Data from: Leaf economics spectrum in rice: Leaf anatomical, biochemical and physiological trait trade-offs

The leaf economics spectrum (LES) is an eco-physiological concept describing the trade-offs of leaf structural, and physiological traits, that has been widely investigated across multiple scales. However, the effects of the breeding process on the LES in crops, as well as the mechanisms of the trait trade-offs underlying the LES, have not been thoroughly elucidated to date. In this study, a dataset, including leaf anatomical, biochemical and functional traits, was constructed to evaluate the trait covariations and trade-offs in domesticated species, rice (Oryza sp.). The slopes and intercepts of the major bivariate correlations of the leaf traits in rice were significantly different from the global LES dataset (Glopnet), which is based on multiple non-crop species in natural ecosystems, although the general patterns were similar. The photosynthetic traits responded differently to leaf structural and biochemical changes, and mesophyll conductance was the most sensitive to leaf N status. A further analysis revealed that the relative limitation of mesophyll conductance declined with leaf N content; however, the limitation of the biochemistry increased relative to leaf N content. These findings indicate that breeding selection and high-resource agricultural environments lead crops to deviate from the leaf trait covariation in wild species, and future breeding to increase the photosynthesis of rice should primarily focus on improvement of the efficiency of photosynthetic enzymes.叶片经济谱（Leaf Economics Spectrum, LES）是一种生态生理学概念，用于描述叶片结构与生理性状间的权衡关系，目前已在多个研究尺度下被广泛探究。然而，截至目前，育种过程对作物叶片经济谱的影响，以及叶片经济谱背后性状权衡的内在机制，仍未得到彻底阐明。本研究构建了一套涵盖叶片解剖性状、生化性状与功能性状的数据集，用以评估驯化物种水稻（Oryza sp.）的性状协同变异与权衡关系。尽管水稻叶片性状的主要双变量相关关系的总体趋势与基于自然生态系统多种非作物物种构建的全球叶片经济谱数据库（Glopnet）相似，但二者的斜率与截距均存在显著差异。光合性状对叶片结构与生化变化的响应存在分化，其中叶肉导度对叶片氮素状态的响应最为敏感。进一步分析显示，叶肉导度的相对限制随叶片氮含量升高而降低，而生化过程的相对限制则随叶片氮含量升高而增强。上述研究结果表明，育种选择与高投入农业环境使作物偏离了野生种的叶片性状协同变异模式；未来旨在提升水稻光合能力的育种工作，应主要聚焦于光合酶效率的改良。