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. ***
