Format: ORAL

Sidonie Bellot1, Alexandre Antonelli1, Steven P. Bachman1, Grace Brewer1, Rodrigo Cmara-Leret2, Fabien Condamine3, Angela Cano4, Thomas Couvreur5, Robyn Cowan1, Laszlo Csiba1, John Dransfield1, Wolf L. Eiserhardt1, Niroshini Epitawalage1, Flix Forest1, W. Daniel Kissling6, Benedikt G. Kuhnhuser1, Ilia J. Leitch1, Yijing Lu1, Kelly Matsunaga7, Olivier Maurin1, Robert J. Morley8, Eimear Nic Lughadha1, Ian Ondo1, Samuel Pironon1, Michelle Siros1, Barnaby E. Walker1, William J. Baker1

1 Royal Botanic Gardens, Kew, Richmond, UK. 2 Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland. 3 Institut des Sciences de l’Evolution de Montpellier (ISEM), Montpellier, France. 4 Cambridge University Botanic Garden, Cambridge, UK. 5 Institut de Recherche pour le Développement, Montpellier, France. 6 Institute for Biodiversity and Ecosystem Dynamics (IBED), University of Amsterdam, Amsterdam, the Netherlands. 7 The University of Kansa, Lawrence, USA. 8 Royal Holloway University of London, Egham, Surrey TW20 0EX, UK.

Palms (Arecaceae) have been studied for decades all around the world, yielding an ever-growing wealth of data on their geographical distribution, traits, fossils, genomes, and uses by people. The combined study of these datasets can help us understand how palms evolved, how they can be used and protected today, and how they may cope with future challenges. We illustrate this here with two examples from our past and current research. First, we show how combining genomic and paleontological data improves our understanding of the relationships, ages and early historical biogeography of palm genera. Up to 1255 nuclear genes were sequenced for each palm genus and the data were used to estimate their phylogeny. Affinities and ages of hundreds of palm fossils were then reviewed and some of the fossils were selected to inform the estimation of early divergence times and historical biogeography in the family. Second, we use machine learning based on occurrence data points to estimate the extinction risk of hundreds of species, and we combine these predictions with trait and ethnobotanical datasets to assess the impact that predicted extinctions could have on palm phylogenetic and functional diversity, and on palm uses around the world. We conclude by discussing how integrating ecological, morphological and genomic data could help to predict and improve palm resilience to global change, highlighting the urgent need and opportunity for collaborative international studies on this topic.