Wei Yuqiu, Zhao Xiangwei, Sun Jun, Liu Haijiao
Institute of Marine Science and Technology, Shandong University, Qingdao, China.
Research Centre for Indian Ocean Ecosystem, Tianjin University of Science and Technology, Tianjin, China.
Front Microbiol. 2019 May 24;10:1164. doi: 10.3389/fmicb.2019.01164. eCollection 2019.
The approach of fast repetition rate fluorometry (FRRF) requires a conversion factor (Φ/ ) to derive ecologically-relevant carbon uptake rates ( ). However, the required Φ/ is commonly measured by C assimilation and varies greatly across phytoplankton taxonomy and environmental conditions. Consequently, the use of FRRF to estimate gross primary productivity ( ), alone or in combination with other approaches, has been restricted by both inherent conversion and procedural inconsistencies. Within this study, based on a hypothesis that the non-photochemical quenching (NPQ) can be used as a proxy for the variability and magnitude of Φ/ , we thus proposed an independent field model coupling with the NPQ-based Φ/ for FRRF-derived carbon, without the need for additional Φ/ in the Bay of Bengal (BOB). Therewith, this robust algorithm was verified by the parallel measures of electron transport rates and C-uptake . NPQ is theoretically caused by the effects of excess irradiance pressure, however, it showed a light and depth-independent response on large spatial scales of the BOB. Trends observed for the maximum quantum efficiency (F/F), the quantum efficiency of energy conversion ( / ) and the efficiency of charge separation ( / ) were similar and representative, which displayed a relative maximum at the subsurface and were collectively limited by excess irradiance. In particular, most observed values of F/F in the BOB were only about half of the values expected for nutrient replete phytoplankton. FRRF-based estimates of electron transport at PSII (ETR) varied significantly, from 0.01 to 8.01 mol e mol RCII s, and showed profound responses to depth and irradiance across the BOB, but fitting with the logistic model. N, P, and irradiance are key environmental drivers in explaining the broad-scale variability of photosynthetic parameters. Furthermore, taxonomic shifts and physiological changes may be better predictors of photosynthetic parameters, and facilitate the selection of better adapted species to optimize photosynthetic efficiency under any particular set of ambient light condition.
快速重复率荧光测定法(FRRF)的方法需要一个转换因子(Φ/ )来推导与生态相关的碳吸收速率( )。然而,所需的Φ/ 通常通过碳同化来测量,并且在浮游植物分类群和环境条件之间差异很大。因此,单独使用FRRF或与其他方法结合使用来估计总初级生产力( ),受到内在转换和程序不一致性的限制。在本研究中,基于非光化学猝灭(NPQ)可作为Φ/ 的变异性和大小的替代指标这一假设,我们提出了一个独立的现场模型,该模型将基于NPQ的Φ/ 与FRRF衍生的碳相结合,在孟加拉湾(BOB)无需额外的Φ/ 。据此,通过电子传输速率和碳吸收的平行测量验证了这种稳健的算法。NPQ理论上是由过量辐照压力的影响引起的,然而,它在BOB的大空间尺度上表现出与光和深度无关的响应。观察到的最大量子效率(F/F)、能量转换量子效率( / )和电荷分离效率( / )的趋势相似且具有代表性,它们在次表层显示出相对最大值,并共同受到过量辐照的限制。特别是,BOB中大多数观察到的F/F值仅约为营养丰富的浮游植物预期值的一半。基于FRRF对PSII处电子传输(ETR)的估计差异很大,从0.01到8.01 mol e mol RCII s,并在整个BOB中对深度和辐照度表现出深刻的响应,但符合逻辑模型。氮、磷和辐照度是解释光合参数广泛变化的关键环境驱动因素。此外,分类学变化和生理变化可能是光合参数更好的预测指标,并有助于选择更适应的物种,以在任何特定的环境光照条件下优化光合效率。