Network Architecture of Leaf Trait Correlations Has Shifted Following Crop Domestication

Abstract

Domestication of crops with the goal of improving yield has led to spectacular shifts in phenotypic traits and their correlation patterns. However, it is relatively unknown whether domestication has driven variation in the architecture of trait correlation networks to optimise carbon return on construction cost along the leaf economics spectrum (LES). Here, we compiled a data set of leaf functional, biochemical, and anatomical traits of 54 wild and cultivated crops. We found that crops tended to be located at the acquisitive end of global LES, typically having low leaf mass per area (LMA), high photosynthetic rate per mass, and high leaf nitrogen and phosphorus content per mass. Architectural changes in trait networks (module number, hub traits, and number of correlations) aligned with the notion of a divergent domestication syndrome due to artificial selection for faster growth and higher yield in high-resource agricultural fields. Domestication has increased the carbon return on resource investment via selecting trait combinations including higher photosynthesis, greater leaf area and LMA. We highlight that strategy-shifts towards faster photosynthetic return on investments in leaves have been coordinated with divergent trait correlation, which has important implications for understanding patterns of trait covariation under crop domestication.