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

小行星9416838 该项目需要对在三种不同的海洋环境中进行的一系列广泛的叶绿素标记实验进行实验室分析，这三种海洋环境代表着非常不同的物理和生物状况：赤道太平洋，海洋上升流区;加州边界流，沿海上升流区;以及Dabob湾，季节性水华的温带峡湾。 使用相同的采样和程序技术获得了大约500个样本，包括多深度（7-8）剖面。 在每种环境中，生长条件的巨大变化（例如， 光照、营养物温度等）是明显的，与物理（例如，厄尔尼诺、季节性上升流、分层）和生物（例如，开花，地理变化）的变化。 这些实验的分析需要使用高效液相色谱法分离叶绿素a以测定其比活性。 结果将产生浮游植物碳：叶绿素比和特定生长率的估计。 将进行相关和回归分析，以深入了解浮游植物生长的物理强迫内和这三个非常不同的环境之间的反应。所产生的数据集碳：叶绿素（C：chl）比率和浮游植物特定生长率（u）在规模和综合性方面将是前所未有的。 由于这些属性，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了解将增加。 这些分析将导致更好地了解这些参数在不同的现场条件下的变化。然而，更重要的是，因为环境中的采样跨越了生长条件的变化，这些比较可以产生定量的洞察力的主变量在确定浮游植物在该领域的具体增长率。 要评估的一个假设是，可以开发一种算法，使得通常测量的参数，如营养物质，光，和物种组成，可以约束浮游植物比生长速率（u）充分建模的目的。 结果将是有用的，估计从建模工作，其中C：叶绿素比或u测量不存在引起的误差。在许多环境中，现场测量u是罕见的。 这三个项目中每一个项目的物理、化学和生物支持数据库将使人们深入了解浮游植物对三种不同环境中每一种环境的物理强迫的反应。 ***

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. ***