Chair of Plant and Crop Science, Estonian University of Life Sciences, Kreutzwaldi 1, 51011, Tartu, Estonia.
Estonian Academy of Sciences, Kohtu 6, 10130, Tallinn, Estonia.
Photosynth Res. 2023 Nov;158(2):131-149. doi: 10.1007/s11120-023-01043-9. Epub 2023 Aug 24.
Leaf photosynthetic capacity (light-saturated net assimilation rate, A) increases from bottom to top of plant canopies as the most prominent acclimation response to the conspicuous within-canopy gradients in light availability. Light-dependent variation in A through plant canopies is associated with changes in key leaf structural (leaf dry mass per unit leaf area), chemical (nitrogen (N) content per area and dry mass, N partitioning between components of photosynthetic machinery), and physiological (stomatal and mesophyll conductance) traits, whereas the contribution of different traits to within-canopy A gradients varies across sites, species, and plant functional types. Optimality models maximizing canopy carbon gain for a given total canopy N content predict that A should be proportionally related to canopy light availability. However, comparison of model expectations with experimental data of within-canopy photosynthetic trait variations in representative plant functional types indicates that such proportionality is not observed in real canopies, and A vs. canopy light relationships are curvilinear. The factors responsible for deviations from full optimality include stronger stomatal and mesophyll diffusion limitations at higher light, reflecting greater water limitations and more robust foliage in higher light. In addition, limits on efficient packing of photosynthetic machinery within leaf structural scaffolding, high costs of N redistribution among leaves, and limited plasticity of N partitioning among components of photosynthesis machinery constrain A plasticity. Overall, this review highlights that the variation of A through plant canopies reflects a complex interplay between adjustments of leaf structure and function to multiple environmental drivers, and that A plasticity is limited by inherent constraints on and trade-offs between structural, chemical, and physiological traits. I conclude that models trying to simulate photosynthesis gradients in plant canopies should consider co-variations among environmental drivers, and the limitation of functional trait variation by physical constraints and include the key trade-offs between structural, chemical, and physiological leaf characteristics.
叶片光合能力（光饱和净同化率，A）随植物冠层由下至上增加，这是对光在冠层内显著梯度变化的最显著适应响应。通过植物冠层的 A 与叶片关键结构（单位叶面积的叶片干质量）、化学（面积和干质量的氮（N）含量、光合机构各组成部分之间的 N 分配）和生理（气孔和叶肉导度）特性的变化有关，而不同特性对冠层内 A 梯度的贡献因地点、物种和植物功能类型而异。最大化给定总冠层 N 含量下的冠层碳增益的最优化模型预测 A 应与冠层光可用性成比例相关。然而，代表性植物功能类型的冠层内光合特性变化的模型预期与实验数据的比较表明，这种比例关系在真实冠层中并不存在，A 与冠层光的关系是曲线的。导致偏离完全最优的因素包括在更高的光下更强的气孔和叶肉扩散限制，反映了在更高的光下更大的水分限制和更健壮的叶片。此外，在叶片结构支架内有效组装光合机构的能力有限、叶片间 N 再分配的高成本以及光合作用机构各组成部分间 N 分配的有限可塑性，限制了 A 的可塑性。总的来说，本综述强调了通过植物冠层的 A 的变化反映了叶片结构和功能对多种环境驱动因素的复杂相互作用，并且 A 的可塑性受到结构、化学和生理特性之间的固有限制和权衡的限制。我得出结论，试图模拟植物冠层中光合作用梯度的模型应该考虑环境驱动因素的共变，以及物理限制对功能特性变化的限制，并包括结构、化学和生理叶片特征之间的关键权衡。
