Academia Journal of Scientific Research 4(10): 345-354, October 2016 DOI: 10.15413/ajsr.2016.0607 ISSN: 2315-7712 ©2016 Academia Publishing

Research Paper

Discriminating Between the Hakes Merluccius Hubbsi and M. Australis on the Basis of their Otolith Morphometrics

Accepted 23rd June, 2016

ABSTRACT

In the Southwest Atlantic south of 47°S, the distributions of Merluccius hubbsi and Merluccius australis partially overlapped. As adult fish of both hakes have a similar appearance, it is suspected that they are often misclassified, particularly by observers on board of commercial vessels. Since otoliths are considered to be potentially determinant features at the specific level, we utilized sagittae morphometry to distinguish between adults (50 to 70 cm) of either species. By considering properly identified specimens of M. hubbsi and M. australis captured during research surveys, some otolith size variables, as well as, shape indices and an outline analysis (Elliptic Fourier Analysis) were used to obtain a discriminant function. This function was then applied to other sets of otolith samples collected from the commercial fleet and presumed to include some misclassifications. Discriminant analysis including all variables (Model 1) correctly classified the surveys samples of M. australis and M. hubbsi with 100% accuracy, whereas Eliptic Fourier Analysis (Model 2) was more effective (91%) than size variables and shape indices (82%, Model 3). This work highlights the advantages of considering together shape indices and Fourier coefficients to achieve more accurate differentiation between species that show similar otoliths. The discriminant function (Model 1) applied to otoliths from commercial fishing suggested that a significant number of M. australis would have been misidentified as M. hubbsi (72% error). Circularity and mainly otolith Federico L. Gorini1* and Claudio C. Buratti1,2 weight also showed significant differences between species, the later appearing as a usefull, easier-to-record alternative to this purpose. On the other hand, 1Instituto Nacional de Investigación y Desarrollo neither the presence or absence of Excisura ostii on the ventral side of the Pesquero (INIDEP), Paseo Victoria Ocampo N°1, B7602HSA Mar del Plata, Argentina. otoliths, nor the border type (serrated or flat) were so powerfull, in spite of 2Facultad de Ciencias Exactas y Naturales, being a flat border (97%) and the presence of E. ostii (84%) more frequent in Universidad Nacional de Mar del Plata, Funes common hakes (M. hubbsi) than among southern hakes (48 and 52%, 3350, B7602AYL Mar del Plata, Argentina. respectively).

*Corresponding author. E-mail: [email protected]. Key words: Merluccius, otolith, morphometry, mixed samples.

INTRODUCTION

Two species of the Genus Merluccius inhabit the Southwest The common hake (M. hubbsi) is the main fishery Atlantic, Merluccius hubbsi and Merluccius australis (Inada, resource in Argentina, where about 257,000 tons were 1981; Cohen et al., 1990; Ho, 1990; Roldán and Pla, 2001; landed during 2014 (http://www.minagri.gob.ar). The Díaz de Astarloa et al., 2007; Campo et al., 2007; Deli species distributes over the continental shelves off Antoni, 2013). Argentina and Uruguay between 34° and 54°S, at depths Academia Journal of Scientific Research; Gorini and Buratti. 346

between 50 and 800 m. Occasionally, because of the research surveys was built by analyzing sagittae shape in presence of sub-Antartic waters along the southern coast both species. Complementarily, the usefulness of other of Brazil (Bezzi et al., 1994), hake is also found in Brazilian otolith features, such as weight, presence or absence of waters. As to the distribution of the southern hake, M. Excisura ostii and type of ventral border (serrated or flat) australis is widely extended over the southern hemisphere, to rapidly identify the fish were also investigated. both in Argentinean and Chilean waters as well as, off New Zealand (Cousseau and Perrotta, 2004; Giussi et al., 2013). In Argentina, although the main concentrations were MATERIALS AND METHODS observed between 50° and 55°S, they can reach 48°S during spring and summer (García de la Rosa et al., 1997). Sample collection and imaging This species is not a direct fishing target, but it is incidentally caught by either factory and freezer vessels In the years 2010 and 2012, several samples were looking for other species, such as longtail hake, collected during research surveys carried out by the Macruronus magellanicus and southern blue whiting, INIDEP, as well as, on board of commercial vessels which Micromesistius australis (Giussi et al., 2004). Southern hake operated within the shared distribution area of of M. annual landings are usually scarce, and they have not hubbsi and M. australis in the Argentine Sea (Figure 1). The exceeded 5000 t during the last fifteen years (Gorini et al., commercial fleet samples were obtained by the staff of the 2013). On-board Observers Program (INIDEP). As a whole, 89 Age-structured assessment models are considered to pairs of otoliths were obtained from research surveys and provide better descriptions of the population dynamics of 131 pairs from commercial fishing (Table 1). The otoliths fish stocks than simpler surplus production models, but were washed with water, dried and stored in labeled they obviously require age data. These data are often polypropylene microtubes. Total length of fish ranged obtained by interpretation and quantification of the between 50 and 70 cm (Table 1). growth rings marked on the fish otoliths, and this is a Left otoliths were weighed on an analytical balance routine activity performed in our institute on both (resolution = 0.0001 g) and arranged horizontally to common and southern hake samples. digitize their external side with an Epson Perfection 4490 During the most recent years, age readings from Photo Scanner (3200 dpi resolution), while a 1 × 1 cm scale commercially fished southern hakes suggested some age- was placed on the upper part for reference purposes. at-size values rather similar to those which are usual for Finally, the presence or absence of E. ostii and the type of the common hake, that is, younger than expected for the border (serrated or flat) on the ventral side of the otolith southern fish. It is noteworthy that even though there are were recorded (Figure 2). some phenotypic characters (number of lateral-line scales, size of the snout and eye diameter) that allow the differentiation between both species (Cousseau and Shape descriptors and fourier coefficients Cotrina, 1981; Cousseau and Perrotta, 2004; Díaz de Astarloa et al., 2007; Deli Antoni, 2013), this is not an easy Otolith shape was described by size variables and shapes task, and so the adults integrating commercial catches may indices (Table 2) as estimated using the ImageJ software be frequently misclassified (Giussi et al., 2000; Arkhipkin (Schneider et al., 2012) according to Tuset et al. (2003), et al., 2003). and further by an outline analysis, the Elliptic Fourier On the other hand, otoliths are considered to be Analysis (Kuhl and Giardina, 1982). particular features at the specific level and there are The Elliptic Fourier Analysis describes the outline several factors both abiotic (depth, temperature) and through different components called harmonics, each biotic (growth, for instance) which are able to affect the harmonic being characterized by four coefficients resulting otolith shape of any species (Gaemers, 1984; Wilson, 1985; from the projection of each point of the contour over the Nolf, 1993; Torres et al., 2000; Gauldie and Crampton, axes x and y. The higher the number of harmonics, the 2002). greater the accuracy of the outline description (Kuhl and Consequently, some studies on the sagittae shape of the Giardina, 1982). The software Shape 1.3 (Iwata and Ukai, Genus Merluccius have been carried out, mainly to identify 2002) was utilized to calculate Fourier Coefficients (FCs) species or to establish phylogenetic relationships in order to make them independent both from the otolith (Lombarte and Castellón, 1991; Torres et al., 2000; size and from its orientation and position with respect to Lombarte et al., 2003; Díaz de Astarloa et al., 2011; the beginning of the outline, wich is arbitrarily defined Delpiani et al., 2012; Deli Antoni, 2013). Taking this into (Rohlf and Archie, 1984). As a consequence of this process, account, the aim of this work was to accurately identify the first three coefficients of the first harmonic are which species the otoliths collected by observers on board constant (a1=1, b1=c1=0) and they are not taken into of commercial vessels belong to. To do this, a account for the analysis. differentiation function from correctly identified Furthermore, Fourier power spectrum (FPS) was specimens of M. hubbsi and M. australis captured during estimated in order to determine the amount of harmonics Academia Journal of Scientific Research; Gorini and Buratti. 347

Figure 1. Distribution of M. hubbsi and M. australis south 44° S. The position of fishing hauls where samples were obtained is also shown. Academia Journal of Scientific Research; Gorini and Buratti. 348

Table 1. Sample size and average size of M. australis and M. hubbsi specimens from research campaigns and obtained by observers on board commercial fleet.

Species Origin N Average size (cm) Merluccius australis Research surveys 31 65.4 Merluccius hubbsi Research surveys 58 63.3 Merluccius australis Commercial fleet 84 58.9 Merluccius hubbsi Commercial fleet 47 56.2

Figure 2. Scanner sagittae images of (A) M. hubbsi (LT= 60 cm) and (B) M. australis (LT= 68 cm). Remarks: AE: anterior extremity, PE: posterior extremity, DM: dorsal margin, VM: ventral margin, EO: excisura ostii; FB: flat border; SB: serrated or petal-like border.

Table 2. Size variables and shape indices.

Size variables Shape indices Otolith length (OL) Circularity: 4π*(A/P2) Otolith width (OW) Aspect ratio: OW/OL Area (A) Roundness: (4*A)/ (π*OL2) Perimeter (P) Otolith weight

which may allow an appropriate reconstruction of the n PF  PFn otolith outline (Crampton, 1995). The Fourier power of a c 1 harmonic is proportional to its amplitude and provides a measure of the amount of ‘shape information' described by A threshold of 99.9% was used to determine the that harmonic. For the nth harmonic the FPS is given by the appropriate number of harmonics to be used in the following expression: subsequent analysis (Stransky et al., 2008).

 A2  B 2  C 2  D 2  n n n n Statistical analysis PF    n  2    An Analysis of Covariance (ANCOVA) was used to determine the possible effect of the fish length on the Where A, B, C and D are the Fourier coefficients of the magnitude of each variable (shape indices and otolith nthharmonic. Subsequently, the percentage of cumulative weigth). Fish length was considered as a continuous, power is estimated according to: independent variable, whereas the shape indices and Academia Journal of Scientific Research; Gorini and Buratti. 349

otolith weight were numerical dependent variables and 80% (Table 4). Model 1, which included all variables, the species was a categorical one. Being those variables achieved a perfect classification (Figure 3). The significantly correlated with fish length, they were determination of the differentiation function by using the transformed by assuming a potential relationship between Fourier coefficients alone (91%, Model 2) was more them and the fish size (Lombarte and Lleonart, 1993). effective than using only the shape indices (82%, Model 3). Given the relationship y= a * xb and with x0 as a reference As a conclusion, in spite of providing acceptable levels of value for the variable x (in this case x0 = average fish accuracy when used separately to differentiate the species length), the new transformed variable (yt) became: (Models 2 and 3), the classifying power of either variable groups (morphometric indices and Fourier coefficients) b greatly increased when used together (Model 1).  x0  yt  y *  When the otolith shape indices were considered  x  separately, the only two variables showing differences between species were otolith weight and circularity Where y is the raw value of the variable (shape indices and (Wilcoxon Test, p < 0.0001 and p < 0.01, respectively). otolith weigth) and b is obtained from the potential Southern hake otoliths were lighter, thinner and presented relationship between the variables and the fish length (x). a greater area (Figure 4). The capacity of otolith weight To eliminate the effect of fish length on the Fourier discrimination for separating samples was 75%, that is, coefficients, the studentized residuals from a linear weaker than that of the previous models. Nevertheless, as regression of each FC on total length were calculated, both the otolith weight is easier to determine, it may be for the survey and commercial fleet data. considered a useful alternative to distinguish fish of these In order to reduce the dimensionality of the data, a two species with an acceptable level of confidence. principal components analysis (PCA) was carried out. The Within the fish caught in research surveys, a flat border classification into species of the verified samples that were (97 %) and presence of E. ostii (84%) were more frequent collected during research surveys was performed through in common hake specimens than among southern hakes a discriminant analysis of the shape indices and FC. The (48 and 52%, respectively). When the most accurate estimated canonical coefficients were subsequently used differentiation function (Model 1) was applied to the to classify the samples obtained by the observers on-board sample of 131 pairs of otoliths from the commercial fleet, a of commercial vessels. The effectiveness of the high degree of on-board misidentification was found. Most discriminant function was measured by the classification (34) out of the 47 specimens identified by the observers as accuracy of the discriminant analysis. Shape indices were common hakes had to be reclassified as M. australis (Table compared between species with a Wilcoxon 5). On the contrary, from the 84 pairs of otoliths originally nonparametric test. Every statistical analysis was classified as southern hake, only four were reclassified as performed by the software Infostat (Di Rienzo et al., 2012). common hake (Figures 5 and 6). More than half (60%) of the misidentified hakes inspected showed a serrated type otolith border, suggesting that most of those fish could RESULTS have actually been southern hakes.

As the first ten harmonics (40 coefficients) achieved a 99.9% of the Fourier cumulative power, that number of DISCUSSION harmonics was considered enough to properly describe the otolith shape of these species. Thus, once the first three Our analyses of the otolith shape for differentiating constant coefficients of the first harmonic were eliminated between M. australis and M. hubbsi conform to the due to the normalization process above described, the classification made by scientists during research surveys; remaining 37 coefficients were used for further analysis. thus, confirming the validity and usefulness of these The attempts for reducing dimensionality through techniques to distiguish between the two species. The principal components analysis were eventually discarded, three models we fit excedeed 80% in power of because even high principal components contributed to differentiation, Model 1 (shape indices and Fourier improve discrimination. coefficients considered together) achieving a perfect Departures from the multivariate normality assumption performance. The advantages of considering together did not invalidate every linear discriminant analyses, since shape indices and Fourier coefficients in order to some simulation studies showed that the linear accurately differentiate between similar species have been discriminant function is usually very robust (Di Rienzo et previously pointed out (Short et al., 2006, Tracey et al., al., 2012). Three combinations of main components and 2006; Mérigot et al., 2007). morphometric indices (Models 1 to 3) obtained from the Otolith morphometrics also provided a powerful way to research surveys samples were tested with a non- detect and correct possible sampling errors. The best standardized differentiation function (Table 3). Every differentiation function used revealed many identification model resulted in a sample classification accuracy over mistakes on board of commercial vessels, mainly Academia Journal of Scientific Research; Gorini and Buratti. 350

Table 3. Differentiation function used to separate the verified samples of Merluccius hubbsi and M. australis collected during research cruises. The canonical differentiation function was: Dn = constant + coef1 * var1 + coef2 * var2 +…..+ coefn * varn.

Canonical variables Variable Model 1 Model 2 Model 3 Constant -29.56 0.0001 -60.53 Otolith weight -31.24 -30.27 Area -10.28 -2.27 Perimeter 7.67 2.49 Circularity 44.20 8.49 Aspect Ratio 0.03 9.06 Roundness -42.09 78.24 CoefFourier4 0.98 -0.07 CoefFourier5 0.01 0.22 CoefFourier6 -0.49 -0.56 CoefFourier7 -0.39 -0.24 CoefFourier8 -1.03 -0.14 CoefFourier9 -0.01 0.13 CoefFourier10 -1.09 -1.55 CoefFourier11 -0.28 -0.07 CoefFourier12 -0.55 -0.66 CoefFourier13 0.56 -0.53 CoefFourier14 -0.91 -1.31 CoefFourier15 -1.72 -1.36 CoefFourier16 0.83 0.35 CoefFourier17 -0.64 -0.98 CoefFourier18 0.98 1.26 CoefFourier19 0.28 -0.33 CoefFourier20 -0.22 -0.17 CoefFourier21 -1.31 -0.49 CoefFourier22 0.06 1.94 CoefFourier23 -1.19 -1.08 CoefFourier24 -0.21 0.33 CoefFourier25 1.81 1.85 CoefFourier26 0.72 -0.01 CoefFourier27 0.35 0.48 CoefFourier28 0.04 0.38 CoefFourier29 0.99 0.81 CoefFourier30 0.49 -0.92 CoefFourier31 1.33 1.31 CoefFourier32 -0.27 -0.22 CoefFourier33 -1.14 -1.14 CoefFourier34 0.17 0.22 CoefFourier35 0.17 -0.02 CoefFourier36 -0.49 -0.22 CoefFourier37 -0.63 -0.42 CoefFourier38 -0.65 0.02 CoefFourier39 -1.07 -0.72 CoefFourier40 -0.20 -0.14 Accuracy 100% 91% 82%

consisting of registering M. australis specimens as M. workshops to reinforce the knowledge of the fish hubbsi. There is an evident need for conducting sampling characteristics that allow for a correct determination. Academia Journal of Scientific Research; Gorini and Buratti. 351

Table 4. Cross-classification matrix and error rate on the validated samples of M. australis y M. hubbsi collected during research cruises.

Models Group Total M. australis M. hubbsi Error (%) M. australis 31 31 0 0 Model 1 M. hubbsi 58 0 58 0 Total 89 31 58 0

M. australis 31 28 3 9.7 Model 2 M. hubbsi 58 5 53 8.6 Total 89 33 56 9.0

M. australis 31 25 6 19.4 Model 3 M. hubbsi 58 10 48 17.2 Total 89 35 54 18.0

12 M. hubbsi 10 M.australis 8

6 Frequency 4

2

0 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 Canonical score

Figure 3. Differentiation coefficients (Model 1) obtained during the analysis of the verified samples of M. hubbsi and M. australis from research surveys.

Difficulties to undoubtly identificate these species were the common hakes presenting E. ostii among fishes longer also reported by different groups of observers on vessels than 400 mm. These percentages are in line with our operating near Islas Malvinas and beyond the Argentinean results, whereas they differ from Díaz de Astarloa et al. Exclusive Economic Zone (Pierce et al., 2002; Arkhipkin (2011) and Delpiani et al. (2012) who have not found this etal., 2003). The frequent presence of E. ostii in otoliths of structure in specimens of southern hake. adult common hakes was recently noticed by Deli (2013), Some previous papers agreed in differentiating between who reported up to 89% of the southern hakes and 39% of species according to the type of ventral border of the Academia Journal of Scientific Research; Gorini and Buratti. 352

Figure 4. Box diagram (average, standard deviation, minimum and maximum) of the shape indices and otolith weigth of M. australis and M. hubbsi specimens identified during research surveys.

Table 5. Cross-classification matrix and error rate in the identification of M. australis and M. hubbsi by observers on board commercial vessels. Results of the application of Model 1 obtained from validated samples.

Species Total M. australis M. hubbsi Error (%) M. australis 84 80 4 5 M. hubbsi 47 34 13 72

otolith, which would be flat among common hakes and like or serrated borders. petal-like in southern hakes (Díaz de Astarloa et al., 2011; Delpiani et al., 2012; Deli, 2013). We found this is a rather subjective characteristic, since it depends on what the Conclusion observer considers to resemble a petal. Our results included a 97% of common hakes presenting flat-bordered It was confirmed that otoliths are thicker and consistenly otoliths and 81% of southern hakes showing either petal- heavier in common hakes than in southern hakes, as Academia Journal of Scientific Research; Gorini and Buratti. 353

16 M. hubbsi 14 M.australis 12 M.australis obs. 10

8

Frequency 6

4

2

0 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Canonical score

Figure 5. Differentiation coefficients obtained from the analysis of verified specimens of M. hubbsi and M. australis and of specimens identified as M. australis by observers on board commercial vessels.

12 M. hubbsi

10 M.australis

8 M. hubbsi obs.

6 Frequency 4

2

0 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Canonical score

Figure 6. Differentiation coefficients obtained from the analysis of verified specimens of M. hubbsi and M. australis as well as of specimens identified as M. hubbsi by observers on board commercial vessels. Academia Journal of Scientific Research; Gorini and Buratti. 354

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