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      The relative role of plasticity and demographic history in Capsella bursa-pastoris: a common garden experiment in Asia and Europe

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          Abstract

          The colonization success of a species depends on the interplay between its phenotypic plasticity, adaptive potential and demographic history. Assessing their relative contributions during the different phases of a species range expansion is challenging, and requires large-scale experiments. Here, we investigated the relative contributions of plasticity, performance and demographic history to the worldwide expansion of the shepherd’s purse, Capsella bursa-pastoris. We installed two large common gardens of the shepherd’s purse, a young, self-fertilizing, allopolyploid weed with a worldwide distribution. One common garden was located in Europe, the other in Asia. We used accessions from three distinct genetic clusters (Middle East, Europe and Asia) that reflect the demographic history of the species. Several life-history traits were measured. To explain the phenotypic variation between and within genetic clusters, we analysed the effects of (i) the genetic clusters, (ii) the phenotypic plasticity and its association to fitness and (iii) the distance in terms of bioclimatic variables between the sampling site of an accession and the common garden, i.e. the environmental distance. Our experiment showed that (i) the performance of C. bursa-pastoris is closely related to its high phenotypic plasticity; (ii) within a common garden, genetic cluster was a main determinant of phenotypic differences; and (iii) at the scale of the experiment, the effect of environmental distance to the common garden could not be distinguished from that of genetic clusters. Phenotypic plasticity and demographic history both play important role at different stages of range expansion. The success of the worldwide expansion of C. bursa-pastoris was undoubtedly influenced by its strong phenotypic plasticity.

          Abstract

          The respective role of demography, plasticity and adaptation in the colonization success of plant species remains an intense topic of investigation in evolutionary ecology and genomics. A screening of phenotypic traits of hundreds of genotypes in large-scale common garden experiments in Eastern Asia and Europe shows that both demography and a high phenotypic plasticity underlie the success of the tetraploid and self-fertilizing species, Capsella bursa-pastoris, the shepherd’s purse, at different stages of expansion. This study provides insight into the causes of the ecological success of a plant species during range expansion.

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          WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas

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            Fitting Linear Mixed-Effects Models Using lme4

            Maximum likelihood or restricted maximum likelihood (REML) estimates of the parameters in linear mixed-effects models can be determined using the lmer function in the lme4 package for R. As for most model-fitting functions in R, the model is described in an lmer call by a formula, in this case including both fixed- and random-effects terms. The formula and data together determine a numerical representation of the model from which the profiled deviance or the profiled REML criterion can be evaluated as a function of some of the model parameters. The appropriate criterion is optimized, using one of the constrained optimization functions in R, to provide the parameter estimates. We describe the structure of the model, the steps in evaluating the profiled deviance or REML criterion, and the structure of classes or types that represents such a model. Sufficient detail is included to allow specialization of these structures by users who wish to write functions to fit specialized linear mixed models, such as models incorporating pedigrees or smoothing splines, that are not easily expressible in the formula language used by lmer. Journal of Statistical Software, 67 (1) ISSN:1548-7660
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              Simultaneous inference in general parametric models.

              Simultaneous inference is a common problem in many areas of application. If multiple null hypotheses are tested simultaneously, the probability of rejecting erroneously at least one of them increases beyond the pre-specified significance level. Simultaneous inference procedures have to be used which adjust for multiplicity and thus control the overall type I error rate. In this paper we describe simultaneous inference procedures in general parametric models, where the experimental questions are specified through a linear combination of elemental model parameters. The framework described here is quite general and extends the canonical theory of multiple comparison procedures in ANOVA models to linear regression problems, generalized linear models, linear mixed effects models, the Cox model, robust linear models, etc. Several examples using a variety of different statistical models illustrate the breadth of the results. For the analyses we use the R add-on package multcomp, which provides a convenient interface to the general approach adopted here. Copyright 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
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                Author and article information

                Contributors
                Role: Associate Editor
                Journal
                AoB Plants
                AoB Plants
                aobpla
                AoB Plants
                Oxford University Press (US )
                2041-2851
                June 2022
                02 April 2022
                02 April 2022
                : 14
                : 3
                : plac011
                Affiliations
                Department of Ecology and Genetics, Evolutionary Biology Centre, Uppsala University , 75236 Uppsala, Sweden
                Université Paris Saclay, INRAE, CNRS, AgroParisTech, GQE - Le Moulon , 91190 Gif-sur-Yvette, France
                Department of Ecology and Genetics, Evolutionary Biology Centre, Uppsala University , 75236 Uppsala, Sweden
                Department of Ecology and Evolutionary Biology, University of Toronto , M5S 3B2 Toronto, ON, Canada
                Key Laboratory of Plant Resources Conservation and Sustainable Utilization, South China Botanical Garden, Chinese Academy of Sciences , Guangzhou 510650, China
                Center of Conservation Biology, Core Botanical Gardens, Chinese Academy of Sciences , Guangzhou 510650, China
                Department of Plant Biology, Swedish University of Agricultural Sciences , 750 07 Uppsala, Sweden
                Department of Ecology and Genetics, Evolutionary Biology Centre, Uppsala University , 75236 Uppsala, Sweden
                Science for Life Laboratory , 752 37 Uppsala, Sweden
                Department of Ecology and Genetics, Evolutionary Biology Centre, Uppsala University , 75236 Uppsala, Sweden
                Department of Ecology and Genetics, Evolutionary Biology Centre, Uppsala University , 75236 Uppsala, Sweden
                Key Laboratory of Plant Resources Conservation and Sustainable Utilization, South China Botanical Garden, Chinese Academy of Sciences , Guangzhou 510650, China
                Center of Conservation Biology, Core Botanical Gardens, Chinese Academy of Sciences , Guangzhou 510650, China
                Department of Ecology and Evolutionary Biology, University of Toronto , M5S 3B2 Toronto, ON, Canada
                Department of Ecology and Genetics, Evolutionary Biology Centre, Uppsala University , 75236 Uppsala, Sweden
                UMR CNRS 6553 ECOBIO, Université de Rennes I , 35042 Rennes Cedex, France
                Department of Ecology and Evolutionary Biology, University of Toronto , M5S 3B2 Toronto, ON, Canada
                Department of Ecology and Genetics, Evolutionary Biology Centre, Uppsala University , 75236 Uppsala, Sweden
                Science for Life Laboratory , 752 37 Uppsala, Sweden
                Author notes
                Corresponding author’s e-mail address: amandine.cornille@ 123456cnrs.fr

                These authors co-directed equally the work.

                These authors contributed equally to the work.

                Article
                plac011
                10.1093/aobpla/plac011
                9162126
                35669442
                cd12474d-8f24-4b5f-9314-7d8a8440a5d4
                © The Author(s) 2022. Published by Oxford University Press on behalf of the Annals of Botany Company.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 18 October 2021
                : 28 March 2022
                : 23 February 2022
                : 02 June 2022
                Page count
                Pages: 13
                Funding
                Funded by: Swedish Research Council, DOI 10.13039/501100004359;
                Funded by: Erik Philip Sörensen Foundation;
                Funded by: Uppsala University, DOI 10.13039/501100007051;
                Funded by: EMBO Short-Term Fellowship;
                Funded by: H2020 European consortium B4EST;
                Funded by: National Natural Science Foundation of China, DOI 10.13039/501100001809;
                Award ID: 31870353
                Funded by: NSERC CGS-M;
                Funded by: Ontario Graduate Scholarship;
                Categories
                Studies
                AcademicSubjects/SCI01210
                Editor's Choice

                Plant science & Botany
                capsella bursa-pastoris,common garden,demographic history,environmental distance,fitness components,phenotypic plasticity

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