The potential of hybridization to adapt to climate change

Climate plays an important role in determining the occurrence of species across the planet. The unprecedented speed of global climate change poses a significant threat to many organisms. Species may evade extinction by either moving to new geographic areas, or by adapting to changing environmental conditions. Species that occur restricted to islands have little opportunities to move to new geographic areas and face unique challenges in adapting to new environmental conditions. Such species may quickly acquire alleles that carry adaptations to new climatic conditions by hybridizing with closely related species that occupy a broader ecological niche, and so be able to cope with rapid environmental changes. Hybrids have long been a subject of controversy in evolutionary biology and may be very relevant in times of climate change. In this project, we aim to explore whether hereditary features that are potentially advantageous in a climate change scenario are exchanged between two closely related butterfly species through hybridization in order to increase their adaptability to survive climate change. As a case study, we are investigating if Papilio hospiton, a butterfly which occurs restricted to the islands of Sardinia and Corsica and which have specific ecological requirements, may profit from receiving genetic features from the widely distributed sibling butterfly species Papilio machaon. The two species are already known to interbreed. We will identify genetic features that are exchanged between the two species and investigate if these features provide a better fitness to the receiving species to cope with climate change. We will study the evolutionary history of the two species and investigate the differences in ecological requirements and potential effects of hybridization considering both, the distribution of adults and microhabitat requirements by their larvae. We will identify microhabitat overlaps and predict the spatial distribution for both species using high-resolution aerial pictures taken from unmanned aerial vehicles.