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ICES Journal of Marine Science: Journal du Conseil Advance Access originally published online on May 18, 2008
ICES Journal of Marine Science: Journal du Conseil 2008 65(6):963-969; doi:10.1093/icesjms/fsn079
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© 2008 International Council for the Exploration of the Sea. Published by Oxford Journals. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Bathymetric preferences of juvenile European hake (Merluccius merluccius)

Valerio Bartolino1, Alessandro Ottavi2, Francesco Colloca1, Gian Domenico Ardizzone1 and Gunnar Stefánsson3

1 Department of Animal and Human Biology, University of Rome "La Sapienza", viale dell’Università, 32, 00185 Rome, Italy
2 Department of Statistics, Probability and Applied Statistics, University of Rome "La Sapienza", piazzale Aldo Moro, 5, 00185 Rome, Italy
3 Department of Mathematics, University of Iceland, Dunhagi, 5, 107 Reykjavík, Iceland

Correspondence to V. Bartolino: tel: +39 0649914763; fax: +39 064958259; e-mail: valerio.bartolino{at}uniroma1.it

Bartolino, V., Ottavi, A., Colloca, F., Ardizzone, G. D., and Stefánsson, G. 2008. Bathymetric preferences of juvenile European hake (Merluccius merluccius). – ICES Journal of Marine Science, 65: 963–969.

The concept of a recruit is a basic notion in fisheries science, but it is still far from being an unequivocal term, and many diverse, even ambiguous, definitions can be found in the literature. We propose a more objective and biologically meaningful way to define the length range of recruits for species that have clear bathymetric segregation during the early stages of their life cycle. The bathymetric distribution of juvenile European hake was studied by fitting a thin plate spline to data from the national autumn trawl survey. Hake showed a stable pattern of depth preference in the 6-year dataset examined. Small hake had the greatest preference for depths of 170–220 m and appeared to move slightly deeper when they reached 10-cm total length. Larger hake persisted on the continental shelf with a preference for water 70–100 m deep, especially when they reached 18–20 cm long. The length at migration was defined as the length at which the minimum depth preference was shown, and it ranged between 13.2 and 15.8 cm depending on the year. There was a relationship between length at and depth of migration, and we provide a full description of the depth preference of juvenile hake, and test the effectiveness of the analytical approach used.

Keywords: bathymetric distribution, hake, recruit, thin plate spline

Received 1 October 2007; accepted 12 April 2008; advance access publication 18 May 2008.


   Introduction
Top
 Introduction
Material and methods
 Results
 Discussion
 References
 
The spatial distribution of marine organisms is generally not homogeneous in space, and different aggregation phases can be recognized in the life cycle of many species (Shima et al., 2002). The environment fish occupy throughout their life often differs between the larval and the adult stages (Sullivan et al., 2000), and size-class relationships for many species are not yet well resolved at a regional or ecosystem level (Methratta and Link, 2007).

Ontogenetic differences in fish populations are often evident, many species having several well-defined phases during their life. Marked variations in morphology and physiology (McCormick, 1998; Fisher et al., 2005), in trophic behaviour (Werner and Gilliam, 1984), and in spatial distribution (Ardizzone and Corsi, 1997) can represent transitions between the different phases. Fish move deeper or shallower, to the surface or the seabed, to feed, to avoid predation, or to reproduce (Neilson and Perry, 1990). Understanding such movements can help us understand fish behaviour better, and improve management and conservation of the resources (Sparre et al., 1989).

Many species of the genus Merluccius make extensive migrations during one or more phases of their life cycle (Cohen et al., 1990; Alheit and Pitcher, 1995). Although no specific analysis was carried out on the bathymetric preference of the European hake (Merluccius merluccius), indirect information came from studies on its spatial distribution (Ardizzone and Corsi, 1997; Fiorentino et al., 2003; Abella et al., 2005). An ontogenetic pattern of distribution was reported by Abella et al. (2005), fish aged 0 being concentrated mostly at between 100 m and 250 m deep, and fish aged 1 year being distributed mainly in shallower water over the shelf.

Although a proper understanding of hake migration from the nursery areas is basic to defining the phase of recruit during which fish concentrate before dispersion, no study has described this process in detail. A better comprehension of hake juvenile distribution would be of particular importance, considering that fisheries such as that for hake in the Mediterranean Sea exploit recruits as a large proportion of the total landings of a species or stock (Abella et al., 1997).

The term recruit has been defined in many different ways in the literature, including the scientific literature. Descriptions differ in the meaning and in relation to the context in which they are used. Scientific fisheries management defines recruits to the fished stock as those fish entering the exploitable component (FAO, 1997). Other biological definitions generally refer to recruits as age 0 fish (e.g. Fiorentino et al., 2003), fish of the youngest cohort (e.g. McBride and Conover, 1991), or simply immature fish.

The purpose of the present study was to analyse the bathymetric distribution of juvenile hake in the Mediterranean Sea with regard to their migration from nursery areas, using an easily applied analytical approach based on thin plate spline (tps) surfaces. A model of bathymetric preference will sharpen the definition of the concept "recruit" if clear size- or age-dependent bathymetric preferences can be identified.

Historically, spline methods were methods of interpolation, basically interpolating functions between observations (Wahba, 1990; Green and Silverman, 1994). The main issue becomes how to weight measurements at different distances from the prediction point. A common method for such interpolation to estimate a process in one or more dimensions is kriging, which uses a variogram to estimate the process variation, giving the weights to be used (Wahba, 1990; Mardia et al., 1996). Smoothing splines have been popularized through generalized additive models (GAMs; Hastie and Tibshirani, 1990). These smoothing splines do not need to go through the data points themselves (nor does kriging with a "nugget effect"). The virtue of GAMs and kriging methods over parametric methods such as generalized linear models (GLMs) lies largely in their flexibility, one no longer needing to specify a functional relationship which has to be valid across the entire space. Instead, GAMs require specification of the degrees of freedom (or knots), which specify how flexible the surface can be. A tps is a recent method in the flora of methods, and is particularly well suited when one cannot easily specify this flexibility a priori. Instead, a smoothness criterion is used (minimization of a penalty function which measures the amount of "wiggliness", controlling the trade-off between data fitting and smoothness), along with cross-validation. On the negative side, it is not obvious how one should conduct formal significance testing, so the method should be considered data analysis rather than formal statistical inference. Here, we were not interested in formally modelling the bathymetric migration of juvenile hake, which can be more appropriately approached with other regression techniques (i.e. a GLM), but we wanted to investigate variations in bathymetric preference and segregation during the first years of life.


   Material and methods
Top
 Introduction
 Material and methods
Results
 Discussion
 References
 
Our study area covered the continental shelf and the upper slope of the central Tyrrhenian Sea, from Cape Argentario to the mouth of the Garigliano River (Figure 1).


Figure 1
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  		Figure 1. Map of the study area.

 
Data were collected in September/October during the Italian national trawl survey project (GRUND), from 1998 to 2004 (no survey was conducted in 1999). The randomized stratification scheme for the surveys was based on five bathymetric strata (10–50, 51–100, 101–200, 201–500, and 501–700 m; for more detail, see Relini, 1998). The hauls, selected randomly, were fixed in the first year and repeated in the following years. Hauls from the first three strata and part of the fourth, up to 330 m deep, were considered for this analysis, to include both the continental shelf and the upper slope, where immature hake are mainly distributed (Table 1).


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  		Table 1. Hauls, mean depth, and number of hake caught in the length range 5–22 cm for each year analysed.

 
The number of hake juveniles analysed each year ranged between 3582 and 24 606, respectively, in 2003 and 1998 (length distributions are shown in Table 2). Indices of abundance were calculated from each haul as the number of fish per swept area (n km–2) for 1-cm length classes in the length range 5–22 cm; this interval was selected because the focus of the study was on the first year of hake life (Garcia-Rodriguez and Esteban, 2002; Morales-Nin and Moranta, 2004; Belcari et al., 2006). The abundance values by haul were averaged by 10-m depth classes to obtain a depth x length matrix of fish density, because the mean is more appropriate than the sum for density data. Finally, to reduce the large differences in the number of fish in different length classes, depth–frequency distributions by 1-cm length class were calculated by normalizing to 1 any column of the depth x length matrix, so obtaining a relative depth preference index (Yl,d) as follows:


Formula

where N is the number of fish per swept area, by length l and depth d.


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  		Table 2. Number of hake analysed by length class and year.

 
tps were used to smooth a surface over the depth preference matrix for each year separately. The Thin plate splines function, implemented in the fields package of R (freely available at http://www.r-project.org/), fits a tps surface to data spaced irregularly. The spline interpolator is based on the kriging estimator, assuming the covariance to be the radial basis function. The smoothing parameter is selected by generalized cross-validation. The function assumed an additive model:


Formula

where f(l, d) is a two-dimensional surface defined by the independent variables length and depth.

This non-parametric method of regression has been used extensively in a variety of specific applications of fish biology, such as morphometrics (e.g. Loy et al., 1999; Valentin et al., 2002), and in the study of spatial and abundance data (e.g. Wood and Horwood, 1995; Augustine et al., 1998; Fox et al., 2000; Howell and Kobayashi, 2006).

Given the resulting bivariate surface, fitted to length and depth, univariate functions describing density as a function of either depth or length can be constructed by alternatively eliminating the other variable. This method, also referred as density profiling, takes the maximum value of the surface for each fixed length, and plots these maxima as a function of length (and similarly for depth). The modes of the original surface are clearly reflected as modes in the univariate plots. The lower values in the density profile with respect to fish size represent the length at which the lower bathymetric preference is observed. Conversely, the minima in the density–depth plots indicate the depth at which the two length groups are better discriminated.


   Results
Top
 Introduction
 Material and methods
 Results
Discussion
 References
 
Two distinct depth–length clusters were shown in all annually estimated surfaces (Figure 2). The clusters had different shape and value in the density peak, but described a common situation throughout the time-series: small hake below a certain length were found over the continental slope, and larger hake preferred shallower water over the shelf. The small hake group (total length, TL, <13–16 cm) had the greatest preference for water 170–220 m deep. In some years, the right side of this cluster was skewed towards deeper water (>220 m), and in 2004, the largest length classes of the small hake cluster moved towards the deeper part of the upper slope (280–300 m). The length minima in the length-density profile plots were found in the 13.2–15.8 cm length range, in 2000 and 1998. For each year, they represented the length class at which the less marked depth preference was observed. The depth at which the two length classes were better discriminated ranged between 117 and 150 m in 1998 and 2000, respectively.


Figure 2
Figure 2
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  		Figure 2. Density profiles with respect to length and depth and estimated length–depth surfaces, 1998–2004.

 
The larger hake length class persisted on the continental shelf with a preference for water 70–100 m deep, especially when fish reached 18–20 cm TL.

A sharp depth change distinguished the two length classes identified in most years except 2000 and 2003, when depth migration appeared to have been more gradual. However, two clusters were found during 2000 and 2003 at 13.2 cm TL and 150 m depth and at 14.1 cm and 125 m, respectively, but the estimated surfaces showed a progressive migration towards shallower water for hake of intermediate length (12–17 cm TL).

A significant linear relationship (r = 0.77, p < 0.05) was found between the estimated length and depth of migration (Figure 3). The two clusters were also discriminated by shallower water in years when hake were predicted to migrate at a larger size, as opposed to when the length-at-migration was expected to be smaller. The year 2003 showed the largest residual from the fitted linear model, and hake recruits were smaller than expected or simply more concentrated in shallower water.


Figure 3
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  		Figure 3. Bivariate regression of the estimated length and depth of migration of European hake in the Mediterranean Sea, 1998–2004.

 

   Discussion
Top
 Introduction
 Material and methods
 Results
 Discussion
References
 
Depth is one of the major environmental gradients in marine ecosystems, influencing the vertical pattern of species distribution both in abundance and size (Macpherson and Duarte, 1991; Clain and Rex, 2000; Moranta et al., 2004). The analytical approach fitting a tps over depth–frequency distribution data gave an accurate description of the bathymetric preference of hake during their early years of life. For hake aged 0, two length aggregations were discriminated by the bathymetric distribution. During the period of the study, the ontogenetic migration between these two groups was in the length range 13.2–15.8 cm. We recognized in the small hake group the true recruits, because those fish concentrated in the nursery areas over the upper slope. In contrast, the larger hake group was formed by juveniles that were no longer true recruits because they were widely dispersed over the continental shelf.

Orsi-Relini et al. (2002) found that hake biomass and abundance were affected by depth, but their analysis did not investigate the relationship between depth and length. They observed greatest abundance coinciding with the 100–200-m depth stratum (five depth strata were analysed), where most nursery grounds of hake in the Mediterranean Sea are located. Similar results were found by other authors in different areas and with a variety of spatial analytical approaches (Ardizzone and Corsi, 1997; Abella et al., 2005).

Our results supported the hypothesis that bathymetric changes are related to a change in diet that would coincide with the migration of juvenile hake from nursery areas on the shelf break and upper slope to the mid-shelf (Andaloro et al., 1985; Ardizzone and Corsi, 1997). Carpentieri et al. (2005) observed a clear change in the diet of European hake in the Mediterranean Sea at 15–16 cm TL. Therefore, migration and a changed bathymetric distribution agree with a shift in diet from small planktonic crustaceans (Euphausiacea) to small pelagic fish such as Sardina pilchardus and Engraulis encrasicolus, which inhabit the coastal continental shelf and form schools usually deeper than 25 m (Fischer et al., 1987). Moreover, such trophic shifts coincide with an increase in the area of the inner ear of hake responsible for the detection and location of objects, which takes place approximately at the same critical size of 14–15 cm (Lombarte and Popper, 1994); this sensorial area could be important in the location of mobile prey such as fish.

Although there are noticeable differences in recruitment strength (Bartolino et al., in press) and growth rate (Morales-Nin and Moranta, 2004) between years and seasons in the central and western Mediterranean, the distribution of hake nurseries was stable and consistent in both space and time, within and throughout years (Abella et al., 2005). As a result, nursery areas were identified mainly along the shelf break and the upper slope. This supports the assumption that spatial and consequently the bathymetric distribution of hake recruits is relatively independent of the time of the year. Therefore, the bathymetric distribution of hake during their first year of life is strongly related to fish size, with a clear depth preference for each length class, and the predicted surfaces can be considered to be a good approximation of the ontogenetic migration hake undertake from the nursery areas to the continental shelf.

A negative linear relationship was found between depth and the length at which fish migrate annually. This relationship suggests that recruits migrate before or at smaller size in years in which nursery areas are deeper. This statement is supported by the departure of the year 2003 from the proposed length–depth model and by the thermal anomaly observed in the Mediterranean during that summer (Marullo and Guarracino, 2003). Perhaps, during summer 2003, hake recruits did not grow sufficiently to reach the size at migration predicted by the simple linear model, or maybe nursery areas were located in shallower water. An increase in water temperature, coupled with reduced hydrodynamics and water stagnation, could have had negative effects on the marine production that consequently affected hake recruitment size and growth during summer and autumn of that year (Bartolino et al., in press). It is not clear, however, how the plankton distribution pattern could have been altered by this thermal anomaly, although it could have influenced the availability and distribution of prey and consequently the growth and bathymetric distribution of hake recruits.

The results of this study suggest that the tps approach is a successful descriptive one to study the bathymetric preference of juvenile European hake. It allowed is to investigate the depth distribution of fish by length during their first year of life, revealing the existence of two distinct bathymetric phases separated by a migration at 12–16 cm TL. The development of an objective and easily applicable protocol to define the length that discriminates pre- and post-migration phases from nurseries could have useful management applications in fisheries science. It could also represent an approach for a more natural and widely acceptable definition of which fish, although still juveniles, cannot be described as recruits, because they are no longer concentrated in nursery areas on the shelf break and slope.

Further developments of this approach will focus on how fast fish move between slope and shelf, and which density-dependent and/or environmental processes can explain the annual variations in length at migration. We believe too that the analytical approach proposed here could be productively applied to explore the depth distribution by length of other phases of the life cycle of hake and other species.


   Acknowledgements
 
We thank two referees for their comments on the submitted manuscript, which helped improve the presentation considerably.


   References
Top
 Introduction
 Material and methods
 Results
 Discussion
 References
 

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