Body shape variation and colour change during growth in a protogynous fish

Fruciano, Carmelo; Tigano, Concetta; Ferrito, Venera

doi:10.1007/s10641-011-9968-y

Cited by 20 publications

(13 citation statements)

References 33 publications

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“…When measurement error has precise directions in shape space which can be modeled (even based on a subset of specimens during a preliminary study), it can often be removed from the data. This strategy—which is accomplished by projecting observations to the subspace orthogonal to a given vector in multivariate space (Gharaibeh, ; Valentin, Penin, Chanut, Sévigny, & Rohlf, )—has been fruitfully used on empirical datasets to remove artefactual variation due to position of the head in pictures of human faces (Gharaibeh, ) and body arching in fish (Franchini et al., ; Fruciano, Tigano, & Ferrito, , ; Fruciano, Franchini, Kovacova, et al., ; Ingram, ; Valentin et al., ), as well as variation due to sexual dimorphism (Fruciano et al., ). Similar procedures could also be used to estimate the amount of variation realistically attributable to measurement error.…”

Section: Discussionmentioning

confidence: 99%

Sharing is caring? Measurement error and the issues arising from combining 3D morphometric datasets

Fruciano

Celik

Butler

et al. 2017

Ecology and Evolution

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Geometric morphometrics is routinely used in ecology and evolution and morphometric datasets are increasingly shared among researchers, allowing for more comprehensive studies and higher statistical power (as a consequence of increased sample size). However, sharing of morphometric data opens up the question of how much nonbiologically relevant variation (i.e., measurement error) is introduced in the resulting datasets and how this variation affects analyses. We perform a set of analyses based on an empirical 3D geometric morphometric dataset. In particular, we quantify the amount of error associated with combining data from multiple devices and digitized by multiple operators and test for the presence of bias. We also extend these analyses to a dataset obtained with a recently developed automated method, which does not require human‐digitized landmarks. Further, we analyze how measurement error affects estimates of phylogenetic signal and how its effect compares with the effect of phylogenetic uncertainty. We show that measurement error can be substantial when combining surface models produced by different devices and even more among landmarks digitized by different operators. We also document the presence of small, but significant, amounts of nonrandom error (i.e., bias). Measurement error is heavily reduced by excluding landmarks that are difficult to digitize. The automated method we tested had low levels of error, if used in combination with a procedure for dimensionality reduction. Estimates of phylogenetic signal can be more affected by measurement error than by phylogenetic uncertainty. Our results generally highlight the importance of landmark choice and the usefulness of estimating measurement error. Further, measurement error may limit comparisons of estimates of phylogenetic signal across studies if these have been performed using different devices or by different operators. Finally, we also show how widely held assumptions do not always hold true, particularly that measurement error affects inference more at a shallower phylogenetic scale and that automated methods perform worse than human digitization.

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Section: Discussionmentioning

confidence: 99%

Sharing is caring? Measurement error and the issues arising from combining 3D morphometric datasets

Fruciano

Celik

Butler

et al. 2017

Ecology and Evolution

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“…Biologically irrelevant shape variation due to dorso‐ventral arching of the fish body was modelled in this study – using a random subset of ten specimens – as a shape change vector and then removed from the data by projection to the multivariate subspace orthogonal to such vector as described by Valentin et al . () and later applied in multiple studies of fish body shape (Fruciano et al ., , ; Franchini et al ., ). To remove the allometric shape variation, a multivariate regression of shape variables on centroid size was carried out in MorphoJ (Klingenberg, ) and regression residuals were used in subsequent analyses.…”

Section: Methodsmentioning

confidence: 99%

“…). To minimize digitization error, each of the 188 specimens was digitized three times using TpsDig (Rohlf, ), and then the coordinates of each point were averaged across the three digitizations (Fruciano, Tigano & Ferrito, , ). The configurations of points thus obtained were then subjected to a generalized Procrustes analysis with sliding of semilandmarks (Bookstein, ) in tpsRelw 1.49 (Rohlf, ) using minimization of the squared Procrustes distance as the sliding criterion (Perez, Bernal & Gonzalez, ).…”

Section: Methodsmentioning

confidence: 99%

Phylogeographical relationships of Sicilian brown trout and the effects of genetic introgression on morphospace occupation

Fruciano

Pappalardo

Tigano

et al. 2014

Biol J Linn Soc Lond

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Genetic introgression of aquaculture stocks in local forms is well documented in many fish species but their evolutionary consequences for the local populations have not been thoroughly explored. Due to its wide geographical range, the existence of many locally adapted forms and the frequent occurrence of introgression of aquaculture stocks in local forms, brown trout represents the ideal system to study the effects of such introgressions. Here, we focus on a group of rivers and streams in Sicily (Italy), and, by using molecular tools, we show that autochthonous populations are probably derived from the Southern Atlantic clade, which is present in the Iberian peninsula and North Africa. Three out of the four studied rivers reveal signs of genetic introgression of domestic stocks. Finally, by using advanced geometric morphometric analyses, we show that genetic introgression produces a higher degree of morphological variability relative to that observed in non-introgressed populations.

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“…To ensure accurate measurements, we performed a preliminary analysis of measurement error by taking – for a pilot set of 20 specimens – repeated measurements (two pictures and two digitization per picture, for a total of four measurements; Fruciano et al . ,b; ) and measuring the consistency of the mouth‐bending angle across repeated measurements (repeatability) with the intraclass correlation coefficient (Fisher ; Fleiss & Shrout ). The value of the repeatability of mouth‐bending angle was high (0.89) and for the rest of the data set a single measurement was deemed sufficiently accurate (Fruciano ).…”

Section: Methodsmentioning

confidence: 99%

Towards understanding the genetic basis of mouth asymmetry in the scale‐eating cichlidPerissodus microlepis

et al. 2016

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How polymorphisms consisting in left-right asymmetries are produced and maintained in natural populations is a tantalizing question, which remains largely unanswered. The scale-eating cichlid fish Perissodus microlepis is a remarkable example of extreme ecological specialization achieved by morphological and behavioural laterality. Its asymmetric mouth is accompanied by a pronounced lateralized foraging behaviour, where a left-bending morph preferentially feeds on the scales of the right side of its prey, while the opposite is true for the right morph. This striking asymmetry made this fish a textbook example of the astounding degree of ecological specialization and negative frequency-dependent selection. Yet, the genetic basis underlying this spectacular laterality remains unknown. We addressed this question through analyses of wild-caught fish using high-throughput DNA sequencing data. A novel array of SNP markers was developed by ddRAD sequencing (ddRADseq) and the use of pooled DNA samples (PoolSeq). We obtained more than 155 000 SNPs using ddRADseq and 3 900 000 SNPs with PoolSeq. Among these, we identified one (ddRAD) SNP, and 38 or 378 (PoolSeq) windows that are differentiated between the left and right morphs accounting for spurious associations due to geographic structuring. This allowed us to uncover candidate genomic regions that potentially contain genes for this trait. Then, this interesting trait has a genetic basis that is likely to be influenced by multiple loci. This result contributes to a greater understanding of the genetic bases of left-right asymmetry and, ultimately, the evolutionary processes governing the maintenance of this striking case of laterality.

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Body shape variation and colour change during growth in a protogynous fish

Cited by 20 publications

References 33 publications

Sharing is caring? Measurement error and the issues arising from combining 3D morphometric datasets

Sharing is caring? Measurement error and the issues arising from combining 3D morphometric datasets

Phylogeographical relationships of Sicilian brown trout and the effects of genetic introgression on morphospace occupation

Towards understanding the genetic basis of mouth asymmetry in the scale‐eating cichlidPerissodus microlepis

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