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      Recent human history governs global ant invasion dynamics

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          Abstract

          Human trade and travel are breaking-down biogeographic barriers, resulting in shifts in the geographical distribution of organisms, yet it remains largely unknown whether different alien species generally follow similar spatiotemporal colonization patterns and how such patterns are driven by trends in global trade. Here, we analyse the global distribution of 241 alien ant species and show that these species comprise four distinct groups that inherently differ in their worldwide distribution from that of native species. The global spread of these four distinct species groups has been greatly, but differentially, influenced by major events in recent human history, in particular historical waves of globalization (approximately 1850-1914, and 1960-present), world wars and global recessions. Species in these four groups also differ in six important morphological and life-history traits and their degree of invasiveness. Combining spatiotemporal distribution data with life-history trait information provides valuable insight into the processes driving biological invasions and facilitates identification of species most likely to become invasive in the future.

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          Most cited references35

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          Diversity and dissimilarity coefficients: A unified approach

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            The Causes and Consequences of Ant Invasions

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              Wavelet analysis of ecological time series.

              Wavelet analysis is a powerful tool that is already in use throughout science and engineering. The versatility and attractiveness of the wavelet approach lie in its decomposition properties, principally its time-scale localization. It is especially relevant to the analysis of non-stationary systems, i.e., systems with short-lived transient components, like those observed in ecological systems. Here, we review the basic properties of the wavelet approach for time-series analysis from an ecological perspective. Wavelet decomposition offers several advantages that are discussed in this paper and illustrated by appropriate synthetic and ecological examples. Wavelet analysis is notably free from the assumption of stationarity that makes most methods unsuitable for many ecological time series. Wavelet analysis also permits analysis of the relationships between two signals, and it is especially appropriate for following gradual change in forcing by exogenous variables.
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                Author and article information

                Journal
                101698577
                46074
                Nat Ecol Evol
                Nat Ecol Evol
                Nature ecology & evolution
                2397-334X
                20 May 2017
                22 June 2017
                July 2017
                22 December 2017
                : 1
                : 7
                : 0184
                Affiliations
                [1 ]Department of Ecology and Evolution, University of Lausanne, Switzerland
                [2 ]Department of Ecology, Systematics and Evolution, Univ. Paris-Sud, CNRS, AgroParisTech, Université Paris-Saclay, Orsay, France
                [3 ]US Forest Service, Northern Research Station, WV, USA
                Author notes
                [* ]Correspondence and requests for materials should be addressed to cleo.bertelsmeier@ 123456unil.ch or laurent.keller@ 123456unil.ch .
                Article
                EMS72761
                10.1038/s41559-017-0184
                5495171
                28685166
                e9f05e28-247f-4c59-918c-3f16e1da1212

                Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms

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