Format: ORAL

Wolf L. Eiserhardt1,2, William J. Baker1,2, Paola de Lima Ferreira1, Lars Emil S. F. Hansen1, Oscar B. Wrisberg1, Melanie Tietje1

1 Department of Biology, Aarhus University, Aarhus, Denmark 2 Royal Botanic Gardens, Kew, Richmond (Surrey), UK

Rainforests occur across the tropics and are consistently the most biodiverse biome on Earth. Despite centuries of scientific interest, the eco-evolutionary drivers of rainforest hyperdiversity remain elusive. That said, it seems clear that explanations have to be sought in deep time, involving dynamics of diversification, migration and adaptation over tens to hundreds of millions of years. Phylogenetic trees can provide a unique window on those deep-time dynamics, but are notoriously hard to obtain at the scale needed to unpick rainforest hyperdiversity. Robust and well-sampled phylogenetic trees tend to be only available for small model groups that may or may not be representative for the assembly of rainforest biotas. Meanwhile, Big Data approaches investigating major groups as a whole (e.g. seed plants) consistently suffer from limited, patchy and biased phylogenetic data. Similar trade-offs exist for the geographic and ecological data needed to assign species to biomes, a prerequisite for investigating biome assembly over time. Here, I will discuss recent efforts to understand the evolutionary assembly of rainforest hyperdiversity using both Big Data and model group approaches, comparing their findings and highlighting the specific challenges, pros and cons of each approach. Specifically, I will report our recent findings based on phylogenetic, geographic and biome association datasets for all seed plants (Spermatophyta), contrasting them with focused studies mostly from the palm family (Arecaceae), a well-established model group for tropical plant ecology and evolution.