Speaker
Description
Understanding genetic mechanisms of high throughput data facilitates landscape genomic approaches to infer how dispersal is controlled by adaptive vs. non-adaptive drivers of gene flow. Invasive plant species are suitable study models because non-native populations are often prone to rapid genomic changes as a result of colonizing a novel range. However, many studies on invasive plants compared only a few populations in large distributions, underestimating variation within each range, and restricting their ability to predict the native source region and the identification of drivers of gene flow. We explore the genomic structure of 103 native and 177 non-native populations of Conyza canadensis across the Northern Hemisphere using ddRADseq. C. canadensis is an interesting model to investigate global gene dispersal because it is a successful invader with a cosmopolitan distribution and an economically significant agricultural weed. We test the hypothesis that an interplay between environmental gradients and non-adaptive, demographic processes dictates its global genomic structure. Results suggest strong differentiation among populations and low variation within populations. We also found pronounced differentiation between the genomic structures of native vs. non-native populations. Partial Mantel tests showed a significant correlation between genetic distances and both spatial and climatic distances of the populations. However, isolation by environment was more pronounced in the native ranges whereas isolation by distance was predominant in the non-native ranges. Furthermore, clustering analysis using admixture coefficients shed light on how population history dictates biotic interactions across large spatio-environmental scales. Our results suggest that high selfing rates determine the global genomic structure. Gene flow among native populations is controlled by functional connectivity whereas non-deterministic dispersal probabilities drive genetic differentiation in the non-native ranges. Upcoming analyses will be presented at iDiv Conference 2024 including gene flow to illustrate the magnitude of relative migration rates and the clustering of similar sampled areas.
| Status Group | Doctoral Researcher |
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