Identifying the multiple drivers of Cactus diversification

Abstract Our understanding of the complexity of forces at play in the rise of major angiosperm lineages remains incomplete. The diversity and heterogeneous distribution of most angiosperm lineages is so extraordinary that it confounds our ability to identify simple drivers of diversification. Using Machine Learning in combination with phylogenetic modelling, we show that 11 separate abiotic and biotic variables significantly contribute to the diversification of Cactaceae. We reconstruct a comprehensive phylogeny, build a dataset of 39 abiotic and biotic variables, and predict the variables of central importance, accounting for interactions. We use state-dependent diversification models to confirm that a rich range of eleven abiotic and biotic variables shape Cactus diversification. Of highest importance is latitude, plant size, and growth form, with lesser importance identified in soil composition, bioclimate, topography, geographic range size, and chromosome count. Our results reveal the need to account for the complexity underlying macroevolution of iconic angiosperm families.