Chlorophyll-Labeling Experiments and the Comparison of Environmental Factors' Influence on Phytoplankton Specific Growth Rates

这个项目需要对在三种不同的海洋环境中进行的一套广泛的叶绿素标记实验进行实验室分析，这些环境代表了非常不同的物理和生物制度：赤道太平洋，海洋上升流区；加利福尼亚边界流，一个沿海上升流点；还有达布湾，这是一个温和的峡湾，季节性开花。使用相同的采样和程序技术，获得了大约500个包括多深度（7-8）剖面的样本。在每个环境中，生长条件（如光照、营养物质温度等）的巨大变化是明显的，与物理（如厄尔尼诺、季节性上升流、分层）和生物（如水华、生物地理变化）变化有关。分析这些实验需要使用高效液相色谱法分离叶绿素a，以确定其比活性。结果将产生浮游植物碳：叶绿素比率和特定生长率的估计。将进行相关和回归分析，以深入了解这三种不同环境内部和之间浮游植物生长对物理强迫的响应。生成的碳：叶绿素（C:chl）比和浮游植物特定生长率(u)数据集在规模和综合方面将是前所未有的。由于这些特性，统计分析将是有意义的，我们对浮游植物生长和细胞适应环境和生物条件的基本理解将会增加。这些分析将有助于更好地了解这些参数在不同现场条件下的可变性。然而，更重要的是，因为在一个环境中采样跨越了生长条件的变化，这些变化是量化的，这些比较可以产生定量的见解，以确定浮游植物在野外的特定生长速度的主要变量。需要评估的一个假设是，可以开发一种算法，使典型的测量参数，如营养物质、光线和物种组成，能够充分约束浮游植物的特定生长率(u)，以达到建模目的。这些结果将有助于估计在不存在C:chl比或u测量的情况下由建模努力引起的误差。在许多环境中，u的现场测量是罕见的。这三个项目中存在的物理、化学和生物支持数据池将有助于深入了解浮游植物在三种不同环境中对物理强迫的反应。＊＊＊

9416838 Newton This project entails laboratory analysis of an extensive set of chlorophyll-labeling experiments that have been conducted in three different marine environments which represent very different physical and biological regimes: the equatorial Pacific, an oceanic upwelling area; the California boundary current, a coastal upwelling site; and Dabob Bay, a temperate fjord with seasonal blooms. Roughly 500 samples comprising multi-depth (7-8) profiles were obtained using identical sampling and procedural techniques. Within each environment, large variations in growth conditions (e.g., light, nutrients temperature, etc.) were evident, associated with physical (e.g., EL Nino, seasonal upwelling, stratification) and biological (e.g., blooms, biogeographical shifts) variation. Analysis of these experiments entails using high-performance liquid chromatography to isolate chlorophyll a for determination of its specific activity. Results will yield estimates of phytoplankton carbon:chlorophyll ratios and specific growth rates. Correlation and regression analysis will be conducted to gain insight into phytoplankton growth response to physical forcing within and between these three very different environments. The data set carbon:chlorophyll (C:chl) ratios and phytoplankton specific growth rates (u) generated will be unprecedented in size and comprehensives. Because of these attributes, statistical analysis will be meaningful and our basic understanding of phytoplankton growth and cellular adaptation in relation to environmental and biological conditions will be increased. These analyses will result in a better appreciation for the variability in these parameters under different field conditions. Yet, more importantly, because sampling within an environment spanned variations in growth conditions that were quantified, these comparisons can yield quantitative insight to the master variables in determining phytoplankton specific growth rate in the field. A hypothesis to be evaluated is that an algorithm can be developed such that typically measured parameters, such as nutrients, light, and species composition, can constrain phytoplankton specific growth rate (u) adequately for modeling purposes. The results will be useful for estimating the errors induced from modeling efforts where C:chl ratio or u measurements do not exist. Field measurements of u are rare in many environments. The pool of physical, chemical and biological support data that exists for each of the three projects will afford insight into phytoplankton response to physical forcing within each of the three different environments. ***