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      Similarity of introduced plant species to native ones facilitates naturalization, but differences enhance invasion success

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          Abstract

          The search for traits associated with plant invasiveness has yielded contradictory results, in part because most previous studies have failed to recognize that different traits are important at different stages along the introduction–naturalization–invasion continuum. Here we show that across six different habitat types in temperate Central Europe, naturalized non-invasive species are functionally similar to native species occurring in the same habitat type, but invasive species are different as they occupy the edge of the plant functional trait space represented in each habitat. This pattern was driven mainly by the greater average height of invasive species. These results suggest that the primary determinant of successful establishment of alien species in resident plant communities is environmental filtering, which is expressed in similar trait distributions. However, to become invasive, established alien species need to be different enough to occupy novel niche space, i.e. the edge of trait space.

          Abstract

          Plant functional traits may help distinguish introduced species that will become invasive from those that do not. Here, Divíšek et al. show that functional profiles of naturalized plant species are similar to natives, while those of invasive plant species exist at the edge of the functional trait space.

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          Most cited references31

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            Rebuilding community ecology from functional traits.

            There is considerable debate about whether community ecology will ever produce general principles. We suggest here that this can be achieved but that community ecology has lost its way by focusing on pairwise species interactions independent of the environment. We assert that community ecology should return to an emphasis on four themes that are tied together by a two-step process: how the fundamental niche is governed by functional traits within the context of abiotic environmental gradients; and how the interaction between traits and fundamental niches maps onto the realized niche in the context of a biotic interaction milieu. We suggest this approach can create a more quantitative and predictive science that can more readily address issues of global change.
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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.

                Author and article information

                Contributors
                Jane.Molofsky@uvm.edu
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                6 November 2018
                6 November 2018
                2018
                : 9
                : 4631
                Affiliations
                [1 ]ISNI 0000 0001 2194 0956, GRID grid.10267.32, Department of Botany and Zoology, , Masaryk University, ; Kotlářská 2, 611 37 Brno, Czech Republic
                [2 ]ISNI 0000 0001 2194 0956, GRID grid.10267.32, Department of Geography, , Masaryk University, ; Kotlářská 2, 611 37 Brno, Czech Republic
                [3 ]ISNI 0000 0004 1936 7689, GRID grid.59062.38, Department of Plant Biology, , University of Vermont, ; Burlington, VT 05405 USA
                [4 ]ISNI 0000 0004 1936 7689, GRID grid.59062.38, Department of Biology, , University of Vermont, ; Burlington, VT 05405 USA
                [5 ]ISNI 0000 0001 2035 1455, GRID grid.424923.a, Department of Invasion Ecology, , Institute of Botany, The Czech Academy of Sciences, ; 252 43 Průhonice, Czech Republic
                [6 ]ISNI 0000 0004 1937 116X, GRID grid.4491.8, Faculty of Science, Department of Ecology, , Charles University, ; 128 43 Praha 2, Czech Republic
                [7 ]ISNI 0000 0001 2214 904X, GRID grid.11956.3a, Centre for Invasion Biology, Department of Botany and Zoology, , Stellenbosch University, ; Matieland, 7602 South Africa
                Author information
                http://orcid.org/0000-0002-5127-5130
                http://orcid.org/0000-0002-8122-3075
                http://orcid.org/0000-0002-5908-6924
                http://orcid.org/0000-0002-5409-7456
                http://orcid.org/0000-0001-9152-7462
                http://orcid.org/0000-0001-8500-442X
                http://orcid.org/0000-0001-9574-8297
                http://orcid.org/0000-0001-7927-516X
                Article
                6995
                10.1038/s41467-018-06995-4
                6219509
                30401825
                7c4ca72d-1edd-4976-af4d-0e6c6e732b47
                © 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
                : 30 March 2018
                : 5 October 2018
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