Rapid increase in dispersal during range expansion in the invasive ladybird <i>Harmonia axyridis</i>

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Abstract

The evolutionary trajectories associated with demographic, genetic and spatial disequilibrium have become an issue of growing interest in population biology. Invasive species provide unique opportunities to explore the impact of recent range expansion on life-history traits, making it possible to test for a spatial arrangement of dispersal abilities along the expanding range, in particular. We carried out controlled experiments in laboratory conditions to test the hypothesis of an increase in dispersal capacity with range expansion in Harmonia axyridis, a ladybird that has been invading Europe since 2001. We found a marked increase in the flight speed of the insects from the core to the front of the invasion range in two independent sampling transects. By contrast, we found that two other traits associated with dispersal (endurance and motivation to fly off) did not follow the same spatial gradient. Our results provide a striking illustration of the way in which predictable directional genetic changes may occur rapidly for some traits associated with dispersal during biological invasions. We discuss the consequences of our results for invasion dynamics and the evolutionary outcomes of spatially expanding populations.

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Detecting the number of clusters of individuals using the software structure: a simulation study

G Evanno, S. Regnaut, J Goudet (2005)

The identification of genetically homogeneous groups of individuals is a long standing issue in population genetics. A recent Bayesian algorithm implemented in the software STRUCTURE allows the identification of such groups. However, the ability of this algorithm to detect the true number of clusters (K) in a sample of individuals when patterns of dispersal among populations are not homogeneous has not been tested. The goal of this study is to carry out such tests, using various dispersal scenarios from data generated with an individual-based model. We found that in most cases the estimated 'log probability of data' does not provide a correct estimation of the number of clusters, K. However, using an ad hoc statistic DeltaK based on the rate of change in the log probability of data between successive K values, we found that STRUCTURE accurately detects the uppermost hierarchical level of structure for the scenarios we tested. As might be expected, the results are sensitive to the type of genetic marker used (AFLP vs. microsatellite), the number of loci scored, the number of populations sampled, and the number of individuals typed in each sample.

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Inference of Population Structure Using Multilocus Genotype Data

Jonathan Pritchard, Matthew Stephens, Peter Donnelly … (2001)

We describe a model-based clustering method for using multilocus genotype data to infer population structure and assign individuals to populations. We assume a model in which there are K populations (where K may be unknown), each of which is characterized by a set of allele frequencies at each locus. Individuals in the sample are assigned (probabilistically) to populations, or jointly to two or more populations if their genotypes indicate that they are admixed. Our model does not assume a particular mutation process, and it can be applied to most of the commonly used genetic markers, provided that they are not closely linked. Applications of our method include demonstrating the presence of population structure, assigning individuals to populations, studying hybrid zones, and identifying migrants and admixed individuals. We show that the method can produce highly accurate assignments using modest numbers of loci—e.g., seven microsatellite loci in an example using genotype data from an endangered bird species. The software used for this article is available from http://www.stats.ox.ac.uk/~pritch/home.html.