The CARRARA pipeline: Using machine-learning techniques for automated species delimitation in intensively hybridising plant genera based on herbarium specimens

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Polyploidisation and hybridisation are two paramount processes that distinguish evolution of and species formation in flowering plants from higher animals. While in the first 3-years funding period of SPP we have worked on solutions for species delimitation in polyploid complexes (in the genus Leucanthemum Mill.), the present proposal will focus on the even more complex questions concerning possibilities for objective and fast machine-learning approaches to automated species delimitation in intensively hybridising plant genera. By implementing high-throughput molecular techniques based on herbarium material (hyRADseq) in combination with the automated extraction of morphological characters and ecological niche-modelling based on museum material, we aim at the fast discovery and delimitation of evolutionary significant units (species) without the necessity of additional field work. Our approach will be exemplified in three plant groups of the sunflower family (Compositae, Asteraceae) known for their critical taxonomy caused by extensive hybridisation: the Senecio nemorensis syngameon (8 species; Europe), the genus Rhodanthemum B.H.Wilcox et al. (15 species; NW Africa), and the genus Baccharis L. in Chile (14 species, 26 hybrid combinations).