INRA UR4 URP3F, BP6, F86600 Lusignan, France
INRA UR4 URP3F, BP6, F86600 Lusignan, France.
AoB Plants. 2015 Oct 3;7:plv116. doi: 10.1093/aobpla/plv116.
Modelling the spatial and temporal distribution of leaf nitrogen (N) is central to specify photosynthetic parameters and simulate canopy photosynthesis. Leaf photosynthetic parameters depend on both local light availability and whole-plant N status. The interaction between these two levels of integration has generally been modelled by assuming optimal canopy functioning, which is not supported by experiments. During this study, we examined how a set of empirical relationships with measurable parameters could be used instead to predict photosynthesis at the leaf and whole-canopy levels. The distribution of leaf N per unit area (Na) within the canopy was related to leaf light irradiance and to the nitrogen nutrition index (NNI), a whole-plant variable accounting for plant N status. Na was then used to determine the photosynthetic parameters of a leaf gas exchange model. The model was assessed on alfalfa canopies under contrasting N nutrition and with N2-fixing and non-fixing plants. Three experiments were carried out to parameterize the relationships between Na, leaf irradiance, NNI and photosynthetic parameters. An additional independent data set was used for model evaluation. The N distribution model showed that it was able to predict leaf N on the set of leaves tested. The Na at the top of the canopy appeared to be related linearly to the NNI, whereas the coefficient accounting for N allocation remained constant. Photosynthetic parameters were related linearly to Na irrespective of N nutrition and the N acquisition mode. Daily patterns of gas exchange were simulated accurately at the leaf scale. When integrated at the whole-canopy scale, the model predicted that raising N availability above an NNI of 1 did not result in increased net photosynthesis. Overall, the model proposed offered a solution for a dynamic coupling of leaf photosynthesis and canopy N distribution without requiring any optimal functioning hypothesis.
建立叶片氮（N）的时空分布模型是确定光合作用参数和模拟冠层光合作用的核心。叶片光合作用参数取决于局部光可用性和整株植物的 N 状况。这两个整合水平之间的相互作用通常通过假设最佳冠层功能来建模，但这一假设并没有得到实验的支持。在本研究中，我们研究了如何使用一组具有可测量参数的经验关系来替代预测叶片和整个冠层水平的光合作用。冠层内单位面积叶片 N 分布（Na）与叶片光辐照度和整株植物的氮营养指数（NNI）有关，NNI 是一个反映植物 N 状况的整体变量。然后，Na 用于确定叶片气体交换模型的光合作用参数。该模型在具有不同氮营养状况的紫花苜蓿冠层以及固氮和非固氮植物上进行了评估。进行了三个实验来确定 Na、叶片辐照度、NNI 和光合作用参数之间的关系。使用另外一组独立的数据来评估模型。N 分布模型表明，它能够预测所测试叶片的叶片 N。冠层顶部的 Na 似乎与 NNI 呈线性相关，而反映 N 分配的系数保持不变。光合作用参数与 Na 呈线性相关，而与氮营养和氮获取模式无关。在叶片尺度上，气体交换的日变化模式被准确地模拟。当整合到整个冠层尺度时，该模型预测，将 NNI 提高到 1 以上不会导致净光合作用增加。总体而言，所提出的模型为叶片光合作用和冠层 N 分布的动态耦合提供了一种解决方案，而无需任何最优功能假设。
