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Deciphering the Routes of invasion of Drosophila suzukii by Means of ABC Random Forest.

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TLDR
It is found that Japan emerges as the most probable source of the earliest recorded invasion into Hawaii, and a new, more efficient, ABC method, ABC random forest (ABC-RF) is used, which out-performs ABC-LDA when using a comparable and more manageable number of simulated datasets.
Abstract
Deciphering invasion routes from molecular data is crucial to understanding biological invasions, including identifying bottlenecks in population size and admixture among distinct populations. Here, we unravel the invasion routes of the invasive pest Drosophila suzukii using a multi-locus microsatellite dataset (25 loci on 23 worldwide sampling locations). To do this, we use approximate Bayesian computation (ABC), which has improved the reconstruction of invasion routes, but can be computationally expensive. We use our study to illustrate the use of a new, more efficient, ABC method, ABC random forest (ABC-RF) and compare it to a standard ABC method (ABC-LDA). We find that Japan emerges as the most probable source of the earliest recorded invasion into Hawaii. Southeast China and Hawaii together are the most probable sources of populations in western North America, which then in turn served as sources for those in eastern North America. European populations are genetically more homogeneous than North American populations, and their most probable source is northeast China, with evidence of limited gene flow from the eastern US as well. All introduced populations passed through bottlenecks, and analyses reveal five distinct admixture events. These findings can inform hypotheses concerning how this species evolved between different and independent source and invasive populations. Methodological comparisons indicate that ABC-RF and ABC-LDA show concordant results if ABC-LDA is based on a large number of simulated datasets but that ABC-RF out-performs ABC-LDA when using a comparable and more manageable number of simulated datasets, especially when analyzing complex introduction scenarios.

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Journal ArticleDOI

Evolution of Multiple Sensory Systems Drives Novel Egg-Laying Behavior in the Fruit Pest Drosophila suzukii.

TL;DR: The results establish that changes in mechanosensation, olfaction, and presumably gustation have contributed to this ecological shift, and support a model in which the emergence of D. suzukii as an agricultural pest is the consequence of the progressive modification of several sensory systems.
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Multiple introductions, admixture and bridgehead invasion characterize the introduction history of Ambrosia artemisiifolia in Europe and Australia.

TL;DR: The historical admixture zone within native North America originated before global invasion of this weed and could act as a potential source of introduced populations, providing evidence supporting the hypothesis that the invasive populations established through multiple introductions from the native range into Europe and subsequent bridgehead invasion into Australia.
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Extraordinarily rapid speciation in a marine fish

TL;DR: Evidence is presented that European flounders in the Baltic Sea exhibiting different breeding behaviors are a species pair arising from a recent event of ecological speciation, the most rapid event of speciation ever reported for any marine vertebrate.
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Sterile insect technique and Wolbachia symbiosis as potential tools for the control of the invasive species Drosophila suzukii

TL;DR: This review summarizes the current information about the biology and dispersal of D. suzukii and suggests a promising alternative avenue through the combination of these two techniques, SIT/IIT, which has been developed and is currently being tested in open-field trials against Aedes mosquito populations.
Journal ArticleDOI

A practical introduction to Random Forest for genetic association studies in ecology and evolution.

TL;DR: This work explores the use of Random Forest, a powerful machine‐learning algorithm, in genomic studies to discern loci underlying both discrete and quantitative traits, particularly when studying wild or nonmodel organisms.
References
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Journal Article

R: A language and environment for statistical computing.

R Core Team
- 01 Jan 2014 - 
TL;DR: Copyright (©) 1999–2012 R Foundation for Statistical Computing; permission is granted to make and distribute verbatim copies of this manual provided the copyright notice and permission notice are preserved on all copies.
Journal ArticleDOI

Controlling the false discovery rate: a practical and powerful approach to multiple testing

TL;DR: In this paper, a different approach to problems of multiple significance testing is presented, which calls for controlling the expected proportion of falsely rejected hypotheses -the false discovery rate, which is equivalent to the FWER when all hypotheses are true but is smaller otherwise.
Journal ArticleDOI

Random Forests

TL;DR: Internal estimates monitor error, strength, and correlation and these are used to show the response to increasing the number of features used in the forest, and are also applicable to regression.
Book

Bayesian Data Analysis

TL;DR: Detailed notes on Bayesian Computation Basics of Markov Chain Simulation, Regression Models, and Asymptotic Theorems are provided.
Journal ArticleDOI

Bayesian data analysis.

TL;DR: A fatal flaw of NHST is reviewed and some benefits of Bayesian data analysis are introduced and illustrative examples of multiple comparisons in Bayesian analysis of variance and Bayesian approaches to statistical power are presented.
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