I v. N

** ** ** **

**

** ** ** ** ** ** ** **

**

** ** **

I v. D

** ** ** ** **

** ** ** **

** **

** ** ** ** **

**

N v. P

**

** ** ** ** ** ** ** ** ** **

** **

** ** **

** ** ** ** **

N v. B

Pair-wise t-test

** ** ** ** ** **

** **

** ** ** **

** ** **

**

N v. D

**

**

** **

**

**

** **

** **

** **

**

P v. B

** ** **

**

**

**

** ** ** ** ** ** **

** **

P v. D

** **

** ** ** ** **

** ** **

**

** ** **

** **

**

B v. D

Table II. Relative amounts (as % of sum mean ± s.d.) of fatty acids and cholesterol (not included in the sum) in the anterior part of the fillet of Gadus morhua from Iceland (I), Norway–Barents Sea (N), Faroe Plateau (P), Faroe Bank (B) and Denmark–Skagerrak (D). **, Significant differences (P < 0⋅01) between locations in levels of FAs

1910 H . J O E N S E N A N D O . G R A H L- N I E L S E N

© 2014 The Fisheries Society of the British Isles, Journal of Fish Biology 2014, 84, 1904–1925

© 2014 The Fisheries Society of the British Isles, Journal of Fish Biology 2014, 84, 1904–1925

0⋅06 ± 0⋅01 12 ± 1 0⋅23 ± 0⋅03 0⋅06 ± 0⋅02 1⋅1 ± 0⋅2 0⋅28 ± 0⋅04 0⋅22 ± 0⋅04 0⋅34 ± 0⋅03 1⋅4 ± 0⋅1 41 ± 2 0⋅05 ± 0⋅01 1⋅2 ± 0⋅1 11 ± 2 23⋅6 ± 0⋅8 17⋅2 ± 0⋅8 59 ± 2 57 ± 2 1⋅57 ± 0⋅09 36 ± 3 11 ± 1

0⋅04 ± 0⋅01 11 ± 2 0⋅12 ± 0⋅03 0⋅08 ± 0⋅03 0⋅5 ± 0⋅1 0⋅23 ± 0⋅05 0⋅21 ± 0⋅07 0⋅39 ± 0⋅04 1⋅2 ± 0⋅1 45 ± 3 0⋅07 ± 0⋅02 1⋅1 ± 0⋅2 16 ± 1 23⋅6 ± 0⋅9 14⋅9 ± 0⋅797 62 ± 4 60 ± 4 1⋅6 ± 0⋅1 38 ± 4 8±1

Norway (n = 23) 0⋅05 ± 0⋅01 12 ± 1 0⋅16 ± 0⋅04 0⋅08 ± 0⋅02 0⋅34 ± 0⋅06 0⋅09 ± 0⋅01 0⋅28 ± 0⋅06 0⋅42 ± 0⋅07 1⋅3 ± 0⋅2 43 ± 2 0⋅11 ± 0⋅02 1⋅7 ± 0⋅1 16 ± 2 27 ± 1 12⋅5 ± 0⋅6 62 ± 2 59 ± 2 1⋅6 ± 0⋅1 37 ± 4 7⋅4 ± 0⋅8

Faroe Plateau (n = 25) 0⋅05 ± 0⋅02 8±1 0⋅09 ± 0⋅01 0⋅09 ± 0⋅03 0⋅16 ± 0⋅04 0⋅08 ± 0⋅01 0⋅4 ± 0⋅1 0⋅8 ± 0⋅1 1⋅0 ± 0⋅2 46 ± 1 0⋅11 ± 0⋅01 1⋅5 ± 0⋅1 17 ± 1 26⋅0 ± 0⋅9 12⋅0 ± 0⋅6 61 ± 2 58 ± 2 2⋅0 ± 0⋅2 29 ± 3 7⋅6 ± 0⋅8

Faroe Bank (n = 25) 0⋅07 ± 0⋅01 13 ± 3 0⋅15 ± 0⋅04 0⋅11 ± 0⋅04 0⋅5 ± 0⋅2 0⋅14 ± 0⋅05 0⋅5 ± 0⋅2 0⋅6 d± 0⋅1 1⋅9 ± 0⋅9 38 ± 4 0⋅09 ± 0⋅02 1⋅3 ± 0⋅2 15 ± 2 26 ± 1 14 ± 2 60 ± 5 57 ± 5 2⋅3 ± 0⋅3 25 ± 4 8±1

Denmark (n = 25)

Pair-wise t-test

**

** ** ** **

** **

** ** **

** ** ** **

** ** ** ** ** **

**

** ** ** ** ** ** ** ** ** ** ** ** ** **

** ** ** ** ** ** ** ** **

**

** ** **

** ** **

**

** **

** ** ** ** **

** **

** ** ** ** ** **

**

** **

**

** ** ** ** ** **

** ** ** ** ** ** ** ** ** ** **

**

** ** ** ** ** **

** **

** ** **

I v. N I v. P I v. B I v. D N v. P N v. B N v. D P v. B P v. D B v. D

n, the number of fish analysed; FA, fatty acid; MUFA, monounsaturated FA; SAFA, saturated FA; PUFA, polyunsaturated FA.

20:3n3 20:5n3 21:5n3 22:0 22:1n11 22:1n9 22:4n6 22:5n6 22:5n3 22:6n3 24:0 24:1n9 Cholesterol ΣSAFA ΣMUFA ΣPUFA Σn3 Σn6 Σn3:Σn6 mg FA g−1 tissue

FA

Iceland (n = 25)

Table II. Continued

D I S T I N G U I S H I N G G A D U S M O R H UA S TO C K S

1911

14:0 14:1n5 Iso-15:0 15:0 16:0 Iso-16:0 16:1n7 16:1n5 16:2n11 16:2n6 16:3n4 16:4n3 16:4n1 17:0 18:0 18:1n9 18:1n7 18:1n5 18:2n6 18:3n3 18:4n3 20:0 20:1n9 20:2n6 20:4n6 20:3n3

FA

1⋅8 ± 0⋅3 0⋅02 ± 0⋅01 0⋅16 ± 0⋅03 0⋅29 ± 0⋅04 15 ± 1 0⋅07 ± 0⋅01 2⋅4 ± 0⋅4 0⋅34 ± 0⋅03 0⋅34 ± 0⋅06 0⋅13 ± 0⋅02 0⋅31 ± 0⋅05 0⋅20 ± 0⋅03 0⋅6 ± 0⋅1 0⋅32 ± 0⋅04 4⋅0 ± 0⋅5 9⋅5 ± 0⋅8 3⋅8 ± 0⋅4 0⋅49 ± 0⋅08 1⋅1 ± 0⋅1 0⋅5 ± 0⋅1 0⋅5 ± 0⋅1 0⋅06 ± 0⋅01 4⋅3 ± 0⋅8 0⋅31 ± 0⋅04 2⋅4 ± 0⋅5 0⋅10 ± 0⋅02

Iceland (n = 25)

1⋅7 ± 0⋅3 0⋅04 ± 0⋅03 0⋅19 ± 0⋅06 0⋅34 ± 0⋅05 16 ± 2 0⋅09 ± 0⋅02 1⋅8 ± 0⋅6 0⋅32 ± 0⋅03 0⋅42 ± 0⋅07 0⋅15 ± 0⋅03 0⋅37 ± 0⋅05 0⋅19 ± 0⋅03 0⋅8 ± 0⋅2 0⋅43 ± 0⋅08 5⋅3 ± 0⋅5 11 ± 1 4⋅8 ± 0⋅5 0⋅38 ± 0⋅07 1⋅0 ± 0⋅1 0⋅38 ± 0⋅09 0⋅2 ± 0⋅1 0⋅06 ± 0⋅01 3⋅6 ± 0⋅8 0⋅33 ± 0⋅04 3⋅4 ± 0⋅8 0⋅07 ± 0⋅02

Norway (n = 21) 1⋅2 ± 0⋅1 0⋅06 ± 0⋅02 0⋅17 ± 0⋅03 0⋅35 ± 0⋅04 17 ± 1 0⋅09 ± 0⋅02 1⋅4 ± 0⋅2 0⋅26 ± 0⋅03 0⋅57 ± 0⋅07 0⋅20 ± 0⋅03 0⋅44 ± 0⋅08 0⋅26 ± 0⋅04 0⋅9 ± 0⋅2 0⋅75 ± 0⋅08 6⋅0 ± 0⋅4 10⋅0 ± 0⋅6 3⋅1 ± 0⋅3 0⋅40 ± 0⋅03 0⋅9 ± 0⋅1 0⋅60 ± 0⋅09 0⋅42 ± 0⋅06 0⋅08 ± 0⋅01 1⋅3 ± 0⋅2 0⋅26 ± 0⋅03 3⋅1 ± 0⋅6 0⋅09 ± 0⋅01

Faroe Plateau (n = 23) 0⋅9 ± 0⋅1 0⋅05 ± 0⋅03 0⋅14 ± 0⋅05 0⋅4 ± 0⋅1 16 ± 2 0⋅09 ± 0⋅03 1⋅6 ± 0⋅4 0⋅25 ± 0⋅04 0⋅6 ± 0⋅1 0⋅20 ± 0⋅04 0⋅61 ± 0⋅08 0⋅4 ± 0⋅1 0⋅9 ± 0⋅2 0⋅8 ± 0⋅1 6⋅2 ± 0⋅4 11 ± 1 3⋅4 ± 0⋅4 0⋅36 ± 0⋅08 0⋅9 ± 0⋅2 0⋅4 ± 0⋅1 0⋅23 ± 0⋅08 0⋅09 ± 0⋅04 0⋅9 ± 0⋅2 0⋅31 ± 0⋅06 6±2 0⋅10 ± 0⋅02

Faroe Bank (n = 25)

** **

**

** ** ** ** ** ** ** ** **

** ** **

** ** ** ** **

I v. N

** ** ** ** ** ** ** ** **

** ** ** ** ** ** ** ** ** ** ** **

** **

I v. P

**

** ** **

** ** ** ** ** ** ** ** ** ** ** ** ** ** ** **

** **

I v. B

**

** ** ** ** ** **

** ** ** **

** ** ** ** ** **

** **

N v. P

Pair-wise t-test

** **

** **

**

** **

** ** ** ** **

**

**

N v. B

** ** **

** **

** **

** **

**

P v. B

Table III. Relative amounts (as % of sum mean ± s.d.) of fatty acids and cholesterol (not included in the sum) in heart tissue of Gadus morhua from Iceland (I), Norway–Barents Sea (N), Faroe Plateau (P), Faroe Bank (B) and Denmark–Skagerrak (D). **, Significant differences (P < 0⋅01) between locations in levels of FAs

1912 H . J O E N S E N A N D O . G R A H L- N I E L S E N

© 2014 The Fisheries Society of the British Isles, Journal of Fish Biology 2014, 84, 1904–1925

© 2014 The Fisheries Society of the British Isles, Journal of Fish Biology 2014, 84, 1904–1925

Pair-wise t-test

14 ± 1 0⋅09 ± 0⋅04 0⋅08 ± 0⋅02 2⋅1 ± 0⋅5 0⋅5 ± 0⋅1 0⋅10 ± 0⋅04 0⋅4 ± 0⋅1 1⋅0 ± 0⋅1 30 ± 2 0⋅09 ± 0⋅02 2⋅8 ± 0⋅5 18 ± 3 22 ± 2 26 ± 4 52 ± 4 46 ± 3 4⋅4 ± 0⋅8 10 ± 2 28 ± 3

9±1 0⋅09 ± 0⋅02 0⋅12 ± 0⋅05 1⋅1 ± 0⋅3 0⋅51 ± 0⋅08 0⋅11 ± 0⋅06 0⋅8 ± 0⋅4 0⋅9 ± 0⋅1 30 ± 3 0⋅07 ± 0⋅02 4±1 32 ± 3 24 ± 3 28 ± 4 48 ± 6 41 ± 4 6±1 7±2 18 ± 2

13⋅0 ± 0⋅7 0⋅09 ± 0⋅03 0⋅11 ± 0⋅02 0⋅6 ± 0⋅2 0⋅15 ± 0⋅03 0⋅17 ± 0⋅06 0⋅7 ± 0⋅3 1⋅1 ± 0⋅2 31 ± 2 0⋅11 ± 0⋅03 3⋅4 ± 0⋅7 25 ± 3 26 ± 2 21 ± 2 54 ± 5 47 ± 3 5±1 9±2 29 ± 3

9±1 0⋅07 ± 0⋅03 0⋅15 ± 0⋅06 0⋅3 ± 0⋅1 0⋅14 ± 0⋅03 0⋅3 ± 0⋅1 1⋅2 ± 0⋅4 1⋅1 ± 0⋅2 30 ± 3 0⋅10 ± 0⋅04 4±2 31 ± 7 25 ± 3 22 ± 4 52 ± 8 41 ± 5 9±3 5±2 20 ± 2 ** ** **

** **

** ** ** ** **

** **

** **

**

**

** **

** ** ** ** **

**

**

**

**

** ** **

**

**

** ** ** ** **

**

** **

** **

**

Iceland (n = 25) Norway (n = 21) Faroe Plateau (n = 23) Faroe Bank (n = 25) I v. N I v. P I v. B N v. P N v. B P v. B

n, number of fish analysed; FA, fatty acid; MUFA, monounsaturated FA; SAFA, saturated FA; PUFA, polyunsaturated FA.

20:5n3 21:5n3 22:0 22:1n11 22:1n9 22:4n6 22:5n6 22:5n3 22:6n3 24:0 24:1n9 Cholesterol ΣSAFA ΣMUFA ΣPUFA Σn3 Σn6 Σn3:Σn6 mg FA g−1 tissue

FA

Table III. Continued

D I S T I N G U I S H I N G G A D U S M O R H UA S TO C K S

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H . J O E N S E N A N D O . G R A H L- N I E L S E N

mg g−1 in the fish from Icelandic waters (Table II). The lipid content in the heart was higher, ranging from 18 mg g−1 in the fish from Norwegian waters to 29 mg g−1 in the fish from the Faroe Plateau (Table III). The proportion of cholesterol was also higher in the heart tissue, between 18 and 32% of the total FAs (Table III), than in the muscle tissue, i.e. between 11 and 17% (Table II). U N I VA R I AT E A N D M U LT I VA R I AT E A N A LY S I S

When compared pair-wise, the FAs of the fillet and heart samples of G. morhua from the five locations (four locations for heart samples) differed significantly (t-test, P < 0⋅01) in most of the 10 (six) cases (Tables II and III). For instance, fish from the Faroe Bank and Barents Sea had significantly higher proportions of 22:6n3 in the fillet than fish from the other areas. Despite the many significant differences in FAs among the locations, it was impossible to discern any stock structure by univariate inspections of the data in Tables II and III. The proportion of cholesterol in both tissues was lowest in fish from Icelandic waters, where the annual mean water temperature is the lowest (Table I). For the muscle tissue, there was a good correlation between cholesterol percentage and water temperature (r2 = 0⋅858) while the cholesterol proportion in the heart tissue was not correlated with the water temperature. A PCA applied to the mean values of FAs in muscle and heart tissues (Tables II and III) revealed the large divergence of the muscle tissue, on the left side of the resulting PC plot (Fig. 2), from the heart tissue, on the right. Mutual differences among the locations, however, were the same for both tissues, as manifested along the second PC. The FAs with the largest differences between the tissues were the ones positioned farthest to the left and right in the plot, i.e. 22:4n6, the n3 FAs and 16:0 had relatively high values in the muscle tissue, and correspondingly lower values in the heart tissue, while the reverse was the case for 16:4n1, in particular, and for the long-chained monoenes and the branched FAs. The FAs most responsible for the differences among the locations were 20:1n9, 22:1n9 and 22:2n11, with highest relative values in the fish from Iceland and lowest values in the fish from the Faroe Bank. The n6 FAs had highest values in the Faroe Bank fish and lowest in the fish from Iceland. The mean values of the FAs in the muscle and heart tissues (Tables II and III) correlated very well with the average annual water temperature at the five harvest locations, as determined by multivariate partial least squares (PLS, Fig. 3; r2 = 0⋅980 for the muscle samples and r2 = 0⋅998 for the heart samples). One significant PLS component was used for the model of the muscle samples, and two significant PLS components were used for the heart samples. The individual FAs contributed similarly to the temperature correlation for the two tissues (Fig. 4). With the exception of 14:0 and the two branched FAs, iso15:0 and iso16:0, all the SAFAs increased with increasing water temperature. For the MUFAs, the correlation with temperature was also systematic, where the proportions of all FAs except the shortest and longest, i.e. 14:1n5 and 24:1n9, decreased with increasing water temperature. For the PUFAs, no systematic trend in the temperature correlation was obvious, although the majority increased with increasing water temperature. When all the data from the 123 samples of fillets, or 94 heart samples, were subjected to PCA simultaneously, G. morhua from the various locations could be distinguished (Figs 5 and 6). Some overlap of the Danish and Norwegian fish and of Norwegian and

© 2014 The Fisheries Society of the British Isles, Journal of Fish Biology 2014, 84, 1904–1925

1915

D I S T I N G U I S H I N G G A D U S M O R H UA S TO C K S

PC2 35%

B

B

D

P

N

14:1n5 17:0 22:5n6 P 20:4n6 16:3n4 22:4n6 16:4n3 16:2n11 20:0 22:0 16:2n6 24:0 24:1n9 18:0 15:0 i-16:0 20:3n3 16:0 18:1n9 22:5n3 20:2n6 18:3n3 22:6n3 i-15:0 18:1n7 20:5n3 18:2n6 16:1n5 18:1n5 18:4n3 21:5n3 16:1n7

16:4n1

N

14:0

I 22:1n9 20:1n9 22:1n11

I PC1 50%

Fig. 2. Principal component (PC) plot of the average values of the fatty acids (FAs) in muscle tissue from Table II, on the left side, and in the heart tissue from Table III, on the right side. I, Iceland; N, Norway–Barents Sea; P, Faroe plateau; B, Faroe Bank, D, Denmark–Skagerrak. The position of the FAs in the plot indicates their importance for the distribution of the samples, i.e. 16:4n1 occur in relatively higher proportions in the heart tissue than in the muscle tissue, while the opposite is the case for 22:4n6 and 21:5n3. The monoenes, 22:1n9, 20:1n9 and 22:1n11, occur in relatively higher proportions in Gadus morhua from the coldest waters, while they also have relatively higher proportions in the heart tissue. The per cent variation along the first and second PC is given. The origin of the plot is indicated with a .

Icelandic fish, however, appeared for the samples of white muscle (Fig. 5), and also some overlap for the fish from the Faroe Bank and Plateau for the heart samples was observed (Fig. 6). By way of SIMCA models of the muscle samples, 110 of the 123 G. morhua were correctly classified to their own stock. The remaining 13 non-classified, one from Iceland, two from Norway, two from Faroe Plateau, one from Faroe Bank and seven from Denmark, were not wrongly classified to any of the other stocks. But six fish from Faroe Plateau and one fish from Faroe Bank were classified both to the Danish stock

© 2014 The Fisheries Society of the British Isles, Journal of Fish Biology 2014, 84, 1904–1925

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H . J O E N S E N A N D O . G R A H L- N I E L S E N

Predicted temperature (°C)

10

(a)

(b)

B

B P

P

8 D 6

4

2

N

N

I

2

r2 = 0·980

4

6

8

r2 = 0·998

I

10

2

4

6

8

10

Measured temperature (° C) Fig. 3. Predicted v. measured annual mean water temperature at the harvest locations: Iceland (I), Norway–Barents Sea (N), Faroe Plateau (P), Faroe Bank (B) and Denmark–Skagerrak (D) (Table I) based on partial least square (PLS) correlation with the average fatty acid composition in the (a) muscle (Table II) and (b) heart (Table III). For the muscle samples, one significant PLS component was used and two for the heart samples.

and to their own. The reason could be that the SIMCA model of the Danish G. morhua was more voluminous due to less controlled sampling. For the heart samples, 83 of the 94 G. morhua were correctly classified to their own stock. The remaining 11 non-classified were not allocated to any stock. No G. morhua was classified to more than one stock. By combining the classifications from the two tissues for the four harvest locations where heart samples were available, only two fish remained unclassified, and no fish was classified to more than one stock. SEX DIFFERENCES

As determined by PLS, the distinction between the sexes was not clear-cut in all cases. For the Norwegian stock, the difference was clear for both tissues. The difference was also clear for the Faroe Bank and Plateau stocks for the heart tissue, while the differences were not clear-cut in the other cases.

DISCUSSION Gadus morhua from the five harvest locations were clearly distinguished by the FA profile of their muscle and heart. With this method, 98% were correctly reassigned to their harvest location. The question arises then if differences in diet might have caused these observed differences in FA profiles of the tissues of G. morhua from the various locations. Numerous studies of the effect of the dietary lipids on fish tissues have been carried out. Some studies conclude that the FA composition of the diet is reflected in the fish fillet (Xu et al., 1993), particularly if unnatural non-marine ingredients, such as plant oil, are included in the diet (Mørkøre et al., 2007). Thus, FA profiles of ground up whole fish are proposed as a tool for studying trophic interactions (Kirsch et al., 1998). A more detailed knowledge is obtained, however, when different tissues and lipid classes are studied separately. The effect of the diet FAs differs among various tissues.

© 2014 The Fisheries Society of the British Isles, Journal of Fish Biology 2014, 84, 1904–1925

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D I S T I N G U I S H I N G G A D U S M O R H UA S TO C K S

4

Fatty acid loadings

2

0

–2

–6

iso 14:0 15 :0 iso 15:0 16 :0 16 :0 17 :0 18 :0 20 :0 22 : 24 0 14 :0 :1 16 n5 :1 16 n7 :1 18 n5 :1 18 n9 :1 18 n7 :1 20 n5 22 :1n9 :1 n 22 11 : 24 1n9 : 16 1n9 :2 16 n11 :2 16 n6 :3 16 n4 :4 16 n1 :4 18 n3 :2 18 n6 :3 18 n3 :4 20 n3 :2 20 n6 :4 20 n6 :3 20 n3 :5 21 n3 :5 22 n3 :4 22 n6 :5 22 n6 :5 22 n3 :6 n3

–4

SAFA

MUFA

PUFA

Fig. 4. The importance, measured as partial least square (PLS) loadings, of the individual fatty acids (FAs) for the multivariate correlation of the combined FAs with the water temperature, as shown in Fig. 3. The FAs with positive loadings were increasing with increase in the temperature, and the ones with negative loadings were decreasing ( , muscle samples; , heart samples).

A study of Atlantic salmon Salmo salar L. 1758 red muscle, white muscle, intestinal fat, liver and heart showed clearly that the heart was least influenced and thereby the most stable tissue (Viga & Grahl-Nielsen, 1990). In another similar study of gills, white muscle, liver and heart and brain of S. salar, Mjaavatten et al. (1998) showed that heart and brain were least affected by the diet FAs. Moreover, the FA composition of the total lipids, and also of phosphatidylcholine and phosphatidylethanolamine in the heart tissue of G. morhua differed substantially from that of the diet (Joensen et al., 2000). In a detailed nutritional study of the lipid classes in white muscle, liver, gills and heart of G. morhua, the FAs in the neutral lipids were influenced to some extent by dietary FAs, but the phospholipids, especially phosphatidylinositol, were independent of the dietary intake (Lie et al., 1992). These studies do not support a reflection of the dietary FAs in tissues and corresponding lipid classes. On the contrary, the dietary FAs are selectively incorporated into the phospholipids in order to obtain carefully regulated physiological levels. The FA profile method (FAPROM) has been utilized successfully for discrimination among different species of freshwater fishes (Kwetegyeka et al., 2006, 2011; Grahl-Nielsen et al., 2011), marine redfish species Sebastes viviparus (Krøyer 1845), Sebastes marinus (Ascanius 1772) and Sebastes mentella Travin 1951 (Joensen & Grahl-Nielsen, 2001) and S. mentella stocks (Joensen & Grahl-Nielsen, 2004). The same samples from S. mentella caught at 11 locations in the North Atlantic Ocean were analysed by five different methods: FAPROM, microsatellites, enzymes, otolith shape and morphology. A comparison of the results showed that the findings from FAPROM and the microsatellite analysis were most similar, almost identical, thereby

© 2014 The Fisheries Society of the British Isles, Journal of Fish Biology 2014, 84, 1904–1925

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PC2 22%

D D D D

D D

D DD D

DD D B BB B B BB B B B BBB BB BBB B B B B B B B

D

D

N

I I I N D P D I NI I II I I PP D PP DN N I P I II I P PPPDP N I NI N ND NNDN I P II I I N P P P N I D N PPP N N NN NP P PP N P N P

P

D

D

N

I

PC1 53% Fig. 5. Plot of principal component 1 (PC1) v. PC2 of Gadus morhua based on the composition of 37 fatty acids (FAs) (Table II) in white muscle. Each letter symbolizes one individual G. morhua: Iceland (I), Norway–Barents Sea (N), Faroe Plateau (P), Faroe Bank (B) and Denmark–Skagerrak (D). The percentage of the total variance along each of the PCs is given. The origin is marked with a .

confirming a close relation between the FA profile in phospholipids and the genetic code (Anon, 2005). Furthermore, a strong genetic component in the determination of the FA composition of the membrane lipids in fish tissues has been suggested by Olsen (1999) and Zenebe et al. (2003). The very low lipid content in the muscle and heart, i.e. FAs around 10 mg g−1 for the muscle samples and between 20 and 30 mg g−1 for the heart tissue (Tables II and III), indicates a low content of storage lipids and triacylglycerides, and that the lipids are dominated by polar, membrane lipids. Based on this, and on the findings in a previous investigation on G. morhua from the Faroe Bank and Plateau and on the many studies showing genetic differences among the various North Atlantic G. morhua stocks, it is reasonable to believe that diet plays a minor role in the differentiation between the stocks. A large-scale programme with the two G. morhua populations was undertaken in 1994. A proportion of the progenies of the wild populations was reared under identical circumstances, with the same feeding regime, from hatching, and therefore all the combined biotic influences (e.g. condition of the fish, swimming activity, growth, age and reproductive cycles with selective mobilization of FAs from the tissues during maturation of the gonads) and abiotic factors (e.g. temperature, pressure, salinity, light, seasonal variations, diet and stress factors such as handling, noise and ionizing radiation) were identical for the individuals in both populations. Despite these identical circumstances, the FA profile method of heart tissue 3 years and 8 months after fertilization discriminated between the Faroe Bank G. morhua and the Faroe Plateau G. morhua (Joensen et al., 2000). These results were interpreted as a genetic difference. More conclusive evidence would be obtained if the two populations in captivity were sampled and analysed over several generations. Numerous studies have investigated population structuring of the North Atlantic G. morhua using a variety of molecular approaches (Bradbury et al., 2011; Pampoulie

© 2014 The Fisheries Society of the British Isles, Journal of Fish Biology 2014, 84, 1904–1925

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D I S T I N G U I S H I N G G A D U S M O R H UA S TO C K S

PC2 10%

B BB B B BB B

B B B B B B

P P PP P P P P P P P P B B P PP P P P PPP BP B P B B P BB B B BB B B B

I I I II I I I I II I II I II I I I I I NN N NN N N N N N N NN N N NN NNN N N N N I

I

I

PC1 56% Fig. 6. Plot of principal component (PC1) v. PC2 of Gadus morhua based on the composition of 24 fatty acids (FAs) (Table III) in heart tissue. Each letter symbolizes one individual G. morhua: Iceland (I), Norway–Barents Sea (N), Faroe Plateau (P), Faroe Bank (B) and Denmark–Skagerrak (D). The encircled letters represent the average values of FAs found in the heart tissue of farmed 3.66 year G. morhua from Faroe Plateau and Faroe Bank, respectively, collected in 1997 (Joensen et al., 2000), projected onto the PC plot without having any influence on the computation of the PCs. The percentage of the total variance along each of the PCs is given. The origin is marked with a .

et al., 2008, 2011). Nielsen et al. (2009) found that two distinct populations occurred in Faroese waters, and these were distinct from G. morhua from west of Scotland and from the northern North Sea. Gadus morhua from the North Sea, Baltic Sea and north-eastern Arctic Ocean were shown by microsatellite markers to belong to different populations (Nielsen et al., 2001). It is a challenge to assign individual G. morhua to a population of origin. This was achieved in the north-eastern part of the Atlantic Ocean with 73% success with SNPs (Bradbury et al., 2011; Poulsen et al., 2011). Using six different biological markers, Higgins et al. (2010) were able to classify G. morhua to five different harvest locations and two farms. Still, the need for biological markers in distinguishing populations of G. morhua has been highlighted (Galley et al., 2006; Higgins et al., 2010). The present results showed that the FA profile method is a valuable complement to other methods for identification of individual North Atlantic G. morhua to their harvest location and stock affiliation. The composition of the FAs was different in the two tissues, with higher proportion of the MUFAs and lower proportion of the PUFAs in the heart tissue, while the sum of the SAFAs was about the same. The muscle tissue had a higher proportion of the n3 FAs and a much lower proportion of the n6 FAs, leading to a much higher n3:n6. Although there were clear differences in the proportion of the FAs between the two tissues, the differences between the locations were in the same direction for each of the FAs in both tissues. This supports the hypothesis that the FA profile has a strong genetic component. The differences in tissue FA profiles of G. morhua from the five populations were correlated with the differences in the yearly average water temperature at the harvest

© 2014 The Fisheries Society of the British Isles, Journal of Fish Biology 2014, 84, 1904–1925

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H . J O E N S E N A N D O . G R A H L- N I E L S E N

locations (Fig. 3). If the differences had been caused by direct effect of temperature on membrane lipids, the result should have been an increase in the PUFAs with decreasing water temperature (Keough et al., 1987; Ruyter et al., 2003; Tocher et al., 2004). In the present case, there was no obvious increase in the PUFAs with decreasing temperature, rather the contrary (Fig. 4). The main response was a decrease of the saturated FAs and an increase in the three MUFAs with 20 and 22 carbons. When the difference in FA composition was not driven by a direct effect of the temperature on the membrane lipids, it is reasonable to believe that the observed temperature adaptation of the FA profile is a phenotypic characteristic that distinguishes the five populations. A genotypic temperature dependence was also detected by Hutchings et al. (2007), who found that adaptive differences in growth and survival of north-west G. morhua were associated with temperature. Bradbury et al. (2010) observed an evolution of multiple genes in G. morhua in response to ocean temperature, and Nielsen et al. (2009) suggested that genetic variation may potentially be driven by temperature adaptation. The observed FA-based discrimination among stocks could be of epigenetic origin (Gilbert & Epel, 2009; Hamilton, 2011). One of the several environmental factors contributing to epigenetic inheritance is temperature (Gilbert & Epel, 2009; Whittle et al., 2009; Feil & Fraga, 2012; Salinas & Munch, 2012). Recent analysis of zebrafish Danio rerio (Hamilton 1822) incubated at different temperature regimes showed clearly a thermal epigenetic regulation of gene expression during maturation (Campos et al., 2012). Methylation of DNA has been proposed as one of the most important processes in epigenetics (Hamilton, 2011; Massicotte et al., 2011; Feil & Fraga, 2012; Schrey et al., 2012). Studies of DNA methylation of natural populations of clonal fishes, i.e. fishes with no genetic variation, found in distinct environments provided clear evidence of epigenetic variation (Massicotte et al., 2011). Flexible epigenetic variation and rigid genetic variation appear to be the two complementing genetic modes exploited in short-term and long-term adaption, respectively, to altered environmental temperature regimes (Massicotte & Angers, 2011). The temporal consistency of the FA profile within the populations was tested by comparing the FA profile from the heart tissue of Faroe Bank and Faroe Plateau G. morhua from 1997 (Joensen et al., 2000) with the heart FA profile of the present fish captured in 2003. A change in profile was obvious (Fig. 6), but the two Faroe populations from 1997 bore a closer resemblance to the Faroe fish from 2003 than to the fish from Icelandic and Norwegian waters. The phenotypic FA profile apparently has a degree of plasticity (Hutchings et al., 2007) which will render a database of FA profiles to be used over several years doubtful. It is difficult to draw a firm conclusion of the durability of the FA profile, however, on the basis of these findings, since the G. morhua from 1994 were farmed while the fish from 2003 were wild. An effect of environment on the FA profile cannot be ruled out before it is tested. The average FA profiles in the heart tissue of Faroe Bank and Plateau G. morhua from 1997 appeared to be quite similar in Fig. 6, while they were distinct in a previous investigation (Joensen et al., 2000). One of the variables contributing most to the distinction in 1997 was cholesterol, but cholesterol was not included in the data matrix used for the PC plot in Fig. 6. Cholesterol was present in higher proportion in heart samples of the Faroe Bank fish than in the fish from Faroe Plateau in 1995 (Joensen et al., 2000). Also, in this study, cholesterol occurred with a significantly (P < 0⋅01) higher proportion in the heart samples of the Faroe Bank fish than of the Faroe Plateau fish. Cholesterol also had a higher

© 2014 The Fisheries Society of the British Isles, Journal of Fish Biology 2014, 84, 1904–1925

D I S T I N G U I S H I N G G A D U S M O R H UA S TO C K S

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proportion in the fillets of the Faroe bank than in Faroe plateau fish, but the difference was not significant. The fillets were not analysed in the previous investigation. The findings of a decrease in SAFA and increase in long-chained MUFA in the cooler compared to the warmer waters (Figs 1 and 4) were in accordance with well-established correlation between melting transition temperature, T m , and the number of introduced double bonds of membrane FAs (Keough et al., 1987; Cevc, 1991; Stillwell & Wassall, 2003). Cholesterol had a similar temperature relation (Tables II and III). Samples from the coldest and warmest areas had the lowest and highest levels of cholesterol, respectively. Analyses using a variety of different methods and techniques reveal a higher affinity between cholesterol and MUFA than with PUFA (Stillwell & Wassall, 2003). The simultaneous increase in MUFA and decline in cholesterol might be the most effective homeoviscous adaptations. This study shows that the FA composition of the fillet and heart tissue is a powerful biological marker for identification of North Atlantic stocks of G. morhua, with the ability to trace individual fish to their harvest location. It can be a valuable complement to genetic and other non-genetic methods. This phenotypic trait may, at least in part, be caused by temperature-driven gene expression. A.-K. Halvorsen and M. Hylland are thanked for their skillful technical assistance.

References Bradbury, I. R., Hubert, S., Higgins, B., Borza, T., Bowman, S., Paterson, I. G., Snelgrove, P. V. R., Morris, C. J., Gregory, R. S., Hardie, D. C., Hutchings, J. A., Ruzzante, D. E., Taggart, C. T. & Bentzen, P. (2010). Parallel adaptive evolution of Atlantic cod on both sides of the Atlantic Ocean in response to temperature. Proceedings of the Royal Society B 277, 3725–3734. Bradbury, I. R., Hubert, S., Higgins, B., Bowman S., Paterson I.G., Snelgrove P.V.R., Morris C.J., Gregory R.S., Hardie D.C., Borza, T. & Bentzen, P. (2011). Evaluating SNP ascertainment bias and its impact on population assignment in Atlantic cod, Gadus morhua. Molecular Ecology Resources 11 (Suppl. 1), 218–225. Campos, C., Valente, L. M. P. & Fernandes, J. M. O. (2012). Molecular evolution of zebrafish dnmt3 genes and thermal plasticity of their expression during embryonic development. Gene 500, 93–100. Carr, S. M. & Marshall, H. D. (1991). Detection of intraspecific DNA sequence variation in the mitochondrial cytochrome b gene of Atlantic cod (Gadus morhua) by the polymerase chain reaction. Canadian Journal of Fisheries and Aquatic Sciences 48, 48–52. Case, R. A. J., Hutchinson, W. F., Hauser, L., Van Oosterhout, C. & Carvalho, G. R. (2005). Macro- and micro-geographic variation in pantophysin (PanI) allele frequencies in NE Atlantic cod Gadus morhua. Marine Ecology Progress Series 301, 267–278. Cevc, G. (1991). How membrane chain-melting phase-transition temperature is affected by the lipid chain asymmetry and degree of unsaturation – an effective chain-length model. Biochemistry 30, 7186–7193. Cross, T. F. & Payne, R. H. (1978). Geographic variation in Atlantic cod, Gadus morhua, off eastern North America: a biochemical systematic approach. Canadian Journal of Fisheries and Aquatic Sciences 35, 117–123. D ́ Avignon, G. & Rose, G. A. (2013). Otolith elemental fingerprints distinguish Atlantic cod spawning areas in Newfoundland and Labrador. Fisheries Research 147, 1–9. Feil, R. & Fraga, M. F. (2012). Epigenetics and the environment: emerging patterns and implications. Nature Reviews Genetics 13, 97–109. Galley, E. A., Wright, P. J. & Gibb, F. M. (2006). Combined methods of otolith shape analysis improve identification of spawning areas of Atlantic cod. ICES Journal of Marine Science 63, 1710–1717.

© 2014 The Fisheries Society of the British Isles, Journal of Fish Biology 2014, 84, 1904–1925

1922

H . J O E N S E N A N D O . G R A H L- N I E L S E N

Galvin, P., Sadusky, T., McGregor, D. & Cross, T. (1995). Population genetics of Atlantic cod using amplified single locus minisatellite VNTR analysis. Journal of Fish Biology 47, 200–208. Gilbert, S. F. & Epel, D. (2009). Ecological Developmental Biology, Integrating Epigenetics, Medicine, and Evolution. Sunderland, MA: Sinauer Associates Inc. Grahl-Nielsen, O. (2005). Fatty acid profiles as natural marks for stock identification. In Stock Identification Methods (Cadrin, S. X., Friedland, K. D. & Waldman, J. R., eds), pp. 239–261. New York, NY: Academic Press. Grahl-Nielsen, O., Averina, E., Pronin, N., Radnaeva, L. & Kakela, R. (2011). Fatty acid profiles in different fish species in Lake Baikal. Aquatic Biology 13, 1–10. Hamilton, J. P. (2011). Epigenetics: principles and practice. Digestive Diseases 29, 130–135. Helyar, S. J., Hemmer-Hansen, J., Bekkevold, D., Taylor, M. I., Ogden, R., Limborg, M. T., Cariani, A., Maes, G. E., Diopere, E., Carvalho, G. R. & Nielsen, E. E. (2011). Analytical approaches, application of SNPs for population genetics of nonmodel organisms: new opportunities and challenges. Molecular Ecology Resources 11 Suppl. 1, 123–136. Higgins, R. M., Danilowicz, B. S., Balbuena, J. A., Daníelsdóttir, A. K., Geffen, A. J., Meijer, W. G., Modin, J., Montero, F. E., Pampoulie, C., Perdiguero-Alonso, D., Schreiber, A., Stefánsson, M. Ø. & Wilson, B. (2010). Multi-disciplinary fingerprints reveal the harvest location of cod Gadus morhua in the northeast Atlantic. Marine Ecology Progress Series 404, 197–206. Hutchings, J. A., Swain, D. P., Rowe, S., Eddington, J. D., Puvanendran, V. & Brown, J. A. (2007). Genetic variation in life-history reaction norms in marine fish. Proceedings of the Royal Society B 274, 1693–1699. Imsland, A. K. & Jónsdóttir, Ó. D. B. (2003). Linking population genetics and growth properties of Atlantic cod. Reviews in Fish Biology and Fisheries 13, 1–26. Jamieson, A. & Birly, A. J. (1989). The demography of haemoglobin polymorphism in the Atlantic cod, Gadus morhua L. Journal of Fish Biology 35, 193–204. Joensen, H. (2002). Discrimination among fish species and stocks by multivariate analysis of fatty acid profiles in selected tissues. Dr. scient. Thesis, 2-7406-053-9. Department of Chemistry, University of Bergen, Norway. Joensen, H. & Grahl-Nielsen, O. (2001). The redfish species Sebastes viviparus, Sebastes marinus and Sebastes mentella have different composition of their tissue fatty acids. Comparative Biochemistry and Physiology B 129, 73–85. Joensen, H. & Grahl-Nielsen, O. (2004). Stock structure of Sebastes mentella in the North Atlantic revealed by chemometry of the fatty acid profile in heart tissue. ICES Journal of Marine Science 61, 113–126. Joensen, H., Steingrund, P., Fjallstein, I. & Grahl-Nielsen, O. (2000). Discrimination between two reared stocks of cod (Gadus morhua) from the Faroe Islands by chemometry of the fatty acid composition in the heart tissue. Marine Biology 136, 573–580. Jónsdóttir, Ó. D. B., Imsland, A. K., Daníelsdóttir, A. K., Thorsteinsson, V. & Nævdal, G. (1999). Genetic differentiation among Atlantic cod in south and south-east Icelandic waters: synaptophysin (SypI) and haemoglobin (HbI) variation. Journal of Fish Biology 54, 1259–1274. ´ & Daníelsdóttir, A. K. (2003). Nuclear Jónsdóttir, Ó. D. B., Imsland, A. K., Atladóttir, Ó. Y. DNA RFLP variation of Atlantic cod in the North Atlantic Ocean. Fisheries Research 63, 429–436. Jónsdóttir, I. G., Campana, S. E. & Marteinsdóttir, G. (2006). Otolith shape and temporal stability of spawning groups of Icelandic cod (Gadus morhua L.). ICES Journal of Marine Science 63, 1501–1512. Keough, K. M. W., Giffin, B. & Kariel, N. (1987). The influence of unsaturation on the phase transition temperatures of a series of heteroacid phosphatidylcholines containing twenty-carbon chains. Biochimica et Biophysica Acta – Biomembranes 902, 1–10. Kirsch, P. E., Iverson, S. J., Bowen, W. D., Kerr, S. R. & Ackman, R. G. (1998). Dietary effects on the fatty acid signature of whole Atlantic cod (Gadus morhua). Canadian Journal of Fisheries and Aquatic Sciences 55, 1378–1386. Kurlansky, M. (1997). Cod: A Biography of the Fish that Changed the World. New York, NY: Walker & Co.

© 2014 The Fisheries Society of the British Isles, Journal of Fish Biology 2014, 84, 1904–1925

D I S T I N G U I S H I N G G A D U S M O R H UA S TO C K S

1923

Kvalheim, O. M. & Karstang, T. V. (1987). A general-purpose program for multivariate data analysis. Chemometrics and Intelligent Laboratory Systems 2, 235–237. Kwetegyeka, J., Mpango, G. & Grahl-Nielsen, O. (2006). Fatty acid composition of muscle and hear tissue of Nile perch, Lates niloticus, and Nile tilapia, Oreochromis niloticus, from various populations in Lakes Victoria and Kioga, Uganda. African Journal of Aquatic Science 31, 297–304. Kwetegyeka, J., Mpango, G. & Grahl-Nielsen, O. (2008). Variation in fatty acid composition in muscle and heart tissues among species and populations of tropical fish in Lakes Victoria and Kyoga. Lipids 43, 1017–1029. Kwetegyeka, J., Masa, J., Kireme, B. T., Mpango, G. B. & Grahl-Nielsen, O. (2011). Fatty acids of polar lipids in heart tissue are good taxonomic markers for tropical African freshwater fish. African Journal of Aquatic Science 36, 115–127. Lie, Ø., Hemre, G. I. & Lambertsen, G. (1992). Influence of dietary fatty acids on the glycerophospholipid composition in organs of cod (Gadus morhua). Lipids 27, 770–775. Magnussen, E. (2007). Interpopulation comparison of growth patterns of 14 fish species on Faroe Bank: are all fishes on the bank fast-growing? Journal of Fish Biology 71, 453–475. Massicotte, R. & Angers, B. (2011). General-purpose genotype or how epigenetics extend the flexibility of a genotype. Genetics Research International 2012, Article ID 317175. doi: 10.1155/2012/317175 Massicotte, R., Whitelaw, E. & Angers, B. (2011). DNA methylation: a source of random variation in natural populations. Epigenetics 6, 421–427. Meier, S., Mjøs, S., Joensen, H. & Grahl-Nielsen, O. (2006). Validation of a one-step extraction/methylation method for determination of fatty acids and cholesterol in marine tissues. Journal of Chromatography A 1104, 291–298. Mjaavatten, O., Levings, C. D. & Poon, P. (1998). Variation in the fatty acid composition of juvenile Chinook and Coho salmon from Fraser river estuary determined by multivariate analysis; role on environment and genetic origin. Comparative Biochemistry and Physiology B 120, 291–309. Mørkøre, T., Netteberg, C., Johnsson, L. & Pickova, J. (2007). Impact of dietary oil source on product quality of farmed Atlantic cod, Gadus morhua. Aquaculture 267, 236–247. Nielsen, E. E., Hansen, M. H., Schmidt, C., Meldrup, D. & Grønkjær, P. (2001). Population of origin of Atlantic cod. Nature 413, 272. Nielsen, E. E., MacKenzie, B. R., Magnussen, E. & Meldrup, D. (2007). Historical analysis of Pan I in Atlantic cod (Gadus morhua): temporal stability of allele frequencies in the southeastern part of the species distribution. Canadian Journal of Fisheries and Aquatic Sciences 64, 1448–1455. Nielsen, E. E., Wright, P. J., Hemmer-Hansen, J., Poulsen, N. A., Gibb, I. M. & Meldrup, D. (2009). Microgeographical population structure of cod Gadus morhua in the North Sea and west of Scotland: the role of sampling loci and individuals. Marine Ecology Progress Series 376, 213–225. Nielsen, E. E., Cariani, A., Mac Aoidh, E., Maes, G. E., Milano, I., Ogden, R., Taylor, M., Hemmer-Hansen, J., Babbucci, M., Bargelloni, L., Bekkevold, D., Diopere, E., Grenfell, L., Helyar, S., Limborg, M. T., Martinsohn, J. T., McEwing, R., Panitz, F., Patarnello, T., Tinti, F., Van Houdt, J. K. J., Volckaert, F. A. M., Waples, R. S., FishPop Trace Consortium & Carvalho, G. R. (2012). Gene-associated markers provide tools for tackling illegal fishing and false eco-certification. Nature Communications 3, 851. doi: 10.1038/ncomms1845 Olsen, Y. (1999). Lipids and essential fatty acids in aquatic food webs: what can freshwater ecologists learn from mariculture?. In Lipids in Freshwater Ecosystems (Arts, M. T. & Wainman, B. C., eds), pp. 161–202. New York, NY: Springer. Pampoulie, C., Stefánsson, M. Ø., Jørundsdóttir, T. D., Danilowicz, B. S. & Daníelsdóttir, A. K. (2008a). Recolonization history and large-scale dispersal in the open sea: the case study of the North Atlantic cod, Gadus morhua L. Biological Journal of the Linnean Society 94, 315–329. Pampoulie, C., Steingrund, P., Stefánsson, M. Ø. & Daníelsdóttir, A. K. (2008b). Genetic divergence among East Icelandic and Faroese populations of Atlantic cod provides evidence for historical imprints at neutral and non-neutral markers. ICES Journal of Marine Science 65, 65–71.

© 2014 The Fisheries Society of the British Isles, Journal of Fish Biology 2014, 84, 1904–1925

1924

H . J O E N S E N A N D O . G R A H L- N I E L S E N

Pampoulie, C., Daniélsdóttir, A. K., Storr-Paulsen, M., Hovgård, H., Hjørleifsson, E. & Steinarsson, B. Æ. (2011). Neutral and nonneutral genetic markers revealed the presence of inshore and offshore stock components of Atlantic cod in Greenland waters. Transactions of the American Fisheries Society 140, 307–319. Pepin, P. & Carr, S. M. (1993). Morphological, meristic, and genetic analysis of stock structure in juvenile Atlantic cod (Gadus morhua) from the Newfoundland shelf. Canadian Journal of Fisheries and Aquatic Sciences 50, 1924–1933. Pogson, G. H., Mesa, K. A. & Boutilier, R. G. (1995). Genetics population structure and gene flow in the Atlantic cod Gadus morhua: a comparison of allozyme and nuclear RFLP loci. Genetics 139, 375–385. Poulsen, N. A., Hemmer-Hansen, J., Loeschcke, V., Carvalho, G. R. & Nielsen, E. E. (2011). Microgeographical population structure and adaptation in Atlantic cod Gadus morhua: spatio-temporal insights form gene-associated DNA markers. Marine Ecology Progress Series 436, 231–243. Rajalahti, T., Arneberg, R., Kroksveen, A. C., Myhr, K.-M. & Kvalheim, O. M. (2009). Discriminating variable test and selectivity ratio plot – quantitative tools for interpretation and variable (biomarker) selection in complex spectral or chromatographic profiles. Analytical Chemistry 81, 2581–2590. Ricker, W. E. (1981). Changes in the average size and average age of Pacific salmon. Canadian Journal of Fisheries and Aquatic Sciences 38, 1636–1656. Righton, D. A., Andersen, K. H., Neat, F., Thorsteinsson, V., Steingrund, P., Svedäng, H., Michalsen, K., Hinrichsen, H.-H., Bendall, V., Neuenfeldt, S., Wright, P., Jonsson, P., Huse, G., van der Kooij, J., Mosegaard, H., Hüssy, K. & Metcalfe, J. (2010). Thermal niche of Atlantic cod Gadus morhua: limits, tolerance and optima. Marine Ecology Progress Series 420, 1–13. Ruyter, B., Røsjø, C., Grisdale-Helland, B., Rosenlund, G., Obach, A. & Thomassen, M. S. (2003). Influence of temperature and high dietary linoleic acid content on esterification, elongation, and desaturation of PUFA in Atlantic salmon hepatocytes. Lipids 38, 833–840. Ruzzante, D. E., Taggart, C. T., Cook, D. & Goddard, S. (1996). Genetic differentiation between inshore and offshore Atlantic cod (Gadus morhua) off Newfoundland: microsatellite DNA variation and antifreeze level. Canadian Journal of Fisheries and Aquatic Sciences 53, 634–645. Salinas, S. & Munch, S. B. (2012). Thermal legacies: transgenerational effects of temperature on growth in a vertebrate. Ecology Letters 15, 159–163. Schrey, A. W., Richards, C. L., Meller, V., Sollars, V. & Ruden, D. M. (2012). The role of epigenetics in evolution: the extended synthesis. Genetics Research International 2012, Article ID 286164. doi: 10.1155/2012/286164 Stillwell, W. & Wassall, S. R. (2003). Docosahexaenoic acid: membrane properties of a unique fatty acid. Chemistry and Physics of Lipids 126, 1–27. Svedäng, H., André, C., Jonsson, P., Elfman, M. & Limburg, K. E. (2010). Migratory behaviour and otolith chemistry suggest fine-scale sub-population structure within a genetically homogenous Atlantic cod population. Environmental Biology of Fishes 89, 383–397. Thorisson, K., Jónsdóttir, I. G., Marteinsdóttir, G. & Campana, S. E. (2011). The use of otolith chemistry to determine the juvenile source of spawning cod in Icelandic waters. ICES Journal of Marine Science 68, 98–106. Tocher, D., Fonseca-Madrigal, J., Dick, J. R., Ng, W. K., Bell, J. G. & Campbell, J. (2004). Effects of water temperature and diets containing palm oil and fatty acid desaturation and oxidation in hepatocytes and intestinal enterocytes of rainbow trout (Oncorhynchus mykiss). Comparative Biochemistry and Physiology B 137, 49–63. Viga, A. & Grahl-Nielsen, O. (1990). Genotypic and phenotypic fatty acid composition in the tissues of salmon, Salmo salar. Comparative Biochemistry and Physiology B 96, 721–727. Whittle, C. A., Otto, S. P., Johnston, M. O. & Krochko, J. E. (2009). Adaptive epigenetic memory of ancestral temperature regime in Arabidopsis thaliana. Botany 87, 650–657. Wold, S. (1978). Cross validatory estimation of the number of components in factor and principal models. Technometrics 20, 397–406.

© 2014 The Fisheries Society of the British Isles, Journal of Fish Biology 2014, 84, 1904–1925

D I S T I N G U I S H I N G G A D U S M O R H UA S TO C K S

1925

Wold, S. & Sjøstrøm, M. (1977). SIMCA: a method for analysing chemical data in terms of similarity and analogy. In Chemometrics: Theory and Application (Kowalski, B., ed), pp. 243–282. Washington DC: American Chemical Society. Xu, R., Hung, S. S. O. & German, J. B. (1993). White sturgeon tissue fatty acid compositions are affected by dietary lipids. Journal of Nutrition 123, 1685–1692. Zenebe, T. G., Boberg, M., Sonesten, L. & Ahlgren, G. (2003). Effects of algal diets and temperature on the growth and fatty acid content of the cichlid fish Oreochromis niloticus L. A laboratory study. Aquatic Ecology 37, 169–182.

Electronic Reference Anon. (2005). Report of the Study Group on Stock Identity and Management Units of Redfishes (SGSIMUR). 31 August–03 September 2004, Bergen, Norway. ICES CM 2005/AFCM:10. Available at http://www.ices.dk/sites/pub/CM%20Doccuments/2005/ ACFM/ACFM1005.pdf/

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