基于叶绿素含量和最大羧化速率同步观测的亚热带常绿针叶林生产力模拟研究

State-of-the-art ecosystem process model have been developed to quantify carbon fluxes by describing physical and physiological processes. The limited availability of parameters of leaf photosynthetic capacity in both space and time has hindered progress in improving gross primary productivity estimates by ecosystem process model. Finding a reliable and easily measurable proxy for leaf photosynthetic parameters plays an important role in modeling developing. This study focuses on evergreen coniferous forests in Subtropical region of China. We will measure foliar chlorophyll and CO2 response curve in Qianyanzhou (QYZ) station every month. Measurements were also made at three canopy layers: upper, middle and lower. The photosynthetic parameters Vcmax and Jmax calculated from the A-Ci curves fitted will be scaled to a common reference temperature of 25°C (Vcmax25 and Jmax25). The seasonal variation of photosynthetic capacity and leaf chlorophyll will be captured. We will examine the relationship between photosynthetic capacity with leaf chlorophyll and leaf nitrogen in evergreen forests to assess the suitability of using leaf chlorophyll to derive seasonal variation of Vcmax. The different slopes of Vcmax and leaf chlorophyll between sunlit leaf and shaded leaf were also explored. We hope to extract a robust relationship between leaf chlorophyll and Vmax25, which can be used to incorporate leaf chlorophyll into ecosystem process model. Their inclusion of leaf chlorophyll into a two-leaf ecosystem process model will be tested how to improve GPP simulations to better capture the daily and seasonal variations of observations. The changes in relationships of leaf photosynthetic capacity and leaf chlorophyll with canopy layers were analyzed. Based on meteorology data, remote sensing data, and eddy flux data, the leaf chlorophyll-based two-leaf ecosystem process model will be used to simulate the long term of carbon flux in subtropical forests. The sensitive factors will be calculated to quantify the response of subtropical forests carbon flux to environmental variables, which help us to better understanding the interaction of forest carbon dynamics and climate change.

关键生理生态参数很难在时空尺度上扩展限制了生态系统过程模型的发展，迫切需要寻找大区域尺度上可靠和易监测的替代因子来改善模型结构，提高模型的模拟能力。项目以亚热带地区三种典型树种为研究对象，通过叶片光合速率、叶绿素含量和叶氮含量的时间（季节变异）和空间（冠层内部）观测，从时间上探讨森林光合能力和叶绿素含量的季节变异特征及其阳生叶和阴生叶的差异，从冠层内部揭示植被光合能力和叶片生理性状的垂直分布规律及其控制机制；通过25℃最大羧化速率Vcmax25和叶绿素含量定量关系的构建，探索叶绿素含量替代叶氮含量来表征植被光合能力的优势，发展基于叶绿素含量的两叶最大羧化速率模型来改进生态过程模型，实现利用遥感信息时空扩展最大羧化速率进而提高亚热带常绿针叶林生产力模拟的精度。开展森林光合作用和叶绿素含量的同步观测和模拟研究，降低生态模型中光合作用模块对气候变异响应的不确定性，推动生态系统模型的发展。

叶片最大羧化速率（Vcmax）是表征叶片固有光合能力的重要指标，也是陆地生态系统生态系统模型的重要输入参数。研究表明通过约束最大羧化速率可以改善陆地生态系统净初级生产力（GPP）的模拟精度，但在全球尺度量化最大羧化速率仍然面临着诸多挑战。一方面，最大羧化速率的实测只能通过叶片测量二氧化碳响应曲线获取；另一方面，最大羧化速率随着季节、树种和叶片所处的冠层位置的不同而不同。以往研究通常采用叶氮含量和最大羧化速率关系来空间扩展最大羧化速率，而越来越多的研究表明叶绿素含量能够更好地指示最大羧化速率。叶片生理和结构、冠层位置的生物/非生物因素都可能会影响叶绿素含量和最大羧化速率的关系。本项目以亚热带常绿林湿地松和木荷为研究对象，连续测定了冠层垂直梯度上的环境因子如光量子通量密度、叶温和饱和水汽压亏缺，叶片光合性状如最大羧化速率、最大电子传递速率、气孔导度、净光合速率，叶片生理参数如叶氮含量、叶绿素含量、比叶面积和比叶重等，构建了亚热带森林光合性状及其环境因子的实测数据库。通过分析了亚热带森林叶片光合性状及其环境因子的时间上（季节）和空间上（冠层内部）变化特征，建立了冠层垂直梯度上叶片光合性状与环境因子的关系；基于最大羧化速率和叶绿素含量在亚热带森林中的时空变异特征，构建了亚热带常绿针叶林和常绿阔叶林不同冠层垂直梯度上最大羧化速率与叶绿素含量的函数关系。基于叶片和区域尺度上荧光和光合的耦合机制来探索生态系统总初级生产力GPP的模拟方法，明确在考虑气候调控因素情况下日光诱导叶绿素荧光可以用于森林生态系统GPP的快速模拟。开展亚热带森林生态系统生物化学过程的研究，对阐明我国陆地生态系统碳平衡及其驱动机制具有重要意义。