Laura E. Tibbs-Cortes, Linqian Han, Jeremy B. Jewell, Puranjit Singh, Haiyan Huang, Ryan Benke, Tony Trieu, Zhou Tang, Soyeon Choi, ZHAO Jianxin, Eudald Illa Berenguer, Thomas Pendergast, Bing Liu, Tina Le, Kankshita Swaminathan, Xiaoyu Weng, Carson Andorf, Michelle A. Graham, Karen Sanguinet, Zhiwu Zhang, Laura Bartley, Yin Bao, Wayne Parrott, KATRIEN M. DEVOS, Thomas Juenger, J. Yu, X Li
Species occupying broad geographic regions have evolved multiple mechanisms to regulate phenological characteristics, enabling adaptations to diverse native habitats. By developing computer vision AI to process citizen science observations across native habitats over North America, we uncovered a consistent latitudinal trend of earlier flowering at higher latitudes in warm-season perennial grasses. To explore the underlying mechanisms of adaptation, we conducted common garden experiments with one species (switchgrass) and discovered the opposite latitudinal flowering-time trend. Integration of differential plasticity of GI-Hd1-FTL1 haplotypes of flowering time regulatory genes, haplotype range, and local environmental profiles found that observations from native habitats capture only part of the genotype-environment-phenotype spectrum established in common garden experiments, therefore reconciling the discrepancy. Two mechanisms emerged as key forces shaping current haplotype ranges and influencing future shifts. Our study highlights the power of combining citizen science observations with designed experiments to uncover mechanisms of adaptation across spatiotemporal scales.