Browsing by Subject "MULLERIAN MIMICRY"

Sort by: Order: Results:

Now showing items 1-3 of 3
  • Mattila, Anniina L. K.; Jiggins, Chris D.; Opedal, Øystein H.; Montejo-Kovacevich, Gabriela; de Castro, Érika; McMillan, William O.; Bacquet, Caroline; Saastamoinen, Marjo (2021)
    Chemical defences against predators underlie the evolution of aposematic coloration and mimicry, which are classic examples of adaptive evolution. Surprisingly little is known about the roles of ecological and evolutionary processes maintaining defence variation, and how they may feedback to shape the evolutionary dynamics of species. Cyanogenic Heliconius butterflies exhibit diverse warning color patterns and mimicry, thus providing a useful framework for investigating these questions. We studied intraspecific variation in de novo biosynthesized cyanogenic toxicity and its potential ecological and evolutionary sources in wild populations of Heliconius erato along environmental gradients, in common-garden broods and with feeding treatments. Our results demonstrate substantial intraspecific variation, including detectable variation among broods reared in a common garden. The latter estimate suggests considerable evolutionary potential in this trait, although predicting the response to selection is likely complicated due to the observed skewed distribution of toxicity values and the signatures of maternal contributions to the inheritance of toxicity. Larval diet contributed little to toxicity variation. Furthermore, toxicity profiles were similar along steep rainfall and altitudinal gradients, providing little evidence for these factors explaining variation in biosynthesized toxicity in natural populations. In contrast, there were striking differences in the chemical profiles of H. erato from geographically distant populations, implying potential local adaptation in the acquisition mechanisms and levels of defensive compounds. The results highlight the extensive variation and potential for adaptive evolution in defense traits for aposematic and mimetic species, which may contribute to the high diversity often found in these systems.
  • Rönkä, Katja; Valkonen, Janne K.; Nokelainen, Ossi; Rojas, Bibiana; Gordon, Swanne; Burdfield-Steel, Emily; Mappes, Johanna (2020)
    Warning signals are predicted to develop signal monomorphism via positive frequency-dependent selection (+FDS) albeit many aposematic systems exhibit signal polymorphism. To understand this mismatch, we conducted a large-scale predation experiment in four countries, among which the frequencies of hindwing warning coloration of the aposematic moth,Arctia plantaginis,differ. Here we show that selection by avian predators on warning colour is predicted by local morph frequency and predator community composition. We found +FDS to be the strongest in monomorphic Scotland and lowest in polymorphic Finland, where the attack risk of moth morphs depended on the local avian community. +FDS was also found where the predator community was the least diverse (Georgia), whereas in the most diverse avian community (Estonia), hardly any models were attacked. Our results support the idea that spatial variation in predator communities alters the strength or direction of selection on warning signals, thus facilitating a geographic mosaic of selection.
  • Bainbridge, Hannah E.; Brien, Melanie N.; Morochz, Carlos; Salazar, Patricio A.; Rastas, Pasi; Nadeau, Nicola J. (2020)
    Mimetic systems allow us to address the question of whether the same genes control similar phenotypes in different species. Although widespread parallels have been found for major effect loci, much less is known about genes that control quantitative trait variation. In this study, we identify and compare the loci that control subtle changes in the size and shape of forewing pattern elements in twoHeliconiusbutterfly co-mimics. We use quantitative trait locus (QTL) analysis with a multivariate phenotyping approach to map the variation in red pattern elements across the whole forewing surface ofHeliconius eratoandHeliconius melpomene. These results are compared with a QTL analysis of univariate trait changes, and show that our resolution for identifying small effect loci is somewhat improved with the multivariate approach, but also that different loci are detected with these different approaches. QTL likely corresponding to the known patterning geneoptixwere found in both species but otherwise, a remarkably low level of genetic parallelism was found. This lack of similarity indicates that the genetic basis of convergent traits may not be as predictable as assumed from studies that focus solely on Mendelian traits.