Harnessing citizen science to contextualize adaptation mechanism discovery
Summary
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 w
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# Harnessing citizen science to contextualize adaptation mechanism discovery
*Published: 2026 May 20*
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.
Published by Elsevier Inc.
DOI: 10.1016/j.cell.2026.04.039