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      Evolution of a complex phenotype with biphasic ontogeny: Contribution of development versus function and climatic variation to skull modularity in toads

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          Abstract

          The theory of morphological integration and modularity predicts that if functional correlations among traits are relevant to mean population fitness, the genetic basis of development will be molded by stabilizing selection to match functional patterns. Yet, how much functional interactions actually shape the fitness landscape is still an open question. We used the anuran skull as a model of a complex phenotype for which we can separate developmental and functional modularity. We hypothesized that functional modularity associated to functional demands of the adult skull would overcome developmental modularity associated to bone origin at the larval phase because metamorphosis would erase the developmental signal. We tested this hypothesis in toad species of the Rhinella granulosa complex using species phenotypic correlation pattern (P‐matrices). Given that the toad species are distributed in very distinct habitats and the skull has important functions related to climatic conditions, we also hypothesized that differences in skull trait covariance pattern are associated to differences in climatic variables among species. Functional and hormonal‐regulated modules are more conspicuous than developmental modules only when size variation is retained on species P‐matrices. Without size variation, there is a clear modularity signal of developmental units, but most species have the functional model as the best supported by empirical data without allometric size variation. Closely related toad species have more similar climatic niches and P‐matrices than distantly related species, suggesting phylogenetic niche conservatism. We infer that the modularity signal due to embryonic origin of bones, which happens early in ontogeny, is blurred by the process of growth that occurs later in ontogeny. We suggest that the species differing in the preferred modularity model have different demands on the orbital functional unit and that species contrasting in climate are subjected to divergent patterns of natural selection associated to neurocranial allometry and T3 hormone regulation.

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          Introduction to Quantitative Genetics

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            Unrepeatable Repeatabilities: A Common Mistake

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              Testing for phylogenetic signal in comparative data: behavioral traits are more labile.

              The primary rationale for the use of phylogenetically based statistical methods is that phylogenetic signal, the tendency for related species to resemble each other, is ubiquitous. Whether this assertion is true for a given trait in a given lineage is an empirical question, but general tools for detecting and quantifying phylogenetic signal are inadequately developed. We present new methods for continuous-valued characters that can be implemented with either phylogenetically independent contrasts or generalized least-squares models. First, a simple randomization procedure allows one to test the null hypothesis of no pattern of similarity among relatives. The test demonstrates correct Type I error rate at a nominal alpha = 0.05 and good power (0.8) for simulated datasets with 20 or more species. Second, we derive a descriptive statistic, K, which allows valid comparisons of the amount of phylogenetic signal across traits and trees. Third, we provide two biologically motivated branch-length transformations, one based on the Ornstein-Uhlenbeck (OU) model of stabilizing selection, the other based on a new model in which character evolution can accelerate or decelerate (ACDC) in rate (e.g., as may occur during or after an adaptive radiation). Maximum likelihood estimation of the OU (d) and ACDC (g) parameters can serve as tests for phylogenetic signal because an estimate of d or g near zero implies that a phylogeny with little hierarchical structure (a star) offers a good fit to the data. Transformations that improve the fit of a tree to comparative data will increase power to detect phylogenetic signal and may also be preferable for further comparative analyses, such as of correlated character evolution. Application of the methods to data from the literature revealed that, for trees with 20 or more species, 92% of traits exhibited significant phylogenetic signal (randomization test), including behavioral and ecological ones that are thought to be relatively evolutionarily malleable (e.g., highly adaptive) and/or subject to relatively strong environmental (nongenetic) effects or high levels of measurement error. Irrespective of sample size, most traits (but not body size, on average) showed less signal than expected given the topology, branch lengths, and a Brownian motion model of evolution (i.e., K was less than one), which may be attributed to adaptation and/or measurement error in the broad sense (including errors in estimates of phenotypes, branch lengths, and topology). Analysis of variance of log K for all 121 traits (from 35 trees) indicated that behavioral traits exhibit lower signal than body size, morphological, life-history, or physiological traits. In addition, physiological traits (corrected for body size) showed less signal than did body size itself. For trees with 20 or more species, the estimated OU (25% of traits) and/or ACDC (40%) transformation parameter differed significantly from both zero and unity, indicating that a hierarchical tree with less (or occasionally more) structure than the original better fit the data and so could be preferred for comparative analyses.
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                Author and article information

                Contributors
                monique.simon@usp.br
                Journal
                Ecol Evol
                Ecol Evol
                10.1002/(ISSN)2045-7758
                ECE3
                Ecology and Evolution
                John Wiley and Sons Inc. (Hoboken )
                2045-7758
                07 November 2017
                December 2017
                : 7
                : 24 ( doiID: 10.1002/ece3.2017.7.issue-24 )
                : 10752-10769
                Affiliations
                [ 1 ] Departamento de Genética e Biologia Evolutiva Instituto de Biociências Universidade de São Paulo São Paulo Brasil
                Author notes
                [*] [* ] Correspondence

                Monique Nouailhetas Simon, Departamento de Genética e Biologia Evolutiva, Instituto de Biociências, Universidade de São Paulo, São Paulo, Brasil.

                Email: monique.simon@ 123456usp.br

                Author information
                http://orcid.org/0000-0003-0106-2660
                Article
                ECE33592
                10.1002/ece3.3592
                5743631
                eec374fd-4d65-406f-b566-20febdb3dcc9
                © 2017 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.

                This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 21 June 2017
                : 29 September 2017
                : 11 October 2017
                Page count
                Figures: 5, Tables: 4, Pages: 18, Words: 14173
                Funding
                Funded by: Fundação de Amparo à Pesquisa do Estado de São Paulo
                Award ID: 2011/07584‐2
                Award ID: 2011/14295‐7
                Award ID: 2009/54203‐4
                Categories
                Original Research
                Original Research
                Custom metadata
                2.0
                ece33592
                December 2017
                Converter:WILEY_ML3GV2_TO_NLMPMC version:5.2.8 mode:remove_FC converted:26.12.2017

                Evolutionary Biology
                adaptive landscape,anuran metamorphosis,morphological integration,stabilizing selection

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