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      Endogenous toxins and the coupling of gregariousness to conspicuousness in Argidae and Pergidae sawflies

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          Abstract

          Phytophagous insects tend to be either cryptic and solitary, or brightly colored and gregarious, as a defense against vertebrate predators. Here, we tested whether potent defensive chemicals produced de novo by larvae of Argidae and Pergidae sawflies have influenced the evolutionary relationship between larval appearance and levels of gregariousness. Phylogeny-based correlation analyses indicated only a weak trend for solitary species to be cryptic, and for gregarious ones to be conspicuous. Numerous Argidae were cryptic–solitary or conspicuous–gregarious, whereas most Pergidae were conspicuous–gregarious. Both families also included not truly gregarious but aggregated species, i.e. with individuals more evenly distributed on the host plant. By considering two specific morphological traits, predominant body coloration and contrasting spots on body, each one was (weakly) associated with appearance but none with gregariousness, which reflects the functional relevance of appearance as a whole. Furthermore, Argidae can display alternate appearances during successive larval instars. Finally, an independent contrasts test showed no obvious correlation between two major toxic peptides. Our results point towards diversely combined patterns of linked ecological traits in these insects. By assuming that warning coloration is more warranted against vertebrate than invertebrate predators, we suggest that the occurrence itself of toxins allowed this diversity via differing predator guilds and environmental factors, to which these insects were confronted during evolution.

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          Stochastic mapping of morphological characters.

          Many questions in evolutionary biology are best addressed by comparing traits in different species. Often such studies involve mapping characters on phylogenetic trees. Mapping characters on trees allows the nature, number, and timing of the transformations to be identified. The parsimony method is the only method available for mapping morphological characters on phylogenies. Although the parsimony method often makes reasonable reconstructions of the history of a character, it has a number of limitations. These limitations include the inability to consider more than a single change along a branch on a tree and the uncoupling of evolutionary time from amount of character change. We extended a method described by Nielsen (2002, Syst. Biol. 51:729-739) to the mapping of morphological characters under continuous-time Markov models and demonstrate here the utility of the method for mapping characters on trees and for identifying character correlation.
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            Host Specialization in Phytophagous Insects

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              SIMMAP: Stochastic character mapping of discrete traits on phylogenies

              Background Character mapping on phylogenies has played an important, if not critical role, in our understanding of molecular, morphological, and behavioral evolution. Until very recently we have relied on parsimony to infer character changes. Parsimony has a number of serious limitations that are drawbacks to our understanding. Recent statistical methods have been developed that free us from these limitations enabling us to overcome the problems of parsimony by accommodating uncertainty in evolutionary time, ancestral states, and the phylogeny. Results SIMMAP has been developed to implement stochastic character mapping that is useful to both molecular evolutionists, systematists, and bioinformaticians. Researchers can address questions about positive selection, patterns of amino acid substitution, character association, and patterns of morphological evolution. Conclusion Stochastic character mapping, as implemented in the SIMMAP software, enables users to address questions that require mapping characters onto phylogenies using a probabilistic approach that does not rely on parsimony. Analyses can be performed using a fully Bayesian approach that is not reliant on considering a single topology, set of substitution model parameters, or reconstruction of ancestral states. Uncertainty in these quantities is accommodated by using MCMC samples from their respective posterior distributions.
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                Author and article information

                Contributors
                Jean-Luc.Boeve@naturalsciences.be
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                5 December 2018
                5 December 2018
                2018
                : 8
                : 17636
                Affiliations
                [1 ]ISNI 0000 0001 2171 9581, GRID grid.20478.39, OD Taxonomy and Phylogeny, , Royal Belgian Institute of Natural Sciences, ; Rue Vautier 29, B-1000 Brussels, Belgium
                [2 ]ISNI 0000 0001 0726 2490, GRID grid.9668.1, Department of Environmental and Biological Sciences, , University of Eastern Finland, ; P.O. Box 111, FI-80101 Joensuu, Finland
                [3 ]ISNI 0000 0004 4910 9859, GRID grid.454322.6, Present Address: Department of Ecosystems in the Barents Region, , Norwegian Institute of Bioeconomy Research, Svanhovd Research Station, ; NO-9925 Svanvik, Norway
                [4 ]GRID grid.410801.c, Department of Zoology, , National Museum of Nature and Science, ; 4-1-1 Amakubo, Tsukuba-shi, Ibaraki 305-0005 Japan
                [5 ]ISNI 0000 0001 1013 3702, GRID grid.452282.b, SNSB - Zoologische Staatssammlung München, ; Münchhausenstr. 21, 81247 Munich, Germany
                Article
                35925
                10.1038/s41598-018-35925-z
                6281571
                30518939
                2629bc40-4acc-4b4e-9a3e-bfc0167877ca
                © The Author(s) 2018

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 28 June 2018
                : 12 November 2018
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100005876, Academy of Finland | Biotieteiden ja Ympäristön Tutkimuksen Toimikunta (Research Council for Biosciences and Environment);
                Award ID: #294466
                Award Recipient :
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