Fire has played a crucial role in plant evolution, exemplified by species in fire-prone ecosystems which rely on fire for reproduction and persistence. The fire landscape, or ‘firescape’, is undergoing rapid change worldwide, with increases in fire frequency being driven by invasive species, land use change and climate change. Plant species are now confronted with novel firescapes and we need to understand how, or if, species will adapt to these pressures to predict whether they will persist or decline across landscapes with changing fire regimes.
Most research on fire-driven evolution has focussed on macroevolutionary scales (among species), providing essential knowledge about how traits, such as seed dormancy and fire-stimulated germination, are shaped by the cumulative effects of historical fire regimes. However, studies of fire-driven adaptation within species are essential for understanding adaptive potential and predicting how fire will affect species under rapid global change. The handful of studies addressing this issue within species has been limited by a lack of spatially contrasting fire histories across species native ranges. However, many European plant species have been introduced into Australia where fire frequency exceeds levels found in their native range (i.e. 3 vs > 6 wildfires in the past 100 years). This presents a unique opportunity to predict how ecosystems will respond to increases in fire frequency that are occurring in Europe under climate change. My project, hosted by the School of Natural Sciences, Trinity College Dublin (TCD) and supervised by Professor Yvonne Buckley, capitalised on this opportunity to investigate the phenotypic and genomic basis underlying adaptation to changing fire regimes in European plant species.
This project used next-generation sequence data from two European species which are invasive in Australia: Ribwort plantain (Plantago lanceolata L., Plantaginaceae) and St John’s wort (Hypericum perforatum L., Clusiaceae)) to address four research objectives:
(i) Quantify the phenotypic distribution of fire-related seed traits in native and non-native ranges (WP1, WP2)
(ii) Quantify continental-scale genomic relationships among populations and identify the European sources of non-native samples (WP1, WP3)
(iii) Use landscape resistance models to analyse the influence of fire history, topography and climatic gradients on genomic structure in native and non-native ranges (WP1, WP3, WP4)
(iv) Integrate demographic population models into landscape resistance analysis to examine the relative contribution of environmental drivers and demography on genomic structure (WP1, WP3, WP5)
