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

多倍化和杂交是区别开花植物和高等动物进化和物种形成的两个最重要的过程。虽然在SPP的第一个三年资助期内，我们致力于解决多倍体复合体(银花属)物种划界的问题，但本提案将侧重于更复杂的问题，即在密集杂交的植物属中客观和快速地采用机器学习方法进行自动物种划界的可能性。通过实施基于标本材料的高通量分子技术(HyRADseq)，结合形态特征的自动提取和基于博物馆材料的生态位建模，我们的目标是快速发现和划定进化的重要单位(物种)，而不需要额外的实地工作。我们的方法将在向日葵科(菊科，菊科)的三个植物群中得到例证，这些植物群以其广泛杂交引起的关键分类而闻名：千里光属(Senecio Nhemens Syngameon)(8种；欧洲)，红花属(Rhodanhemum B.H.Wilcox)等。(15种；非洲西北部)和智利的巴查里斯属(14种，26个杂交组合)。

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).