Abstract

Experiments comparing native to introduced populations or distinct introduced populations to each other show that phenotypic evolution is common and often involves a suit of interacting phenotypic traits. We define such sets of traits that evolve in concert and contribute to the success of invasive populations as an ‘invasion syndrome’. The invasive Harlequin ladybird Harmonia axyridis displays such an invasion syndrome with, for instance, females from invasive populations being larger and heavier than individuals from native populations, allocating more resources to reproduction, and spreading reproduction over a longer lifespan. Invasion syndromes could emerge due to selection acting jointly and directly on a multitude of traits, or due to selection on one or a few key traits that drive correlated indirect responses in other traits. Here, we investigated the degree to which the H. axyridis invasion syndrome would emerge in response to artificial selection on either female body mass or on age at first reproduction, two traits involved in their invasion syndrome. To further explore the interaction between environmental context and evolutionary change in molding the phenotypic response, we phenotyped the individuals from the selection experiments in two environments, one with abundant food resources and one with limited resources. The two artificial selection experiments show that the number of traits showing a correlated response depends upon the trait undergoing direct selection. Artificial selection on female body mass resulted in few correlated responses and hence poorly reproduced the invasion syndrome. In contrast, artificial selection on age at first reproduction resulted in more widespread phenotypic changes, which nevertheless corresponded only partly to the invasion syndrome. The artificial selection experiments also revealed a large impact of diet on the traits, with effects dependent on the trait considered and the selection regime. Overall, our results indicate that direct selection on multiple traits was likely necessary in the evolution of the H. axyridis invasion syndrome. Furthermore, they show the strength of using artificial selection to identify the traits that are correlated in different selective contexts, which represents a crucial first step in understanding the evolution of complex phenotypic patterns, including invasion syndromes.

Highlights

  • The field of biological invasions has its own quest for the Holy Grail: establishing a list of traits that can predict invasion success

  • At generation 9, female body mass increased by 12% on average in the heavy lines and decreased by 4% in the light lines compared to the control lines (Figure 1B)

  • We investigated the mechanisms underlying the emergence of the invasion syndrome occurring in invasive populations of H. axyridis using two distinct artificial selection experiments performed on two traits involved in this syndrome

Read more

Summary

Introduction

The field of biological invasions has its own quest for the Holy Grail: establishing a list of traits that can predict invasion success. Traits linked to invasion success and ecological or economic impact are already used in risk assessment to identify potentially harmful species, and focus efforts to prevent introduction of those species (Kumschick, Richardson 2013) In plants, such risk assessment is commonly based on the evaluation of five characteristics related to reproduction and habitat use (seed mass, chromosome number, native range size, wetland association and maximum height; Schmidt et al 2012). These trait-based approaches have met limited success, belying the existence of universal traits that predict invasiveness (Catford et al 2009; Perkins et al 2011). A first step in this process is acknowledging that traits do not exist in isolation from each other; organisms are physiologically integrated units (Ketterson et al 2009), and organismal traits are constrained by physiological and genetic trade-offs

Objectives
Methods
Results
Discussion
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call