sign in sign up
<<
Home , Lophius piscatorius

"Not to be cited without prior reference to the author" CM 2004/EE:22 Theme Session EE

Morphometric and meristic study of white and black ( piscatorius and L. budegassa) from the south-west of Ireland to the south- western Mediterranean

R. Duarte1, I. Bruno2, I. Quincoces3, A.C. Fariña4 and J. Landa5

1Rafael Duarte: Instituto Nacional de Investigação Agrária e das Pescas INIAP-IPIMAR, Av. Brasilia, 1449-006 Lisboa, Portugal, [tel: + 351 21 302 7000, fax: +351 21 301 5948, e-mail: [email protected]]. 2Isabel Bruno: Instituto Español de Oceanografía, IEO Instituto Español de Oceanografía, Apdo 1552. 6200 Vigo, Spain [e-mail: [email protected]]. 3Iñaki Quincoces: Txatxarramendi ugartea z/g, 48395 Sukarrieta, Bizkaia, Basque Country, Spain [tel: +34 94 6029400, fax:+34 94 6870006, e-mail: [email protected]]. 4A.Celso Fariña: Instituto Español de Oceanografía, Muelle de Ánimas s/n , 15001 A Coruña, Spain [tel: +34 981 205362, fax: +34 981 229077, e-mail: [email protected]]. 5Jorge Landa: Instituto Español de Oceanografía, Promontorio de San Martín s/n, 39004 Santander, Spain [tel: +34 942 291070, fax: +34 942 275072, e-mail: [email protected]]

Abstract Two species of anglerfish are found in the Northeast Atlantic and Mediterranean, white (Lophius piscatorius) and black anglerfish (L. budegassa). Both species are highly valuable in trawl and gill net . In the present study, the morphometric and meristic variation of both anglerfish species is analysed along the Atlantic coast between the west of Ireland and the south of Portugal and also the south-western Mediterranean. In this Atlantic area ICES considers for assessment purposes two anglerfish stocks, northern and southern, with the geographical barrier between them in the Cap Breton Canyon. Results showed a reasonable classification of specimens in certain areas, namely between western Ireland, western France and northern Spain for L. piscatorius and between western France and southern Portugal for L. budegassa. The population structure of the two European anglerfishes seems to be more complex than considered by the actual ICES stock limits.

Keywords: Anglerfish, Lophius piscatorius, L. budegassa, Northeast Atlantic, Mediterranean, Morphometry, Meristic, Stock Structure.

Introduction

Two species of anglerfish are found in the north eastern Atlantic, the white anglerfish Lophius piscatorius and the black anglerfish L. budegassa. Both species have a wide distribution with a great overlap: L. piscatorius appears from the south western to the Straits of Gibraltar, Mediterranean and to Senegal and L. budegassa from the British Islands and Ireland to Senegal, including also the Mediterranean (Quero, 1984, Caruso, 1986).

Both anglerfish species have a high commercial value in European markets and are therefore highly exploited. In Western and Southern Europe they are caught by trawl and artisanal (fixed nets) fleets from Spain, France, Ireland, UK and Portugal. For management purposes two stocks are considered in the northeast Atlantic for both anglerfish species: the Northern Stock covering ICES Divisions VIIb-k and VIIIabd, and the Southern Stock including ICES Division VIIIc and IXa (ICES, 2004). This delimitation was not based on biological criteria. The Cape Breton Canyon in the extreme south eastern corner of the Bay of Biscay was considered as a geographical barrier between both stocks.

Sustainable and effective management is only possible with a correct and accurate stock definition in combination with estimation of the degree of exchange between stocks. In spite of this importance, the great majority of the stocks managed world wide are defined by political criteria and not based on biological information (Begg et al., 1999). The type of biological information that can contribute to the delimitation of stocks is of a great variety and the integration of different types of information is essential (Begg and Waldman, 1999).

In the identification of stocks several methodologies can be applied (Waldman et al., 1988). Among these methodologies is the analysis of morphometric and meristic characters, which have been widely used in the identification of stocks (Meng and Stocker, 1984; Junquera and Pérez-Gándaras, 1993; Elliot et al., 1995; Hurlbut and Clay, 1998; Murta, 2000; Saborido-Rey and Nedreaas, 2000; Abaunza et al., 2001).

For L. piscatorius and L. budegassa, morphometric and meristic studies with the objective of stock discrimination have not been used before. In the Lophius genera, stock structure studies using morphological characters were only performed for the african angler (Lophius vomerinus), giving important discrimination between areas that was not in agreement with the genetic homogenous results (Leslie and Grant, 1990).

The objective of the present study is to perform a morphometric and meristic study of L. piscatorius and L. budegassa in the north western Atlantic and Mediterranean. The results are discussed in relation to the actual stock delimitations and in relation to the work published on the genetic structure of populations of European anglerfishes.

2 Methods

The study area was the northeast Atlantic from southwest of Ireland to south of Portugal and the southwest Mediterranean (Figure 1). The sampling period was between May 2000 and November 2001. Three laboratories were involved in the sampling collection: “Instituto Español de Oceanografia” (IEO), “Instituto Tecnológico, Pesquero y Alimentario” (AZTI) and “Instituto Nacional de Investigação Agrária e das Pescas“ (INIAP/IPIMAR), each covering different areas (Table 1).

Figure 1. Sampling area in the NE Atlantic (ICES Divisions) and West Mediterranean.

Table 1. Sampling areas and laboratory responsible for the sampling.

ICES Division and Mediterranean Laboratory VIIcj IEO VIIIabd AZTI VIIIc IEO IXa IPIMAR + IEO Southwest Mediterranean IEO

3 In order to obtain a good homogeneity between the sampled areas, the length range was initially restricted to 40-47 cm and 30-37 cm of total length for respectively L. piscatorius and L. budegassa. These length ranges were chosen in order to cover as much as possible only one age group for each species, but due to sampling difficulties the length range was extended in order to increase the number of sampled anglerfish.

A total of 160 L. piscatorius were sampled (Table 2) but in areas IXa (11 specimens) and Mediterranean (3 specimens) sampling was low probably due to the lower occurrence of this species. These areas were therefore excluded for L. piscatorius and only ICES Divisions VIIcj, VIIIabd and VIIIc were considered for morphometric analysis. For L. budegassa, a total of 298 specimens were sampled (Table 3) and all areas were equivalently represented. For both species most sampling was in year 2000, only L.piscatorius in area VIIcj was mainly obtained in January 2001.

Table 2. Number of sampled L. piscatorius.

2000 2001

Zone Mai. Jun. Jul. Sep. Oct. Nov. NA Total Jan. Feb. Mai. Jun. Aug. Sep. Oct. Nov. Total Total

VIIcj 0 0 1 0 0 6 0 7 40 0 0 0 0 0 0 0 40 47 VIIIabd 12 0 26 8 0 0 0 46 0 0 0 0 0 0 0 0 0 46 VIIIc 0 1 0 0 7 22 2 32 0 0 4 0 0 0 9 8 21 53 IXa 0 0 0 0 0 1 0 1 0 1 2 4 2 1 0 0 10 11 Med. 0 0 0 0 1 0 0 1 0 0 0 0 0 2 0 0 2 3 Total 12 1 27 8 8 29 2 87 40 1 6 4 2 3 9 8 73 160

Table 3. Number of sampled L. budegassa.

2000 2001 Zone Jun. Jul. Aug. Oct. Nov. Dec. NA Total Jan. Mar. Sep. Total Total

VIIcj 0 2 0 0 6 41 0 49 0 0 0 0 49 VIIIabd 18 35 0 0 0 0 0 53 0 0 0 0 53

VIIIc 15 11 0 1 22 0 1 50 0 0 0 0 50 IXa 41 1 3 1 0 23 0 69 3 5 0 8 77 Med. 0 0 0 59 0 0 0 59 0 0 10 10 69

Total 74 49 3 61 28 64 1 280 3 5 10 18 298

Anglerfish are scaleless and have a variable contour due to the flexible properties of the skin which is normally covered by a gelatinous matrix. Due to this characteristic, landmarks for the morphometric study were mainly based on the cephalic spines that are characteristic of the Lophius species. Leslie and Grant (1990; 1994) also adopted cephalic spines as landmarks for the southern African anglerfish L. vomerinus. The adopted landmarks were numbered from 1 to 34 and groups of cephalic spines were defined in order to cover more efficiently the total body (Figure 2).

4

Figure 2. Landmarks (from 1 to 34) and groups of spines.

A digitized image was taken from each specimen and using image analysis software the coordinates of each landmark were obtained. The distances between landmarks were then calculated using the coordinates. The cephalic groups contain more than two landmarks and this way, several distances were obtained between two different groups. All distances linking two cephalic groups were highly correlated (correlation coefficients higher than 0.95) and therefore only one cephalic spine per group was adopted as landmark for the morphometric analysis. A Truss network (Strauss and Bookstein, 1982) was established between the adopted landmarks (Figure 3) and the distances between the landmarks along the Truss network were adopted as the morphometric variables. This way, a total of 29 and 36 distances were adopted for respectively L. piscatorius and L. budegassa.

Figure 3. Truss network with the solid line for both species, dot line for L. piscatorius and dashed line for L. budegassa.

5

All morphometric variables are highly correlated with the body size. In order to remove the length effect, morphometric variables were standardized to the overall mean length using the following equation:

b æTL ö ç ÷ MV * = MV ´ç ÷ èTL ø

MV* and MV are respectively the standardized and non-standardized individual morphometric variables, TL is the overall mean total length, TL is the total fish length and b is the regression slope between the log transformed fish length and each morphometric variable. Since there is no relationship of dependence between TL and each MV the Ricker regression was used (Ricker, 1973). This method was used in order to account for possible allometric growth between the variables and the fish length (Cadrin, 2000).

An exploratory analysis was performed with the standardized variables. The length frequencies and the distribution of each variable were analyzed by area, using boxplots (with the 1st quartile, the median and the 3rd quartile for the hinges and 1.5 times the interquartile range for the whisker).

A discriminant analysis was performed using linear discriminant function (Manly, 1997) in order to study the consistency of the geographical areas. The obtained linear functions were used to reallocate each individual to a geographical division. The percentage of correct reallocation was used as an indication of how well the geographical areas can be separated using the available morphometric variables.

An agglomerative hierarchical clustering was performed using the group average linkage (Manly, 1997) and Euclidean distances. Variables were previously standardized by subtracting the variable's mean value and dividing by the variable's mean absolute deviation. This way, all variables are equally important in determining the link distances.

The meristic characters used in the present study were the number of rays of paired and unpaired fins. For both species, 8 meristic characters of each specimen were taken (Table 4). A discriminant analysis was performed and each individual was allocated to a geographical area according to the discriminant functions.

Table 4. Meristic variables for both species.

Variable Description ND1 Number of first rays ND2 Number of second dorsal fin rays NC Number of caudal fin rays NLP Number of left pectoral fin rays NRP Number of right pectoral fin rays NLV Number of left ventral fin rays NRV Number of right ventral fin rays NA Number of anal fin rays

6 All calculations were performed using the R software, a language and environment for statistical computing (R Development Core Team, 1993).

Results

The sampled anglerfish were taken from a limited length range. L. piscatorius (Figure 4) ranged between 400 and 500 mm except in ICES division VIIIc with higher lengths, and L. budegassa (Figure 5) ranged between 300 and 400 mm except in the Mediterranean also with higher lengths.

Figure 4. Length frequency for L. piscatorius.

Figure 5. Length frequency for L. budegassa.

7

Table 5. Correlation coefficients between morphometric variables for L. piscatorius. Before standardization below the diagonal and after standardization above the diagonal.

tl X2.4 X2.20 X2.22 X4.6 X4.8 X4.11 X4.20 X4.22 X4.26 X6.8 X6.11 X6.18 X8.11 X8.22 X8.26 X8.29 X11.17 X11.26 X11.29 X17.18 X17.29 X18.24 X20.22 X22.24 X22.26 X22.29 X24.26 X24.29 X26.29 ------tl 0.28 0.26 0.24 0.41 0.33 0.31 0.22 0.23 0.24 0.32 0.32 0.15 0.28 -0.28 0.28 0.22 -0.43 -0.23 -0.25 -0.1 -0.4 -0.15 -0.31 -0.39 -0.4 -0.37 -0.36 -0.38 -0.36 X2.4 0.87 0.3 0.41 0.07 0.65 0.36 0.89 0.78 0.74 0.66 0.46 0.2 0.3 0.3 0.31 0.3 0.2 0.48 0.45 0.3 0.33 0.43 0.35 0.06 0.2 0.18 0.22 0.23 0.19 X2.20 0.88 0.82 0.58 0.19 0.31 0.28 0.67 0.45 0.45 0.35 0.35 0.18 0.24 0.29 0.39 0.4 0.1 0.39 0.33 0.24 0.16 0.32 0.15 0.18 0.14 0.16 0.23 0.21 0.24 X2.22 0.9 0.86 0.9 0.26 0.23 0.38 0.54 0.81 0.37 0.13 0.23 0.34 0.4 0.84 0.4 0.59 0.27 0.45 0.42 0.17 0.22 0.38 0.87 0.22 0.71 0.65 0.71 0.68 0.42 X4.6 0.69 0.59 0.65 0.68 0.24 0.41 0.1 0.22 0.17 0.25 0.15 0.15 0.27 0.3 0.17 0.28 0.15 0.14 0.15 0.11 0.21 0.16 0.25 0.51 0.35 0.37 0.36 0.31 0.33 X4.8 0.8 0.88 0.77 0.77 0.62 0.79 0.68 0.64 0.83 0.79 0.78 0.19 0.19 0.19 0.1 0.07 0.22 0.25 0.24 -0.01 0.31 0.29 0.09 0.24 0.28 0.35 0.18 0.31 0.13 X4.11 0.83 0.81 0.78 0.83 0.71 0.93 0.44 0.62 0.71 0.44 0.78 0.25 0.28 0.49 0.29 0.29 0.13 0.2 0.07 -0.13 0.26 0.27 0.27 0.41 0.51 0.64 0.34 0.55 0.23 X4.20 0.91 0.97 0.93 0.91 0.64 0.89 0.85 0.82 0.82 0.68 0.55 0.23 0.29 0.35 0.41 0.38 0.15 0.53 0.46 0.32 0.31 0.49 0.28 0.1 0.19 0.19 0.22 0.25 0.18 X4.22 0.92 0.95 0.88 0.97 0.68 0.88 0.9 0.97 0.75 0.48 0.53 0.37 0.34 0.75 0.43 0.51 0.3 0.51 0.46 0.18 0.33 0.48 0.69 0.2 0.63 0.62 0.56 0.63 0.3 X4.26 0.9 0.94 0.88 0.88 0.66 0.93 0.92 0.97 0.95 0.66 0.72 0.26 0.18 0.36 0.58 0.4 0.23 0.55 0.4 0.13 0.3 0.4 0.17 0.16 0.17 0.32 0.06 0.3 0.05 X6.8 0.81 0.89 0.8 0.76 0.63 0.92 0.8 0.9 0.85 0.89 0.74 0.19 0.27 -0.06 0.01 0 0.13 0.25 0.27 0.23 0.27 0.32 -0.01 0.15 0.01 0.02 0.11 0.1 0.11 X6.11 0.8 0.83 0.77 0.77 0.58 0.92 0.93 0.86 0.86 0.91 0.9 0.23 0.15 0.23 0.25 0.14 0.05 0.12 0.01 0.03 0.25 0.32 0.08 0.25 0.23 0.32 0.2 0.36 0.07 X6.18 0.96 0.85 0.86 0.91 0.69 0.79 0.83 0.9 0.92 0.89 0.81 0.8 0.33 0.37 0.24 0.42 0.28 0.38 0.38 0.58 0.04 0.32 0.3 0.11 0.31 0.35 0.34 0.39 0.37 X8.11 0.87 0.81 0.8 0.86 0.66 0.73 0.77 0.84 0.85 0.81 0.76 0.71 0.88 0.21 0.02 0.44 0.12 0.46 0.41 0.18 0.15 0.21 0.39 0.2 0.29 0.3 0.36 0.29 0.57 X8.22 0.86 0.81 0.81 0.96 0.68 0.74 0.85 0.85 0.94 0.85 0.66 0.75 0.88 0.78 0.55 0.61 0.35 0.42 0.37 0.05 0.24 0.36 0.83 0.32 0.86 0.86 0.71 0.82 0.34 X8.26 0.86 0.81 0.84 0.86 0.62 0.7 0.78 0.86 0.87 0.9 0.68 0.74 0.86 0.73 0.87 0.66 0.25 0.67 0.42 0.21 0.21 0.34 0.28 0.14 0.12 0.29 0.02 0.29 0.05 X8.29 0.92 0.85 0.88 0.93 0.7 0.74 0.81 0.9 0.92 0.89 0.74 0.75 0.93 0.88 0.91 0.92 0.28 0.6 0.65 0.26 0.12 0.32 0.48 0.27 0.36 0.46 0.35 0.37 0.62 X11.17 0.62 0.59 0.53 0.65 0.44 0.57 0.56 0.6 0.67 0.62 0.52 0.5 0.64 0.54 0.68 0.6 0.64 0.41 0.51 -0.11 0.38 0.17 0.29 0.1 0.35 0.35 0.3 0.38 0.2 X11.26 0.92 0.88 0.88 0.9 0.66 0.78 0.8 0.92 0.92 0.92 0.79 0.75 0.92 0.88 0.87 0.92 0.94 0.68 0.83 0.31 0.26 0.42 0.34 0.08 0.12 0.23 0.13 0.26 0.33 X11.29 0.91 0.87 0.86 0.89 0.65 0.77 0.75 0.9 0.9 0.88 0.79 0.71 0.92 0.87 0.85 0.86 0.94 0.71 0.97 0.28 0.29 0.3 0.34 0.13 0.22 0.19 0.27 0.19 0.42 X17.18 0.96 0.87 0.88 0.88 0.68 0.77 0.78 0.91 0.9 0.88 0.82 0.78 0.97 0.85 0.82 0.84 0.91 0.55 0.92 0.9 -0.11 0.64 0.11 0.02 -0.09 -0.11 0.07 -0.03 0.23 X17.29 0.71 0.69 0.63 0.68 0.55 0.67 0.67 0.71 0.72 0.71 0.66 0.65 0.67 0.62 0.67 0.65 0.66 0.61 0.7 0.7 0.63 0.26 0.21 0.29 0.23 0.14 0.2 0.12 0.01 X18.24 0.96 0.89 0.88 0.91 0.68 0.81 0.84 0.93 0.93 0.91 0.83 0.82 0.95 0.86 0.87 0.87 0.92 0.62 0.93 0.91 0.97 0.72 0.29 0.1 0.21 0.26 0.25 0.3 0.27 X20.22 0.82 0.79 0.74 0.95 0.62 0.66 0.75 0.8 0.91 0.77 0.64 0.66 0.84 0.81 0.94 0.77 0.85 0.63 0.82 0.82 0.79 0.62 0.83 0.2 0.78 0.68 0.74 0.7 0.42 X22.24 0.68 0.58 0.62 0.66 0.7 0.62 0.72 0.63 0.67 0.65 0.57 0.62 0.67 0.62 0.69 0.61 0.68 0.42 0.63 0.63 0.65 0.59 0.67 0.6 0.4 0.43 0.45 0.26 0.31 X22.26 0.67 0.63 0.6 0.83 0.59 0.63 0.75 0.65 0.8 0.65 0.51 0.61 0.71 0.66 0.9 0.59 0.71 0.61 0.64 0.66 0.61 0.54 0.68 0.88 0.63 0.92 0.83 0.85 0.39 X22.29 0.74 0.68 0.66 0.85 0.65 0.71 0.85 0.71 0.84 0.75 0.57 0.7 0.77 0.71 0.93 0.71 0.79 0.64 0.73 0.71 0.68 0.56 0.75 0.85 0.68 0.95 0.69 0.88 0.46 X24.26 0.75 0.71 0.7 0.88 0.64 0.65 0.73 0.73 0.84 0.68 0.62 0.66 0.78 0.75 0.88 0.62 0.77 0.61 0.71 0.75 0.72 0.58 0.76 0.89 0.68 0.9 0.85 0.83 0.46 X24.29 0.72 0.68 0.66 0.84 0.6 0.68 0.79 0.71 0.83 0.73 0.59 0.7 0.76 0.69 0.91 0.69 0.75 0.65 0.72 0.69 0.66 0.52 0.74 0.86 0.57 0.92 0.94 0.91 0.37 X26.29 0.8 0.73 0.75 0.83 0.65 0.66 0.71 0.77 0.8 0.72 0.66 0.63 0.83 0.85 0.77 0.67 0.88 0.53 0.8 0.82 0.81 0.51 0.81 0.78 0.62 0.67 0.74 0.76 0.69

8

Table 6. Correlation coefficients between morphometric variables for L. budegassa. Before standardization below the diagonal and after standardization above the diagonal.

tl X2.4 X2.20 X2.22 X4.6 X4.8 X4.11 X4.20 X4.22 X4.26 X6.8 X6.11 X8.11 X8.22 X8.26 X11.16 X11.26 X11.29 X17.18 X17.34 X20.22 X22.26 X22.24 X22.29 X24.26 X24.29 X26.29 X8.29 X6.16 X24.34 X29.34 X16.29 X11.34 X16.34 X16.17 X16.18 X18.34 tl -0.25 -0.32 -0.2 -0.42 -0.32 -0.29 -0.2 -0.19 -0.22 -0.27 -0.3 -0.29 -0.21 -0.31 -0.35 -0.21 -0.2 -0.17 -0.31 -0.25 -0.28 -0.39 -0.27 -0.26 -0.28 -0.33 -0.21 -0.31 -0.3 -0.35 -0.19 -0.21 -0.22 -0.3 -0.19 -0.21 X2.4 0.87 0.06 0.47 -0.02 0.62 0.48 0.83 0.81 0.73 0.66 0.61 0.26 0.48 0.28 0.15 0.33 0.39 -0.07 0.11 0.6 0.43 0.08 0.37 0.44 0.43 0.24 0.37 0.32 0.23 0.07 0.38 0.29 0.39 0.11 0.07 0.25 X2.20 0.81 0.7 0.62 0.17 0 -0.01 0.55 0.24 0.14 0.09 0.04 0.19 0.26 0.39 0.44 0.35 0.35 0.2 0.35 0.14 0.08 0.21 0.08 0.22 0.11 0.41 0.51 0.27 0.25 0.36 0.42 0.38 0.22 0.45 0.07 -0.08 X2.22 0.92 0.89 0.88 0.18 0.33 0.31 0.72 0.78 0.5 0.38 0.37 0.19 0.77 0.48 0.3 0.46 0.52 0.11 0.32 0.83 0.58 0.12 0.5 0.64 0.56 0.46 0.67 0.38 0.39 0.25 0.46 0.49 0.41 0.26 0.16 0.07 X4.6 0.67 0.52 0.55 0.63 0.37 0.45 0.04 0.17 0.27 0.37 0.21 0.17 0.26 0.16 0.19 0.15 0.16 0.09 0.23 0.16 0.33 0.55 0.4 0.26 0.24 0.31 0.21 0.12 0.2 0.21 0.12 0.19 0.15 0.13 0.13 0.06 X4.8 0.83 0.88 0.63 0.82 0.66 0.9 0.55 0.75 0.87 0.84 0.83 0.11 0.55 0.09 -0.04 0.17 0.32 -0.24 -0.05 0.4 0.74 0.31 0.74 0.5 0.64 0.1 0.1 0.44 0.32 -0.1 0.21 0.17 0.42 -0.06 0.12 0.32 X4.11 0.85 0.85 0.66 0.84 0.72 0.96 0.45 0.7 0.84 0.68 0.87 0.2 0.67 0.24 -0.06 0.26 0.26 -0.27 0 0.36 0.76 0.34 0.81 0.49 0.68 0.11 0.21 0.5 0.38 -0.06 0.19 0.16 0.41 -0.04 0.06 0.24 X4.20 0.92 0.96 0.86 0.95 0.59 0.87 0.87 0.84 0.73 0.61 0.56 0.26 0.57 0.4 0.29 0.44 0.51 -0.01 0.22 0.53 0.43 0.13 0.39 0.49 0.44 0.36 0.56 0.41 0.32 0.18 0.53 0.42 0.45 0.27 0.05 0.15 X4.22 0.92 0.96 0.79 0.97 0.63 0.92 0.92 0.97 0.85 0.71 0.74 0.18 0.84 0.38 0.12 0.39 0.49 -0.1 0.15 0.79 0.77 0.15 0.71 0.7 0.73 0.3 0.51 0.46 0.41 0.08 0.42 0.39 0.5 0.08 0.13 0.25 X4.26 0.9 0.94 0.75 0.91 0.65 0.95 0.95 0.95 0.97 0.74 0.8 0.14 0.69 0.48 0.09 0.45 0.47 -0.16 0.08 0.5 0.64 0.29 0.71 0.41 0.61 0.07 0.41 0.51 0.38 0.01 0.39 0.33 0.49 0.08 0.07 0.27 X6.8 0.87 0.91 0.7 0.86 0.68 0.94 0.9 0.91 0.93 0.93 0.82 0.26 0.4 -0.01 0.09 0.2 0.36 -0.12 0 0.41 0.57 0.24 0.53 0.54 0.56 0.24 0.14 0.37 0.28 -0.04 0.33 0.22 0.42 0.07 0.13 0.3 X6.11 0.84 0.88 0.67 0.84 0.6 0.94 0.96 0.89 0.93 0.94 0.94 0.15 0.63 0.24 0.05 0.19 0.2 -0.23 0.01 0.42 0.69 0.17 0.69 0.55 0.71 0.1 0.21 0.55 0.43 -0.01 0.29 0.15 0.46 0.05 0.06 0.26 X8.11 0.81 0.76 0.69 0.78 0.57 0.68 0.73 0.79 0.78 0.75 0.76 0.7 0.02 0.06 -0.05 0.62 0.5 0.15 0.16 0.17 0.04 0.23 0.1 0.18 0.09 0.48 0.35 0.11 0.02 0.07 0.23 0.21 0.19 0.2 0.1 0.15 X8.22 0.91 0.88 0.79 0.96 0.66 0.87 0.91 0.93 0.97 0.94 0.86 0.9 0.73 0.59 0.1 0.41 0.41 -0.09 0.24 0.76 0.85 0.22 0.83 0.7 0.8 0.25 0.6 0.5 0.53 0.16 0.35 0.4 0.47 0.08 0.12 0.14 X8.26 0.82 0.78 0.77 0.85 0.55 0.67 0.75 0.84 0.83 0.85 0.68 0.75 0.66 0.88 0.36 0.66 0.39 0.15 0.39 0.38 0.15 0.23 0.3 0.07 0.25 0.11 0.74 0.44 0.37 0.36 0.43 0.4 0.3 0.36 0 0.01 X11.16 0.78 0.71 0.77 0.79 0.55 0.59 0.61 0.78 0.74 0.71 0.68 0.64 0.57 0.73 0.74 0.12 0.09 0.31 0.51 0.16 -0.08 0.1 -0.04 0.05 0.02 0.3 0.37 0.52 0.47 0.68 0.71 0.49 0.32 0.71 -0.1 -0.11 X11.26 0.91 0.85 0.81 0.91 0.63 0.78 0.82 0.91 0.9 0.9 0.82 0.8 0.89 0.9 0.9 0.72 0.78 0.11 0.31 0.36 0.08 0.28 0.25 0.12 0.19 0.37 0.67 0.37 0.21 0.18 0.47 0.5 0.32 0.32 -0.04 0.07 X11.29 0.92 0.87 0.81 0.93 0.64 0.82 0.83 0.92 0.92 0.91 0.86 0.81 0.86 0.9 0.83 0.72 0.96 0.01 0.21 0.42 0.27 0.26 0.25 0.33 0.2 0.45 0.69 0.34 0.16 0.05 0.54 0.55 0.36 0.24 0.01 0.12 X17.18 0.96 0.81 0.78 0.88 0.62 0.72 0.75 0.87 0.86 0.83 0.8 0.75 0.79 0.84 0.79 0.78 0.88 0.87 0.38 0.06 -0.22 0.08 -0.21 -0.06 -0.17 0.17 0.17 -0.02 0.02 0.38 0.22 0.2 0.1 0.4 0.53 0.39 X17.34 0.81 0.71 0.75 0.81 0.58 0.6 0.66 0.78 0.77 0.73 0.67 0.65 0.68 0.78 0.77 0.79 0.8 0.78 0.84 0.26 0.07 0.18 0.12 0.17 0.15 0.31 0.4 0.27 0.38 0.75 0.46 0.74 0.49 0.58 -0.06 -0.16 X20.22 0.88 0.9 0.73 0.96 0.6 0.81 0.83 0.9 0.96 0.89 0.85 0.84 0.75 0.94 0.81 0.73 0.87 0.89 0.84 0.77 0.64 0.05 0.53 0.65 0.6 0.38 0.52 0.32 0.34 0.17 0.32 0.37 0.37 0.11 0.17 0.16 X22.26 0.86 0.84 0.69 0.9 0.66 0.91 0.93 0.87 0.94 0.91 0.88 0.9 0.69 0.96 0.72 0.63 0.8 0.84 0.77 0.69 0.9 0.28 0.91 0.78 0.86 0.18 0.25 0.39 0.46 -0.02 0.16 0.22 0.43 -0.09 0.19 0.21 X22.24 0.71 0.6 0.61 0.66 0.71 0.66 0.7 0.66 0.67 0.7 0.66 0.62 0.63 0.68 0.63 0.55 0.7 0.7 0.66 0.6 0.6 0.67 0.4 0.25 0.14 0.23 0.24 0.11 0.03 0.16 0.16 0.18 0.15 0.09 0.11 0.15 X22.29 0.86 0.83 0.7 0.89 0.69 0.91 0.94 0.86 0.93 0.93 0.87 0.9 0.71 0.96 0.79 0.64 0.84 0.84 0.77 0.71 0.87 0.97 0.73 0.62 0.85 0.22 0.32 0.41 0.51 0 0.16 0.26 0.45 -0.02 0.14 0.18 X24.26 0.88 0.86 0.75 0.92 0.64 0.84 0.86 0.89 0.93 0.86 0.88 0.87 0.75 0.93 0.71 0.69 0.82 0.87 0.81 0.74 0.91 0.94 0.67 0.89 0.83 0.4 0.33 0.34 0.39 0.11 0.26 0.3 0.38 0.03 0.18 0.17 X24.29 0.85 0.84 0.7 0.89 0.62 0.87 0.9 0.87 0.93 0.9 0.87 0.91 0.7 0.95 0.76 0.65 0.81 0.82 0.77 0.71 0.89 0.96 0.61 0.95 0.95 0.19 0.27 0.45 0.57 0.07 0.19 0.27 0.45 0.03 0.13 0.16 X26.29 0.81 0.76 0.76 0.84 0.62 0.67 0.7 0.82 0.8 0.73 0.75 0.69 0.81 0.78 0.66 0.71 0.82 0.85 0.79 0.73 0.8 0.72 0.62 0.73 0.81 0.72 0.6 0.23 0.23 0.21 0.36 0.37 0.26 0.32 0.12 0.02 X8.29 0.92 0.87 0.85 0.95 0.65 0.77 0.82 0.93 0.92 0.9 0.82 0.81 0.82 0.93 0.92 0.8 0.94 0.95 0.89 0.83 0.9 0.83 0.7 0.85 0.86 0.83 0.87 0.41 0.35 0.29 0.6 0.55 0.41 0.4 0.08 0.03 X6.16 0.82 0.78 0.73 0.83 0.54 0.8 0.83 0.83 0.85 0.85 0.8 0.85 0.68 0.85 0.79 0.81 0.83 0.83 0.76 0.73 0.79 0.8 0.59 0.81 0.79 0.82 0.71 0.84 0.64 0.36 0.42 0.4 0.2 0.26 -0.19 -0.05 X24.34 0.83 0.76 0.72 0.84 0.58 0.75 0.79 0.82 0.84 0.82 0.77 0.8 0.65 0.87 0.77 0.79 0.8 0.79 0.79 0.78 0.8 0.82 0.54 0.84 0.81 0.86 0.71 0.83 0.87 0.61 0.4 0.44 0.25 0.34 -0.08 -0.17 X29.34 0.78 0.67 0.73 0.77 0.54 0.54 0.6 0.74 0.72 0.67 0.62 0.61 0.62 0.73 0.73 0.85 0.74 0.71 0.8 0.89 0.71 0.62 0.56 0.63 0.69 0.65 0.66 0.76 0.74 0.84 0.48 0.71 0.35 0.57 -0.01 -0.14 X16.29 0.93 0.88 0.84 0.92 0.63 0.81 0.83 0.93 0.92 0.9 0.87 0.84 0.8 0.9 0.85 0.88 0.91 0.93 0.91 0.85 0.87 0.83 0.7 0.83 0.86 0.82 0.82 0.94 0.85 0.85 0.83 0.63 0.72 0.74 0.05 0.14 X11.34 0.92 0.85 0.82 0.92 0.64 0.77 0.79 0.91 0.91 0.88 0.83 0.78 0.77 0.9 0.83 0.82 0.91 0.92 0.9 0.92 0.88 0.83 0.67 0.84 0.86 0.83 0.82 0.93 0.83 0.86 0.89 0.94 0.69 0.53 0.03 0 X16.34 0.91 0.86 0.77 0.9 0.61 0.82 0.85 0.9 0.91 0.9 0.86 0.85 0.76 0.9 0.8 0.77 0.87 0.89 0.87 0.86 0.86 0.86 0.65 0.86 0.86 0.86 0.77 0.9 0.77 0.81 0.79 0.95 0.95 0.52 0.26 0.33 X16.17 0.84 0.74 0.8 0.82 0.56 0.64 0.68 0.82 0.78 0.76 0.73 0.7 0.72 0.77 0.78 0.89 0.82 0.81 0.85 0.84 0.75 0.67 0.59 0.7 0.73 0.7 0.75 0.85 0.75 0.78 0.83 0.92 0.87 0.87 0.01 -0.11 X16.18 0.94 0.82 0.75 0.88 0.63 0.77 0.8 0.86 0.88 0.85 0.82 0.79 0.77 0.86 0.76 0.69 0.85 0.86 0.95 0.74 0.84 0.82 0.67 0.82 0.84 0.81 0.76 0.86 0.71 0.76 0.72 0.87 0.87 0.88 0.77 0.36 X18.34 0.93 0.84 0.7 0.85 0.6 0.81 0.82 0.87 0.88 0.86 0.84 0.81 0.77 0.85 0.74 0.67 0.85 0.86 0.93 0.71 0.83 0.81 0.67 0.81 0.82 0.8 0.73 0.85 0.72 0.72 0.67 0.88 0.85 0.89 0.73 0.92

9 For both species, the correlation between morphometric variables decreased after standardizing to the overall mean length (Table 5 and 6). Correlation coefficients were high before standardization reaching values above 0.9 with some variables, while after standardization only two variables had a correlation above 0.9 (X22.26 and X22.29). This indicates that after standardization no variables should be removed since there is no obvious redundancy in the data.

A previous analysis of each morphometric variable using box plots showed for L. piscatorius six specimens that had outlying values for two or more variables (as an example, variables X8.22 > 100 mm, X8.11 > 35 mm, X11.26 > 55 mm, X20.22 > 65 mm, X16.18 > 220 mm). These six outliers were removed from the following analysis. For L. budegassa four outliers were identified with more than one variable (variables X8.22 > 90 mm, X8.11 > 35 and X26.29 < 18 mm) and were also excluded. All specimens that showed outlying values for only one variable were not excluded. The box plots in Figures 6 and 7 do not include the removed outliers. It is possible to see in these Figures that the majority of the variables follow a normal distribution by area.

Figure 6. Box-plots for each morphometric variable for L. piscatorius, by area (1- VIIcj, 2- VIIIabd and 3- VIIIc).

10

Figure 7. Box-plots for each morphometric variable for L. budegassa, by area (1- VIIcj, 2- VIIIabd, 3- VIIIc, 4- IXa, 5- Med.).

11

The discriminant analysis for L. piscatorius estimated two discriminant functions that explain the total variance between groups. The first accounts for 80% of the between group variance and the second for 20%. In Figure 8 each specimen is plotted according to both discriminant functions. There is a clear separation between areas. The first discriminant function separates clearly VIIcj from VIIIabd and VIIIc. The second discriminant function separates area VIIIc from the other two areas. Areas VIIIabd and VIIIc have closer values for both functions. The centroids for each area are plotted with circles representing two times the standard deviation of the Euclidean distance between each point and the respective centroid. The circles do not overlap, confirming the high segregation between all areas.

Figure 8. Centroids for each area of the two discriminant functions, for L. piscatorius, using morphometric variables.

The reallocation of each specimen to the geographical areas (Table 7) shows high correct reallocation, with 95% in VIIcj, 87% in VIIIabd and 84% in VIIIc. The total correct reallocation was of 89%, confirming the good segregation between L. piscatorius specimens of these three areas.

12

Table 7. Percentage and numbers in brackets of reallocation for L. piscatorius for morphometric analysis.

VIIcj VIIIabd VIIIc Total VIIcj 95.3 (41) 0 4.7 (2) 100 (43) VIIIabd 2.6 (1) 87.2 (34) 10.3 (4) 100 (39) VIIIc 5.9 (3) 9.8 (5) 84.3 (43) 100 (51)

The cluster dendrogram (Figure 9) for L. piscatorius corroborates the discriminant analysis results, showing that areas VIIIabd and VIIIc are closer relative to area VIIcj, with a distance to VIIcj equal to it’s linkage distance.

Figure 9. Cluster dendrogram for L. piscatorius, using morphometric variables.

The discriminant analysis for L. budegassa estimated four discriminant functions with respectively 50%, 26%, 16% and 8% of the between group variance. In Figure 10 each specimen is plotted according to the first and second discriminant functions. The first and second discriminant functions are the most important and explain together 76% of the total variance. The first discriminant function segregates area IXa from the other areas and the second function has on both edges area VIIIabd and the Mediterranean. But the second function shows an overlap of the standard deviation circles with areas VIIcj and VIIIc, displaying a partly north-south gradient.

13

Figure 10. Centroids for each area of the two discriminant functions, for L. budegassa, using morphometric variables.

The reallocation of specimens shows high correct values (Table 8). Highest correct reallocation was obtained in areas VIIIabd (90%) and the Mediterranean (84%), followed by the IXa (73%) and VIIIc (70%). The lowest value was the most northern area (VIIcj) with 58%. The total correct allocation was of 76%, considering all areas.

Table 8. Percentage and numbers in brackets of reallocation for L. budegassa using morphometric variables.

VIIcj VIIIabd VIIIc IXa Med Total VIIcj 57.5 (23) 7.5 (3) 20.0 (8) 0 15.0 (6) 100 (40) VIIIabd 2.0 (1) 90.0 (45) 6.0 (3) 0 2.0 (1) 100 (50) VIIIc 15.2 (7) 6.5 (3) 69.6 (32) 2.2 (1) 6.5 (3) 100 (46) IXa 7.0 (5) 1.4 (1) 11.3 (8) 73.2 (52) 7.0 (5) 100 (71) Med. 8.1 (5) 0 8.1 (5) 0 83.9 (52) 100 (62)

The cluster dendrogram (Figure 11) links more closely areas VIIcj and VIIIc, followed by area VIIIabd. The most southern areas are linked after the more northern areas.

14

Figure 11. Cluster dendrogram for L. budegassa, using morphometric variables.

For the meristic analysis there was no need of size standardization, since meristic characters are defined during larval development and are not size dependent. An exploratory analysis showed that some meristic characters (NC, NLV and NRV) did not change along the sampled area and had always the same value for all analysed specimens. These variables were excluded for the discriminant analysis. Correlations between variables were low for both species and had values around 0.2 for L. piscatorius and around 0.1 for L. budegassa. Results from the linear discriminant function and from the reallocations are in Tables 9 and 10.

Table 9. Percentages and numbers in brackets of reallocation for L. piscatorius, as estimated by the discriminant function using meristic characters.

VIIcj VIIIabd VIIIc Total VIIcj 71.4 (35) 6.1 (3) 22.4 (11) 100 (49*) VIIIabd 12.8 (6) 59.6 (28) 27.7 (13) 100 (47*) VIIIc 15.1 (8) 34 (18) 50.9 (27) 100 (53) *Additional specimens were included (not included in the morphometric analysis)

Table 10. Percentages and numbers in brackets of reallocation for L. budegassa, as estimated by the discriminant function using meristic characters.

VIIcj VIIIabd VIIIc IXa Med Total VIIcj 34.7 (17) 12.2 (6) 0 (0) 49 (24) 4.1 (2) 100 (49) VIIIabd 11.1 (6) 27.8 (15) 5.6 (3) 48.1 (26) 7.4 (4) 100 (54*) VIIIc 18.9 (7) 27 (10) 2.7 (1) 43.2 (16) 8.1 (3) 100 (37) IXa 25 (18) 15.3 (11) 1.4 (1) 45.8 (33) 12.5 (9) 100 (72) Med. 14.3 (11) 27.3 (21) 2.6 (2) 50.6 (39) 5.2 (4) 100 (77*) *Additional specimens were included (not included in the morphometric analysis)

15

Total correct reallocation was of 60% for L. piscatorius and 24% for L. budegassa. Areas with highest correct reallocation were VIIcj for L. piscatorius (71%) and IXa for L. budegassa (46%). For L. piscatorius higher values between areas VIIIabd and VIIIc were obtained, while for L. budegassa an important part of all specimens were classified in area IXa.

Discussion

The results from the morphometric analysis show an important segregation between the analysed areas for both species. L. piscatorius between ICES Divisions VIIcj, VIIIabd and VIIIc and L. budegassa showed a high segregation of the Portuguese coast (Division IXa) and a north-south gradient.

The discriminant function and the cluster dendrogram of the morphometric analysis show for both species an agreement between their results. The areas estimated closer by the discriminant function were also closer linked by the dendrogram. For L. piscatorius the total correct allocation was of 89%. Areas VIIIabd and VIIIc were closer in both analyses with the discriminant function showing higher allocation percentages between these two divisions, compared to division VIIcj. The cluster dendrogram shows a link distance around the double to area VIIcj. For L. budegassa, areas VIIcj and VIIIc are closer linked in the dendrogram and have the highest reallocation percentage between both (15% and 20%). They also show close centroids for the first two discriminant functions and a total overlap of the standard deviation circles. The global correct reallocation for L. budegassa was of 76%, below L. piscatorius.

These results do not support the actual stock boundaries. The northern stocks (that include ICES Divisions VIIcj and VIIIabd) consider together two areas that in the present morphometric study are highly segregated for L. piscatorius. Area VIIIc is also segregated from the other two but is for management considered part of the southern stock. Further analysis should be performed in order to investigate the consistency of the IXa area with the VIIIc area, which build together the southern stock.

For L. budegassa the present morphometric results also show disagreement with the actual ICES stock boundaries. Area VIIIc and IXa build the southern stock but according to the present analysis they are clearly segregated. Only 2% of VIIIc specimens were classified as IXa and only 11% of IXa were classified as VIIIc. The VIIIc area is closer to the northern area (VIIcj and VIIIabd) than to the southern area, since 15% and 6% of VIIIc were classified in VIIcj and VIIIabd, respectively. Also, 20% of VIIcj specimens were classified as VIIIc.

The meristic analysis points to a greater degree of similarity between nearby geographical areas. For L. piscatorius the total correct reallocation was of 60% and specimens not correctly classified were attributed in greater percentage to geographical closer areas. L. budegassa global correct reallocation was of 24%, much lower compared to L. piscatorius and a great part of all specimens were allocated in area IXa.

16

In the present study, the meristic analysis gave a lower segregation between areas, for both species. This could partially be explained by the fact that meristic characters are set early in the larval development while morphometric characters are influenced during a longer period of the specimen’s growth.

The morphometric differences obtained in the present study can be a consequence of different environmental conditions between the analysed areas. Migration between areas is very likely to happen but the settlement of specimens in each area is probably long enough to adapt to the local environmental factors.

For stock discrimination studies it is important to compare different methodologies. For this area a microsatellite DNA analysis was performed under the EU project GESSAN (2001) showing that the proportion of total genetic variation between stocks was relatively small (0.21% for L. budegassa and 0.35% for L. piscatorius), not supporting a boundary between Northern and Southern stocks. In this genetic study, more than 98% of the total genetic variation was attributed in both species to differences within populations, which suggest high gene flow among populations. This result is not in agreement with the results obtained in the present morphometric study, since differences were observed between different areas.

Moreover, the displacements of tagged anglerfish between the Southern and Northern stocks after tagging-recapture experiments performed under two EU projects (DEMASSESS, 2000; GESSAN, 2001), also provide useful information on interactions between the components of both stocks and serve to question the biological basis of the currently considered stocks (Pereda and Landa, 1997). From a total of 68 recaptures, 9 specimens crossed the border between the southern and the northern stocks (Fariña et al., 2004)

Different results between morphometric and genetic analysis have been obtained also in other studies, namely for other Lophius species (L. vomerinus) from the southern African coast (Leslie and Grant, 1990). In some cases there is sufficient gene flow among areas in each generation to prevent genetic differentiation. According to Ward (2000) gene flow rates of 1% will give genetic homogeneity among samples and thus cannot be distinguished. This way only a few migrants between areas are required to prevent allele- frequency differences from accumulating among areas (Leslie and Grant, 1990, Elliott et al, 1995). But for managers it is crucial to identify populations or sub-populations and to know until what extend migrants can prevent sub-populations to recover from an intensive exploitation. Our study shows that for both European anglerfishes several sub-populations may exist and that their population structure seems to be more complex, than considered by the actual ICES stock limits.

Acknowledgements This study was partially supported by EU DG-XIV (Study contract 99/013 - GESSAN). Special thanks also to José Castro, from IEO-Vigo, for his important collaboration.

17

References

Abaunza, P., Mattiucci, S. ,Magoulas, A., Cimmaruta, R., Bullini, L. and Nascetti, G., 2001. Morphometric and meristic variation in European hake Merluccius merluccius, from the Northeast and . ICES CM 2001/J:01.

Begg, G.A. and Walkman, J.R., 1999. An holistic approach to fish stock identification. Fish Res 43: 35-44.

Begg, G.A., Friedland, K.D. and Pearce, J.B., 1999. Stock identification and its role in stock assessment and fisheries management: an overview. Fish Res 43: 1-8.

Cadrin, S.X. 2000. Advances in morphometric identification of fishery stocks. Reviews in Fish Biology and Fisheries, 10: 91-112.

Caruso, J.H., 1986. Lophiidae. In Whitehead, P.J., Bauchot, M. L., Nielson, J. and Tortonese, E. (eds). of the North-eastern Atlantic and the Mediterranean. FAO, UNESCO, Paris, Vol. III: 1362-1363.

DEMASSESS, 2000. New assessment and biology of the main commercial fish species: Hake and Anglerfishes of the Southern shelf demersal stocks in the South Western Europe (DEMASSESS) - Final Report. UE DG XIV 97/035.

Elliott, N.G., Haskard, K. and Koslow, J.A., 1995. Morphometric analysis of orange roughy (Hoplostethus atlanticus) off the continental slope of southern Australia. J Fish Biol 46: 202-220.

Fariña, A.C., Duarte, R., Landa, J., Quincoces, I. and Sánchez, J.A. 2004. Multiple stock identification approaches of anglerfish (Lophius piscatorius and L. budegassa) in western and southern European waters ICES CM 2004/EE: 25.

GESSAN, 2001. Genetic characterization and stock structure of the two species of anglerfish (Lophius piscatorius and L. budegassa) of the northeast Atlantic. Final Report. EU DGXIV Fisheries. Study Contract 99/013.

Hurlbut, T. and Clay, D., 1998. Morphometric and meristic differences between shallow- and deep-water populations of white hake (Urophycis tenuis) in the southern Gulf of St Lawrence. Canadian Journal of Fisheries and Aquatic Sciences, 55:2274- 2282.

ICES, 2004. Report of the Working Group on the Assessment of Southern Shelf Stocks of Hake, Monk and Megrim, ICES CM 2004/ACFM:02

Junquera, S. and Perez-Gándaras, G., 1993. Population diversity in Bay of Biscay (Engraulis encrasicholus L. 1758) as revealed by multivariate analysis of

18 morphometric and meristic characters. ICES Journal of Marine Science, 50: 383- 391.

Leslie, R.W. and Grant, W.S., 1990. Lack of congruence between genetic and morphological stock structure of the Southern African anglerfish Lophius vomerinus. S Afr J Mar Sci 9: 379-389.

Leslie, R.W. and Grant, W.S., 1994. Meristic and morphometric variation among anglerfish of the genus Lophius (Lophiiformes). J Zool 232, 4: 565-584.

Manly, B.F.J., 1997. Multivariate statistical methods – A primer (2nd edition), Chapman & Hall, 215pp.

Meng, H.J. and Stocker, M., 1984. An evaluation of morphometrics and for stock separation of Pacific (Clupea harengus pallasi). Canadian Journal of Fisheries and Aquatic Sciences, 41: 414-422.

Murta, A.G., 2000. Morphological variation of horse (Trachurus trachurus) in the Iberian and North African Atlantic: implications for stock identification. ICES Journal of Marine Science, 57:1240-1248.

Quero, J. C., 1984. Les Poissons de Mer des Pêches Françaises: Les Lophiiformes. In Graucher, J. (ed.), 146-148.

R Development Core Team, 2003. R: A language and environment for statistical computing. R Foundation for Statistical Computing. Vienna, Austria (http://www.R-project.org)

Ricker, W.E., 1973. Linear regression in fishery research. Journal of the Fisheries Research Board of Canada, 30: 409-434.

Saborido-Rey, F. and Nedreaas, K.H., 2000. Geographic variation of Sebastes mentella in the Northeast Arctic derived from morphometric approach. ICES Journal of Marine Science, 57:965-975.

Strauss, R.E. and Bookstein, F.L., 1982. The Truss: Body form reconstructions in morphometrics. Syst Zool 31, 2: 113-135.

Waldman, J.R., Grossfield, J. and Wrigin, I., 1988. Review of stock discrimination techniques for striped bass. N. Am. J. Fish. Mgmt., 8: 410-425.

Ward, R.D. 2000. Genetics in fisheries management. In: A.M. Sole, C.A.M. Russo and J.P. Thorpe (eds): Marine Genetics. Hydrobiologia, 420: 191-201.

19