2010
DOI: 10.3354/ab00301
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Shell morphology changes in the scallop Aequipecten tehuelchus during its life span: a geometric morphometric approach

Abstract: Shell morphology is a central feature of bivalve biology in fields such as taxonomy, evolution, and functional anatomy. When allometric shell growth occurs, traditional morphometric methods usually fail to provide robust, size-free shape variables. We used a more integrative approach, geometric morphometrics, to examine ontogenetic changes in the shell of the scallop Aequipecten tehuelchus. A single cohort that settled early in 2004 at a site in San José Gulf in northern Patagonia, Argentina, was sampled at ir… Show more

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Cited by 27 publications
(22 citation statements)
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“…Despite the clear differences in life style between juveniles and adults regarding burial ability, feeding habits and food availability, D. chilensis shell shape remains constant over lifetime both in the river and in the lake population. In contrast, shell shape changes related to changing behavioural patterns throughout life have been reported for several species (Demayo, Cabacaba, & Torres, 2012;Guarneri et al, 2014;Márquez, Amoroso, Gowland Sainz, & Van der Molen, 2010).…”
Section: Discussionmentioning
confidence: 98%
See 1 more Smart Citation
“…Despite the clear differences in life style between juveniles and adults regarding burial ability, feeding habits and food availability, D. chilensis shell shape remains constant over lifetime both in the river and in the lake population. In contrast, shell shape changes related to changing behavioural patterns throughout life have been reported for several species (Demayo, Cabacaba, & Torres, 2012;Guarneri et al, 2014;Márquez, Amoroso, Gowland Sainz, & Van der Molen, 2010).…”
Section: Discussionmentioning
confidence: 98%
“…Recently, geometric morphometric analysis has been increasingly employed in bivalve studies with different objectives: recognition of phenotypic fishery stocks (Márquez, Robledo, Escati Peñaloza, & Van der Molen, 2010;Palmer, Pons, & Linde, 2004;Rufino et al, 2012), paleoenvironmental and paleoclimate reconstruction (Aguirre, Perez, & Sirch, 2006;Aguirre, Richiano, Álvarez, & Farinati, 2016;Gordillo, Márquez, Cárdenas, & Zubimendia, 2011), and analysis of evolutionary processes (Schneider, Fürsich, Schulz-Mirbach, & Werner, 2010;Sherratt, Alejandrino, Kraemer, Serb, & Adams, 2016;Tang & Pantel, 2005). In addition, geometric morphometrics have been used to study ontogenetic shape changes (Márquez, Amoroso, Gowland Sainz, & Van der, 2010) and to evaluate the invasive success of introduced freshwater species (Sousa et al, 2007). Among geometric morphometrics techniques, landmarks together with semilandmarks have been successfully applied recently in bivalve studies (Leyva-Valencia et al, 2012;Morais et al, 2013).…”
mentioning
confidence: 99%
“…A number of studies deal with geometric morphometric analyses within species (Zelditch & Fink 1995, Rosas & Bastir 2002, M arquez et al 2010) and among species (Penin & Berge 2001, Rosenberg 2002 Kosnik et al 2006, Ampili & Shiny Sreedhar 2015 and to examine pattern of shell development (Roopnarine 2001, Tang & Pantel 2005. To facilitate the discrimination between Ruditapes philippinarum and Ruditapes decussatus, a non-invasive morphometric method based on the elliptic Fourier analyses of the external shell shape was recently suggested (Costa et al 2008(Costa et al , 2010.…”
Section: Introductionmentioning
confidence: 99%
“…Overall and localized fluctuating asymmetries were determined by subjecting the paired landmark coordinates to Procrustes ANOVA following the method of Klingenberg (1998) and using the SAGE software version 1.0 [17]. Landmark-based geometric morphometric analysis was used to describe the body shape variation that exists among Ambassis interrupta fish samples from Masao River, Butuan City, Philippines.…”
Section: Fluctuating Asymmetry Analysismentioning
confidence: 99%
“…The differences between population means, or the deviation an individual from its population mean are visualized in at least two ways by the landmark data. An alternative way to inspect the variability of landmark points in tangent space is to run a principal component analysis (PCA) on the tangent coordinates derived from Procrustes analysis [17]. The result of the Principal Component Analysis (PCA) is shown in Table III.…”
Section: Fluctuating Asymmetry Analysismentioning
confidence: 99%