On Saturating Response Curves from the Dual Perspectives of Photosynthesis and Nitrogen Metabolism
On Saturating Response Curves from the Dual Perspectives of Photosynthesis and Nitrogen Metabolism
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从光合作用和氮代谢双重角度探讨饱和响应曲线
DOI：
10.1007/978-3-319-30259-1_8
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发表时间：
2016
影响因子：
5.9
通讯作者：
P. Glibert
中科院分区：
文献类型：
--
作者：
T. Kana;P. Glibert
饱和动力学曲线是浮游植物生态学中最著名的关系之一。典型的例子是光合作用-辐照关系和养分吸收动力学。在饱和曲线上，低浓度时独立因素起控制作用，高浓度时不起控制作用。这个简单、重要而深刻的概念是几乎所有生物和生态系统模型的核心，也是评估环境因素“限制”的基础，无论是在细胞生理学水平还是生态系统响应水平。在这里，使用光合作用和营养吸收的例子，我们描述了细胞如何以及为什么不仅仅是“上下”响应曲线;在曲线的需求侧（当供应低时获得所需的东西）和资源的同化（最大速率总是由生化反应及其常数设定）之间存在强烈的生物调节。我们讨论了如何生物调控的限制和饱和部分的曲线应该是重点，而不是曲线本身，为了解生物反应，我们描述的重要性，能量和氨基酸的比例作为光合色素调节和氮吸收调节的信号，分别。而使用经典的，描述性的曲线建立浮游植物生产力模型是传统的，我们主张发展动态的，监管模型，更好地描述了复杂环境中的资源获取的变化范围。
Saturation kinetic curves are one of the most well-known relationships in phytoplankton ecology. Classic examples are those of the photosynthesis–irradiance relationship and of nutrient uptake kinetics. With saturation curves, the independent factor is controlling at low concentrations and noncontrolling at high concentrations. This simple, nontrivial, and profound concept is at the heart of nearly all biological and ecological systems models and is commonly the basis for evaluating “limitation” by environmental factors, whether it is at the level of cell physiology or ecosystem response. Here, using examples from both photosynthesis and nutrient uptake, we describe how and why a cell does more than “ride up and down” the response curve; there is strong biological regulation between the demand side of the curve (getting what is needed when supplies are low) and the assimilation of the resource (the maximal rate always set by the biochemical reactions and their constants). We discuss how the biological regulation of the limiting and saturating portion of the curve should be the focus—rather than the curve itself—for understanding biological responses and we describe the importance of energy and amino acid ratios as signals for photosynthetic pigment regulation and nitrogen uptake regulation, respectively. Whereas the use of classic, descriptive curves for building phytoplankton productivity models is traditional, we advocate the development of dynamic, regulatory models that better describe the range of variability in resource acquisition in complex environments.