Differences in absolute and relative growth between two shell forms of Pinna nobilis (Mollusca: Bivalvia) along the Tunisian coastline

Journal of Sea Research 66 (2011) 95–103

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Journal of Sea Research j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / s e a r e s

Differences in absolute and relative growth between two shell forms of Pinna nobilis (Mollusca: Bivalvia) along the Tunisian coastline Lotfi Rabaoui a,⁎, Sabiha Tlig-Zouari a, Stelios Katsanevakis b, Walid Belgacem a, Oum Kalthoum Ben Hassine a a b

Research Unit of Biology, Ecology and Parasitology of Aquatic Organisms, Department of Biology, Faculty of Science of Tunis, University Campus, El Manar 2092, Tunis, Tunisia Institute of Marine Biological Resources, Hellenic Centre for Marine Research, 46.7 km Athens-Sounio, 19013 Anavyssos, Greece

a r t i c l e

i n f o

Article history: Received 3 February 2011 Received in revised form 6 April 2011 Accepted 2 May 2011 Available online 24 May 2011 Keywords: Pinna nobilis shell morphometry Information theory approach Tunisia

a b s t r a c t This study investigated the absolute and relative growth patterns of the fan mussel Pinna nobilis along the Tunisian coastline, taking into consideration both the variability among different areas and between the two shell forms “combed” and “straight and wide”. Five subpopulations of the species were sampled, one from northern, two from eastern and two from southern Tunisia. Various assumptions on the growth patterns were tested based on an information theory approach and multi-model inference. For absolute growth, the assumption of different growth patterns between the two shell forms of P. nobilis and no difference among subpopulations was the most supported by the data. For the same age, “straight and wide” individuals gained on average greater lengths than the “combed” individuals. The absolute growth of the species was found to be asymptotic and the logistic model was the one most supported by the data. As for the relative growth, apart from the classical allometric model Y = aX b, more complicated models of the form lnY = f(lnX) that either assumed non-linearities or breakpoints were tested in combination with assumptions for possible differences between the two forms and among subpopulations. Among the eight studied relationships between morphometric characters, the classical allometric model was supported in only two cases, while in all other cases more complicated models were supported. Moreover, the assumption of different growth patterns between the two forms was supported in three cases and the assumption of different growth patterns among subpopulations in four cases. Although precise relationships between the morphometric plasticity of the fan mussel and environmental factors have not been proven in this paper, local small scale constraints might be responsible of the different growth patterns observed in the same locality. A possible co-action of genetic factors should be evaluated in the future. Crown Copyright © 2011 Published by Elsevier B.V. All rights reserved.

1. Introduction The fan mussel Pinna nobilis Linnaeus, 1758 is endemic to the Mediterranean Sea. It is one of the largest bivalves of the world, attaining anterio-posterior lengths up to 120 cm (Zavodnik et al., 1991) and may live over 20 years (Galinou-Mitsoudi et al., 2006). It has very variable recruitment (Butler et al., 1993), and occurs at depths between 0.5 and 60 m, mostly in soft bottom areas overgrown by meadows of the seagrasses Posidonia oceanica, Cymodocea nodosa, Zostera marina or Zostera noltii (Zavodnik et al., 1991) but also in bare sandy bottoms (Katsanevakis, 2006a, 2007). The populations of P. nobilis have been greatly reduced during the past few decades as a result of recreational and commercial fishing for food, use of its shell for decorative purposes, and incidental killing by trawling and anchoring (García-March et al., 2007a; Katsanevakis, 2009; Rabaoui

⁎ Correspondence. Tel.: + 216 97 754 019. E-mail address: [email protected] (L. Rabaoui).

et al., 2008; Rabaoui et al., 2010). In the European Union, it has been listed as an endangered species and is under strict protection according to the European Council Directive 92/43/EEC. However, it still suffers illegal fishing (Katsanevakis, 2009). The shell of Pinna nobilis is characterized by important morphological differences not only between juveniles and adults but also among adult specimens. This morphological variability was enounced since the first description of the species. Czihak and Dierl (1961) reported – based on the description done by Linnaeus, 1758 – that the width and color of P. nobilis shell depend on the age of the animal and the environment where it lived: young fan mussels, sized between 20 and 30 cm, used to be named as P. nobilis, while the largest (with a size of about 60 cm) which are thicker and darker used to be named as P. squamosa. These authors described two different forms of P. nobilis shell, crassa and papyracea. In the former shell form, the axis of the shell bending (flexion) is in the ventral part, the shell is strong, dark brown with a maximum width of approximately 20 cm. The latter shell form is not bent on the ventral side, the shell is thinner with a strong scaling of the distal part, an ocher brown color, and a maximum

1385-1101/$ – see front matter. Crown Copyright © 2011 Published by Elsevier B.V. All rights reserved. doi:10.1016/j.seares.2011.05.002

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on an information theory approach (Burnham and Anderson, 2002), several growth models were defined a priori based on biological assumptions, and it was investigated whether important differences in growth patterns existed between the two shell forms “combed” and “straight and wide” as well as among the northern, eastern, and southern subpopulation groups. 2. Material and methods 2.1. Sampling

Fig. 1. Location of the five populations of the present study. N Bizerta lagoon, E1 Stah Jaber, E2 Kerkennah Island, S1 El Bibane lagoon, S2 El Ketef.

width exceeding 30 cm (Czihak and Dierl, 1961). The most important difference of the two forms is the ventral curvature, but it is difficult to distinguish the differences in color, distal peeling or outer edge (García-March, 2005). Thereafter, García-March and Márquez-Aliaga (2006) noted that the morphologic types of the fan mussel are more diverse and they distinguished three main morphologic types, i.e. “straight and wide”, “straight and narrow”, and “combed”. The latter authors reported also that these forms can be jointly observed in the same population and bathymetric range. During a study on the distribution and growth of P. nobilis along the Tunisian coastline (Rabaoui et al., 2007, 2008, 2010), the coexistence of the different shell forms, in particular “combed” and “straight and wide” ones, was observed. The distinction between the two latter forms is possible and clear not only in adult specimens but also in juveniles. Several studies were published on the growth of P. nobilis (e.g. Galinou-Mitsoudi et al., 2006; García-March et al., 2007a; Moreteau and Vicente, 1982; Rabaoui et al., 2007; Richardson et al., 1999, 2004; Šiletić and Peharda, 2003), but none of them took into consideration the existence of distinct shapes of P. nobilis shell. To better study the absolute and relative growth patterns of the species, the morphometric variability should be taken into account in the analysis. Such an approach was followed in the present study to investigate the absolute and relative growth patterns of P. nobilis specimens from five sites of the northern, eastern, and southern Tunisian coasts. Based

A total of 171 specimens of P. nobilis were collected from five sites located along the Tunisian coastline, one from the North (Bizerta lagoon “N”: 33 individuals), two from the East (Stah Jaber “E1”: 33 individuals; Kerkannah Island “E2”: 35 individuals) and two from the South (El Bibane Lagoon “S1”: 39 individuals; El Ketef “S2”: 31 individuals) (Fig. 1). At each site, specimens were randomly collected by SCUBA diving at depths between 2 and 6 m; the main characteristics of each sampling site were recorded (Table 1). The shells were classified into “combed” and “straight and wide” forms based on García-March (2005) and particularly the ventral curvature which is the most important difference between the two forms (García-March, 2005). The morphometric difference between the latter two forms is given in Fig. 2. Note that no specimens with “straight and narrow” shell shape (the third category considered by García-March (2005)) were encountered in the sample. On each specimen, nine morphometric characters were measured as in Fig. 3. Age was determined by counting the number of adductor-muscle scar rings on the shells. Because the first year's muscle-scar ring is either absent or inconspicuous (Richardson et al., 1999), the age was estimated as the number of rings plus 1. 2.2. Absolute growth Several models have been proposed to estimate the mean individual growth in a population; some of these are based on purely empirical relationships, whereas others have a theoretical basis and are arrived at by differential equations that link the anabolic and catabolic processes. The most studied and commonly applied model among all the length–age models is the von Bertalanffy (1938) growth model (VBGM). However, the practice of a priori using VBGM has often been criticized (e.g. Katsanevakis and Maravelias, 2008), and for many aquatic species other models like Gompertz (1825) or the logistic model (Ricker, 1975) better describe absolute growth. All the above models assume asymptotic growth but some aquatic invertebrates do not seem to grow asymptotically (e.g. Jackson and Choat, 1992) and non-asymptotic models, like the power model, have been proposed in these cases. A set of 16 candidate models were used to model absolute growth (i.e. the relationship between L and age t) of P. nobilis in the Tunisian coastline (gi, i = 1 to 16), (Table 2). In models g1 to g4 it was assumed that there was no difference in absolute growth among the subpopulations or between the two shell morphotypes (“combed” and “straight and wide”), i.e. all sampled individuals had common growth parameters. In models g5 to g8 it was assumed that the growth

Table 1 Environmental features of the sampling localities, total number of collected pinnids, and number (and percentages) of “combed” and “straight and wide” shell forms in each sample. Population

N

E1

E2

S1

S2

Habitat (Lagoon/Open sea) Dominant substratum Dominant vegetation Hydrodynamics Total number of collected pinnids Number of “combed” shells (%) Number of “straight and wide” shells (%)

Lagoon Sandy–muddy + biodetritus Cymodocea nodosa Moderately exposed 33 24 (72.7%) 9 (27.3%)

Open sea Sandy Posidonia oceanica Exposed 33 12 (36.4%) 21 (63.6%)

Open sea Sandy Cymodocea nodosa–Posidonia oceanica Exposed 35 16 (45.7%) 19 (54.3%)

Lagoon Sandy–muddy Cymodocea nodosa Moderately exposed 39 30 (76.9%) 9 (23.1%)

Open sea Sandy Cymodocea nodosa Exposed 31 23 (74.2%) 8 (25.8%)

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Fig. 2. Different shapes of Pinna nobilis, encountered during the present study. A and B, “straight and wide” shell form; C and D, “combed” shell form; E and F, juvenile “straight and wide” and “combed” specimens respectively (scale bar 2 cm).

parameters differed between the two shell forms but not among subpopulations. In models g9 to g12 it was assumed that the growth patterns differed between the northern (N), eastern (E1 and E2), and southern (S1 and S2) subpopulations but not between the two shell morphotypes. In models g13 to g16, it was assumed that the growth parameters differed both among subpopulations and between shell forms. The VBGM L(t) = L∞(1 − e − k1(t − t1)) was used in models g1, g5, g9, and g13, the Gompertz growth model L(t) = L∞ exp(− e − k2(t − t2)) in g2, g6, g10, and g14, the Logistic model L(t) = L∞(1 + e − k3(t − t3)) − 1 in g3, g7, g11, and g15, and the Power model L(t) = c0 + c1 ⋅ t c2 in g4, g8, g12, and g16. L∞ (asymptotic length), ki, ti, and ci are estimable regression parameters. Details on the underlying principles, definition of parameters appearing in the equations, and mathematical description of the corresponding curves are given in Katsanevakis (2006b).

2.3. Relative growth Growth is often accompanied by changes in proportion as well as in size, the phenomenon of relative or allometric growth. The most extensively used model for relative growth during ontogeny is the allometric equation Y= aXb (Huxley, 1932), where the size of a part of the body Y is related to a reference dimension X. The exponent b is a measure of the difference in the growth rates of the two parts of the body. However, the classic allometric equation frequently fails to adequately fit the data and more complex models of the form lnY= f (lnX) should be used (Katsanevakis et al., 2007). The reason might be either the existence of nonlinearity or the existence of breakpoints in f. Table 2 The set of candidate models used to model the absolute growth. k is the total number of estimable parameters (regression parameters plus 1). Model Description g1 g2 g3 g4 g5 g6 g7 g8 g9 g10 g11 g12

Fig. 3. Morphometric characters measured in P. nobilis specimens. L total size, D distance from the top of the shell hinge to the top of the valve, A1 maximum width of the shell, A2 width of the shell in the inflection point, M1 perpendicular distance from the center of the maximum width A1 to the posterior border of the shell, M2 perpendicular distance from the center of the width A2 to the posterior border of the shell, T thickness of the shell measured at the thickest point, Hp distance from where T is measured to the most posterior part of the shell, Pm distance from the newest scar of the anterior adductor muscle to the most anterior part of the shell.

g13 g14 g15 g16

Bertalanffy, common parameters for the five populations + common parameters for the two shell forms Gompertz, common parameters for the five populations + common parameters for the two shell forms Logistic, common parameters for the five populations + common parameters for the two shell forms Power, common parameters for the five populations + common parameters for the two shell forms Bertalanffy, common parameters for the five populations + different parameters for the two shell forms Gompertz, common parameters for the five populations + different parameters for the two shell forms Logistic, common parameters for the five populations + different parameters for the two shell forms Power, common parameters for the five populations + different parameters for the two shell forms Bertalanffy, different parameters for north, east, and south populations groups + common parameters for the two shell forms Gompertz, different parameters for north, east, and south populations groups + common parameters for the two shell forms Logistic, different parameters for north, east, and south populations groups + common parameters for the two shell forms Power, different parameters for north, east, and south populations groups + common parameters for the two shell forms Bertalanffy, different parameters for north, east, and south populations groups + different parameters for the two shell forms Gompertz, different parameters for north, east, and south populations groups + different parameters for the two shell forms Logistic, different parameters for north, east, and south populations groups + different parameters for the two shell forms Power, different parameters for north, east, and south populations groups + different parameters for the two shell forms

k 4 4 4 4 7 7 7 7 10 10 10 10 19 19 19 19

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The existence of breakpoints in allometric data has been recognized since the allometric equation was first proposed (Huxley, 1932). Such changes in the growth trajectories of morphological characters during ontogeny are a potentially useful source of information as they may be caused by marked events in the life history of the species (e.g. maturity) or fast ecological change, and should not be overlooked. The allometric growth of D, A1, A2, M1, M2, T, Hp, and Pm in relation to L was investigated. Twelve candidate models (fi, i = 1 to 12) for the relationship lnY = f(lnL) were fitted to the ln-transformed data, where Y is any of the measured characters (Table 3). In models f1 to f3, it was assumed that there was no difference in relative growth among subpopulations or between the two shell morphotypes. In models f4 to f6 it was assumed that the growth parameters differed between the two shell forms but not among subpopulations. In models f7 to f9 it was assumed that the growth patterns differed between the northern (N), eastern (E1 and E2), and southern (S1 and S2) subpopulations but not between the two shell forms. In models f10 to f12 it was assumed that the growth parameters differed both among the northern, eastern, and southern subpopulations and between the two shell forms. The linear model (L), ln Y = a1 + b1 ln L, was used in f1, f4, f7, and f10, the quadratic model (Q), ln Y = a1 + b1 ln L + b2(ln 8 L) 2, in f2, f5, f8, and f11, and the broken< a + b lnL; L≤B 1 1 , in f3, stick model (BS), lnY = : a1 + ðb1 −b2 Þ lnB + b2 lnL; L N B f6, f9, and f12 (Table 3). In the current context, the allometric exponent b was generalized to mean the first derivative of f with respect to lnL, i.e.b= f′(ln L), according to Katsanevakis et al. (2007). The L model is the classical allometric equation, assuming that allometry does not change as body size increases (b = b1 = constant). The Q model assumes that a non-linearity exists in the relationship of lnY and lnL and that b changes continuously with an increasing body size (b= b1 + 2b2lnL). The BS model assumes a marked morphological change at a specific size of L = B and represents two straight line segments with different slopes that intersect at L = B. 2.4. Model fitting–model selection–MMI The candidate models gi for absolute growth were fitted with nonlinear least squares with iterations by means of Marquardt's algorithm, Table 3 The set of candidate models used to model the relative growth. k is the total number of estimable parameters (regression parameters plus 1). Model Description f1 f2 f3 f4 f5 f6 f7 f8 f9 f10 f11 f12

L model, common parameters for the five populations + common parameters for the two shell forms Q model, common parameters for the five populations + common parameters for the two shell forms BS model, common parameters for the five populations + common parameters for the two shell forms L model, common parameters for the five populations + different parameters for the two shell forms Q model, common parameters for the five populations + different parameters for the two shell forms BS model, common parameters for the five populations + different parameters for the two shell forms L model, different parameters for north, east, and south populations groups + common parameters for the two shell forms Q model, different parameters for north, east, and south populations groups + common parameters for the two shell forms BS model, different parameters for north, east, and south populations groups + common parameters for the two shell forms L model, different parameters for north, east, and south populations groups + different parameters for the two shell forms Q model, different parameters for north, east, and south populations groups + different parameters for the two shell forms BS model, different parameters for north, east, and south populations groups + different parameters for the two shell forms

k

assuming additive error structure. The L model was fitted with simple linear regression, whereas polynomial regression was used for the Q model. To fit the BS model, the breakpoint B was allowed to vary between the minimum and maximum value of L with a sufficiently small step. For each value of the breakpoint, two separate lines were fitted with linear regression to the data before and after the breakpoint (connected lines at the breakpoint) and the corresponding residual sum of squares (RSS) was calculated as the sum of the two RSS for the two lines; this was done automatically in MS-Excel by what-if analysis (one variable data table). The value of the breakpoint that gave the minimum RSS was found and the corresponding model parameters were estimated. The small-sample, bias-corrected form AICc (Hurvich and Tsai, 1989) of the Akaike information criterion (Akaike, 1973; Burnham and Anderson, 2002) was used for model selection. The model with the smallest AICc value (AICc, min) was selected as the ‘best’ among the models tested. The AICc differences Δi = AICc,i − AICc,min were computed over all candidate models gi. According to Burnham and Anderson (2002), models with Δi N 10 have essentially no support and might be omitted from further consideration, while models with Δi b 2 have substantial support. To quantify the plausibility of each model, given the data and the set of candidate models, the ‘Akaike weight’ wi of each model was calculated, where wi = 5 expð−0:5Δi Þ . The ‘Akaike ∑ expð−0:5Δk Þ

k=1

weight’ is considered as the weight of evidence in favor of model i being the actual best model of the available set of models (Akaike, 1983; Buckland et al., 1997; Burnham and Anderson, 2002). Akaike weights may be interpreted as a posterior probability distribution over the model set. To obtain more robust inferences, the final results were based on model-averaging the response variable using Akaike weights, rather than simply on the ‘best’ model (Burnham and Anderson, 2002). When the data support evidence of more than one model, model averaging the predicted response variable across models is advantageous in reaching a robust inference that is not conditional on a single model. Rather than estimating parameters from only the ‘best’ model, parameter estimation can be made from several or even from all the models considered. This procedure is termed multi-model inference (MMI) and has several theoretical and practical advantages (Burnham and Anderson, 2002). 3. Results 3.1. Sample The present study revealed the presence of the two shell forms of P. nobilis, “combed” and “straight and wide”, along the Tunisian

3 4 5 5 7 9 7 10 13 13 19 25

Table 4 Values of residual sum squares (RSS), the small sample bias corrected form of Akaike information criterion (AICc), AICc distances (Δi) and the ‘Akaike weights’ (wi) for the 16 models gi of absolute growth. The models with Δi b 4 are given in bold. Model

RSS

K

AICc

Δi

wi

g1 g2 g3 g4 g5 g6 g7 g8 g9 g10 g11 g12 g13 g14 g15 g16

481.6 447.5 441.3 506.9 368.9 333.4 328.3 389.0 434.6 359.4 358.2 383.4 340.9 292.8 297.9 297.9

4 4 4 4 7 7 7 7 10 10 10 10 19 19 19 19

184.9 171.0 168.3 194.7 140.7 121.4 118.5 150.8 178.4 142.4 141.7 154.6 153.5 124.6 127.9 127.9

66.4 52.4 49.8 76.1 22.1 2.9 0.0 32.3 59.9 23.8 23.2 36.1 35.0 6.1 9.4 9.4

0.0% 0.0% 0.0% 0.0% 0.0% 17.9% 77.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 3.6% 0.7% 0.7%

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scars were observed in the sampled shells. The size of “combed” shells ranged between 10.2 and 49.1 cm, while “straight and wide” ones had a size range between 17.8 and 51.8 cm. “Combed” shell form prevailed in the samples from N, S1, and S2, while “straight and wide” form prevailed in the samples from E1 and E2 (Table 1).

3.2. Absolute growth

Fig. 4. Size-at-age raw data showing the distinction between the two shell forms “combed” and “straight and wide”. The data were jittered by adding a small random quantity to the horizontal coordinate to separate overplotted points and have a better visualization of the dataset.

coastline. “Combed” and “straight and wide” forms were found coexistent in each of the five sampled subpopulations. The total sample (171 shells) consisted of 105 “combed” and 66 “straight and wide” shells (Table 1). It is worth noting that no breaking or fracture

For each candidate model, RSS, AICc, Δi, and wi were calculated (Table 4). Model g7 was the best model, g6 was also supported, while all other models had essentially less or no support. The models that assumed common (g1 to g4) and different absolute growth parameters only among northern, eastern and southern subpopulation groups (g9 to g12) had a sum of Akaike weights of 0%, thus these assumptions had no support by the data. The models that assumed differences in growth parameters as well among northern, eastern, and southern subpopulation groups as between the two shell forms (g13 to g16) had a sum of Akaike weights of 5.0%, while models assuming that growth parameters differed only among the two shell forms (g5 to g8) had a sum of Akaike weights of 95.0% (Table 4). Hence, the data indicated that the assumption of different growth parameters among the two forms “combed” and “straight and wide” but no differences in absolute growth among subpopulations is the most plausible. The

Table 5 Values of AICc, AICc differences (Δi) and of the ‘Akaike weights’ wi for the twelve models fi of the measured morphometric characters. For each character, values of wi corresponding to models with Δi b 4 are given in bold. Model

D = f(L)

A1 = f(L)

A2 = f(L)

M1 = f(L)

M2 = f(L)

T = f(L)

Hp = f(L)

Pm = f(L)

AICc f1 f2 f3 f4 f5 f6 f7 f8 f9 f10 f11 f12

− 842.94 − 840.85 − 849.78 − 864.68 − 870.66 − 875.13 − 863.51 − 862.96 − 865.77 − 877.34 − 868.36 − 869.44

− 835.41 − 840.50 − 844.48 − 993.25 − 998.55 − 1004.12 − 858.69 − 855.93 − 856.48 − 980.20 − 994.62 − 973.09

− 883.38 − 890.23 − 903.06 − 921.05 − 926.17 − 933.99 − 889.92 − 921.15 − 935.87 − 942.43 − 973.94 − 959.18

− 957.18 − 990.88 − 1047.55 − 966.04 − 1011.13 − 1042.62 − 990.57 − 1037.29 − 1052.67 − 997.81 − 1029.48 − 1023.80

− 828.39 − 944.53 − 1094.50 − 845.97 − 973.82 − 1089.37 − 838.55 − 1017.39 − 1117.90 − 874.75 − 1018.99 − 1092.65

− 850.73 − 879.83 − 889.94 − 854.31 − 878.08 − 885.74 − 845.72 − 879.28 − 888.88 − 847.49 − 875.14 − 874.80

− 1325.37 − 1332.53 − 1334.44 − 1326.52 − 1327.25 − 1327.39 − 1319.75 − 1321.19 − 1316.61 − 1310.95 − 1308.59 − 1298.24

− 996.12 − 994.33 − 994.00 − 992.84 − 988.79 − 990.35 − 993.16 − 994.78 − 988.71 − 985.85 − 977.65 − 965.63

Δi f1 f2 f3 f4 f5 f6 f7 f8 f9 f10 f11 f12

34.40 36.49 27.56 12.66 6.67 2.21 13.82 14.38 11.56 0.00 8.97 7.90

168.70 163.62 159.63 10.86 5.56 0.00 145.43 148.19 147.64 23.92 9.50 31.02

90.57 83.72 70.89 52.89 47.77 39.95 84.02 52.79 38.07 31.51 0.00 14.76

95.49 61.79 5.12 86.64 41.54 10.05 62.10 15.38 0.00 54.87 23.19 28.87

289.51 173.38 23.40 271.93 144.08 28.53 279.35 100.52 0.00 243.15 98.91 25.25

39.22 10.11 0.00 35.63 11.87 4.21 44.23 10.67 1.07 42.45 14.80 15.15

9.07 1.91 0.00 7.92 7.19 7.05 14.69 13.25 17.83 23.49 25.85 36.20

0.00 1.78 2.11 3.28 7.33 5.77 2.96 1.34 7.41 10.26 18.47 30.49

wi f1 f2 f3 f4 f5 f6 f7 f8 f9 f10 f11 f12

0.0% 0.0% 0.0% 0.1% 2.5% 23.6% 0.1% 0.1% 0.2% 71.2% 0.8% 1.4%

0.0% 0.0% 0.0% 0.4% 5.8% 93.0% 0.0% 0.0% 0.0% 0.0% 0.8% 0.0%

0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 99.9% 0.1%

0.0% 0.0% 7.1% 0.0% 0.0% 0.6% 0.0% 0.0% 92.2% 0.0% 0.0% 0.0%

0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 100.0% 0.0% 0.0% 0.0%

0.0% 0.4% 58.0% 0.0% 0.2% 7.1% 0.0% 0.3% 34.0% 0.0% 0.0% 0.0%

0.7% 26.1% 67.9% 1.3% 1.9% 2.0% 0.0% 0.1% 0.0% 0.0% 0.0% 0.0%

35.7% 14.6% 12.4% 6.9% 0.9% 2.0% 8.1% 18.2% 0.9% 0.2% 0.0% 0.0%

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equations of the best model (g7) for the two shell forms are the following:

asymptotic growth of the species is favored. The size-at-age raw data and the average model are given in Fig. 4.

  ð−0:275ðt−7:28ÞÞ ðt in yr; L in cmÞ g7 ðstraight and wideÞ : Lðt Þ = 60:4 = 1 + e

3.3. Relative growth

  ð−0:279ðt−7:95ÞÞ ðt in yr; L in cmÞ: g7 ðcombedÞ : Lðt Þ = 62:7 = 1 + e The models assuming non-asymptotic growth (g4, g8, g12, and g16) had a sum of Akaike weights of 0.7%, while the models assuming asymptotic growth (all the rest) had a sum of Akaike weights of 99.3%. Thus, (based on the current set of available models) the assumption of

For each morphometric character and for each model, RSS, AICc, Δi, and wi were calculated (Table 5). The assumption that all subpopulations and shell forms had a common relative growth pattern was substantially supported by the data for three out of eight cases: T (f3 was the best model with an Akaike weight of 58.0%), Hp (f3 was the best model with an Akaike weight of 67.9%) and Pm (f1 was the best model with an Akaike weight of 35.7%). The assumption of different

Fig. 5. Left panel Raw data of the measured morphometric characters in relation to the shell length (L). Right panel Average models of relative growth. N, E and S stand for the northern, eastern and southern populations respectively, while S and C denote the “straight and wide” and “combed” individuals respectively; abbreviations for morphometric characters as in Fig. 2. Symbolization: star NS, open diamond NC, open square ES, open triangle EC, multi SS, open circle SC.

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Fig. 5 (continued).

patterns between the two shell forms but no differences among subpopulations was supported by the data only for A1 (f6 was the best model with an Akaike weight of 93.0%), while the assumption of different patterns among northern, eastern, and southern subpopulations was the best alternative for M1 (f9 was the best model with an Akaike weight of 92.2%) and M2 (f9 was the best model with an Akaike weight of 100.0%). The assumption of different relative growth patterns among both subpopulations and shell forms was supported by the data in the cases of D (f10 was the best model with an Akaike weight of 71.2%) and A2 (f11 was the best model with an Akaike weight of 99.9%). BS model was found to be the most supported by the data in five out of eight cases (A1, M1, M2, T, and Hp). The linear model was the most supported by the data for D and Pm, while the quadratic model

was found to be the best only for A2. The raw data and the average models for all morphometric characters are shown in Fig. 5. 4. Discussion 4.1. Absolute growth Although the existence of different shell forms of P. nobilis was reported before, none of the previous growth studies of the species took into consideration this morphological variability. This is the first study which incorporated in the growth models not only the variability among different subpopulations but also between the two different shell forms “combed” and “straight and wide”. It was

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clearly shown that, at the same age, “straight and wide” individuals reach a higher shell length than “combed” individuals. In fact, during most of the species life, “straight and wide” form is longer than “combed” form (Fig. 4). This can be explained by the fact that individuals having the latter shell form have a more tendency, during their life, to curve ventrally rather than to elongate as “straight and wide” fan mussels do. Thus, studies of absolute growth using lengthat-age data that ignore heterogeneity in growth rates due to morphological variability might reach imprecise estimates or even biased conclusions, especially in comparisons of growth rates among different populations. Had we ignored heterogeneity between the shell forms of the species, i.e. only included g1–g4 and g9–g12 in the set of candidate models, we would have selected g10 and g11 as the best models (based on minimum AICc; Table 4) and thus would have falsely concluded that substantial differences in absolute growth existed among subpopulations. However, this would be because of the different proportions of the two shell forms in the studied subpopulations and not because of ‘real’ differences in growth rates. Caution is needed when shell length is used for growth rate estimations in cases of evident morphological heterogeneity. 4.2. Relative growth The relative growth analysis showed varying patterns either between the two shell forms or among subpopulations, except for T, Hp and Pm which showed common growth parameters both among subpopulations and between shell forms. The support of the assumption of different relative growth parameters among the two shells forms “combed” and “straight and wide”, obtained with A1 could be explained by the fact that at the same shell length, the maximum width is different between the two forms. This founding was already enounced before by Czihak and Dierl (1961) who reported that “straight and wide”-form fan mussels reach a greater shell width than that reached by “combed”-form individuals. Since the two shell forms were encountered coexistent in each of the five subpopulations, the variability in the shell shape of the species could be due to various factors such as the shell orientation in relation to the main current flow direction or the influence of some environmental factors that may change at small-scale such as local hydrodynamics or the vegetation surrounding fan mussels. Combelles et al. (1986) reported a phenomenon of ecomorphosis with juveniles of P. nobilis, pointing out that smooth juveniles where usually found in the meadows, whereas spiny ones where found in bare sediments. The morphologic plasticity of the species could be also related to intrinsic factors related to the biology of the species. In fact, García-March and Márquez-Aliaga (2006) noted that the degree of anterior abrasion and the rate of posterior migration of soft tissues considerably influence the shell form of P. nobilis. Within this context, it was reported that the latter factor is proportional to the deposition of new layers and to shell construction (Yonge, 1953). The process of shell abrasion and reconstruction leads to an effective shell reshaping during ontogeny, which also explains the differences between juvenile and adult forms. But the influence of anterior shell abrasion on shell form means that individuals from the same population and bathymetric range, with the same height but different shape, usually have different ages (García-March and Márquez-Aliaga, 2006). Regarding the variability between the subpopulations, obtained with M1 and M2, this can be due to the variability, at large scale, of the environmental factors such as hydrodynamics and drag forces which are higher on large pinnids (García-March et al., 2007b). Besides, the variability obtained with the latter parameters could be also due to the density of seagrass meadows in which the pinnids are settled. Within this context, it is well known that in very dense and well developed meadows, hydrodynamic forces are exponentially reduced, so that large Pinna's may benefit of a small-scale shelter effect, even in

more exposed habitats. It was reported that P. oceanica leaves sway with water movement (Granata et al., 2001) reducing the drag forces. Morphometric intraspecific variability has been reported for many other bivalve species, e.g. Mytilus edulis (Seed, 1968), Septifer virgatus (Richardson et al., 1995), Mytilus chilensis (Valladares et al., 2010), Anomalocardia squamosa (Roopnarine and Signorelli, 2008), Pisidium subtruncatum (Funk and Reckendorfer, 2008), and Cerastoderma spp. (Brock, 1991; Mariani et al., 2002; Rygg, 1970). This morphometric variability has been attributed to various environmental factors such as temperature, salinity, sediment type, wave exposure, and hydrodynamics activity. In conclusion, the present study confirmed the morphometric plasticity of P. nobilis and revealed the coexistence of two varieties, “combed” and “straight and wide”, within the same habitat. This result seems to reflect that within the same biotope, differing levels of specific factors, e.g. the type of substratum, the orientation of individuals, and the effect of hydrodynamism, might cause such morphological variation. Further analyses to test for fine differences in the distribution of morphotypes in relation to small scale habitat location, ad hoc pairwise comparisons between site-specific factors (e.g. bare sediments vs. vegetated bottoms, muddy vs. coarse sediments, deep buried vs. shallow buried specimens, different shell orientation to wave/currents direction) at constant depth level should be taken into account for future research. A possible co-action of genetic factors should be also evaluated in the future. Acknowledgments The authors are grateful to all persons who helped to ameliorate the quality of the manuscript through their discussions, in particular to Dr. Jose Rafael García-March (University of Valencia, Spain). We also thank the referees who evaluated this paper and contributed to its improvement. References Akaike, H., 1973. Information theory as an extension of the maximum likelihood principle. In: Petrov, B.N., Csaki, F. (Eds.), Proceedings of the Second International Symposium on Information Theory. Akademiai Kiado, Budapest, pp. 267–281. Akaike, H., 1983. Information measures and model selection. Int. Stat. Ins. 44, 277–291. Bertalanffy von, L., 1938. A quantitative theory of organic growth (inquiries on growth laws II). Hum. Biol. 10, 181–213. Brock, V., 1991. An Interdisciplinary Study of Evolution in the Crockles Cardium (Cerastoderma) edule, C. glaucum, and C. lamarcki. Vestjydsk Forlag, Vinderup, Denmark. 7830 pp. Buckland, S.T., Burnham, K.P., Augustin, N.H., 1997. Model selection: an integral part of inference. Biometrics 53, 603–618. Burnham, K.P., Anderson, D.R., 2002. Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach, 2nd edition. Springer, New York. 485 pp. Butler, A.J., Vicente, N., De Gaulejac, B., 1993. Ecology of the pteroid bivalves Pinna bicolor Gmelin and Pinna nobilis L. Mar. Lif. 3, 37–45. Combelles, S., Moreteau, J.C., Vicente, N., 1986. Contribution à la connaissance de l'écologie de Pinna nobilis L. (Mollusque eulamellibranche). Sci. Rep. Port-Cros Nat. Par. 12, 29–43. Czihak, G., Dierl, W., 1961. Pinna nobilis L. eine Prëparationsanleitung. Gustav Fisher Verlag, Stuttgart. 44 pp. Funk, A., Reckendorfer, W., 2008. Environmental heterogeneity and morphological variability in Pisidium subtruncatum (Sphaeriidae, Bivalvia). Int. Rev. Hydrobiol. 93, 188–199. Galinou-Mitsoudi, S., Vlahavas, G., Papoutsi, O., 2006. Population study of the protected bivalve Pinna nobilis (Linnaeus, 1758) in Thermaikos Gulf (North Aegean Sea). J. Biol. Res. 5, 47–53. García-March, J.R., 2005. Aportaciones al conocimiento de la biología de Pinna nobilis Linneo, 1758 (Mollusca: Bivalvia) en el litoral mediterráneo Ibérico. PhD Thesis, Faculty of Biology, Universidad de Valencia, Spain, 332 pp. García-March, J.R., Márquez-Aliaga, A., 2006. Polymorphism and shell reshaping in Pinna nobilis L., 1758: the reliability of shell dimensions for ontogenetic age and population growth rate estimates. Organisms Diversity & Evolution, 6 http://www. senckenberg.de/odes/06-16.htm. Electronic Supplement 16. García-March, J.R., García-Carrascosa, A.M., Peña Cantero, A.L., Wang, Y.G., 2007a. Population structure, mortality and growth of Pinna nobilis Linnaeus, 1758 (Mollusca: Bivalvia) at different depths in Moraira Bay (Alicante, Western Mediterranean). Mar. Biol. 150, 861–871. García-March, J.R., García-Carrascosa, A.M., Perez-Rojas, L., 2007b. Influence of hydrodynamic forces on population structure of Pinna nobilis L., 1758 (Mollusca:

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