Test of colonisation scenarios reveals complex invasion history of the red tomato spider mite Tetranychus evansi - PubMed
Test of colonisation scenarios reveals complex invasion history of the red tomato spider mite Tetranychus evansi
Angham Boubou et al. PLoS One. 2012.
Abstract
The spider mite Tetranychus evansi is an emerging pest of solanaceous crops worldwide. Like many other emerging pests, its small size, confusing taxonomy, complex history of associations with humans, and propensity to start new populations from small inocula, make the study of its invasion biology difficult. Here, we use recent developments in Approximate Bayesian Computation (ABC) and variation in multi-locus genetic markers to reconstruct the complex historical demography of this cryptic invasive pest. By distinguishing among multiple pathways and timing of introductions, we find evidence for the "bridgehead effect", in which one invasion serves as source for subsequent invasions. Tetranychus evansi populations in Europe and Africa resulted from at least three independent introductions from South America and involved mites from two distinct sources in Brazil, corresponding to highly divergent mitochondrial DNA lineages. Mites from southwest Brazil (BR-SW) colonized the African continent, and from there Europe through two pathways in a "bridgehead" type pattern. One pathway resulted in a widespread invasion, not only to Europe, but also to other regions in Africa, southern Europe and eastern Asia. The second pathway involved the mixture with a second introduction from BR-SW leading to an admixed population in southern Spain. Admixture was also detected between invasive populations in Portugal. A third introduction from the Brazilian Atlantic region resulted in only a limited invasion in Europe. This study illustrates that ABC methods can provide insights into, and distinguish among, complex invasion scenarios. These processes are critical not only in understanding the biology of invasions, but also in refining management strategies for invasive species. For example, while reported observations of the mite and outbreaks in the invaded areas were largely consistent with estimates of geographical expansion from the ABC approach, historical observations failed to recognize the complex pathways involved and the corresponding effects on genetic diversity.
Conflict of interest statement
Competing Interests: The authors have declared that no competing interests exist.
Figures

a) entire dataset which identified cluster I and II; b) samples within cluster I and II analysed separately; c) samples from introduced areas. The associated geographical region (abbreviations) for different localities is indicated Table 1, and colour codes are as in Figure 2 and 3. Individuals are represented by vertical lines divided into parts proportional to their proposed ancestry in each
structure-defined genetic cluster.

Four populations were considered in each analysis as identified by the clustering
structureanalysis (see text and Figure 1). Nei and Ni correspond to effective population sizes and number of founder individuals, respectively, and they were assumed to be different in all considered populations. The time of event (ti), in number of generations, corresponds to the time at which an introduced population has diverged from its source population; the duration of the initial bottleneck (db) was assumed to be the same in all introduced populations. Time 0 is the sampling date. Admixture rate r relative to population BR-SW and 1-r to either population AF (scenarios 7 and 8) or EU (scenarios 3 and 6). We assumed that all populations evolved as isolated demes and no exchange of migrants occurred after the introduction. All parameters with associated prior distributions are described in Table S2.

The arrows indicate the most likely pathway. Populations were defined according to
structureanalysis (Figure 1). See Figures 1 and 2 for color codes and Table 1 for population abbreviations.

a) t1: the divergence time between eastern African (AF) and European (EU) populations; b) t4: between Mediterranean (MED) and eastern African (AF) populations; c) t2: between (BR-SW) and (AF) populations; d) N2; e) N4 and f) N3: estimates of the propagule size for introductions in AF, MED and EU respectively. Geographical codes as in Table 1. Y-axis: probability density of estimated parameters. The dotted and solid lines correspond to the prior and posterior density curves, respectively. The best estimates of parameters occur where the posterior probability density function peaks.

Two parental populations studied: Luz de Tavira and Lagos (corresponding respectively to AF+EU and POR-CAT clusters as in Figure 1) with constant effective population sizes Ne1 and Ne2, having diverged at time (td) from an ancestral population of size Nb. At time ta, an admixture event occurred between individuals from Lagos (1) and Luz de Tavira (2) giving birth to an admixed population POR (3) with effective size Ne3 and with an admixture rate r relative to population 1 and 1-r to population 2. All parameters with associated prior distributions are described in Table S2.

a) ta: the admixture time in the hybrid population (POR), b) td: the divergence time between the two parental populations (Luz de Tavira and Lagos) belonging respectively to the two main clusters (I and II) detected by
structureanalysis (Figure 1), and c) r: genetic admixture rate. The dotted and solid lines correspond to the prior and posterior density curves, respectively. Y-axis: probability density of estimated parameters. The best estimates of parameters occur where the posterior probability density function peaks.
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