Morphometric Differentiation Between Juveniles of Bluefin Tuna and Little

Morphometric diﬀerentiation between juveniles of blueﬁn tuna and little tunny caught in Western Mediterranean Sea

Jairo Castro-Gutiérrez*1, SámarSaber2, David Mac´ıas2, Mar´ıaJoséGómez-Vives2, Matxalen Pauly3 and Josetxu Ortiz de Urbina2

*Corresponding author: [email protected] 1Universidad de Málaga, Departamento de Biolog´ıaAnimal, 29071 Málaga. 2Instituto Español de Oceanograf´ıa,Centro Oceanográficode Málaga,Puerto Pesquero, s/n, 29640 Fuengirola, Málaga. 3IPD, Investigación Planificacióny Desarrollo, S.A.

Keywords: Morphometric characters, Taxonomy, Thunnus thynnus, Euthynnus alletteratus, Juveniles

Introduction

Bluefin tuna (Thunnus thynnus, L. 1758) and little tunny (Euthynnus alletteratus, Rafinesque 1810) are highly migratory species that inhabit Atlantic Ocean and Mediterranean Sea (Collette and Nauen, 1983). The Mediterranean Sea is a spawning area for both species (Alemany et al., 2010; Oray and Karakulak, 2005; Rodr´ıguez-Roda, 1964). Juveniles of tuna species can be found in mixed schools and catches. The very young juveniles of bluefin tuna and little tunny are difficult to differentiate. Differentiation of species is essential for biology, fishery management and conservation studies. Genetics is an accurate method to discriminate species but is expensive, time consuming and results are not immediate. The objective of this study is to identify morphometric characters to discriminate between juvenile of bluefin tuna and little tunny.

Material and methods

Juvenile of bluefin tuna and little tunny were caught between August and September from 2016 to 2018 from four localities throughout Western Mediterranean Sea. A total of 142 bluefin tuna (ranged from 121 to 357 mm) and 101 little tunny (ranged from 85 to 315 mm) were analysed (Table1). The individuals were caught as bycatch by purse seine targeting small pelagic species (anchovy and sardine) and sport fishery. Juvenile of bluefin tuna (smaller than the minimum landing size) were collected under the provision of the International Commission of the Atlantic Tunas (ICCAT) Atlantic Wide Research Program for Bluefin Tuna (GBYP).

1 Table 1: Blueﬁn juvenile and little tunny catches used in this study.

The specimens kept frozen at -20◦C until further analysis in the laboratory, except ten specimens of bluefin tuna that were analysed in fresh. For each individual fork length (FL) was measured with an ichtyometer to the nearest mm or a caliper to the nearest 0.01 mm. The excess of water was eliminated with a piece of paper and then, body weight (BW) was measured to the nearest 0.01 g (± 0.01). Thirteen morphometric measurements were recorded: (1) Fork length, FL; (2) Snout length, SL; (3) Eye diameter, ED; (4) Post- orbital length, PO; (5) Head length, LH; (6) First pre-drosal length, LD1; (7) Maximum body height, H; (8) Pectoral fin length, LP ; (9) Second dorsal height, HD2; (10) Anal fin length, LA; (11) Caudal fin height, CC; (12) Dorsal fins distance, FD; (13) Mouth cleft length, MCL. All measurements were taken on the left side by consensus. A digital caliper was used to measure the morphometric variables (2-13) to the nearest 0.01 millimeter (± 0.01). A non-parametric Kruskal-Wallis Test was performed to determine if there are statistically significant differences between the morphometric variables. To identify the variables that can explain the differences between populations the principal component analysis (PCA) was used. Barlett’s Sphericity test and Kaiser-Meyer-Olkin test was performed to check the factorization validity conditions. All statistical analyses was performed with R statistical software with a significance level of α= 0.05.

Results

The variable “caudal fin height” was discarded of the statistical analysis because the objectivity of the measure was conditioned by the fin shape after defrosting. Samples with at least one not-registered variable were discarded. Then a total of 127 bluefin tuna and 82 little tunny were analysed. The variables were scaled to the fork length or to the head length to remove any possible size effect.

2 Figure 1: Fig. 1

Kaiser-Meyer-Olkin (KMO) adequacy value (KMO = 0.866) indicate that the sampling is adequate for Factor Analysis (KMO values between 0.8 and 1 indicate the sampling is adequate). Bartlett’s sphericity tests the hypothesis that the correlation matrix is an identity matrix, which would indicate that the variables are unrelated and therefore unsuitable for structure detection. Barlett’s sphericity test (χ2 = 1696,96; p < 0.001), provided a correlation value between the variables sufficient to apply the factor analysis. The number of principal components in the PCA is based on: a) Eigenvaluees and/or cumulative variance quantity explained and b) based on a scree plot (Peres-Neto et al., 2005). The PCA showed that the first five principal components account for 88.04% of the total variance of the original thirteen morphological variables (48.5% for PC1, 19.8% for PC2, 9.2% for PC3, 6% for PC4 and 4.5% for PC5). The variables included in the first component were: H, HD2, LD1, LH, LP, MCL, and SL. The variables included in the second component were: ED, PO, FD and LA. The position of individuals in the principal components are represented in Figure1.

Acknowledgments

We are grateful to all the skippers and crews of the commercial and recreational fisheries. The collaboration of Jesus Torralba is also enormously appreciated. This project has been co-funded by the EU through the European Maritime and Fisheries Fund (EMFF) within the National Program of collection, management and use of data in the fisheries sector and support for scientific advice regarding the Common Fisheries Policy.

3 References

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