Moises Exposito-Alonso, Rocío Gómez Rodríguez, Cristina Barragán, Giovanna Capovilla, Eunyoung Chae, Jane Devos, Ezgi S Dogan, Claudia Friedemann, Caspar Gross, Patricia Lang, Derek Lundberg, Vera Middendorf, Jorge Kageyama, Talia Karasov, Sonja Kersten, Sebastian Petersen, Leily Rabbani, Julian Regalado, Lukas Reinelt, Beth Rowan, Danelle K Seymour, Efthymia Symeonidi, Rebecca Schwab, Diep Thi Ngoc Tran, Kavita Venkataramani, Anna-Lena Van de Weyer, François Vasseur, George Wang, Ronja Wedegärtner, Frank Weiss, Rui Wu, Wanyan Xi, Maricris Zaidem, Wangsheng Zhu, Fernando García-Arenal, Hernán A Burbano, Oliver Bossdorf, Detlef Weigel
The gold standard for studying natural selection and adaptation in the wild is to quantify lifetime fitness of individuals from natural populations that have been grown together in a common garden, or that have been reciprocally transplanted. By combining fitness values with species traits and genome sequences, one can infer selection coefficients at the genetic level. Here we present a rainfall-manipulation experiment with 517 whole-genome sequenced natural accessions of the plant Arabidopsis thaliana spanning the global distribution of the species. The experiments were conducted in two field stations in contrasting climates, in the Mediterranean and in Central Europe, where we built rainout shelters and simulated high and low rainfall. Using custom image analysis we quantified fitness- and phenology-related traits for 23,154 pots, which contained about 14,500 plants growing independently, and over 310,000 plants growing in small populations (max. 30 plants). This large field experiment dataset, which associates fitness and ecologically-relevant traits with genomes, will provide an important resource to test eco-evolutionary genetic theories and to understand the potential evolutionary impacts of future climates on an important plant model species.