Leaf thermoregulation and consequent leaf-to-air temperature difference (ΔT) are tightly linked to plant metabolic rates and health. Current knowledge mainly focus on the regulation of environmental conditions on ΔT, while an accurate assessment of biotic regulations with field data remains lacking. Here, we used a trait-based model that integrates a coupled photosynthesis-stomatal conductance model with a leaf energy balance model to explore how six leaf traits (i.e. leaf width, emissivity, visible and near-infrared light absorptance, photosynthetic capacity—V_c,max25, and stomatal slope—g₁) regulate ΔT variability across the diel timescale. We evaluated the model with field observations collected from temperate to tropical forests. Our results show that: (1) leaf traits mediate large ΔT variability, with the noon-time trait-mediated ΔT variability reaching c. 15.0 °C; (2) leaf width, V_c,max25, and g₁ are the three most important traits and their relative importance in ΔT regulation varies strongly across the diel timescale; and (3) model-derived trait-ΔT relationships match field observations that were collected close to either midday or midnight. These findings advance our understanding of biotic controls of leaf-level ΔT variability, highlighting a trait-based representation of leaf energy balance that can improve simulations of diverse leaf thermoregulation strategies across species and physiological responses to climate change.

叶片温度调节和随之而来的叶片与空气温差 ( ΔT ) 与植物代谢率和健康密切相关。目前的知识主要集中在环境条件对ΔT的调节上，而利用现场数据对生物调节的准确评估仍然缺乏。在这里，我们使用基于特征的模型，将耦合光合作用-气孔导度模型与叶片能量平衡模型相结合，探索了六种叶片性状（即叶宽、发射率、可见光和近红外光吸收率、光合能力—V _{c ,max25} , 和气孔坡度— g ₁ ) 调节ΔT跨时间尺度的可变性。我们使用从温带到热带森林收集的实地观察来评估该模型。我们的结果表明：（1）叶片性状介导较大的ΔT变异性，中午性状介导的ΔT变异性达到c。15.0℃；(2) 叶宽、V _c、max25和g ₁是三个最重要的性状，它们在ΔT调节中的相对重要性在整个昼夜时间尺度上变化很大；(3) 模型衍生的性状-ΔT关系匹配接近中午或午夜收集的现场观察。这些发现促进了我们对叶水平 Δ 的生物控制的理解T变异性，突出了基于特征的叶片能量平衡表示，可以改进跨物种和对气候变化的生理反应的不同叶片温度调节策略的模拟。