From green to red: Urban heat stress drives leaf color evolution

Urban environments, occupying approximately 1% of total land area, often impose novel biotic and abiotic selective pressures on organisms and provide valuable opportunities to understand the eco-evolutionary dynamics between nature and human societies. Prevalence of impervious surface and resulting higher temperatures in urban areas, known as urban heat islands, comprises prominent characteristics in global cities. However, it is not known whether and how urban plants adapt to such heat stress. This study focused on Oxalis corniculata, which has intraspecific polymorphism in leaf color (green, red), and examined whether the leaf color variation is associated with urban heat stress. Field observations revealed consistent associations between leaf color and habitat types (green vs. urban) at local (< 500m), landscape (< 50km), and global scales. Green-leaved plants were dominant in green habitats, and red-leaved individuals had increased in number in urban habitats. Growth and photosynthesis experiments indicated the adaptive benefit and cost of red/green leaves associated with heat stresses. Red-leaved individuals had higher growth rates and photosynthetic efficiency under heat stress, while green-leaved individuals displayed higher growth rates and photosynthetic efficiency under non-stressful conditions. Genome-wide SNP analysis suggests that the red leaf trait may have evolved multiple times from the ancestral green leaf, rather than spreading from a single origin of red leaf evolution. Overall, the results suggested that the dominance of red leaves of O. corniculata seen in cities worldwide would be evidence of plant adaptative evolution due to urban heat islands.

Methods
To explore this evolutionary hypothesis, three different approaches were combined: (1) comparing leaf color distribution between urban and non-urban settings at local, landscape, and global scales; (2) quantifying the adaptive benefits and costs of green and red leaves by comparing biomass growth and photosynthetic ability under heat-stress and non-heat conditions between green and red leaves; and (3) estimating evolutionary scenarios of red leaves through genome-wide SNPs analysis.

This dataset contains results of (1) and (2).